Graphical Description of Johnson-Neyman Outcomes for Linear and Quadratic Regression Surfaces.
ERIC Educational Resources Information Center
Schafer, William D.; Wang, Yuh-Yin
A modification of the usual graphical representation of heterogeneous regressions is described that can aid in interpreting significant regions for linear or quadratic surfaces. The standard Johnson-Neyman graph is a bivariate plot with the criterion variable on the ordinate and the predictor variable on the abscissa. Regression surfaces are drawn…
Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.
Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg
2009-11-01
G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.
Bivariate categorical data analysis using normal linear conditional multinomial probability model.
Sun, Bingrui; Sutradhar, Brajendra
2015-02-10
Bivariate multinomial data such as the left and right eyes retinopathy status data are analyzed either by using a joint bivariate probability model or by exploiting certain odds ratio-based association models. However, the joint bivariate probability model yields marginal probabilities, which are complicated functions of marginal and association parameters for both variables, and the odds ratio-based association model treats the odds ratios involved in the joint probabilities as 'working' parameters, which are consequently estimated through certain arbitrary 'working' regression models. Also, this later odds ratio-based model does not provide any easy interpretations of the correlations between two categorical variables. On the basis of pre-specified marginal probabilities, in this paper, we develop a bivariate normal type linear conditional multinomial probability model to understand the correlations between two categorical variables. The parameters involved in the model are consistently estimated using the optimal likelihood and generalized quasi-likelihood approaches. The proposed model and the inferences are illustrated through an intensive simulation study as well as an analysis of the well-known Wisconsin Diabetic Retinopathy status data. Copyright © 2014 John Wiley & Sons, Ltd.
Suzuki, Taku; Iwamoto, Takuji; Shizu, Kanae; Suzuki, Katsuji; Yamada, Harumoto; Sato, Kazuki
2017-05-01
This retrospective study was designed to investigate prognostic factors for postoperative outcomes for cubital tunnel syndrome (CubTS) using multiple logistic regression analysis with a large number of patients. Eighty-three patients with CubTS who underwent surgeries were enrolled. The following potential prognostic factors for disease severity were selected according to previous reports: sex, age, type of surgery, disease duration, body mass index, cervical lesion, presence of diabetes mellitus, Workers' Compensation status, preoperative severity, and preoperative electrodiagnostic testing. Postoperative severity of disease was assessed 2 years after surgery by Messina's criteria which is an outcome measure specifically for CubTS. Bivariate analysis was performed to select candidate prognostic factors for multiple linear regression analyses. Multiple logistic regression analysis was conducted to identify the association between postoperative severity and selected prognostic factors. Both bivariate and multiple linear regression analysis revealed only preoperative severity as an independent risk factor for poor prognosis, while other factors did not show any significant association. Although conflicting results exist regarding prognosis of CubTS, this study supports evidence from previous studies and concludes early surgical intervention portends the most favorable prognosis. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.
Principal component regression analysis with SPSS.
Liu, R X; Kuang, J; Gong, Q; Hou, X L
2003-06-01
The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with SPSS 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correlations procedures in SPSS 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with SPSS.
ASURV: Astronomical SURVival Statistics
NASA Astrophysics Data System (ADS)
Feigelson, E. D.; Nelson, P. I.; Isobe, T.; LaValley, M.
2014-06-01
ASURV (Astronomical SURVival Statistics) provides astronomy survival analysis for right- and left-censored data including the maximum-likelihood Kaplan-Meier estimator and several univariate two-sample tests, bivariate correlation measures, and linear regressions. ASURV is written in FORTRAN 77, and is stand-alone and does not call any specialized libraries.
NASA Astrophysics Data System (ADS)
Rock, N. M. S.; Duffy, T. R.
REGRES allows a range of regression equations to be calculated for paired sets of data values in which both variables are subject to error (i.e. neither is the "independent" variable). Nonparametric regressions, based on medians of all possible pairwise slopes and intercepts, are treated in detail. Estimated slopes and intercepts are output, along with confidence limits, Spearman and Kendall rank correlation coefficients. Outliers can be rejected with user-determined stringency. Parametric regressions can be calculated for any value of λ (the ratio of the variances of the random errors for y and x)—including: (1) major axis ( λ = 1); (2) reduced major axis ( λ = variance of y/variance of x); (3) Y on Xλ = infinity; or (4) X on Y ( λ = 0) solutions. Pearson linear correlation coefficients also are output. REGRES provides an alternative to conventional isochron assessment techniques where bivariate normal errors cannot be assumed, or weighting methods are inappropriate.
A generalized right truncated bivariate Poisson regression model with applications to health data.
Islam, M Ataharul; Chowdhury, Rafiqul I
2017-01-01
A generalized right truncated bivariate Poisson regression model is proposed in this paper. Estimation and tests for goodness of fit and over or under dispersion are illustrated for both untruncated and right truncated bivariate Poisson regression models using marginal-conditional approach. Estimation and test procedures are illustrated for bivariate Poisson regression models with applications to Health and Retirement Study data on number of health conditions and the number of health care services utilized. The proposed test statistics are easy to compute and it is evident from the results that the models fit the data very well. A comparison between the right truncated and untruncated bivariate Poisson regression models using the test for nonnested models clearly shows that the truncated model performs significantly better than the untruncated model.
A generalized right truncated bivariate Poisson regression model with applications to health data
Islam, M. Ataharul; Chowdhury, Rafiqul I.
2017-01-01
A generalized right truncated bivariate Poisson regression model is proposed in this paper. Estimation and tests for goodness of fit and over or under dispersion are illustrated for both untruncated and right truncated bivariate Poisson regression models using marginal-conditional approach. Estimation and test procedures are illustrated for bivariate Poisson regression models with applications to Health and Retirement Study data on number of health conditions and the number of health care services utilized. The proposed test statistics are easy to compute and it is evident from the results that the models fit the data very well. A comparison between the right truncated and untruncated bivariate Poisson regression models using the test for nonnested models clearly shows that the truncated model performs significantly better than the untruncated model. PMID:28586344
Pointwise influence matrices for functional-response regression.
Reiss, Philip T; Huang, Lei; Wu, Pei-Shien; Chen, Huaihou; Colcombe, Stan
2017-12-01
We extend the notion of an influence or hat matrix to regression with functional responses and scalar predictors. For responses depending linearly on a set of predictors, our definition is shown to reduce to the conventional influence matrix for linear models. The pointwise degrees of freedom, the trace of the pointwise influence matrix, are shown to have an adaptivity property that motivates a two-step bivariate smoother for modeling nonlinear dependence on a single predictor. This procedure adapts to varying complexity of the nonlinear model at different locations along the function, and thereby achieves better performance than competing tensor product smoothers in an analysis of the development of white matter microstructure in the brain. © 2017, The International Biometric Society.
Ding, Aidong Adam; Hsieh, Jin-Jian; Wang, Weijing
2015-01-01
Bivariate survival analysis has wide applications. In the presence of covariates, most literature focuses on studying their effects on the marginal distributions. However covariates can also affect the association between the two variables. In this article we consider the latter issue by proposing a nonstandard local linear estimator for the concordance probability as a function of covariates. Under the Clayton copula, the conditional concordance probability has a simple one-to-one correspondence with the copula parameter for different data structures including those subject to independent or dependent censoring and dependent truncation. The proposed method can be used to study how covariates affect the Clayton association parameter without specifying marginal regression models. Asymptotic properties of the proposed estimators are derived and their finite-sample performances are examined via simulations. Finally, for illustration, we apply the proposed method to analyze a bone marrow transplant data set.
Aspects of porosity prediction using multivariate linear regression
DOE Office of Scientific and Technical Information (OSTI.GOV)
Byrnes, A.P.; Wilson, M.D.
1991-03-01
Highly accurate multiple linear regression models have been developed for sandstones of diverse compositions. Porosity reduction or enhancement processes are controlled by the fundamental variables, Pressure (P), Temperature (T), Time (t), and Composition (X), where composition includes mineralogy, size, sorting, fluid composition, etc. The multiple linear regression equation, of which all linear porosity prediction models are subsets, takes the generalized form: Porosity = C{sub 0} + C{sub 1}(P) + C{sub 2}(T) + C{sub 3}(X) + C{sub 4}(t) + C{sub 5}(PT) + C{sub 6}(PX) + C{sub 7}(Pt) + C{sub 8}(TX) + C{sub 9}(Tt) + C{sub 10}(Xt) + C{sub 11}(PTX) + C{submore » 12}(PXt) + C{sub 13}(PTt) + C{sub 14}(TXt) + C{sub 15}(PTXt). The first four primary variables are often interactive, thus requiring terms involving two or more primary variables (the form shown implies interaction and not necessarily multiplication). The final terms used may also involve simple mathematic transforms such as log X, e{sup T}, X{sup 2}, or more complex transformations such as the Time-Temperature Index (TTI). The X term in the equation above represents a suite of compositional variable and, therefore, a fully expanded equation may include a series of terms incorporating these variables. Numerous published bivariate porosity prediction models involving P (or depth) or Tt (TTI) are effective to a degree, largely because of the high degree of colinearity between p and TTI. However, all such bivariate models ignore the unique contributions of P and Tt, as well as various X terms. These simpler models become poor predictors in regions where colinear relations change, were important variables have been ignored, or where the database does not include a sufficient range or weight distribution for the critical variables.« less
Anodic microbial community diversity as a predictor of the power output of microbial fuel cells.
Stratford, James P; Beecroft, Nelli J; Slade, Robert C T; Grüning, André; Avignone-Rossa, Claudio
2014-03-01
The relationship between the diversity of mixed-species microbial consortia and their electrogenic potential in the anodes of microbial fuel cells was examined using different diversity measures as predictors. Identical microbial fuel cells were sampled at multiple time-points. Biofilm and suspension communities were analysed by denaturing gradient gel electrophoresis to calculate the number and relative abundance of species. Shannon and Simpson indices and richness were examined for association with power using bivariate and multiple linear regression, with biofilm DNA as an additional variable. In simple bivariate regressions, the correlation of Shannon diversity of the biofilm and power is stronger (r=0.65, p=0.001) than between power and richness (r=0.39, p=0.076), or between power and the Simpson index (r=0.5, p=0.018). Using Shannon diversity and biofilm DNA as predictors of power, a regression model can be constructed (r=0.73, p<0.001). Ecological parameters such as the Shannon index are predictive of the electrogenic potential of microbial communities. Copyright © 2014 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Caimmi, R.
2011-08-01
Concerning bivariate least squares linear regression, the classical approach pursued for functional models in earlier attempts ( York, 1966, 1969) is reviewed using a new formalism in terms of deviation (matrix) traces which, for unweighted data, reduce to usual quantities leaving aside an unessential (but dimensional) multiplicative factor. Within the framework of classical error models, the dependent variable relates to the independent variable according to the usual additive model. The classes of linear models considered are regression lines in the general case of correlated errors in X and in Y for weighted data, and in the opposite limiting situations of (i) uncorrelated errors in X and in Y, and (ii) completely correlated errors in X and in Y. The special case of (C) generalized orthogonal regression is considered in detail together with well known subcases, namely: (Y) errors in X negligible (ideally null) with respect to errors in Y; (X) errors in Y negligible (ideally null) with respect to errors in X; (O) genuine orthogonal regression; (R) reduced major-axis regression. In the limit of unweighted data, the results determined for functional models are compared with their counterparts related to extreme structural models i.e. the instrumental scatter is negligible (ideally null) with respect to the intrinsic scatter ( Isobe et al., 1990; Feigelson and Babu, 1992). While regression line slope and intercept estimators for functional and structural models necessarily coincide, the contrary holds for related variance estimators even if the residuals obey a Gaussian distribution, with the exception of Y models. An example of astronomical application is considered, concerning the [O/H]-[Fe/H] empirical relations deduced from five samples related to different stars and/or different methods of oxygen abundance determination. For selected samples and assigned methods, different regression models yield consistent results within the errors (∓ σ) for both heteroscedastic and homoscedastic data. Conversely, samples related to different methods produce discrepant results, due to the presence of (still undetected) systematic errors, which implies no definitive statement can be made at present. A comparison is also made between different expressions of regression line slope and intercept variance estimators, where fractional discrepancies are found to be not exceeding a few percent, which grows up to about 20% in the presence of large dispersion data. An extension of the formalism to structural models is left to a forthcoming paper.
NASA Astrophysics Data System (ADS)
de Andrés, Javier; Landajo, Manuel; Lorca, Pedro; Labra, Jose; Ordóñez, Patricia
Artificial neural networks have proven to be useful tools for solving financial analysis problems such as financial distress prediction and audit risk assessment. In this paper we focus on the performance of robust (least absolute deviation-based) neural networks on measuring liquidity of firms. The problem of learning the bivariate relationship between the components (namely, current liabilities and current assets) of the so-called current ratio is analyzed, and the predictive performance of several modelling paradigms (namely, linear and log-linear regressions, classical ratios and neural networks) is compared. An empirical analysis is conducted on a representative data base from the Spanish economy. Results indicate that classical ratio models are largely inadequate as a realistic description of the studied relationship, especially when used for predictive purposes. In a number of cases, especially when the analyzed firms are microenterprises, the linear specification is improved by considering the flexible non-linear structures provided by neural networks.
Using the social cognitive theory to understand physical activity among dialysis patients.
Patterson, Megan S; Umstattd Meyer, M Renée; Beaujean, A Alexander; Bowden, Rodney G
2014-08-01
The purpose of this study was to use the social cognitive theory (SCT) constructs self-efficacy, outcome expectations, and self-regulation to better understand associations of physical activity (PA) behaviors among dialysis patients after controlling for demographic and health-related factors. This study was cross-sectional in design. Participants (N = 115; mean age = 61.51 years, SD = 14.01) completed self-report questionnaires during a regularly scheduled dialysis treatment session. Bivariate and hierarchical linear regression analyses were conducted to examine relationships among SCT constructs and PA. Significant relationships between PA and self-efficacy (r = .336), self-regulation (r = .280), and outcome expectations (r = .265) were detected among people on dialysis in bivariate analyses. Hierarchical linear regression revealed significant increases in variance explained for the addition of self-efficacy, self-regulation, and covariates (p < .01). Younger age, self-efficacy, and self-regulation were associated (p < .10) with greater participation in physical activity in the final model (R² = .272). Conclusion/Implication: This research supports the use of SCT in understanding PA among people undergoing dialysis treatment. The findings of this study can help health educators and health care practitioners better understand PA and how to promote it among this population. Future research should further investigate which activities dialysis patients participate in across the life span of their disease. Future PA programs should focus on increasing a patient's self-efficacy and self-regulation.
On Deriving and Solving the Generalized Bivariate, Linear Location Problems.
1982-09-01
average (Eisenhart, 1978). Francis Galton indirectly coined the term "regression" in his 1885 publication, Natural Inheritance, when he studied sweet...David, F. N. Francis Galton . In W. H. Kruskal & J. Tanur (Eds.), International encyclopedia of statistics (Vol. 1). New York: Free Press, 1978. Dean, W...mhhhEmhnhhEEEI I fllfllfllfllfllfllfl EEEMMhMhMhhhMhI 1111 . I 28 12.5 1.:, 1 2 . 1.21111 1 4 11111I. IIIII~ JIII1L MICROCOPY RESOLUTION TEST CHART NATIONAL
Applied Statistics: From Bivariate through Multivariate Techniques [with CD-ROM
ERIC Educational Resources Information Center
Warner, Rebecca M.
2007-01-01
This book provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked…
The relationship between severity of violence in the home and dating violence.
Sims, Eva Nowakowski; Dodd, Virginia J Noland; Tejeda, Manuel J
2008-01-01
This study used propositions from the social learning theory to explore the effects of the combined influences of child maltreatment, childhood witness to parental violence, sibling violence, and gender on dating violence perpetration using a modified version of the Conflict Tactics Scale 2 (CTS2). A weighted scoring method was utilized to determine how severity of violence in the home impacts dating violence perpetration. Bivariate correlations and linear regression models indicate significant associations between child maltreatment, sibling violence perpetration, childhood witness to parental violence, gender, and subsequent dating violence perpetration. Multiple regression analyses indicate that for men, history of severe violence victimization (i.e., child maltreatment and childhood witness to parental violence) and severe perpetration (sibling violence) significantly predict dating violence perpetration.
Ronzitti, Silvia; Soldini, Emiliano; Lutri, Vittorio; Smith, Neil; Clerici, Massimo; Bowden-Jones, Henrietta
2016-01-01
Background and aim Previous international research emphasized that some forms of gambling are more “addictive” than others. More recently, research has shown that we should shift our attention from the type of gambling activity to the level of involvement in a number of different gambling activities. The aim of our study was to verify whether a higher Problem Gambling Severity Index (PGSI) score was associated with particular gambling activities and evaluate the impact of involvement on gambling behavior. Methods A total of 736 treatment-seeking individuals with gambling disorder were assessed at the National Problem Gambling Clinic in London. First, the independent two-sample t-test and the Mann–Whitney test were used to verify if the PGSI score changed significantly according to the gambling activity at a bivariate level. Second, we conducted a cluster analysis and finally, we fitted a linear regression model in order to verify if some variables are useful to predict gambling addiction severity. Results The PGSI score was significantly higher for lower stakes gaming machine gamblers (1% significance level) and for fixed-odds betting terminal (FOBT) gamblers (5% significance level) at a bivariate level. Moreover, such finding was confirmed by cluster and linear regression analyses. Conclusions The results of this study indicated that gambling addiction severity was related to gambling involvement and, for a given level of gambling involvement, gambling addiction severity may vary according to gambling type, with a particularly significant increase for FOBT and gaming machine gambling. PMID:27677350
Ronzitti, Silvia; Soldini, Emiliano; Lutri, Vittorio; Smith, Neil; Clerici, Massimo; Bowden-Jones, Henrietta
2016-09-01
Background and aim Previous international research emphasized that some forms of gambling are more "addictive" than others. More recently, research has shown that we should shift our attention from the type of gambling activity to the level of involvement in a number of different gambling activities. The aim of our study was to verify whether a higher Problem Gambling Severity Index (PGSI) score was associated with particular gambling activities and evaluate the impact of involvement on gambling behavior. Methods A total of 736 treatment-seeking individuals with gambling disorder were assessed at the National Problem Gambling Clinic in London. First, the independent two-sample t-test and the Mann-Whitney test were used to verify if the PGSI score changed significantly according to the gambling activity at a bivariate level. Second, we conducted a cluster analysis and finally, we fitted a linear regression model in order to verify if some variables are useful to predict gambling addiction severity. Results The PGSI score was significantly higher for lower stakes gaming machine gamblers (1% significance level) and for fixed-odds betting terminal (FOBT) gamblers (5% significance level) at a bivariate level. Moreover, such finding was confirmed by cluster and linear regression analyses. Conclusions The results of this study indicated that gambling addiction severity was related to gambling involvement and, for a given level of gambling involvement, gambling addiction severity may vary according to gambling type, with a particularly significant increase for FOBT and gaming machine gambling.
Milot, Marie-Hélène; Spencer, Steven J.; Chan, Vicky; Allington, James P.; Klein, Julius; Chou, Cathy; Pearson-Fuhrhop, Kristin; Bobrow, James E.; Reinkensmeyer, David J.; Cramer, Steven C.
2014-01-01
Background Robotic training can help improve function of a paretic limb following a stroke, but individuals respond differently to the training. A predictor of functional gains might improve the ability to select those individuals more likely to benefit from robot based therapy. Studies evaluating predictors of functional improvement after a robotic training are scarce. One study has found that white matter tract integrity predicts functional gains following a robotic training of the hand and wrist. Objective Determine the predictive ability of behavioral and brain measures to improve selection of individuals for robotic training. Methods Twenty subjects with chronic stroke participated in an 8-week course of robotic exoskeletal training for the arm. Before training, a clinical evaluation, fMRI, diffusion tensor imaging, and transcranial magnetic stimulation (TMS) were each measured as predictors. Final functional gain was defined as change in the Box and Block Test (BBT). Measures significant in bivariate analysis were fed into a multivariate linear regression model. Results Training was associated with an average gain of 6±5 blocks on the BBT (p<0.0001). Bivariate analysis revealed that lower baseline motor evoked potential (MEP) amplitude on TMS, and lower laterality M1 index on fMRI each significantly correlated with greater BBT change. In the multivariate linear regression analysis, baseline MEP magnitude was the only measure that remained significant. Conclusion Subjects with lower baseline MEP magnitude benefited the most from robotic training of the affected arm. These subjects might have reserve remaining for the training to boost corticospinal excitability, translating into functional gains. PMID:24642382
Analysis of Blood Transfusion Data Using Bivariate Zero-Inflated Poisson Model: A Bayesian Approach.
Mohammadi, Tayeb; Kheiri, Soleiman; Sedehi, Morteza
2016-01-01
Recognizing the factors affecting the number of blood donation and blood deferral has a major impact on blood transfusion. There is a positive correlation between the variables "number of blood donation" and "number of blood deferral": as the number of return for donation increases, so does the number of blood deferral. On the other hand, due to the fact that many donors never return to donate, there is an extra zero frequency for both of the above-mentioned variables. In this study, in order to apply the correlation and to explain the frequency of the excessive zero, the bivariate zero-inflated Poisson regression model was used for joint modeling of the number of blood donation and number of blood deferral. The data was analyzed using the Bayesian approach applying noninformative priors at the presence and absence of covariates. Estimating the parameters of the model, that is, correlation, zero-inflation parameter, and regression coefficients, was done through MCMC simulation. Eventually double-Poisson model, bivariate Poisson model, and bivariate zero-inflated Poisson model were fitted on the data and were compared using the deviance information criteria (DIC). The results showed that the bivariate zero-inflated Poisson regression model fitted the data better than the other models.
Analysis of Blood Transfusion Data Using Bivariate Zero-Inflated Poisson Model: A Bayesian Approach
Mohammadi, Tayeb; Sedehi, Morteza
2016-01-01
Recognizing the factors affecting the number of blood donation and blood deferral has a major impact on blood transfusion. There is a positive correlation between the variables “number of blood donation” and “number of blood deferral”: as the number of return for donation increases, so does the number of blood deferral. On the other hand, due to the fact that many donors never return to donate, there is an extra zero frequency for both of the above-mentioned variables. In this study, in order to apply the correlation and to explain the frequency of the excessive zero, the bivariate zero-inflated Poisson regression model was used for joint modeling of the number of blood donation and number of blood deferral. The data was analyzed using the Bayesian approach applying noninformative priors at the presence and absence of covariates. Estimating the parameters of the model, that is, correlation, zero-inflation parameter, and regression coefficients, was done through MCMC simulation. Eventually double-Poisson model, bivariate Poisson model, and bivariate zero-inflated Poisson model were fitted on the data and were compared using the deviance information criteria (DIC). The results showed that the bivariate zero-inflated Poisson regression model fitted the data better than the other models. PMID:27703493
Modeling animal-vehicle collisions using diagonal inflated bivariate Poisson regression.
Lao, Yunteng; Wu, Yao-Jan; Corey, Jonathan; Wang, Yinhai
2011-01-01
Two types of animal-vehicle collision (AVC) data are commonly adopted for AVC-related risk analysis research: reported AVC data and carcass removal data. One issue with these two data sets is that they were found to have significant discrepancies by previous studies. In order to model these two types of data together and provide a better understanding of highway AVCs, this study adopts a diagonal inflated bivariate Poisson regression method, an inflated version of bivariate Poisson regression model, to fit the reported AVC and carcass removal data sets collected in Washington State during 2002-2006. The diagonal inflated bivariate Poisson model not only can model paired data with correlation, but also handle under- or over-dispersed data sets as well. Compared with three other types of models, double Poisson, bivariate Poisson, and zero-inflated double Poisson, the diagonal inflated bivariate Poisson model demonstrates its capability of fitting two data sets with remarkable overlapping portions resulting from the same stochastic process. Therefore, the diagonal inflated bivariate Poisson model provides researchers a new approach to investigating AVCs from a different perspective involving the three distribution parameters (λ(1), λ(2) and λ(3)). The modeling results show the impacts of traffic elements, geometric design and geographic characteristics on the occurrences of both reported AVC and carcass removal data. It is found that the increase of some associated factors, such as speed limit, annual average daily traffic, and shoulder width, will increase the numbers of reported AVCs and carcass removals. Conversely, the presence of some geometric factors, such as rolling and mountainous terrain, will decrease the number of reported AVCs. Published by Elsevier Ltd.
Lu, Shan; Zhao, Lan-Juan; Chen, Xiang-Ding; Papasian, Christopher J.; Wu, Ke-Hao; Tan, Li-Jun; Wang, Zhuo-Er; Pei, Yu-Fang; Tian, Qing
2018-01-01
Several studies indicated bone mineral density (BMD) and alcohol intake might share common genetic factors. The study aimed to explore potential SNPs/genes related to both phenotypes in US Caucasians at the genome-wide level. A bivariate genome-wide association study (GWAS) was performed in 2069 unrelated participants. Regular drinking was graded as 1, 2, 3, 4, 5, or 6, representing drinking alcohol never, less than once, once or twice, three to six times, seven to ten times, or more than ten times per week respectively. Hip, spine, and whole body BMDs were measured. The bivariate GWAS was conducted on the basis of a bivariate linear regression model. Sex-stratified association analyses were performed in the male and female subgroups. In males, the most significant association signal was detected in SNP rs685395 in DYNC2H1 with bivariate spine BMD and alcohol drinking (P = 1.94 × 10−8). SNP rs685395 and five other SNPs, rs657752, rs614902, rs682851, rs626330, and rs689295, located in the same haplotype block in DYNC2H1 were the top ten most significant SNPs in the bivariate GWAS in males. Additionally, two SNPs in GRIK4 in males and three SNPs in OPRM1 in females were suggestively associated with BMDs (of the hip, spine, and whole body) and alcohol drinking. Nine SNPs in IL1RN were only suggestively associated with female whole body BMD and alcohol drinking. Our study indicated that DYNC2H1 may contribute to the genetic mechanisms of both spine BMD and alcohol drinking in male Caucasians. Moreover, our study suggested potential pleiotropic roles of OPRM1 and IL1RN in females and GRIK4 in males underlying variation of both BMD and alcohol drinking. PMID:28012008
Moazzez, Ashkan; de Virgilio, Christian
2016-10-01
With constant changes in health-care laws and payment methods, profitability, and financial sustainability of hospitals are of utmost importance. The purpose of this study is to determine the relationship between surgical services and hospital profitability. The Office of Statewide Health Planning and Development annual financial databases for the years 2009 to 2011 were used for this study. The hospitals' characteristics and income statement elements were extracted for statistical analysis using bivariate and multivariate linear regression. A total of 989 financial records of 339 hospitals were included. On bivariate analysis, the number of inpatient and ambulatory operating rooms (ORs), the number of cases done both as inpatient and outpatient in each OR, and the average minutes used in inpatient ORs were significantly related with the net income of the hospital. On multivariate regression analysis, when controlling for hospitals' payer mix and the study year, only the number of inpatient cases done in the inpatient ORs (β = 832, P = 0.037), and the number of ambulatory ORs (β = 1,485, 466, P = 0.001) were significantly related with the net income of the hospital. These findings suggest that hospitals can maximize their profitability by diverting and allocating outpatient surgeries to ambulatory ORs, to allow for more inpatient surgeries.
Ludbrook, John
2010-07-01
1. There are two reasons for wanting to compare measurers or methods of measurement. One is to calibrate one method or measurer against another; the other is to detect bias. Fixed bias is present when one method gives higher (or lower) values across the whole range of measurement. Proportional bias is present when one method gives values that diverge progressively from those of the other. 2. Linear regression analysis is a popular method for comparing methods of measurement, but the familiar ordinary least squares (OLS) method is rarely acceptable. The OLS method requires that the x values are fixed by the design of the study, whereas it is usual that both y and x values are free to vary and are subject to error. In this case, special regression techniques must be used. 3. Clinical chemists favour techniques such as major axis regression ('Deming's method'), the Passing-Bablok method or the bivariate least median squares method. Other disciplines, such as allometry, astronomy, biology, econometrics, fisheries research, genetics, geology, physics and sports science, have their own preferences. 4. Many Monte Carlo simulations have been performed to try to decide which technique is best, but the results are almost uninterpretable. 5. I suggest that pharmacologists and physiologists should use ordinary least products regression analysis (geometric mean regression, reduced major axis regression): it is versatile, can be used for calibration or to detect bias and can be executed by hand-held calculator or by using the loss function in popular, general-purpose, statistical software.
Perceptions of Shared Decision Making Among Patients with Spinal Cord Injuries/Disorders.
Locatelli, Sara M; Etingen, Bella; Heinemann, Allen; Neumann, Holly DeMark; Miskovic, Ana; Chen, David; LaVela, Sherri L
2016-01-01
Background: Individuals with spinal cord injuries/disorders (SCI/D) are interested in, and benefit from, shared decision making (SDM). Objective: To explore SDM among individuals with SCI/D and how demographics and health and SCI/D characteristics are related to SDM. Method: Individuals with SCI/D who were at least 1 year post injury, resided in the Chicago metropolitan area, and received SCI care at a Veterans Affairs (VA; n = 124) or an SCI Model Systems facility ( n = 326) completed a mailed survey measuring demographics, health and SCI/D characteristics, physical and mental health status, and perceptions of care, including SDM, using the Combined Outcome Measure for Risk Communication and Treatment Decision-Making Effectiveness (COMRADE) that assesses decision-making effectiveness (effectiveness) and risk communication (communication). Bivariate analyses and multiple linear regression were used to identify variables associated with SDM. Results: Participants were mostly male (83%) and White (70%) and were an average age of 54 years ( SD = 14.3). Most had traumatic etiology, 44% paraplegia, and 49% complete injury. Veteran/civilian status and demographics were unrelated to scores. Bivariate analyses showed that individuals with tetraplegia had better effectiveness scores than those with paraplegia. Better effectiveness was correlated with better physical and mental health; better communication was correlated with better mental health. Multiple linear regressions showed that tetraplegia, better physical health, and better mental health were associated with better effectiveness, and better mental health was associated with better communication. Conclusion: SCI/D and health characteristics were the only variables associated with SDM. Interventions to increase engagement in SDM and provider attention to SDM may be beneficial, especially for individuals with paraplegia or in poorer physical and mental health.
Milot, Marie-Hélène; Spencer, Steven J; Chan, Vicky; Allington, James P; Klein, Julius; Chou, Cathy; Pearson-Fuhrhop, Kristin; Bobrow, James E; Reinkensmeyer, David J; Cramer, Steven C
2014-01-01
Robotic training can help improve function of a paretic limb following a stroke, but individuals respond differently to the training. A predictor of functional gains might improve the ability to select those individuals more likely to benefit from robot-based therapy. Studies evaluating predictors of functional improvement after a robotic training are scarce. One study has found that white matter tract integrity predicts functional gains following a robotic training of the hand and wrist. Objective. To determine the predictive ability of behavioral and brain measures in order to improve selection of individuals for robotic training. Twenty subjects with chronic stroke participated in an 8-week course of robotic exoskeletal training for the arm. Before training, a clinical evaluation, functional magnetic resonance imaging (fMRI), diffusion tensor imaging, and transcranial magnetic stimulation (TMS) were each measured as predictors. Final functional gain was defined as change in the Box and Block Test (BBT). Measures significant in bivariate analysis were fed into a multivariate linear regression model. Training was associated with an average gain of 6 ± 5 blocks on the BBT (P < .0001). Bivariate analysis revealed that lower baseline motor-evoked potential (MEP) amplitude on TMS, and lower laterality M1 index on fMRI each significantly correlated with greater BBT change. In the multivariate linear regression analysis, baseline MEP magnitude was the only measure that remained significant. Subjects with lower baseline MEP magnitude benefited the most from robotic training of the affected arm. These subjects might have reserve remaining for the training to boost corticospinal excitability, translating into functional gains. © The Author(s) 2014.
Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach
Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao
2018-01-01
When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach, and has several attractive features compared to the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, since the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. PMID:26303591
Daily commuting to work is not associated with variables of health.
Mauss, Daniel; Jarczok, Marc N; Fischer, Joachim E
2016-01-01
Commuting to work is thought to have a negative impact on employee health. We tested the association of work commute and different variables of health in German industrial employees. Self-rated variables of an industrial cohort (n = 3805; 78.9 % male) including absenteeism, presenteeism and indices reflecting stress and well-being were assessed by a questionnaire. Fasting blood samples, heart-rate variability and anthropometric data were collected. Commuting was grouped into one of four categories: 0-19.9, 20-44.9, 45-59.9, ≥60 min travelling one way to work. Bivariate associations between commuting and all variables under study were calculated. Linear regression models tested this association further, controlling for potential confounders. Commuting was positively correlated with waist circumference and inversely with triglycerides. These associations did not remain statistically significant in linear regression models controlling for age, gender, marital status, and shiftwork. No other association with variables of physical, psychological, or mental health and well-being could be found. The results indicate that commuting to work has no significant impact on well-being and health of German industrial employees.
Depression and coping in subthreshold eating disorders.
Dennard, E Eliot; Richards, C Steven
2013-08-01
The eating disorder literature has sought to understand the role of comorbid psychiatric diagnoses and coping in relation to eating disorders. The present research extends these findings by studying the relationships among depression, coping, and the entire continuum of disordered eating behaviors, with an emphasis on subthreshold eating disorders. 109 undergraduate females completed questionnaires to assess disordered eating symptoms, depressive symptoms, and the use of active and avoidant coping mechanisms. Hypotheses were tested using bivariate linear regression and multivariate linear regression. Results indicated that depression was a significant predictor of disordered eating symptoms after controlling for relationships between depression and coping. Although avoidant coping was positively associated with disordered eating, it was not a significant predictor after controlling for depression and coping. Previous research has found associations between depression and diagnosable eating disorders, and this research extends those findings to the entire continuum of disordered eating. Future research should continue to investigate the predictors and correlates of the disordered eating continuum using more diverse samples. Testing for mediation and moderation among these variables may also be a fruitful area of investigation. Published by Elsevier Ltd.
Cunningham, Marc; Bock, Ariella; Brown, Niquelle; Sacher, Suzy; Hatch, Benjamin; Inglis, Andrew; Aronovich, Dana
2015-09-01
Contraceptive prevalence rate (CPR) is a vital indicator used by country governments, international donors, and other stakeholders for measuring progress in family planning programs against country targets and global initiatives as well as for estimating health outcomes. Because of the need for more frequent CPR estimates than population-based surveys currently provide, alternative approaches for estimating CPRs are being explored, including using contraceptive logistics data. Using data from the Demographic and Health Surveys (DHS) in 30 countries, population data from the United States Census Bureau International Database, and logistics data from the Procurement Planning and Monitoring Report (PPMR) and the Pipeline Monitoring and Procurement Planning System (PipeLine), we developed and evaluated 3 models to generate country-level, public-sector contraceptive prevalence estimates for injectable contraceptives, oral contraceptives, and male condoms. Models included: direct estimation through existing couple-years of protection (CYP) conversion factors, bivariate linear regression, and multivariate linear regression. Model evaluation consisted of comparing the referent DHS prevalence rates for each short-acting method with the model-generated prevalence rate using multiple metrics, including mean absolute error and proportion of countries where the modeled prevalence rate for each method was within 1, 2, or 5 percentage points of the DHS referent value. For the methods studied, family planning use estimates from public-sector logistics data were correlated with those from the DHS, validating the quality and accuracy of current public-sector logistics data. Logistics data for oral and injectable contraceptives were significantly associated (P<.05) with the referent DHS values for both bivariate and multivariate models. For condoms, however, that association was only significant for the bivariate model. With the exception of the CYP-based model for condoms, models were able to estimate public-sector prevalence rates for each short-acting method to within 2 percentage points in at least 85% of countries. Public-sector contraceptive logistics data are strongly correlated with public-sector prevalence rates for short-acting methods, demonstrating the quality of current logistics data and their ability to provide relatively accurate prevalence estimates. The models provide a starting point for generating interim estimates of contraceptive use when timely survey data are unavailable. All models except the condoms CYP model performed well; the regression models were most accurate but the CYP model offers the simplest calculation method. Future work extending the research to other modern methods, relating subnational logistics data with prevalence rates, and tracking that relationship over time is needed. © Cunningham et al.
Cunningham, Marc; Brown, Niquelle; Sacher, Suzy; Hatch, Benjamin; Inglis, Andrew; Aronovich, Dana
2015-01-01
Background: Contraceptive prevalence rate (CPR) is a vital indicator used by country governments, international donors, and other stakeholders for measuring progress in family planning programs against country targets and global initiatives as well as for estimating health outcomes. Because of the need for more frequent CPR estimates than population-based surveys currently provide, alternative approaches for estimating CPRs are being explored, including using contraceptive logistics data. Methods: Using data from the Demographic and Health Surveys (DHS) in 30 countries, population data from the United States Census Bureau International Database, and logistics data from the Procurement Planning and Monitoring Report (PPMR) and the Pipeline Monitoring and Procurement Planning System (PipeLine), we developed and evaluated 3 models to generate country-level, public-sector contraceptive prevalence estimates for injectable contraceptives, oral contraceptives, and male condoms. Models included: direct estimation through existing couple-years of protection (CYP) conversion factors, bivariate linear regression, and multivariate linear regression. Model evaluation consisted of comparing the referent DHS prevalence rates for each short-acting method with the model-generated prevalence rate using multiple metrics, including mean absolute error and proportion of countries where the modeled prevalence rate for each method was within 1, 2, or 5 percentage points of the DHS referent value. Results: For the methods studied, family planning use estimates from public-sector logistics data were correlated with those from the DHS, validating the quality and accuracy of current public-sector logistics data. Logistics data for oral and injectable contraceptives were significantly associated (P<.05) with the referent DHS values for both bivariate and multivariate models. For condoms, however, that association was only significant for the bivariate model. With the exception of the CYP-based model for condoms, models were able to estimate public-sector prevalence rates for each short-acting method to within 2 percentage points in at least 85% of countries. Conclusions: Public-sector contraceptive logistics data are strongly correlated with public-sector prevalence rates for short-acting methods, demonstrating the quality of current logistics data and their ability to provide relatively accurate prevalence estimates. The models provide a starting point for generating interim estimates of contraceptive use when timely survey data are unavailable. All models except the condoms CYP model performed well; the regression models were most accurate but the CYP model offers the simplest calculation method. Future work extending the research to other modern methods, relating subnational logistics data with prevalence rates, and tracking that relationship over time is needed. PMID:26374805
Impact of national income and inequality on sugar and caries relationship.
Masood, M; Masood, Y; Newton, T
2012-01-01
The aim of this study was to examine the impact that national income and income inequality in high and low income countries have on the relationship between dental caries and sugar consumption. An ecological study design was used in this study of 73 countries. The mean decayed, missing, or filled permanent teeth (DMFT) for 12-year-old children were obtained from the WHO Oral Health Country/Area Profile Programme. United Nations Food and Agricultural Organization data were used for per capita sugar consumption. Gross national incomes per capita based on purchasing power parity and the Gini coefficient were obtained from World Bank data. Bivariate and multivariate linear regression analysis was performed to estimate the associations between mean DMFT and per capita sugar consumption in different income and income inequality countries. Bivariate and multivariate regression analysis showed that countries with a high national income and low income inequality have a strong negative association between sugar consumption and caries (B = -2.80, R2 = 0.17), whereas countries with a low income and high income inequality have a strong positive relationship between DMFT and per capita sugar consumption (B = -0.89, R2 = 0.20). The relationship between per capita consumption of sugar and dental caries is modified by the absolute level of income of the country, but not by the level of income inequality within a country. Copyright © 2012 S. Karger AG, Basel.
Ranking of factors determining potassium mass balance in bicarbonate haemodialysis.
Basile, Carlo; Libutti, Pasquale; Lisi, Piero; Teutonico, Annalisa; Vernaglione, Luigi; Casucci, Francesco; Lomonte, Carlo
2015-03-01
One of the most important pathogenetic factors involved in the onset of intradialysis arrhytmias is the alteration in electrolyte concentration, particularly potassium (K(+)). Two studies were performed: Study A was designed to investigate above all the isolated effect of the factor time t on intradialysis K(+) mass balance (K(+)MB): 11 stable prevalent Caucasian anuric patients underwent one standard (∼4 h) and one long-hour (∼8 h) bicarbonate haemodialysis (HD) session. The latter were pair-matched as far as the dialysate and blood volume processed (90 L) and volume of ultrafiltration are concerned. Study B was designed to identify and rank the other factors determining intradialysis K(+)MB: 63 stable prevalent Caucasian anuric patients underwent one 4-h standard bicarbonate HD session. Dialysate K(+) concentration was 2.0 mmol/L in both studies. Blood samples were obtained from the inlet blood tubing immediately before the onset of dialysis and at t60, t120, t180 min and at end of the 4- and 8-h sessions for the measurement of plasma K(+), blood bicarbonates and blood pH. Additional blood samples were obtained at t360 min for the 8 h sessions. Direct dialysate quantification was utilized for K(+)MBs. Direct potentiometry with an ion-selective electrode was used for K(+) measurements. Study A: mean K(+)MBs were significantly higher in the 8-h sessions (4 h: -88.4 ± 23.2 SD mmol versus 8 h: -101.9 ± 32.2 mmol; P = 0.02). Bivariate linear regression analyses showed that only mean plasma K(+), area under the curve (AUC) of the hourly inlet dialyser diffusion concentration gradient of K(+) (hcgAUCK(+)) and AUC of blood bicarbonates and mean blood bicarbonates were significantly related to K(+)MB in both 4- and 8-h sessions. A multiple linear regression output with K(+)MB as dependent variable showed that only mean plasma K(+), hcgAUCK(+) and duration of HD sessions per se remained statistically significant. Study B: mean K(+)MBs were -86.7 ± 22.6 mmol. Bivariate linear regression analyses showed that only mean plasma K(+), hcgAUCK(+) and mean blood bicarbonates were significantly related to K(+)MB. Again, only mean plasma K(+) and hcgAUCK(+) predicted K(+)MB at the multiple linear regression analysis. Our studies enabled to establish the ranking of factors determining intradialysis K(+)MB: plasma K(+) → dialysate K(+) gradient is the main determinant; acid-base balance plays a much less important role. The duration of HD session per se is an independent determinant of K(+)MB. © The Author 2014. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.
Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach.
Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao
2016-01-15
When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach and has several attractive features compared with the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, because the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. Copyright © 2015 John Wiley & Sons, Ltd.
Schlattmann, Peter; Verba, Maryna; Dewey, Marc; Walther, Mario
2015-01-01
Bivariate linear and generalized linear random effects are frequently used to perform a diagnostic meta-analysis. The objective of this article was to apply a finite mixture model of bivariate normal distributions that can be used for the construction of componentwise summary receiver operating characteristic (sROC) curves. Bivariate linear random effects and a bivariate finite mixture model are used. The latter model is developed as an extension of a univariate finite mixture model. Two examples, computed tomography (CT) angiography for ruling out coronary artery disease and procalcitonin as a diagnostic marker for sepsis, are used to estimate mean sensitivity and mean specificity and to construct sROC curves. The suggested approach of a bivariate finite mixture model identifies two latent classes of diagnostic accuracy for the CT angiography example. Both classes show high sensitivity but mainly two different levels of specificity. For the procalcitonin example, this approach identifies three latent classes of diagnostic accuracy. Here, sensitivities and specificities are quite different as such that sensitivity increases with decreasing specificity. Additionally, the model is used to construct componentwise sROC curves and to classify individual studies. The proposed method offers an alternative approach to model between-study heterogeneity in a diagnostic meta-analysis. Furthermore, it is possible to construct sROC curves even if a positive correlation between sensitivity and specificity is present. Copyright © 2015 Elsevier Inc. All rights reserved.
Heaphy, Emily Lenore Goldman; Loue, Sana; Sajatovic, Martha; Tisch, Daniel J
2010-11-01
Latinos in the United States have been identified as a high-risk group for depression, anxiety, and substance abuse. HIV/AIDS has disproportionately impacted Latinos. Review findings suggest that HIV-risk behaviors among persons with severe mental illness (SMI) are influenced by a multitude of factors including psychiatric illness, cognitive-behavioral factors, substance use, childhood abuse, and social relationships. To examine the impact of psychiatric and social correlates of HIV sexual risk behavior in Puerto Rican women with SMI. Data collected longitudinally (from 2002 to 2005) in semi-structured interviews and from non-continuous participant observation was analyzed using a cross-sectional design. Bivariate associations between predictor variables and sexual risk behaviors were examined using binary and ordinal logistic regression. Linear regression was used to examine the association between significant predictor variables and the total number of risk behaviors the women engaged in during the 6 months prior to baseline. Just over one-third (35.9%) of the study population (N = 53) was diagnosed with bipolar disorder and GAF scores ranged from 30 to 80 with a median score of 60. Participants ranged in age from 18 to 50 years (M = 32.6 ± 8.7), three-fourths reported a history of either sexual or physical abuse or of both in childhood, and one-fourth had abused substances in their lifetimes. Bivariate analyses indicated that psychiatric and social factors were differentially associated with sexual risk behaviors. Multivariate linear regression models showed that suffering from increased severity of psychiatric symptoms and factors and living below the poverty line are predictive of engagement in a greater number of HIV sexual risk behaviors. Puerto Rican women with SMI are at high risk for HIV infection and are in need of targeted sexual risk reduction interventions that simultaneously address substance abuse prevention and treatment, childhood abuse, and the indirect effects associated with SMI such as living in poverty. Mental health programs should address risk behavior among adults with SMI in the context of specific symptomatology and comorbidities.
Brunette, Amanda M; Holm, Kristen E; Wamboldt, Frederick S; Kozora, Elizabeth; Moser, David J; Make, Barry J; Crapo, James D; Meschede, Kimberly; Weinberger, Howard D; Moreau, Kerrie L; Bowler, Russell P; Hoth, Karin F
2018-05-01
This study examined the association of perceived cognitive difficulties with objective cognitive performance in former smokers. We hypothesized that greater perceived cognitive difficulties would be associated with poorer performance on objective executive and memory tasks. Participants were 95 former smokers recruited from the COPDGene study. They completed questionnaires (including the Cognitive Difficulties Scale [CDS] and the Hospital Anxiety and Depression Scale [HADS]), neuropsychological assessment, and pulmonary function testing. Pearson correlations and t-tests were conducted to examine the bivariate association of the CDS (total score and subscales for attention/concentration, praxis, delayed recall, orientation for persons, temporal orientation, and prospective memory) with each domain of objective cognitive functioning (memory recall, executive functioning/processing speed, visuospatial processing, and language). Simultaneous multiple linear regression was used to further examine all statistically significant bivariate associations. The following covariates were included in all regression models: age, sex, pack-years, premorbid functioning (WRAT-IV Reading), HADS total score, and chronic obstructive pulmonary disease (COPD) status (yes/no based on GOLD criteria). In regression models, greater perceived cognitive difficulties overall (using CDS total score) were associated with poorer performance on executive functioning/processing speed tasks (b = -0.07, SE = 0.03, p = .037). Greater perceived cognitive difficulties on the CDS praxis subscale were associated with poorer performance on executive functioning/processing speed tasks (b = -3.65, SE = 1.25, p = .005), memory recall tasks (b = -4.60, SE = 1.75, p = .010), and language tasks (b = -3.89, SE = 1.39, p = .006). Clinicians should be aware that cognitive complaints may be indicative of problems with the executive functioning/processing speed and memory of former smokers with and without COPD.
Caruso, Rosario; Scordino, Monica; Traulo, Pasqualino; Gagliano, Giacomo
2012-01-01
A capillary GC-flame ionization detection (FID) method to determine volatile compounds (ethyl acetate, 1,1-diethoxyethane, methyl alcohol, 1-propanol, 2-methyl-1-propanol, 2-methyl-1-butanol, 3-methyl-1-butanol, 1-butanol, and 2-butanol) in wine was investigated in terms of calculation of detection limits and calibration method. The main objectives were: (1) calculation of regression coefficient parameters by ordinary least-squares (OLS) and bivariate least-squares (BLS) regression models, taking into account errors in both axes; (2) estimation of linear dynamic range (LDR) according to International Conference on Harmonization recommendations; (3) performance evaluation of a method by using three different internal standards (ISs) such as acetonitrile, acetone, and 1-pentanol; (4) evaluation of LODs according to the U.S. Environmental Protection Agency (EPA) 3sigma approach and the Hubaux-Vos (H-V) method; (5) application of H-V theory to a gas chromatographic analytical method and to a food matrix; and (6) accuracy assessment of the method relative to methyl alcohol content through a Unione Italiana Vini (UIV) interlaboratory proficiency test. Calibration curves calculated via BLS and OLS show similar slopes, while intercepts are closer to zero in the first case, independent of the chosen IS. The studied ISs show a substantially equivalent behavior, even though the IS closer to the analyte retention time seems to be more appropriate in terms of LDR and LOD. Results indicate an underestimation of LODs using the EPA 3sigma approach instead of the more realistic H-V method, both with OLS and BLS regression models. Methanol contents compared with UIV average values indicate recovery between 90 and 110%.
Multi scale habitat relationships of Martes americana in northern Idaho, U.S.A.
Tzeidle N. Wasserman; Samuel A. Cushman; David O. Wallin; Jim Hayden
2012-01-01
We used bivariate scaling and logistic regression to investigate multiple-scale habitat selection by American marten (Martes americana). Bivariate scaling reveals dramatic differences in the apparent nature and strength of relationships between marten occupancy and a number of habitat variables across a range of spatial scales. These differences include reversals in...
Language and hope in schizophrenia-spectrum disorders.
Bonfils, Kelsey A; Luther, Lauren; Firmin, Ruth L; Lysaker, Paul H; Minor, Kyle S; Salyers, Michelle P
2016-11-30
Hope is integral to recovery for those with schizophrenia. Considering recent advancements in the examination of clients' lexical qualities, we were interested in how clients' words reflect hope. Using computerized lexical analysis, we examined social, emotion, and future words' relations to hope and its pathways and agency components. Forty-five clients provided detailed narratives about their life and mental illness. Transcripts were analyzed using the Linguistic Inquiry and Word Count program (LIWC), which assigns words to categories (e.g., "anxiety") based on a pre-existing dictionary. Correlations and linear multiple regression were used to examine relationships between lexical qualities and hope. Hope and its subcomponents had significant or trending bivariate correlations in expected directions with several emotion-related word categories (anger and sadness) but were not associated with expected categories such as social words, positive emotions, optimism, achievement, and future words. In linear multiple regressions, no LIWC variable significantly predicted hope agency, but anger words significantly predicted both total hope and hope pathways. Our findings indicate lexical analysis tools can be used to investigate recovery-oriented concepts such as hope, and results may inform clinical practice. Future research should aim to replicate our findings in larger samples. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Social determinants of childhood asthma symptoms: an ecological study in urban Latin America.
Fattore, Gisel L; Santos, Carlos A T; Barreto, Mauricio L
2014-04-01
Asthma is an important public health problem in urban Latin America. This study aimed to analyze the role of socioeconomic and environmental factors as potential determinants of asthma symptoms prevalence in children from Latin American (LA) urban centers. We selected 31 LA urban centers with complete data, and an ecological analysis was performed. According to our theoretical framework, the explanatory variables were classified in three levels: distal, intermediate, and proximate. The association between variables in the three levels and prevalence of asthma symptoms was examined by bivariate and multivariate linear regression analysis weighed by sample size. In a second stage, we fitted several linear regression models introducing sequentially the variables according to the predefined hierarchy. In the final hierarchical model Gini Index, crowding, sanitation, variation in infant mortality rates and homicide rates, explained great part of the variance in asthma prevalence between centers (R(2) = 75.0 %). We found a strong association between socioeconomic and environmental variables and prevalence of asthma symptoms in LA urban children, and according to our hierarchical framework and the results found we suggest that social inequalities (measured by the Gini Index) is a central determinant to explain high prevalence of asthma in LA.
Bivariate discrete beta Kernel graduation of mortality data.
Mazza, Angelo; Punzo, Antonio
2015-07-01
Various parametric/nonparametric techniques have been proposed in literature to graduate mortality data as a function of age. Nonparametric approaches, as for example kernel smoothing regression, are often preferred because they do not assume any particular mortality law. Among the existing kernel smoothing approaches, the recently proposed (univariate) discrete beta kernel smoother has been shown to provide some benefits. Bivariate graduation, over age and calendar years or durations, is common practice in demography and actuarial sciences. In this paper, we generalize the discrete beta kernel smoother to the bivariate case, and we introduce an adaptive bandwidth variant that may provide additional benefits when data on exposures to the risk of death are available; furthermore, we outline a cross-validation procedure for bandwidths selection. Using simulations studies, we compare the bivariate approach proposed here with its corresponding univariate formulation and with two popular nonparametric bivariate graduation techniques, based on Epanechnikov kernels and on P-splines. To make simulations realistic, a bivariate dataset, based on probabilities of dying recorded for the US males, is used. Simulations have confirmed the gain in performance of the new bivariate approach with respect to both the univariate and the bivariate competitors.
de Freitas, Brunnella Alcantara Chagas; Sant'Ana, Luciana Ferreira da Rocha; Longo, Giana Zarbato; Siqueira-Batista, Rodrigo; Priore, Silvia Eloiza; Franceschin, Sylvia do Carmo Castro
2012-01-01
Objective To analyze the process of care provided to premature infants in a neonatal intensive care unit and the factors associated with their mortality. Methods Cross-sectional retrospective study of premature infants in an intensive care unit between 2008 and 2010. The characteristics of the mothers and premature infants were described, and a bivariate analysis was performed on the following characteristics: the study period and the "death" outcome (hospital, neonatal and early) using Pearson's chi-square test, Fisher's exact test or a chi-square test for linear trends. Bivariate and multivariable logistic regression analyses were performed using a stepwise backward logistic regression method between the variables with p<0.20 and the "death" outcome. A p value <0.05 was considered to be significant. Results In total, 293 preterm infants were studied. Increased access to complementary tests (transfontanellar ultrasound and Doppler echocardiogram) and breastfeeding rates were indicators of improving care. Mortality was concentrated in the neonatal period, especially in the early neonatal period, and was associated with extreme prematurity, small size for gestational age and an Apgar score <7 at 5 minutes after birth. The late-onset sepsis was also associated with a greater chance of neonatal death, and antenatal corticosteroids were protective against neonatal and early deaths. Conclusions Although these results are comparable to previous findings regarding mortality among premature infants in Brazil, the study emphasizes the need to implement strategies that promote breastfeeding and reduce neonatal mortality and its early component. PMID:23917938
Landscape controls on total and methyl Hg in the Upper Hudson River basin, New York, USA
Burns, Douglas A.; Riva-Murray, K.; Bradley, P.M.; Aiken, G.R.; Brigham, M.E.
2012-01-01
Approaches are needed to better predict spatial variation in riverine Hg concentrations across heterogeneous landscapes that include mountains, wetlands, and open waters. We applied multivariate linear regression to determine the landscape factors and chemical variables that best account for the spatial variation of total Hg (THg) and methyl Hg (MeHg) concentrations in 27 sub-basins across the 493 km2 upper Hudson River basin in the Adirondack Mountains of New York. THg concentrations varied by sixfold, and those of MeHg by 40-fold in synoptic samples collected at low-to-moderate flow, during spring and summer of 2006 and 2008. Bivariate linear regression relations of THg and MeHg concentrations with either percent wetland area or DOC concentrations were significant but could account for only about 1/3 of the variation in these Hg forms in summer. In contrast, multivariate linear regression relations that included metrics of (1) hydrogeomorphology, (2) riparian/wetland area, and (3) open water, explained about 66% to >90% of spatial variation in each Hg form in spring and summer samples. These metrics reflect the influence of basin morphometry and riparian soils on Hg source and transport, and the role of open water as a Hg sink. Multivariate models based solely on these landscape metrics generally accounted for as much or more of the variation in Hg concentrations than models based on chemical and physical metrics, and show great promise for identifying waters with expected high Hg concentrations in the Adirondack region and similar glaciated riverine ecosystems.
Giacomino, Agnese; Abollino, Ornella; Malandrino, Mery; Mentasti, Edoardo
2011-03-04
Single and sequential extraction procedures are used for studying element mobility and availability in solid matrices, like soils, sediments, sludge, and airborne particulate matter. In the first part of this review we reported an overview on these procedures and described the applications of chemometric uni- and bivariate techniques and of multivariate pattern recognition techniques based on variable reduction to the experimental results obtained. The second part of the review deals with the use of chemometrics not only for the visualization and interpretation of data, but also for the investigation of the effects of experimental conditions on the response, the optimization of their values and the calculation of element fractionation. We will describe the principles of the multivariate chemometric techniques considered, the aims for which they were applied and the key findings obtained. The following topics will be critically addressed: pattern recognition by cluster analysis (CA), linear discriminant analysis (LDA) and other less common techniques; modelling by multiple linear regression (MLR); investigation of spatial distribution of variables by geostatistics; calculation of fractionation patterns by a mixture resolution method (Chemometric Identification of Substrates and Element Distributions, CISED); optimization and characterization of extraction procedures by experimental design; other multivariate techniques less commonly applied. Copyright © 2010 Elsevier B.V. All rights reserved.
ERIC Educational Resources Information Center
Kim, Hyung Jin; Brennan, Robert L.; Lee, Won-Chan
2017-01-01
In equating, when common items are internal and scoring is conducted in terms of the number of correct items, some pairs of total scores ("X") and common-item scores ("V") can never be observed in a bivariate distribution of "X" and "V"; these pairs are called "structural zeros." This simulation…
Interpreting Bivariate Regression Coefficients: Going beyond the Average
ERIC Educational Resources Information Center
Halcoussis, Dennis; Phillips, G. Michael
2010-01-01
Statistics, econometrics, investment analysis, and data analysis classes often review the calculation of several types of averages, including the arithmetic mean, geometric mean, harmonic mean, and various weighted averages. This note shows how each of these can be computed using a basic regression framework. By recognizing when a regression model…
Molenaar, Dylan; Tuerlinckx, Francis; van der Maas, Han L J
2015-01-01
A generalized linear modeling framework to the analysis of responses and response times is outlined. In this framework, referred to as bivariate generalized linear item response theory (B-GLIRT), separate generalized linear measurement models are specified for the responses and the response times that are subsequently linked by cross-relations. The cross-relations can take various forms. Here, we focus on cross-relations with a linear or interaction term for ability tests, and cross-relations with a curvilinear term for personality tests. In addition, we discuss how popular existing models from the psychometric literature are special cases in the B-GLIRT framework depending on restrictions in the cross-relation. This allows us to compare existing models conceptually and empirically. We discuss various extensions of the traditional models motivated by practical problems. We also illustrate the applicability of our approach using various real data examples, including data on personality and cognitive ability.
Neighbourhood fast food outlets and obesity in children and adults: the CLAN Study.
Crawford, David A; Timperio, Anna F; Salmon, Jo A; Baur, Louise; Giles-Corti, Billie; Roberts, Rebecca J; Jackson, Michelle L; Andrianopoulos, Nick; Ball, Kylie
2008-01-01
We examined associations between density of and proximity to fast food outlets and body weight in a sample of children (137 aged 8-9 years and 243 aged 13-15 years) and their parents (322 fathers and 362 mothers). Children's measured and parents' self-reported heights and weights were used to calculate body mass index (BMI). Locations of major fast food outlets were geocoded. Bivariate linear regression analyses examined associations between the presence of any fast food outlet within a 2 km buffer around participants' homes, fast food outlet density within the 2 km buffer, and distance to the nearest outlet and BMI. Each independent variable was also entered into separate bivariate logistic regression analyses to predict the odds of being overweight or obese. Among older children, those with at least one outlet within 2 km had lower BMI z-scores. The further that fathers lived from an outlet, the higher their BMI. Among 13-15-year-old girls and their fathers, the likelihood of overweight/obesity was reduced by 80% and 50%, respectively, if they had at least one fast food outlet within 2 km of their home. Among older girls, the likelihood of being overweight/obese was reduced by 14% with each additional outlet within 2 km. Fathers' odds of being overweight/obese increased by 13% for each additional kilometre to the nearest outlet. While consumption of fast food has been shown to be associated with obesity, this study provides little support for the concept that exposure to fast food outlets in the local neighbourhood increases risk of obesity.
Demographic and clinical features related to perceived discrimination in schizophrenia.
Fresán, Ana; Robles-García, Rebeca; Madrigal, Eduardo; Tovilla-Zarate, Carlos-Alfonso; Martínez-López, Nicolás; Arango de Montis, Iván
2018-04-01
Perceived discrimination contributes to the development of internalized stigma among those with schizophrenia. Evidence on demographic and clinical factors related to the perception of discrimination among this population is both contradictory and scarce in low- and middle-income countries. Accordingly, the main purpose of this study is to determine the demographic and clinical factors predicting the perception of discrimination among Mexican patients with schizophrenia. Two hundred and seventeen adults with paranoid schizophrenia completed an interview on their demographic status and clinical characteristics. Symptom severity was assessed using the Positive and Negative Syndrome Scale; and perceived discrimination using 13 items from the King's Internalized Stigma Scale. Bivariate linear associations were determined to identify the variables of interest to be included in a linear regression analysis. Years of education, age of illness onset and length of hospitalization were associated with discrimination. However, only age of illness onset and length of hospitalization emerged as predictors of perceived discrimination in the final regression analysis, with longer length of hospitalization being the independent variable with the greatest contribution. Fortunately, this is a modifiable factor regarding the perception of discrimination and self-stigma. Strategies for achieving this as part of community-based mental health care are also discussed. Copyright © 2017 Elsevier B.V. All rights reserved.
The bivariate regression model and its application
NASA Astrophysics Data System (ADS)
Pratikno, B.; Sulistia, L.; Saniyah
2018-03-01
The paper studied a bivariate regression model (BRM) and its application. The maximum power and minimum size are used to choose the eligible tests using non-sample prior information (NSPI). In the simulation study on real data, we used Wilk’s lamda to determine the best model of the BRM. The result showed that the power of the pre-test-test (PTT) on the NSPI is a significant choice of the tests among unrestricted test (UT) and restricted test (RT), and the best model of the BRM is Y (1) = ‑894 + 46X and Y (2) = 78 + 0.2X with significant Wilk’s lamda 0.88 < 0.90 (Wilk’s table).
Salazar, Edwin; Buitrago, Carolina; Molina, Federico; Alzate, Catalina Arango
2015-05-01
Determine the trend in mortality from external causes in pregnant and postpartum women and its relationship to socioeconomic factors. Descriptive study, based on the official registries of deaths reported by the National Statistics Agency, 1998-2010. The trend was analyzed using Poisson regressions. Bivariate correlations and multiple linear regression models were constructed to explore the relationship between mortality and socioeconomic factors: human development index, Gini index, gross domestic product, unsatisfied basic needs, unemployment rate, poverty, extreme poverty, quality of life index, illiteracy rate, and percentage of affiliation to the Social Security System. A total of 2 223 female deaths from external causes were recorded, of which 1 429 occurred during pregnancy and 794 in the postpartum period. The gross mortality rate dropped from 30.7 per 100 000 live births plus fetal deaths in 1998 to 16.7 in 2010. A downward curve with no significant inflection points was shown in the risk of dying from this cause. The multiple linear regression model showed a correlation between mortality and extreme poverty and the illiteracy rate, suggesting that these indicators could explain 89.4% of the change in mortality from external causes in pregnant and postpartum women each year in Colombia. Mortality from external causes in pregnant and postpartum women showed a significant downward trend that may be explained by important socioeconomic changes in the country, including a decrease in extreme poverty and in the illiteracy rate.
Thakar, Sumit; Sivaraju, Laxminadh; Jacob, Kuruthukulangara S; Arun, Aditya Atal; Aryan, Saritha; Mohan, Dilip; Sai Kiran, Narayanam Anantha; Hegde, Alangar S
2018-01-01
OBJECTIVE Although various predictors of postoperative outcome have been previously identified in patients with Chiari malformation Type I (CMI) with syringomyelia, there is no known algorithm for predicting a multifactorial outcome measure in this widely studied disorder. Using one of the largest preoperative variable arrays used so far in CMI research, the authors attempted to generate a formula for predicting postoperative outcome. METHODS Data from the clinical records of 82 symptomatic adult patients with CMI and altered hindbrain CSF flow who were managed with foramen magnum decompression, C-1 laminectomy, and duraplasty over an 8-year period were collected and analyzed. Various preoperative clinical and radiological variables in the 57 patients who formed the study cohort were assessed in a bivariate analysis to determine their ability to predict clinical outcome (as measured on the Chicago Chiari Outcome Scale [CCOS]) and the resolution of syrinx at the last follow-up. The variables that were significant in the bivariate analysis were further analyzed in a multiple linear regression analysis. Different regression models were tested, and the model with the best prediction of CCOS was identified and internally validated in a subcohort of 25 patients. RESULTS There was no correlation between CCOS score and syrinx resolution (p = 0.24) at a mean ± SD follow-up of 40.29 ± 10.36 months. Multiple linear regression analysis revealed that the presence of gait instability, obex position, and the M-line-fourth ventricle vertex (FVV) distance correlated with CCOS score, while the presence of motor deficits was associated with poor syrinx resolution (p ≤ 0.05). The algorithm generated from the regression model demonstrated good diagnostic accuracy (area under curve 0.81), with a score of more than 128 points demonstrating 100% specificity for clinical improvement (CCOS score of 11 or greater). The model had excellent reliability (κ = 0.85) and was validated with fair accuracy in the validation cohort (area under the curve 0.75). CONCLUSIONS The presence of gait imbalance and motor deficits independently predict worse clinical and radiological outcomes, respectively, after decompressive surgery for CMI with altered hindbrain CSF flow. Caudal displacement of the obex and a shorter M-line-FVV distance correlated with good CCOS scores, indicating that patients with a greater degree of hindbrain pathology respond better to surgery. The proposed points-based algorithm has good predictive value for postoperative multifactorial outcome in these patients.
Song, Yong-Ze; Yang, Hong-Lei; Peng, Jun-Huan; Song, Yi-Rong; Sun, Qian; Li, Yuan
2015-01-01
Particulate matter with an aerodynamic diameter <2.5 μm (PM2.5) represents a severe environmental problem and is of negative impact on human health. Xi'an City, with a population of 6.5 million, is among the highest concentrations of PM2.5 in China. In 2013, in total, there were 191 days in Xi’an City on which PM2.5 concentrations were greater than 100 μg/m3. Recently, a few studies have explored the potential causes of high PM2.5 concentration using remote sensing data such as the MODIS aerosol optical thickness (AOT) product. Linear regression is a commonly used method to find statistical relationships among PM2.5 concentrations and other pollutants, including CO, NO2, SO2, and O3, which can be indicative of emission sources. The relationships of these variables, however, are usually complicated and non-linear. Therefore, a generalized additive model (GAM) is used to estimate the statistical relationships between potential variables and PM2.5 concentrations. This model contains linear functions of SO2 and CO, univariate smoothing non-linear functions of NO2, O3, AOT and temperature, and bivariate smoothing non-linear functions of location and wind variables. The model can explain 69.50% of PM2.5 concentrations, with R2 = 0.691, which improves the result of a stepwise linear regression (R2 = 0.582) by 18.73%. The two most significant variables, CO concentration and AOT, represent 20.65% and 19.54% of the deviance, respectively, while the three other gas-phase concentrations, SO2, NO2, and O3 account for 10.88% of the total deviance. These results show that in Xi'an City, the traffic and other industrial emissions are the primary source of PM2.5. Temperature, location, and wind variables also non-linearly related with PM2.5. PMID:26540446
Fananapazir, Ghaneh; Benzl, Robert; Corwin, Michael T; Chen, Ling-Xin; Sageshima, Junichiro; Stewart, Susan L; Troppmann, Christoph
2018-07-01
Purpose To determine whether the predonation computed tomography (CT)-based volume of the future remnant kidney is predictive of postdonation renal function in living kidney donors. Materials and Methods This institutional review board-approved, retrospective, HIPAA-compliant study included 126 live kidney donors who had undergone predonation renal CT between January 2007 and December 2014 as well as 2-year postdonation measurement of estimated glomerular filtration rate (eGFR). The whole kidney volume and cortical volume of the future remnant kidney were measured and standardized for body surface area (BSA). Bivariate linear associations between the ratios of whole kidney volume to BSA and cortical volume to BSA were obtained. A linear regression model for 2-year postdonation eGFR that incorporated donor age, sex, and either whole kidney volume-to-BSA ratio or cortical volume-to-BSA ratio was created, and the coefficient of determination (R 2 ) for the model was calculated. Factors not statistically additive in assessing 2-year eGFR were removed by using backward elimination, and the coefficient of determination for this parsimonious model was calculated. Results Correlation was slightly better for cortical volume-to-BSA ratio than for whole kidney volume-to-BSA ratio (r = 0.48 vs r = 0.44, respectively). The linear regression model incorporating all donor factors had an R 2 of 0.66. The only factors that were significantly additive to the equation were cortical volume-to-BSA ratio and predonation eGFR (P = .01 and P < .01, respectively), and the final parsimonious linear regression model incorporating these two variables explained almost the same amount of variance (R 2 = 0.65) as did the full model. Conclusion The cortical volume of the future remnant kidney helped predict postdonation eGFR at 2 years. The cortical volume-to-BSA ratio should thus be considered for addition as an important variable to living kidney donor evaluation and selection guidelines. © RSNA, 2018.
Miner, Patricia Johnson; Alexander, Jeffrey; Ewing, Helen; Gerace, Laina
2013-08-01
The purpose of this study was to determine the association between adherence to prescribed antiepileptic medication in a convenience sample of caregivers (n = 100) of children diagnosed with epilepsy, ages 2-14 years, and caregivers' beliefs about the medication. Using the Beliefs about Medication Questionnaire and Medication Adherence Report Scale, caregivers were questioned about beliefs of necessity and concerns associated with medication adherence. Using bivariate linear regression, no significant correlation was found between necessity for antiepileptic drug treatment or caregiver's concerns and medication adherence. Nevertheless, although only 28% of the respondents reported complete adherence, the majority of caregivers perceived their child's medication was necessary to maintain good health. Educational aspects and social desirability in this setting may have contributed to the discordance between adherence and caregivers' beliefs.
Pelvic-floor strength in women with incontinence as assessed by the brink scale.
FitzGerald, Mary P; Burgio, Kathryn L; Borello-France, Diane F; Menefee, Shawn A; Schaffer, Joseph; Kraus, Stephen; Mallett, Veronica T; Xu, Yan
2007-10-01
The purpose of this study was to describe how clinical pelvic-floor muscle (PFM) strength (force-generating capacity) is related to patient characteristics, lower urinary tract symptoms, and fecal incontinence symptoms. Data were obtained from 643 women who were participating in a randomized surgical trial for treatment of stress urinary incontinence. Patient demographic variables, baseline urinary and fecal incontinence symptom questionnaires, urodynamic data and urinary diary data, pad test results, and standardized assessment of pelvic organ support were compared with PFM strength as described by the Brink scoring system. Bivariate analysis of factors associated with the Brink scale score was done using analysis of variance and linear regression. Multivariate analysis included patient variables that were significant on bivariate analysis. The mean Brink scale score was 9 (SD=2) and did not vary widely in this large, but highly select, patient sample. We found a weak, but statistically strong, relationship between age and Brink score. Brink scores were not related to diary and pad test measures of incontinence severity. Overall, PFM strength was good in this sample of women with stress incontinence. Scores tended to be similar, and it is possible that the Brink scale does not reflect real clinical differences in PFM strength.
Du, Juan; Yang, Fang; Zhang, Zhiqiang; Hu, Jingze; Xu, Qiang; Hu, Jianping; Zeng, Fanyong; Lu, Guangming; Liu, Xinfeng
2018-05-15
An accurate prediction of long term outcome after stroke is urgently required to provide early individualized neurorehabilitation. This study aimed to examine the added value of early neuroimaging measures and identify the best approaches for predicting motor outcome after stroke. This prospective study involved 34 first-ever ischemic stroke patients (time since stroke: 1-14 days) with upper limb impairment. All patients underwent baseline multimodal assessments that included clinical (age, motor impairment), neurophysiological (motor-evoked potentials, MEP) and neuroimaging (diffusion tensor imaging and motor task-based fMRI) measures, and also underwent reassessment 3 months after stroke. Bivariate analysis and multivariate linear regression models were used to predict the motor scores (Fugl-Meyer assessment, FMA) at 3 months post-stroke. With bivariate analysis, better motor outcome significantly correlated with (1) less initial motor impairment and disability, (2) less corticospinal tract injury, (3) the initial presence of MEPs, (4) stronger baseline motor fMRI activations. In multivariate analysis, incorporating neuroimaging data improved the predictive accuracy relative to only clinical and neurophysiological assessments. Baseline fMRI activation in SMA was an independent predictor of motor outcome after stroke. A multimodal model incorporating fMRI and clinical measures best predicted the motor outcome following stroke. fMRI measures obtained early after stroke provided independent prediction of long-term motor outcome.
NASA Astrophysics Data System (ADS)
Xenopoulos, M. A.; Vogt, R. J.
2014-12-01
There is now increasing evidence that non-linearity is a common response in ecological systems to pressures caused by human activities. There is also increasing evidence that exogenous environmental drivers, such as climate, induce spatial and temporal synchrony in a wide range of ecological variables. Using Moran's I and Pearson's correlation, we quantified the synchrony of dissolved organic carbon concentration (DOC) and quality (DOM; e.g., specific UV absorbance, Fluorescence Index, PARAFAC), nutrients, discharge and temperature in 40 streams that span an agriculture gradient (0 to >70% cropland), over 10 years. We then used breakpoint regression, 2D-Kolmogorov-Smirnov test and significant zero crossings (SiZer) analyses to quantify the prevalence of nonlinearity and ecological thresholds (breakpoints) where applicable. There was a high degree of synchrony in DOM quality (r > 0.7) but not DOC (r < 0.4). The degree of synchrony was driven in part by the catchment's land use. With respect to the nonlinear analyses we found non-linearity in ~50% of bivariate datasets analyzed. Non-linearity was also driven in part by the catchment's land use. Breakpoints defined different DOM properties. Nonlinearity and synchronous behaviour in DOM are intimately linked to land use.
Agarwal, Shivani; Jawad, Abbas F; Miller, Victoria A
2016-11-01
The current study examined how a comprehensive set of variables from multiple domains, including at the adolescent and family level, were predictive of glycemic control in adolescents with type 1 diabetes (T1D). Participants included 100 adolescents with T1D ages 10-16 yrs and their parents. Participants were enrolled in a longitudinal study about youth decision-making involvement in chronic illness management of which the baseline data were available for analysis. Bivariate associations with glycemic control (HbA1C) were tested. Hierarchical linear regression was implemented to inform the predictive model. In bivariate analyses, race, family structure, household income, insulin regimen, adolescent-reported adherence to diabetes self-management, cognitive development, adolescent responsibility for T1D management, and parent behavior during the illness management discussion were associated with HbA1c. In the multivariate model, the only significant predictors of HbA1c were race and insulin regimen, accounting for 17% of the variance. Caucasians had better glycemic control than other racial groups. Participants using pre-mixed insulin therapy and basal-bolus insulin had worse glycemic control than those on insulin pumps. This study shows that despite associations of adolescent and family-level variables with glycemic control at the bivariate level, only race and insulin regimen are predictive of glycemic control in hierarchical multivariate analyses. This model offers an alternative way to examine the relationship of demographic and psychosocial factors on glycemic control in adolescents with T1D. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Squires, Janet E; Estabrooks, Carole A; Newburn-Cook, Christine V; Gierl, Mark
2011-05-19
There is a lack of acceptable, reliable, and valid survey instruments to measure conceptual research utilization (CRU). In this study, we investigated the psychometric properties of a newly developed scale (the CRU Scale). We used the Standards for Educational and Psychological Testing as a validation framework to assess four sources of validity evidence: content, response processes, internal structure, and relations to other variables. A panel of nine international research utilization experts performed a formal content validity assessment. To determine response process validity, we conducted a series of one-on-one scale administration sessions with 10 healthcare aides. Internal structure and relations to other variables validity was examined using CRU Scale response data from a sample of 707 healthcare aides working in 30 urban Canadian nursing homes. Principal components analysis and confirmatory factor analyses were conducted to determine internal structure. Relations to other variables were examined using: (1) bivariate correlations; (2) change in mean values of CRU with increasing levels of other kinds of research utilization; and (3) multivariate linear regression. Content validity index scores for the five items ranged from 0.55 to 1.00. The principal components analysis predicted a 5-item 1-factor model. This was inconsistent with the findings from the confirmatory factor analysis, which showed best fit for a 4-item 1-factor model. Bivariate associations between CRU and other kinds of research utilization were statistically significant (p < 0.01) for the latent CRU scale score and all five CRU items. The CRU scale score was also shown to be significant predictor of overall research utilization in multivariate linear regression. The CRU scale showed acceptable initial psychometric properties with respect to responses from healthcare aides in nursing homes. Based on our validity, reliability, and acceptability analyses, we recommend using a reduced (four-item) version of the CRU scale to yield sound assessments of CRU by healthcare aides. Refinement to the wording of one item is also needed. Planned future research will include: latent scale scoring, identification of variables that predict and are outcomes to conceptual research use, and longitudinal work to determine CRU Scale sensitivity to change.
Role of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) in local dengue epidemics in Taiwan.
Tsai, Pui-Jen; Teng, Hwa-Jen
2016-11-09
Aedes mosquitoes in Taiwan mainly comprise Aedes albopictus and Ae. aegypti. However, the species contributing to autochthonous dengue spread and the extent at which it occurs remain unclear. Thus, in this study, we spatially analyzed real data to determine spatial features related to local dengue incidence and mosquito density, particularly that of Ae. albopictus and Ae. aegypti. We used bivariate Moran's I statistic and geographically weighted regression (GWR) spatial methods to analyze the globally spatial dependence and locally regressed relationship between (1) imported dengue incidences and Breteau indices (BIs) of Ae. albopictus, (2) imported dengue incidences and BI of Ae. aegypti, (3) autochthonous dengue incidences and BI of Ae. albopictus, (4) autochthonous dengue incidences and BI of Ae. aegypti, (5) all dengue incidences and BI of Ae. albopictus, (6) all dengue incidences and BI of Ae. aegypti, (7) BI of Ae. albopictus and human population density, and (8) BI of Ae. aegypti and human population density in 348 townships in Taiwan. In the GWR models, regression coefficients of spatially regressed relationships between the incidence of autochthonous dengue and vector density of Ae. aegypti were significant and positive in most townships in Taiwan. However, Ae. albopictus had significant but negative regression coefficients in clusters of dengue epidemics. In the global bivariate Moran's index, spatial dependence between the incidence of autochthonous dengue and vector density of Ae. aegypti was significant and exhibited positive correlation in Taiwan (bivariate Moran's index = 0.51). However, Ae. albopictus exhibited positively significant but low correlation (bivariate Moran's index = 0.06). Similar results were observed in the two spatial methods between all dengue incidences and Aedes mosquitoes (Ae. aegypti and Ae. albopictus). The regression coefficients of spatially regressed relationships between imported dengue cases and Aedes mosquitoes (Ae. aegypti and Ae. albopictus) were significant in 348 townships in Taiwan. The results indicated that local Aedes mosquitoes do not contribute to the dengue incidence of imported cases. The density of Ae. aegypti positively correlated with the density of human population. By contrast, the density of Ae. albopictus negatively correlated with the density of human population in the areas of southern Taiwan. The results indicated that Ae. aegypti has more opportunities for human-mosquito contact in dengue endemic areas in southern Taiwan. Ae. aegypti, but not Ae. albopictus, and human population density in southern Taiwan are closely associated with an increased risk of autochthonous dengue incidence.
Ganz, Patricia A; Petersen, Laura; Castellon, Steven A; Bower, Julienne E; Silverman, Daniel H S; Cole, Steven W; Irwin, Michael R; Belin, Thomas R
2014-11-01
This report examines cognitive complaints and neuropsychological (NP) testing outcomes in patients with early-stage breast cancer after the initiation of endocrine therapy (ET) to determine whether this therapy plays any role in post-treatment cognitive complaints. One hundred seventy-three participants from the Mind Body Study (MBS) observational cohort provided data from self-report questionnaires and NP testing obtained at enrollment (T1, before initiation of ET), and 6 months later (T2). Bivariate analyses compared demographic and treatment variables, cognitive complaints, depressive symptoms, quality of life, and NP functioning between those who received ET versus not. Multivariable linear regression models examined predictors of cognitive complaints at T2, including selected demographic variables, depressive symptoms, ET use, and other medical variables, along with NP domains that were identified in bivariate analyses. Seventy percent of the 173 MBS participants initiated ET, evenly distributed between tamoxifen or aromatase inhibitors. ET-treated participants reported significantly increased language and communication (LC) cognitive complaints at T2 (P = .003), but no significant differences in NP test performance. Multivariable regression on LC at T2 found higher LC complaints significantly associated with T1 LC score (P < .001), ET at T2 (P = .004), interaction between ET and past hormone therapy (HT) (P < .001), and diminished improvement in NP psychomotor function (P = .05). Depressive symptoms were not significant (P = .10). Higher LC complaints are significantly associated with ET 6 months after starting treatment and reflect diminished improvements in some NP tests. Past HT is a significant predictor of higher LC complaints after initiation of ET. © 2014 by American Society of Clinical Oncology.
Ganz, Patricia A.; Petersen, Laura; Castellon, Steven A.; Bower, Julienne E.; Silverman, Daniel H.S.; Cole, Steven W.; Irwin, Michael R.; Belin, Thomas R.
2014-01-01
Purpose This report examines cognitive complaints and neuropsychological (NP) testing outcomes in patients with early-stage breast cancer after the initiation of endocrine therapy (ET) to determine whether this therapy plays any role in post-treatment cognitive complaints. Patients and Methods One hundred seventy-three participants from the Mind Body Study (MBS) observational cohort provided data from self-report questionnaires and NP testing obtained at enrollment (T1, before initiation of ET), and 6 months later (T2). Bivariate analyses compared demographic and treatment variables, cognitive complaints, depressive symptoms, quality of life, and NP functioning between those who received ET versus not. Multivariable linear regression models examined predictors of cognitive complaints at T2, including selected demographic variables, depressive symptoms, ET use, and other medical variables, along with NP domains that were identified in bivariate analyses. Results Seventy percent of the 173 MBS participants initiated ET, evenly distributed between tamoxifen or aromatase inhibitors. ET-treated participants reported significantly increased language and communication (LC) cognitive complaints at T2 (P = .003), but no significant differences in NP test performance. Multivariable regression on LC at T2 found higher LC complaints significantly associated with T1 LC score (P < .001), ET at T2 (P = .004), interaction between ET and past hormone therapy (HT) (P < .001), and diminished improvement in NP psychomotor function (P = .05). Depressive symptoms were not significant (P = .10). Conclusion Higher LC complaints are significantly associated with ET 6 months after starting treatment and reflect diminished improvements in some NP tests. Past HT is a significant predictor of higher LC complaints after initiation of ET. PMID:25267747
Brewer, Michael J; Armstrong, J Scott; Parker, Roy D
2013-06-01
The ability to monitor verde plant bug, Creontiades signatus Distant (Hemiptera: Miridae), and the progression of cotton, Gossypium hirsutum L., boll responses to feeding and associated cotton boll rot provided opportunity to assess if single in-season measurements had value in evaluating at-harvest damage to bolls and if multiple in-season measurements enhanced their combined use. One in-season verde plant bug density measurement, three in-season plant injury measurements, and two at-harvest damage measurements were taken in 15 cotton fields in South Texas, 2010. Linear regression selected two measurements as potentially useful indicators of at-harvest damage: verde plant bug density (adjusted r2 = 0.68; P = 0.0004) and internal boll injury of the carpel wall (adjusted r2 = 0.72; P = 0.004). Considering use of multiple measurements, a stepwise multiple regression of the four in-season measurements selected a univariate model (verde plant bug density) using a 0.15 selection criterion (adjusted r2 = 0.74; P = 0.0002) and a bivariate model (verde plant bug density-internal boll injury) using a 0.25 selection criterion (adjusted r2 = 0.76; P = 0.0007) as indicators of at-harvest damage. In a validation using cultivar and water regime treatments experiencing low verde plant bug pressure in 2011 and 2012, the bivariate model performed better than models using verde plant bug density or internal boll injury separately. Overall, verde plant bug damaging cotton bolls exemplified the benefits of using multiple in-season measurements in pest monitoring programs, under the challenging situation when at-harvest damage results from a sequence of plant responses initiated by in-season insect feeding.
Grieve, Richard; Nixon, Richard; Thompson, Simon G
2010-01-01
Cost-effectiveness analyses (CEA) may be undertaken alongside cluster randomized trials (CRTs) where randomization is at the level of the cluster (for example, the hospital or primary care provider) rather than the individual. Costs (and outcomes) within clusters may be correlated so that the assumption made by standard bivariate regression models, that observations are independent, is incorrect. This study develops a flexible modeling framework to acknowledge the clustering in CEA that use CRTs. The authors extend previous Bayesian bivariate models for CEA of multicenter trials to recognize the specific form of clustering in CRTs. They develop new Bayesian hierarchical models (BHMs) that allow mean costs and outcomes, and also variances, to differ across clusters. They illustrate how each model can be applied using data from a large (1732 cases, 70 primary care providers) CRT evaluating alternative interventions for reducing postnatal depression. The analyses compare cost-effectiveness estimates from BHMs with standard bivariate regression models that ignore the data hierarchy. The BHMs show high levels of cost heterogeneity across clusters (intracluster correlation coefficient, 0.17). Compared with standard regression models, the BHMs yield substantially increased uncertainty surrounding the cost-effectiveness estimates, and altered point estimates. The authors conclude that ignoring clustering can lead to incorrect inferences. The BHMs that they present offer a flexible modeling framework that can be applied more generally to CEA that use CRTs.
ERIC Educational Resources Information Center
West, Lindsey M.; Davis, Telsie A.; Thompson, Martie P.; Kaslow, Nadine J.
2011-01-01
Protective factors for fostering reasons for living were examined among low-income, suicidal, African American women. Bivariate logistic regressions revealed that higher levels of optimism, spiritual well-being, and family social support predicted reasons for living. Multivariate logistic regressions indicated that spiritual well-being showed…
Serrano-Gallardo, Pilar; Martínez-Marcos, Mercedes; Espejo-Matorrales, Flora; Arakawa, Tiemi; Magnabosco, Gabriela Tavares; Pinto, Ione Carvalho
2016-01-01
ABSTRACT Objective: to identify the students' perception about the quality of clinical placements and asses the influence of the different tutoring processes in clinical learning. Methods: analytical cross-sectional study on second and third year nursing students (n=122) about clinical learning in primary health care. The Clinical Placement Evaluation Tool and a synthetic index of attitudes and skills were computed to give scores to the clinical learning (scale 0-10). Univariate, bivariate and multivariate (multiple linear regression) analyses were performed. Results: the response rate was 91.8%. The most commonly identified tutoring process was "preceptor-professor" (45.2%). The clinical placement was assessed as "optimal" by 55.1%, relationship with team-preceptor was considered good by 80.4% of the cases and the average grade for clinical learning was 7.89. The multiple linear regression model with more explanatory capacity included the variables "Academic year" (beta coefficient = 1.042 for third-year students), "Primary Health Care Area (PHC)" (beta coefficient = 0.308 for Area B) and "Clinical placement perception" (beta coefficient = - 0.204 for a suboptimal perception). Conclusions: timeframe within the academic program, location and clinical placement perception were associated with students' clinical learning. Students' perceptions of setting quality were positive and a good team-preceptor relationship is a matter of relevance. PMID:27627124
Guerrero, Erick G; Heslin, Kevin C; Chang, Evelyn; Fenwick, Karissa; Yano, Elizabeth
2015-07-01
This study explored the role of organizational factors in the ability of Veterans Health Administration (VHA) clinics to implement colocated mental health care in primary care settings (PC-MH). The study used data from the VHA Clinical Practice Organizational Survey collected in 2007 from 225 clinic administrators across the United States. Clinic degree of implementation of PC-MH was the dependent variable, whereas independent variables included policies and procedures, organizational context, and leaders' perceptions of barriers to change. Pearson bivariate correlations and multivariable linear regression were used to test hypotheses. Results show that depression care training for primary care providers and clinics' flexibility and participation were both positively correlated with implementation of PC-MH. However, after accounting for other factors, regressions show that only training primary care providers in depression care was marginally associated with degree of implementation of PC-MH (p = 0.051). Given the importance of this topic for implementing integrated care as part of health care reform, these null findings underscore the need to improve theory and testing of more proximal measures of colocation in future work.
Guerrero, Erick G.; Heslin, Kevin C.; Chang, Evelyn; Fenwick, Karissa; Yano, Elizabeth
2014-01-01
This study explored the role of organizational factors in the ability of Veterans Health Administration (VHA) clinics to implement colocated mental health care in primary care settings (PC-MH). The study used data from the VHA Clinical Practice Organizational Survey collected in 2007 from 225 clinic administrators across the United States. Clinic degree of implementation of PC-MH was the dependent variable, whereas independent variables included policies and procedures, organizational context, and leaders’ perceptions of barriers to change. Pearson bivariate correlations and multivariable linear regression were used to test hypotheses. Results show that depression care training for primary care providers and clinics’ flexibility and participation were both positively correlated with implementation of PC-MH. However, after accounting for other factors, regressions show that only training primary care providers in depression care was marginally associated with degree of implementation of PC-MH (p = 0.051). Given the importance of this topic for implementing integrated care as part of health care reform, these null findings underscore the need to improve theory and testing of more proximal measures of colocation in future work. PMID:25096986
Structural Analysis of Women’s Heptathlon
Gassmann, Freya; Fröhlich, Michael; Emrich, Eike
2016-01-01
The heptathlon comprises the results of seven single disciplines, assuming an equal influence from each discipline, depending on the measured performance. Data analysis was based on the data recorded for the individual performances of the 10 winning heptathletes in the World Athletics Championships from 1987 to 2013 and the Olympic Games from 1988 to 2012. In addition to descriptive analysis methods, correlations, bivariate and multivariate linear regressions, and panel data regressions were used. The transformation of the performances from seconds, centimeters, and meters into points showed that the individual disciplines do not equally affect the overall competition result. The currently valid conversion formula for the run, jump, and throw disciplines prefers the sprint and jump disciplines but penalizes the athletes performing in the 800 m run, javelin throw, and shotput disciplines. Furthermore, 21% to 48% of the variance of the sum of points can be attributed to the performances in the disciplines of long jump, 200 m sprint, 100 m hurdles, and high jump. To balance the effects of the single disciplines in the heptathlon, the formula to calculate points should be reevaluated. PMID:29910260
Subica, Andrew M
2013-10-01
Trauma and posttraumatic stress disorder (PTSD) frequently co-occur with serious mental illness, yet the unique mental and physical health influences of childhood physical abuse (CPA), childhood sexual abuse (CSA), and forced sexual trauma on individuals with serious mental illness remain unevaluated. The present study of 172 individuals with serious mental illness investigated the adverse effects of CPA, CSA, and forced sexual trauma on severity of PTSD and depression, and overall mental and physical health functioning. Data analysis consisted of chi-square tests, independent t tests, bivariate odds ratios, and linear regressions. Prevalence of CPA (44.8%), CSA (29.1%), and forced sexual trauma (33.1%) were elevated, and nearly one third of participants (31.4%) reported clinical PTSD. Participants exposed to CSA or forced sexual trauma evidenced bivariate ORs ranging from 4.13 to 7.02 for PTSD, 2.44 to 2.50 for major depression, and 2.14 to 2.31 for serious physical illness/disability. Sexual trauma exposure associated with heightened PTSD and depression, and reduced mental and physical health functioning, with CSA uniquely predicting PTSD, depression, and physical health difficulties. CPA less significantly affected these clinical domains. Sexual traumas have profound negative effects on mental and physical health outcomes among individuals with serious mental illness; increased screening and treatment of sexual traumas is needed. Copyright © 2013 International Society for Traumatic Stress Studies.
Oral health status and academic performance among Ohio third-graders, 2009-2010.
Detty, Amber M R; Oza-Frank, Reena
2014-01-01
Although recent literature indicated an association between dental caries and poor academic performance, previous work relied on self-reported measures. This analysis sought to determine the association between academic performance and untreated dental caries (tooth decay) using objective measures, controlling for school-level characteristics. School-level untreated caries prevalence was estimated from a 2009-2010 oral health survey of Ohio third-graders. Prevalence estimates were combined with school-level academic performance and other school characteristics obtained from the Ohio Department of Education. Linear regression models were developed as a result of bivariate testing, and final models were stratified based upon the presence of a school-based dental sealant program (SBSP). Preliminary bivariate analysis indicated a significant relationship between untreated caries and academic performance, which was more pronounced at schools with an SBSP. After controlling for other school characteristics, the prevalence of untreated caries was found to be a significant predictor of academic performance at schools without an SBSP (P=0.001) but not at schools with an SBSP (P=0.833). The results suggest the association between untreated caries and academic performance may be affected by the presence of a school-based oral health program. Further research focused on oral health and academic performance should consider the presence and/or availability of these programs. © 2014 American Association of Public Health Dentistry.
De Haas, Y; Janss, L L G; Kadarmideen, H N
2007-10-01
Genetic correlations between body condition score (BCS) and fertility traits in dairy cattle were estimated using bivariate random regression models. BCS was recorded by the Swiss Holstein Association on 22,075 lactating heifers (primiparous cows) from 856 sires. Fertility data during first lactation were extracted for 40,736 cows. The fertility traits were days to first service (DFS), days between first and last insemination (DFLI), calving interval (CI), number of services per conception (NSPC) and conception rate to first insemination (CRFI). A bivariate model was used to estimate genetic correlations between BCS as a longitudinal trait by random regression components, and daughter's fertility at the sire level as a single lactation measurement. Heritability of BCS was 0.17, and heritabilities for fertility traits were low (0.01-0.08). Genetic correlations between BCS and fertility over the lactation varied from: -0.45 to -0.14 for DFS; -0.75 to 0.03 for DFLI; from -0.59 to -0.02 for CI; from -0.47 to 0.33 for NSPC and from 0.08 to 0.82 for CRFI. These results show (genetic) interactions between fat reserves and reproduction along the lactation trajectory of modern dairy cows, which can be useful in genetic selection as well as in management. Maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in mid lactation when the genetic variance for BCS is largest, and the genetic correlations between BCS and fertility is strongest.
Nikoloulopoulos, Aristidis K
2017-10-01
A bivariate copula mixed model has been recently proposed to synthesize diagnostic test accuracy studies and it has been shown that it is superior to the standard generalized linear mixed model in this context. Here, we call trivariate vine copulas to extend the bivariate meta-analysis of diagnostic test accuracy studies by accounting for disease prevalence. Our vine copula mixed model includes the trivariate generalized linear mixed model as a special case and can also operate on the original scale of sensitivity, specificity, and disease prevalence. Our general methodology is illustrated by re-analyzing the data of two published meta-analyses. Our study suggests that there can be an improvement on trivariate generalized linear mixed model in fit to data and makes the argument for moving to vine copula random effects models especially because of their richness, including reflection asymmetric tail dependence, and computational feasibility despite their three dimensionality.
Taliaferro, Lindsay A; Hetler, Joel; Edwall, Glenace; Wright, Catherine; Edwards, Anne R; Borowsky, Iris W
2013-06-01
To compare depression identification and management perceptions and practices between professions and disciplines in primary care and examine factors that increase the likelihood of administering a standardized depression screening instrument, asking about patients' depressive symptoms, and using best practice when managing depressed adolescents. Data came from an online survey of clinicians in Minnesota (20% response rate). Analyses involved bivariate tests and linear regressions. The analytic sample comprised 260 family medicine physicians, 127 pediatricians, 96 family nurse practitioners, and 54 pediatric nurse practitioners. Overall, few differences emerged between physicians and nurse practitioners or family and pediatric clinicians regarding addressing depression among adolescents. Two factors associated with administering a standardized instrument included having clear protocols for follow-up after depression screening and feeling better prepared to address depression among adolescents. Enhancing clinicians' competence to address depression and developing postscreening protocols could help providers implement universal screening in primary care.
Krempa, Heather M.
2015-10-29
Relative percent differences between methods were greater than 10 percent for most analyzed trace elements. Barium, cobalt, manganese, and boron had concentrations that were significantly different between sampling methods. Barium, molybdenum, boron, and uranium method concentrations indicate a close association between pump and grab samples based on bivariate plots and simple linear regressions. Grab sample concentrations were generally larger than pump concentrations for these elements and may be because of using a larger pore sized filter for grab samples. Analysis of zinc blank samples suggests zinc contamination in filtered grab samples. Variations of analyzed trace elements between pump and grab samples could reduce the ability to monitor temporal changes and potential groundwater contamination threats. The degree of precision necessary for monitoring potential groundwater threats and application objectives need to be considered when determining acceptable variation amounts.
Psychosocial correlates of suicidal ideation in rural South African adolescents.
Shilubane, Hilda N; Ruiter, Robert A C; Bos, Arjan E R; van den Borne, Bart; James, Shamagonam; Reddy, Priscilla S
2014-01-01
Suicide is a prevalent problem among young people in Southern Africa, but prevention programs are largely absent. This survey aimed to identify the behavioral and psychosocial correlates of suicidal ideation among adolescents in Limpopo. A two-stage cluster sample design was used to establish a representative sample of 591 adolescents. Bivariate correlations and multiple linear regression analyses were conducted. Findings show that suicidal ideation is prevalent among adolescents. The psychosocial factors perceived social support and negative feelings about the family and the behavioral factors forced sexual intercourse and physical violence by the partner were found to increase the risk of suicidal ideation. Depression mediated the relationship between these psychosocial and behavioral risk factors and suicidal ideation. This study increased our understanding of the psychosocial and behavioral predictors of adolescent suicidal ideation. The findings provide target points for future intervention programs and call for supportive structures to assist adolescents with suicidal ideation.
NASA Astrophysics Data System (ADS)
Metwally, Fadia H.
2008-02-01
The quantitative predictive abilities of the new and simple bivariate spectrophotometric method are compared with the results obtained by the use of multivariate calibration methods [the classical least squares (CLS), principle component regression (PCR) and partial least squares (PLS)], using the information contained in the absorption spectra of the appropriate solutions. Mixtures of the two drugs Nifuroxazide (NIF) and Drotaverine hydrochloride (DRO) were resolved by application of the bivariate method. The different chemometric approaches were applied also with previous optimization of the calibration matrix, as they are useful in simultaneous inclusion of many spectral wavelengths. The results found by application of the bivariate, CLS, PCR and PLS methods for the simultaneous determinations of mixtures of both components containing 2-12 μg ml -1 of NIF and 2-8 μg ml -1 of DRO are reported. Both approaches were satisfactorily applied to the simultaneous determination of NIF and DRO in pure form and in pharmaceutical formulation. The results were in accordance with those given by the EVA Pharma reference spectrophotometric method.
Chaitoff, Alexander; Sun, Bob; Windover, Amy; Bokar, Daniel; Featherall, Joseph; Rothberg, Michael B; Misra-Hebert, Anita D
2017-10-01
To identify correlates of physician empathy and determine whether physician empathy is related to standardized measures of patient experience. Demographic, professional, and empathy data were collected during 2013-2015 from Cleveland Clinic Health System physicians prior to participation in mandatory communication skills training. Empathy was assessed using the Jefferson Scale of Empathy. Data were also collected for seven measures (six provider communication items and overall provider rating) from the visit-specific and 12-month Consumer Assessment of Healthcare Providers and Systems Clinician and Group (CG-CAHPS) surveys. Associations between empathy and provider characteristics were assessed by linear regression, ANOVA, or a nonparametric equivalent. Significant predictors were included in a multivariable linear regression model. Correlations between empathy and CG-CAHPS scores were assessed using Spearman rank correlation coefficients. In bivariable analysis (n = 847 physicians), female sex (P < .001), specialty (P < .01), outpatient practice setting (P < .05), and DO degree (P < .05) were associated with higher empathy scores. In multivariable analysis, female sex (P < .001) and four specialties (obstetrics-gynecology, pediatrics, psychiatry, and thoracic surgery; all P < .05) were significantly associated with higher empathy scores. Of the seven CG-CAHPS measures, scores on five for the 583 physicians with visit-specific data and on three for the 277 physicians with 12-month data were positively correlated with empathy. Specialty and sex were independently associated with physician empathy. Empathy was correlated with higher scores on multiple CG-CAHPS items, suggesting improving physician empathy might play a role in improving patient experience.
Pousa, Esther; Duñó, Rosó; Blas Navarro, J; Ruiz, Ada I; Obiols, Jordi E; David, Anthony S
2008-05-01
Poor insight and impairment in Theory of Mind (ToM) reasoning are common in schizophrenia, predicting poorer clinical and functional outcomes. The present study aimed to explore the relationship between these phenomena. 61 individuals with a DSM-IV diagnosis of schizophrenia during a stable phase were included. ToM was assessed using a picture sequencing task developed by Langdon and Coltheart (1999), and insight with the Scale to Assess Unawareness of Mental Disorder (SUMD; Amador et al., 1993). Multivariate linear regression analysis was carried out to estimate the predictive value of insight on ToM, taking into account several possible confounders and interaction variables. No direct significant associations were found between any of the insight dimensions and ToM using bivariate analysis. However, a significant linear regression model which explained 48% of the variance in ToM was revealed in the multivariate analysis. This included the 5 insight dimensions and 3 interaction variables. Misattribution of symptoms--in aware patients with age at onset >20 years--and unawareness of need for medication--in patients with GAF >60--were significantly predictive of better ToM. Insight and ToM are two complex and distinct phenomena in schizophrenia. Relationships between them are mediated by psychosocial, clinical, and neurocognitive variables. Intact ToM may be a prerequisite for aware patients to attribute their symptoms to causes other than mental illness, which could in turn be associated with denial of need for medication.
Factors Predicting a Good Symptomatic Outcome After Prostate Artery Embolisation (PAE).
Maclean, D; Harris, M; Drake, T; Maher, B; Modi, S; Dyer, J; Somani, B; Hacking, N; Bryant, T
2018-02-26
As prostate artery embolisation (PAE) becomes an established treatment for benign prostatic obstruction, factors predicting good symptomatic outcome remain unclear. Pre-embolisation prostate size as a predictor is controversial with a handful of papers coming to conflicting conclusions. We aimed to investigate if an association existed in our patient cohort between prostate size and clinical benefit, in addition to evaluating percentage volume reduction as a predictor of symptomatic outcome following PAE. Prospective follow-up of 86 PAE patients at a single institution between June 2012 and January 2016 was conducted (mean age 64.9 years, range 54-80 years). Multiple linear regression analysis was performed to assess strength of association between clinical improvement (change in IPSS) and other variables, of any statistical correlation, through Pearson's bivariate analysis. No major procedural complications were identified and clinical success was achieved in 72.1% (n = 62) at 12 months. Initial prostate size and percentage reduction were found to have a significant association with clinical improvement. Multiple linear regression analysis (r 2 = 0.48) demonstrated that percentage volume reduction at 3 months (r = 0.68, p < 0.001) had the strongest correlation with good symptomatic improvement at 12 months after adjusting for confounding factors. Both the initial prostate size and percentage volume reduction at 3 months predict good symptomatic outcome at 12 months. These findings therefore aid patient selection and counselling to achieve optimal outcomes for men undergoing prostate artery embolisation.
Shelton, Rachel C.; Puleo, Elaine; Bennett, Gary G.; McNeill, Lorna H.; Sorensen, Glorian; Emmons, Karen M.
2010-01-01
Background Research on the association between self-reported racial or gender discrimination and body mass index (BMI) has been limited and inconclusive to date, particularly among lower-income populations. Objectives The aim of the current study was to examine the association between self-reported racial and gender discrimination and BMI among a sample of adult residents living in 12 urban lower-income housing sites in Boston, Masschusetts (USA). Methods Baseline survey data were collected among 1,307 (weighted N=1907) study participants. For analyses, linear regression models with a cluster design were conducted using SUDAAN and SAS statistical software. Results Our sample was predominately Black (weighted n=956) and Hispanic (weighted n=857), and female (weighted n=1420), with a mean age of 49.3 (SE: .40) and mean BMI of 30.2 kg m−2 (SE: .19). Nearly 47% of participants reported ever experiencing racial discrimination, and 24.8% reported ever experiencing gender discrimination. In bivariate and multivariable linear regression models, no main effect association was found between either racial or gender discrimination and BMI. Conclusions While our findings suggest that self-reported discrimination is not a key determinant of BMI among lower-income housing residents, these results should be considered in light of study limitations. Future researchers may want to investigate this association among other relevant samples, and other social contextual and cultural factors should be explored to understand how they contribute to disparities. PMID:19769005
Shelton, Rachel C; Puleo, Elaine; Bennett, Gary G; McNeill, Lorna H; Sorensen, Glorian; Emmons, Karen M
2009-01-01
Research on the association between self-reported racial or gender discrimination and body mass index (BMI) has been limited and inconclusive to date, particularly among lower-income populations. The aim of the current study was to examine the association between self-reported racial and gender discrimination and BMI among a sample of adult residents living in 12 urban lower-income housing sites in Boston, Masschusetts (USA). Baseline survey data were collected among 1,307 (weighted N = 1907) study participants. For analyses, linear regression models with a cluster design were conducted using SUDAAN and SAS statistical software. Our sample was predominately Black (weighted n = 956) and Hispanic (weighted n = 857), and female (weighted n = 1420), with a mean age of 49.3 (SE: .40) and mean BMI of 30.2 kg m(-2) (SE: .19). Nearly 47% of participants reported ever experiencing racial discrimination, and 24.8% reported ever experiencing gender discrimination. In bivariate and multivariable linear regression models, no main effect association was found between either racial or gender discrimination and BMI. While our findings suggest that self-reported discrimination is not a key determinant of BMI among lower-income housing residents, these results should be considered in light of study limitations. Future researchers may want to investigate this association among other relevant samples, and other social contextual and cultural factors should be explored to understand how they contribute to disparities.
Regression analysis for bivariate gap time with missing first gap time data.
Huang, Chia-Hui; Chen, Yi-Hau
2017-01-01
We consider ordered bivariate gap time while data on the first gap time are unobservable. This study is motivated by the HIV infection and AIDS study, where the initial HIV contracting time is unavailable, but the diagnosis times for HIV and AIDS are available. We are interested in studying the risk factors for the gap time between initial HIV contraction and HIV diagnosis, and gap time between HIV and AIDS diagnoses. Besides, the association between the two gap times is also of interest. Accordingly, in the data analysis we are faced with two-fold complexity, namely data on the first gap time is completely missing, and the second gap time is subject to induced informative censoring due to dependence between the two gap times. We propose a modeling framework for regression analysis of bivariate gap time under the complexity of the data. The estimating equations for the covariate effects on, as well as the association between, the two gap times are derived through maximum likelihood and suitable counting processes. Large sample properties of the resulting estimators are developed by martingale theory. Simulations are performed to examine the performance of the proposed analysis procedure. An application of data from the HIV and AIDS study mentioned above is reported for illustration.
Modeling hardwood crown radii using circular data analysis
Paul F. Doruska; Hal O. Liechty; Douglas J. Marshall
2003-01-01
Cylindrical data are bivariate data composed of a linear and an angular component. One can use uniform, first-order (one maximum and one minimum) or second-order (two maxima and two minima) models to relate the linear component to the angular component. Crown radii can be treated as cylindrical data when the azimuths at which the radii are measured are also recorded....
2011-01-01
Background There is a lack of acceptable, reliable, and valid survey instruments to measure conceptual research utilization (CRU). In this study, we investigated the psychometric properties of a newly developed scale (the CRU Scale). Methods We used the Standards for Educational and Psychological Testing as a validation framework to assess four sources of validity evidence: content, response processes, internal structure, and relations to other variables. A panel of nine international research utilization experts performed a formal content validity assessment. To determine response process validity, we conducted a series of one-on-one scale administration sessions with 10 healthcare aides. Internal structure and relations to other variables validity was examined using CRU Scale response data from a sample of 707 healthcare aides working in 30 urban Canadian nursing homes. Principal components analysis and confirmatory factor analyses were conducted to determine internal structure. Relations to other variables were examined using: (1) bivariate correlations; (2) change in mean values of CRU with increasing levels of other kinds of research utilization; and (3) multivariate linear regression. Results Content validity index scores for the five items ranged from 0.55 to 1.00. The principal components analysis predicted a 5-item 1-factor model. This was inconsistent with the findings from the confirmatory factor analysis, which showed best fit for a 4-item 1-factor model. Bivariate associations between CRU and other kinds of research utilization were statistically significant (p < 0.01) for the latent CRU scale score and all five CRU items. The CRU scale score was also shown to be significant predictor of overall research utilization in multivariate linear regression. Conclusions The CRU scale showed acceptable initial psychometric properties with respect to responses from healthcare aides in nursing homes. Based on our validity, reliability, and acceptability analyses, we recommend using a reduced (four-item) version of the CRU scale to yield sound assessments of CRU by healthcare aides. Refinement to the wording of one item is also needed. Planned future research will include: latent scale scoring, identification of variables that predict and are outcomes to conceptual research use, and longitudinal work to determine CRU Scale sensitivity to change. PMID:21595888
Northrup, Angela A; Smaldone, Arlene
This exploratory study examined maternal attitudes, normative beliefs, subjective norms, and meal selection behaviors of mothers of 2- and 3-year-old children. Guided by the Theory of Reasoned Action, we had mothers complete three surveys, two interviews, and a feeding simulation exercise. Data were analyzed using descriptive and bivariate statistics and multivariate linear regression. A total of 31 mothers (50% Latino, 34% Black, 46.9% ≤ high school education, 31.3% poor health literacy) of 32 children (37.5% overweight/obese) participated in this study. Maternal normative beliefs (knowledge of U.S. Department of Agriculture recommendations) did not reflect actual U.S. Department of Agriculture recommendations. Collectively, regression models explained 13% (dairy) to 51% (vegetables) of the variance in behavioral intent, with normative belief an independent predictor in all models except grain and dairy. Meal selection behaviors, on average, were predicted by poor knowledge of U.S. Department of Agriculture recommendations. Dietary guidance appropriate to health literacy level should be incorporated into well-child visits. Copyright © 2016 National Association of Pediatric Nurse Practitioners. Published by Elsevier Inc. All rights reserved.
Predictors of Upper-Extremity Physical Function in Older Adults.
Hermanussen, Hugo H; Menendez, Mariano E; Chen, Neal C; Ring, David; Vranceanu, Ana-Maria
2016-10-01
Little is known about the influence of habitual participation in physical exercise and diet on upper-extremity physical function in older adults. To assess the relationship of general physical exercise and diet to upper-extremity physical function and pain intensity in older adults. A cohort of 111 patients 50 or older completed a sociodemographic survey, the Rapid Assessment of Physical Activity (RAPA), an 11-point ordinal pain intensity scale, a Mediterranean diet questionnaire, and three Patient- Reported Outcomes Measurement Information System (PROMIS) based questionnaires: Pain Interference to measure inability to engage in activities due to pain, Upper-Extremity Physical Function, and Depression. Multivariable linear regression modeling was used to characterize the association of physical activity, diet, depression, and pain interference to pain intensity and upper-extremity function. Higher general physical activity was associated with higher PROMIS Upper-Extremity Physical Function and lower pain intensity in bivariate analyses. Adherence to the Mediterranean diet did not correlate with PROMIS Upper-Extremity Physical Function or pain intensity in bivariate analysis. In multivariable analyses factors associated with higher PROMIS Upper-Extremity Physical Function were male sex, non-traumatic diagnosis and PROMIS Pain Interference, with the latter accounting for most of the observed variability (37%). Factors associated with greater pain intensity in multivariable analyses included fewer years of education and higher PROMIS Pain Interference. General physical activity and diet do not seem to be as strongly or directly associated with upper-extremity physical function as pain interference.
Basques, Bryce A; Golinvaux, Nicholas S; Bohl, Daniel D; Yacob, Alem; Toy, Jason O; Varthi, Arya G; Grauer, Jonathan N
2014-10-15
Retrospective database review. To evaluate whether microscope use during spine procedures is associated with increased operating room times or increased risk of infection. Operating microscopes are commonly used in spine procedures. It is debated whether the use of an operating microscope increases operating room time or confers increased risk of infection. The American College of Surgeons National Surgical Quality Improvement Program database, which includes data from more than 370 participating hospitals, was used to identify patients undergoing elective spinal procedures with and without the use of an operating microscope for the years 2011 and 2012. Bivariate and multivariate linear regressions were used to test the association between microscope use and operating room times. Bivariate and multivariate logistic regressions were similarly conducted to test the association between microscope use and infection occurrence within 30 days of surgery. A total of 23,670 elective spine procedures were identified, of which 2226 (9.4%) used an operating microscope. The average patient age was 55.1±14.4 years. The average operative time (incision to closure) was 125.7±82.0 minutes.Microscope use was associated with minor increases in preoperative room time (+2.9 min, P=0.013), operative time (+13.2 min, P<0.001), and total room time (+18.6 min, P<0.001) on multivariate analysis.A total of 328 (1.4%) patients had an infection within 30 days of surgery. Multivariate analysis revealed no significant difference between the microscope and nonmicroscope groups for occurrence of any infection, superficial surgical site infection, deep surgical site infection, organ space infection, or sepsis/septic shock, regardless of surgery type. We did not find operating room times or infection risk to be significant deterrents for use of an operating microscope during spine surgery. 3.
Basques, Bryce A.; Golinvaux, Nicholas S.; Bohl, Daniel D.; Yacob, Alem; Toy, Jason O.; Varthi, Arya G.; Grauer, Jonathan N.
2014-01-01
Study Design Retrospective database review. Objective To evaluate whether microscope use during spine procedures is associated with increased operating room times or increased risk of infection. Summary of Background Data Operating microscopes are commonly used in spine procedures. It is debated whether the use of an operating microscope increases operating room time or confers increased risk of infection. Methods The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database, which includes data from over 370 participating hospitals, was used to identify patients undergoing elective spinal procedures with and without an operating microscope for the years 2011 and 2012. Bivariate and multivariate linear regressions were used to test the association between microscope use and operating room times. Bivariate and multivariate logistic regressions were similarly conducted to test the association between microscope use and infection occurrence within 30 days of surgery. Results A total of 23,670 elective spine procedures were identified, of which 2,226 (9.4%) used an operating microscope. The average patient age was 55.1 ± 14.4 years. The average operative time (incision to closure) was 125.7 ± 82.0 minutes. Microscope use was associated with minor increases in preoperative room time (+2.9 minutes, p=0.013), operative time (+13.2 minutes, p<0.001), and total room time (+18.6 minutes, p<0.001) on multivariate analysis. A total of 328 (1.4%) patients had an infection within 30 days of surgery. Multivariate analysis revealed no significant difference between the microscope and non-microscope groups for occurrence of any infection, superficial surgical site infection (SSI), deep SSI, organ space infection, or sepsis/septic shock, regardless of surgery type. Conclusions We did not find operating room times or infection risk to be significant deterrents for use of an operating microscope during spine surgery. PMID:25188600
Factors that influence concussion knowledge and self-reported attitudes in high school athletes.
Kurowski, Brad; Pomerantz, Wendy J; Schaiper, Courtney; Gittelman, Michael A
2014-09-01
Many organizations and health care providers support educating high school (HS) athletes about concussions to improve their attitudes and behaviors about reporting. The objectives of this study were to determine if previous education, sport played, and individual factors were associated with better knowledge about concussion and to determine if more knowledge was associated with improved self-reported attitudes toward reporting concussions among HS athletes. We conducted a survey of HS athletes aged 13 years to 18 years from two large, urban HSs. Players were recruited from selected seasonal (fall and winter) as well as men and women's sports. During preseason, each participant was given a survey asking about his or her previous education, current knowledge, and self-reported attitudes and behaviors about reporting concussions. Bivariate and multivariate linear regression was used to evaluate the association of age, sex, sport, and previous concussion education with knowledge and self-reported attitudes and behaviors about reporting concussions. Surveys were completed by 496 athletes. The median age was 15 years, and 384 (77.4%) were male. A total of 212 (42.7%) participated in football, 123 (24.8%) in soccer, 89 (17.9%) in basketball, and 72 (14.5%) in wrestling. One hundred sixteen (23.4%) reported a history of concussion. Improved knowledge regarding concussions was not associated with improved self-reported behaviors (p = 0.63) in bivariate regression models. The multivariate model demonstrated that older age (p = 0.01) and female sex (p = 0.03) were associated with better knowledge. Younger age (p = 0.01), female sex (p = 0.0002), and soccer participation (p = 0.02) were associated with better self-reported behaviors around reporting concussions. Previous education on concussions was less predictive of knowledge about concussions when controlling for other factors such as sport and sex. Younger age, female sex, and soccer participation were more likely to be associated with better self-reported behaviors. Future studies need to focus on the development of interventions to improve concussion-specific knowledge and behaviors.
Gebreyesus, Grum; Lund, Mogens S; Buitenhuis, Bart; Bovenhuis, Henk; Poulsen, Nina A; Janss, Luc G
2017-12-05
Accurate genomic prediction requires a large reference population, which is problematic for traits that are expensive to measure. Traits related to milk protein composition are not routinely recorded due to costly procedures and are considered to be controlled by a few quantitative trait loci of large effect. The amount of variation explained may vary between regions leading to heterogeneous (co)variance patterns across the genome. Genomic prediction models that can efficiently take such heterogeneity of (co)variances into account can result in improved prediction reliability. In this study, we developed and implemented novel univariate and bivariate Bayesian prediction models, based on estimates of heterogeneous (co)variances for genome segments (BayesAS). Available data consisted of milk protein composition traits measured on cows and de-regressed proofs of total protein yield derived for bulls. Single-nucleotide polymorphisms (SNPs), from 50K SNP arrays, were grouped into non-overlapping genome segments. A segment was defined as one SNP, or a group of 50, 100, or 200 adjacent SNPs, or one chromosome, or the whole genome. Traditional univariate and bivariate genomic best linear unbiased prediction (GBLUP) models were also run for comparison. Reliabilities were calculated through a resampling strategy and using deterministic formula. BayesAS models improved prediction reliability for most of the traits compared to GBLUP models and this gain depended on segment size and genetic architecture of the traits. The gain in prediction reliability was especially marked for the protein composition traits β-CN, κ-CN and β-LG, for which prediction reliabilities were improved by 49 percentage points on average using the MT-BayesAS model with a 100-SNP segment size compared to the bivariate GBLUP. Prediction reliabilities were highest with the BayesAS model that uses a 100-SNP segment size. The bivariate versions of our BayesAS models resulted in extra gains of up to 6% in prediction reliability compared to the univariate versions. Substantial improvement in prediction reliability was possible for most of the traits related to milk protein composition using our novel BayesAS models. Grouping adjacent SNPs into segments provided enhanced information to estimate parameters and allowing the segments to have different (co)variances helped disentangle heterogeneous (co)variances across the genome.
1990-05-01
THUMBBR THUMB BREADTH NO. VARIABLE CONSTANT REGRESS. COEF. ST.ERROR ADJUQTED (.ERR OF ESTIMATE E4 58 HANDBRTH 7.623 0.183 ( 0.006) 1.124 .319 59 HANDCIRC...945, 956, 965 TRAGION TO TOP OF HEAD (TRAGT, 255) 39,51, 718, 851, 899, 945, 956, 965 Trapezius Post 23 Trochanter 23 TROCHArNTERION HEIGHT (TROQINT...THGHCLR, 105) 33, 40, 673, M08 881,927, 955, 964 Thigh Poia 23 THUMB BREADTH (THUMBBR, 106) 34, 49, 674,88 882,94955, 964 ThumlAip 23 THUMBTIP REACH
Wei McIntosh, Elizabeth; Morley, Christopher P
2016-05-01
If medical schools are to produce primary care physicians (family medicine, pediatrics, or general internal medicine), they must provide educational experiences that enable medical students to maintain existing or form new interests in such careers. This study examined three mechanisms for doing so, at one medical school: participation as an officer in a family medicine interest group (FMIG), completion of a dual medical/public health (MD/MPH) degree program, and participation in a rural medical education (RMED) clinical track. Specialty Match data for students who graduated from the study institution between 2006 and 2015 were included as dependent variables in bivariate analysis (c2) and logistic regression models, examining FMIG, MD/MPH, and RMED participation as independent predictors of specialty choice (family medicine yes/no, or any primary care (PC) yes/no), controlling for student demographic data. In bivariate c2 analyses, FMIG officership did not significantly predict matching with family medicine or any PC; RMED and MD/MPH education were significant predictors of both family medicine and PC. Binary logistic regression analyses replicated the bivariate findings, controlling for student demographics. Dual MD/MPH and rural medical education had stronger effects in producing primary care physicians than participation in a FMIG as an officer, at one institution. Further study at multiple institutions is warranted.
NASA Astrophysics Data System (ADS)
Takeuchi, Tsutomu T.
2010-08-01
We provide an analytic method to construct a bivariate distribution function (DF) with given marginal distributions and correlation coefficient. We introduce a convenient mathematical tool, called a copula, to connect two DFs with any prescribed dependence structure. If the correlation of two variables is weak (Pearson's correlation coefficient |ρ| < 1/3), the Farlie-Gumbel-Morgenstern (FGM) copula provides an intuitive and natural way to construct such a bivariate DF. When the linear correlation is stronger, the FGM copula cannot work anymore. In this case, we propose using a Gaussian copula, which connects two given marginals and is directly related to the linear correlation coefficient between two variables. Using the copulas, we construct the bivariate luminosity function (BLF) and discuss its statistical properties. We focus especially on the far-infrared-far-ulatraviolet (FUV-FIR) BLF, since these two wavelength regions are related to star-formation (SF) activity. Though both the FUV and FIR are related to SF activity, the univariate LFs have a very different functional form: the former is well described by the Schechter function whilst the latter has a much more extended power-law-like luminous end. We construct the FUV-FIR BLFs using the FGM and Gaussian copulas with different strengths of correlation, and examine their statistical properties. We then discuss some further possible applications of the BLF: the problem of a multiband flux-limited sample selection, the construction of the star-formation rate (SFR) function, and the construction of the stellar mass of galaxies (M*)-specific SFR (SFR/M*) relation. The copulas turn out to be a very useful tool to investigate all these issues, especially for including complicated selection effects.
Factors associated with interest in novel interfaces for upper limb prosthesis control
Engdahl, Susannah M.; Chestek, Cynthia A.; Kelly, Brian; Davis, Alicia
2017-01-01
Background Surgically invasive interfaces for upper limb prosthesis control may allow users to operate advanced, multi-articulated devices. Given the potential medical risks of these invasive interfaces, it is important to understand what factors influence an individual’s decision to try one. Methods We conducted an anonymous online survey of individuals with upper limb loss. A total of 232 participants provided personal information (such as age, amputation level, etc.) and rated how likely they would be to try noninvasive (myoelectric) and invasive (targeted muscle reinnervation, peripheral nerve interfaces, cortical interfaces) interfaces for prosthesis control. Bivariate relationships between interest in each interface and 16 personal descriptors were examined. Significant variables from the bivariate analyses were then entered into multiple logistic regression models to predict interest in each interface. Results While many of the bivariate relationships were significant, only a few variables remained significant in the regression models. The regression models showed that participants were more likely to be interested in all interfaces if they had unilateral limb loss (p ≤ 0.001, odds ratio ≥ 2.799). Participants were more likely to be interested in the three invasive interfaces if they were younger (p < 0.001, odds ratio ≤ 0.959) and had acquired limb loss (p ≤ 0.012, odds ratio ≥ 3.287). Participants who used a myoelectric device were more likely to be interested in myoelectric control than those who did not (p = 0.003, odds ratio = 24.958). Conclusions Novel prosthesis control interfaces may be accepted most readily by individuals who are young, have unilateral limb loss, and/or have acquired limb loss However, this analysis did not include all possible factors that may have influenced participant’s opinions on the interfaces, so additional exploration is warranted. PMID:28767716
Factors associated with interest in novel interfaces for upper limb prosthesis control.
Engdahl, Susannah M; Chestek, Cynthia A; Kelly, Brian; Davis, Alicia; Gates, Deanna H
2017-01-01
Surgically invasive interfaces for upper limb prosthesis control may allow users to operate advanced, multi-articulated devices. Given the potential medical risks of these invasive interfaces, it is important to understand what factors influence an individual's decision to try one. We conducted an anonymous online survey of individuals with upper limb loss. A total of 232 participants provided personal information (such as age, amputation level, etc.) and rated how likely they would be to try noninvasive (myoelectric) and invasive (targeted muscle reinnervation, peripheral nerve interfaces, cortical interfaces) interfaces for prosthesis control. Bivariate relationships between interest in each interface and 16 personal descriptors were examined. Significant variables from the bivariate analyses were then entered into multiple logistic regression models to predict interest in each interface. While many of the bivariate relationships were significant, only a few variables remained significant in the regression models. The regression models showed that participants were more likely to be interested in all interfaces if they had unilateral limb loss (p ≤ 0.001, odds ratio ≥ 2.799). Participants were more likely to be interested in the three invasive interfaces if they were younger (p < 0.001, odds ratio ≤ 0.959) and had acquired limb loss (p ≤ 0.012, odds ratio ≥ 3.287). Participants who used a myoelectric device were more likely to be interested in myoelectric control than those who did not (p = 0.003, odds ratio = 24.958). Novel prosthesis control interfaces may be accepted most readily by individuals who are young, have unilateral limb loss, and/or have acquired limb loss However, this analysis did not include all possible factors that may have influenced participant's opinions on the interfaces, so additional exploration is warranted.
Ayuso, Mercedes; Bermúdez, Lluís; Santolino, Miguel
2016-04-01
The analysis of factors influencing the severity of the personal injuries suffered by victims of motor accidents is an issue of major interest. Yet, most of the extant literature has tended to address this question by focusing on either the severity of temporary disability or the severity of permanent injury. In this paper, a bivariate copula-based regression model for temporary disability and permanent injury severities is introduced for the joint analysis of the relationship with the set of factors that might influence both categories of injury. Using a motor insurance database with 21,361 observations, the copula-based regression model is shown to give a better performance than that of a model based on the assumption of independence. The inclusion of the dependence structure in the analysis has a higher impact on the variance estimates of the injury severities than it does on the point estimates. By taking into account the dependence between temporary and permanent severities a more extensive factor analysis can be conducted. We illustrate that the conditional distribution functions of injury severities may be estimated, thus, providing decision makers with valuable information. Copyright © 2016 Elsevier Ltd. All rights reserved.
Beyond Reading Alone: The Relationship Between Aural Literacy And Asthma Management
Rosenfeld, Lindsay; Rudd, Rima; Emmons, Karen M.; Acevedo-García, Dolores; Martin, Laurie; Buka, Stephen
2010-01-01
Objectives To examine the relationship between literacy and asthma management with a focus on the oral exchange. Methods Study participants, all of whom reported asthma, were drawn from the New England Family Study (NEFS), an examination of links between education and health. NEFS data included reading, oral (speaking), and aural (listening) literacy measures. An additional survey was conducted with this group of study participants related to asthma issues, particularly asthma management. Data analysis focused on bivariate and multivariable logistic regression. Results In bivariate logistic regression models exploring aural literacy, there was a statistically significant association between those participants with lower aural literacy skills and less successful asthma management (OR:4.37, 95%CI:1.11, 17.32). In multivariable logistic regression analyses, controlling for gender, income, and race in separate models (one-at-a-time), there remained a statistically significant association between those participants with lower aural literacy skills and less successful asthma management. Conclusion Lower aural literacy skills seem to complicate asthma management capabilities. Practice Implications Greater attention to the oral exchange, in particular the listening skills highlighted by aural literacy, as well as other related literacy skills may help us develop strategies for clear communication related to asthma management. PMID:20399060
Comparison of Positive Youth Development for Youth With Chronic Conditions With Healthy Peers.
Maslow, Gary R; Hill, Sherika N; Pollock, McLean D
2016-12-01
Adolescents with childhood-onset chronic condition (COCC) are at increased risk for physical and psychological problems. Despite being at greater risk and having to deal with traumatic experiences and uncertainty, most adolescents with COCC do well across many domains. The Positive Youth Development (PYD) perspective provides a framework for examining thriving in youth and has been useful in understanding positive outcomes for general populations of youth as well as at-risk youth. This study aimed to compare levels of PYD assets between youth with COCC and youth without illness. Participants with COCC were recruited from specialty pediatric clinics while healthy participants were recruited from a large pediatric primary care practice. Inclusion criteria for participants included being (1) English speaking, (2) no documented intellectual disability in electronic medical record, and (3) aged between 13 and 18 years during the recruitment period. Univariate and bivariate analyses on key variables were conducted for adolescents with and without COCC. Finally, we performed multivariable linear regressions for PYD and its subdomains. There were no significant differences between overall PYD or any of the subdomains between the two groups. Multivariable linear regression models showed no statistically significant relationship between chronic condition status and PYD or the subdomains. The findings from this study support the application of the PYD perspective to this population of youth. The results of this study suggest that approaches shown to benefit healthy youth, could be used to promote positive outcomes for youth with COCC. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.
Saha, Rajib; Misra, Raghunath; Saha, Indranil
2015-10-01
To assess the quality of life among thalassemic children and to find out association of quality of life (QOL) with the socio-demographic factors, and clinico-therapeutic profile. This cross sectional descriptive epidemiological study was conducted from July 2011 through June 2012 on 365 admitted thalassemic patients of 5 to 12 y of age in the Burdwan Medical College and Hospital. Parents of the children were interviewed using Paediatric Quality of Life Inventory 4.0 Generic Core Scale. Statistically significant variables in bivariate analysis were considered for correlation matrix where independent variables were found inter related. So, partial correlation was done and statistically significant variables in partial correlation were considered for linear regression. The mean age of 365 thalassemic children was 8.3 ± 2.4 y. Multiple linear regressions predicted that only 70.5 % variation of total summary score depended on duration since splenectomy (31.2 % variation), last pre transfusion Hb level (20.7 %), family history of thalassemia (17.3 %) and frequency of blood transfusions (1.3 %). After splenectomy, thalassemic children could lead a better quality of life upto 5 y only. The betterment of the quality of life needs maintaining pre transfusion Hb level above 7 g/dl. Previous experience of the disease among the family members enriches the awareness among them and helps them to take correct decisions timely about the child and that leads to better QOL. More awareness regarding the maintenance of pre transfusion Hb level should be built up among parents and families where such disease has occurred for the first time.
Donor milk volume and characteristics of donors and their children.
Sierra-Colomina, Gemma; García-Lara, Nadia Raquel; Escuder-Vieco, Diana; Alonso-Díaz, Clara; Esteban, Eva María Andrés; Pallás-Alonso, Carmen Rosa
2014-05-01
Little is known regarding the effect of the characteristics of donors and their children on the volume of donor milk delivered to a human milk bank (HMB). Our study aimed to determine the relationship between different social and demographic variables of donors and their infants with the volume of human milk delivered. We included donors accepted at the Hospital Doce de Octubre HMB from January 1st, 2009 until April 31st, 2013, and who had finished their donation. Data of social and demographic characteristics of the donors and their children, and the total volume of DHM given were obtained from our HMB database. Included variables were previous donors, donor age, number of children, place of residence, gestational age of the infant at birth, child's age at the start of the donation, hospital admission, and death of the infant. A linear regression model was used to study the relationship between independent variables that were significant in bivariate analysis and the volume of donated milk. A total of 415 donations from 391 women were included. The median volume of milk delivered was 3.1l (IQR-interquartile range-1.3-8.3l). In the linear regression model, previous donors, smaller gestational age of children, and the start of donation at earlier stages of lactation were associated with a larger quantity of HMB donated (p≤0.001). Previous donors, smaller gestational age of children, and the start of donation at earlier stages of lactation are associated with a larger quantity of milk donated to the HMB. Copyright © 2014 Elsevier Ltd. All rights reserved.
On-line pachymetry outcome of ablation in aberration free mode TransPRK.
Adib-Moghaddam, Soheil; Arba-Mosquera, Samuel; Salmanian, Bahram; Omidvari, Amir-Houshang; Noorizadeh, Farsad
2014-01-01
There are many independent factors that influence the outcome of refractive surgeries, consisting of patient characteristics and environmental factors. We studied the accuracy of central ablation depth compared to online pachymetry results. A total of 153 eyes that underwent TransPRK at Bina Eye Hospital, Tehran, Iran, were evaluated from November 2010 to January 2012 in a retrospective cross-sectional study. The relevant data were registered and bivariate correlations and linear regression association were investigated statistically. The mean age was 29 ± 5 years. Distribution of refractive errors was as follows: compound myopic astigmatism 123 (80.4%), simple myopia 24 (15.7%), and mixed astigmatism 6 (3.9%). Mean ambient temperature and humidity levels intraoperatively were 23.49 ± 1.16°C and 28.91 ± 6.16%, respectively. There was a significant difference (p<0.001) between the preassumed central ablation depth (131.68 ± 32.72 µm) and the net level of ablation depth (measured by online pachymetry, 168.04 ± 41.47 µm). Temperature and humidity levels were not in any statistically significant correlation with the net amount of difference found. The backward linear regression was done to reveal the association between ablation depth and several variables. This study showed that there is deviation in optical coherence pachymetry online measurements done with SCHWIND AMARIS laser. Ambient temperature and humidity levels intraoperatively do not influence the outcome. However, basic structural characteristics of patients along with change in refractive index and corneal shrinkage because of corneal dehydration are associated with the differences.
Fleming, Paul J; Patterson, Thomas L; Chavarin, Claudia V; Semple, Shirley J; Magis-Rodriguez, Carlos; Pitpitan, Eileen V
2018-04-01
Men's misogynistic attitudes (i.e., dislike or contempt for women) have been shown to be associated with men's perpetration of physical/sexual violence against women and poor health outcomes for women. However, these attitudes have rarely been examined for their influence on men's own health. This paper examines the socio-demographic, substance use, and mental health correlates of misogynistic attitudes among a binational sample of men (n=400) in Tijuana, Mexico with high-risk substance use and sexual behaviors. We used a 6-item scale to measure misogynistic attitudes ( α = .72), which was developed specifically for this context. We used descriptive statistics to describe our sample population and the extent to which they hold misogynistic attitudes. Then, using misogynistic attitudes as our dependent variable, we conducted bivariate linear regression and multivariable linear regression to examine the relationship between these attitudes and socio-demographic characteristics, substance use behaviors (i.e., use of alcohol, marijuana, heroin, methamphetamines, cocaine), and mental health (i.e., depression, self-esteem). In the multivariable model, we found significant relationships between misogynistic attitudes and education level ( t = -4.34, p < 0.01), heroin use in the past 4 months ( t = 2.50, p = 0.01), and depressive symptoms ( t = 3.37, p < 0.01). These findings suggest that misogynistic attitudes are linked to poor health outcomes for men and future research needs to further explore the temporality of these relationships and identify strategies for reducing men's misogynistic attitudes with the ultimate aim of improving the health and well-being of both women and men.
Does body image perception relate to quality of life in middle-aged women?
Medeiros de Morais, Maria Socorro; Vieira, Mariana Carmem Apolinário; Moreira, Mayle Andrade; da Câmara, Saionara Maria Aires; Campos Cavalcanti Maciel, Álvaro; Almeida, Maria das Graças
2017-01-01
Objective In Brazil, information about the influence of body image on the various life domains of women in menopausal transition is scarce. Thus, the objective of the study was to analyze the relationship between body image and quality of life in middle-aged Brazilian women. Methods This was a cross-sectional study of 250 women between 40 and 65 years old, living in Parnamirim/RN, Brazil, who were evaluated in relation to body image and quality of life. For body image, women were classified as: dissatisfied due to low weight, satisfied (with their body weight) and dissatisfied due to being overweight. Quality of life was assessed through a questionnaire in which higher values indicate higher quality of life. Multiple linear regression was performed to analyze the relationship between body image and quality of life, adjusted for covariates that presented p<0.20 in the bivariate analysis. Results The average age was 52.1 (± 5.6) years, 82% of the women reported being dissatisfied due to being overweight, and 4.4% were dissatisfied due to having low weight. After multiple linear regression analyzes, body image remained associated with health (p<0.001), emotional (p = 0.016), and sexual (p = 0.048) domains of quality of life, as well as total score of the questionnaire (p<0.001). Conclusion Women who reported being dissatisfied with their body image due to having low weight or overweight had worse quality of life in comparison to those who were satisfied (with their body weight). PMID:28926575
Computational approach to Thornley's problem by bivariate operational calculus
NASA Astrophysics Data System (ADS)
Bazhlekova, E.; Dimovski, I.
2012-10-01
Thornley's problem is an initial-boundary value problem with a nonlocal boundary condition for linear onedimensional reaction-diffusion equation, used as a mathematical model of spiral phyllotaxis in botany. Applying a bivariate operational calculus we find explicit representation of the solution, containing two convolution products of special solutions and the arbitrary initial and boundary functions. We use a non-classical convolution with respect to the space variable, extending in this way the classical Duhamel principle. The special solutions involved are represented in the form of fast convergent series. Numerical examples are considered to show the application of the present technique and to analyze the character of the solution.
Comparison of connectivity analyses for resting state EEG data
NASA Astrophysics Data System (ADS)
Olejarczyk, Elzbieta; Marzetti, Laura; Pizzella, Vittorio; Zappasodi, Filippo
2017-06-01
Objective. In the present work, a nonlinear measure (transfer entropy, TE) was used in a multivariate approach for the analysis of effective connectivity in high density resting state EEG data in eyes open and eyes closed. Advantages of the multivariate approach in comparison to the bivariate one were tested. Moreover, the multivariate TE was compared to an effective linear measure, i.e. directed transfer function (DTF). Finally, the existence of a relationship between the information transfer and the level of brain synchronization as measured by phase synchronization value (PLV) was investigated. Approach. The comparison between the connectivity measures, i.e. bivariate versus multivariate TE, TE versus DTF, TE versus PLV, was performed by means of statistical analysis of indexes based on graph theory. Main results. The multivariate approach is less sensitive to false indirect connections with respect to the bivariate estimates. The multivariate TE differentiated better between eyes closed and eyes open conditions compared to DTF. Moreover, the multivariate TE evidenced non-linear phenomena in information transfer, which are not evidenced by the use of DTF. We also showed that the target of information flow, in particular the frontal region, is an area of greater brain synchronization. Significance. Comparison of different connectivity analysis methods pointed to the advantages of nonlinear methods, and indicated a relationship existing between the flow of information and the level of synchronization of the brain.
Hoyer, A; Kuss, O
2015-05-20
In real life and somewhat contrary to biostatistical textbook knowledge, sensitivity and specificity (and not only predictive values) of diagnostic tests can vary with the underlying prevalence of disease. In meta-analysis of diagnostic studies, accounting for this fact naturally leads to a trivariate expansion of the traditional bivariate logistic regression model with random study effects. In this paper, a new model is proposed using trivariate copulas and beta-binomial marginal distributions for sensitivity, specificity, and prevalence as an expansion of the bivariate model. Two different copulas are used, the trivariate Gaussian copula and a trivariate vine copula based on the bivariate Plackett copula. This model has a closed-form likelihood, so standard software (e.g., SAS PROC NLMIXED) can be used. The results of a simulation study have shown that the copula models perform at least as good but frequently better than the standard model. The methods are illustrated by two examples. Copyright © 2015 John Wiley & Sons, Ltd.
Modeling animal movements using stochastic differential equations
Haiganoush K. Preisler; Alan A. Ager; Bruce K. Johnson; John G. Kie
2004-01-01
We describe the use of bivariate stochastic differential equations (SDE) for modeling movements of 216 radiocollared female Rocky Mountain elk at the Starkey Experimental Forest and Range in northeastern Oregon. Spatially and temporally explicit vector fields were estimated using approximating difference equations and nonparametric regression techniques. Estimated...
Wolf, Lisa
2013-02-01
To explore the relationship between multiple variables within a model of critical thinking and moral reasoning. A quantitative descriptive correlational design using a purposive sample of 200 emergency nurses. Measured variables were accuracy in clinical decision-making, moral reasoning, perceived care environment, and demographics. Analysis was by bivariate correlation using Pearson's product-moment correlation coefficients, chi square and multiple linear regression analysis. The elements as identified in the integrated ethically-driven environmental model of clinical decision-making (IEDEM-CD) corrected depict moral reasoning and environment of care as factors significantly affecting accuracy in decision-making. The integrated, ethically driven environmental model of clinical decision making is a framework useful for predicting clinical decision making accuracy for emergency nurses in practice, with further implications in education, research and policy. A diagnostic and therapeutic framework for identifying and remediating individual and environmental challenges to accurate clinical decision making. © 2012, The Author. International Journal of Nursing Knowledge © 2012, NANDA International.
Buccoliero, Luca; Bellio, Elena; Mazzola, Maria; Solinas, Elisa
2016-02-09
The study aims at investigating the characteristics and the satisfaction determinants of the emerging patient profile. This profile appears to be more demanding and "empowered" compared to the ones traditionally conceived, asking for unconventional healthcare services and for a closer relationship with providers. Both qualitative (semi-structured interviews and focus groups) and quantitative (survey) analyses were performed on a random sample of 2808 Italian citizens-patients. Analyses entailed descriptive statistics, bivariate analysis and linear regressions. Four relevant dimensions of patient 2.0 experience were identified through a literature review on experiential marketing in healthcare. Beta coefficients exhibited the effect that different healthcare experiential elements have on patient 2.0 satisfaction. Results allow to state that a new marketing approach, based on patient 2.0 characteristics and value drivers, should be adopted in the healthcare sector. Critical satisfaction drivers and new technological healthcare guidelines are identified in order to match the new patient profile needs.
Resilience in women with autoimmune rheumatic diseases.
Rojas, Manuel; Rodriguez, Yhojan; Pacheco, Yovana; Zapata, Elizabeth; Monsalve, Diana M; Mantilla, Rubén D; Rodríguez-Jimenez, Monica; Ramírez-Santana, Carolina; Molano-González, Nicolás; Anaya, Juan-Manuel
2017-12-28
To evaluate the relationship between resilience and clinical outcomes in patients with autoimmune rheumatic diseases. Focus groups, individual interviews, and chart reviews were done to collect data on 188 women with autoimmune rheumatic diseases, namely rheumatoid arthritis (n=51), systemic lupus erythematosus (n=70), systemic sclerosis (n=35), and Sjögren's syndrome (n=32). Demographic, clinical, and laboratory variables were assessed including disease activity by patient reported outcomes. Resilience was evaluated by using the Brief Resilience Scale. Bivariate, multiple linear regression, and classification and regression trees were used to analyse data. Resilience was influenced by age, duration of disease, and socioeconomic status. Lower resilience scores were observed in younger patients (<48years) with systemic lupus erythematosus, rheumatoid arthritis, and systemic sclerosis who had low socioeconomic status, whereas older patients (>50years) had higher resilience scores regardless of socioeconomic status. There was no influence of disease activity on resilience. A particular behaviour was observed in systemic sclerosis in which patients with high socioeconomic status and regular physical activity had higher resilience scores. Resilience in patients with autoimmune rheumatic diseases is a continuum process influenced by age and socioeconomic status. The ways in which these variables along with exercise influence resilience deserve further investigation. Copyright © 2017 Société française de rhumatologie. Published by Elsevier SAS. All rights reserved.
Cognitive Factors Related to Drug Abuse Among a Sample of Iranian Male Medical College Students
Jalilian, Farzad; Ataee, Mari; Matin, Behzad Karami; Ahmadpanah, Mohammad; Jouybari, Touraj Ahmadi; Eslami, Ahmad Ali; Mahboubi, Mohammad; Alavijeh, Mehdi Mirzaei
2015-01-01
Backgrounds: Drug abuse is one of the most serious social problems in many countries. College students, particularly at their first year of education, are considered as one of the at risk groups for drug abuse. The present study aimed to determine cognitive factors related to drug abuse among a sample of Iranian male medical college students based on the social cognitive theory (SCT). Method: This cross-sectional study was carried out on 425 Iranian male medical college students who were randomly selected to participate voluntarily in the study. The participants filled out a self-administered questionnaire. Data were analyzed by the SPSS software (ver. 21.0) using bivariate correlations, logistic and linear regression at 95% significant level. Results: Attitude, outcome expectation, outcome expectancies, subjective norms, and self-control were cognitive factors that accounted for 49% of the variation in the outcome measure of the intention to abuse drugs. Logistic regression showed that attitude (OR=1.062), outcome expectancies (OR=1.115), and subjective norms (OR=1.269) were the most influential predictors for drug abuse. Conclusions: The findings suggest that designing and implementation of educational programs may be useful to increase negative attitude, outcome expectancies, and subjective norms towards drug abuse for college students in order to prevent drug abuse. PMID:26156919
Victimization and Health Risk Factors among Weapon-Carrying Youth
ERIC Educational Resources Information Center
Stayton, Catherine; McVeigh, Katharine H.; Olson, E. Carolyn; Perkins, Krystal; Kerker, Bonnie D.
2011-01-01
Objective: To compare health risks of 2 subgroups of weapon carriers: victimized and nonvictimized youth. Methods: 2003-2007 NYC Youth Risk Behavior Surveys were analyzed using bivariate analyses and multinomial logistic regression. Results: Among NYC teens, 7.5% reported weapon carrying without victimization; 6.9% reported it with victimization.…
Hamilton, Jada G; Waters, Erika A
2018-02-01
People who believe that cancer has both genetic and behavioral risk factors have more accurate mental models of cancer causation and may be more likely to engage in cancer screening behaviors than people who do not hold such multifactorial causal beliefs. This research explored possible health cognitions and emotions that might produce such differences. Using nationally representative cross-sectional data from the US Health Information National Trends Survey (N = 2719), we examined whether endorsing a multifactorial model of cancer causation was associated with perceptions of risk and other cancer-related cognitions and affect. Data were analyzed using linear regression with jackknife variance estimation and procedures to account for the complex survey design and weightings. Bivariate and multivariable analyses indicated that people who endorsed multifactorial beliefs about cancer had higher absolute risk perceptions, lower pessimism about cancer prevention, and higher worry about harm from environmental toxins that could be ingested or that emanate from consumer products (Ps < .05). Bivariate analyses indicated that multifactorial beliefs were also associated with higher feelings of risk, but multivariable analyses suggested that this effect was accounted for by the negative affect associated with reporting a family history of cancer. Multifactorial beliefs were not associated with believing that everything causes cancer or that there are too many cancer recommendations to follow (Ps > .05). Holding multifactorial causal beliefs about cancer are associated with a constellation of risk perceptions, health cognitions, and affect that may motivate cancer prevention and detection behavior. Copyright © 2017 John Wiley & Sons, Ltd.
Dlugonski, Deirdre; Motl, Robert W
2012-02-01
Persons with multiple sclerosis (MS) have consistently reported lower levels of self-esteem compared with the general population. Despite this, very little is known about the antecedents and consequences of self-esteem in persons with MS. To examine (1) physical activity and social support as potentially modifiable correlates (i.e., antecedents) of self-esteem and (2) physical and psychological health-related quality of life as possible consequences of self-esteem in persons with MS. Participants (N = 46) wore an Actigraph accelerometer for 7 days and then completed a battery of questionnaires, including the Rosenberg Self-Esteem Scale (RSES), Multiple Sclerosis Impact Scale (MSIS-29), and Social Provisions Scale (SPS). The data were analyzed using PASW Statistics 18. Bivariate correlation analysis indicated that average daily step counts (r = .298, p = .026) and social support (r = .366, p = .007) were significantly correlated with self-esteem. Multiple linear regression analysis indicated that only social support was a significant predictor of self-esteem scores (β = .411, p = .004); pedometer steps approached significance as a predictor of self-esteem (β = .178, p = .112). Bivariate correlation analysis further indicated significant negative associations between self-esteem and physical (r = -.391, p = .004) and psychological (r = -.540, p = .0001) domains of health-related quality of life (HRQOL), indicating that higher self-esteem was associated with more positive HRQOL. Social support is a potentially modifiable variable that may be important to target when designing interventions to improve self-esteem and this might have implications for improving physical and psychological HRQOL in persons with MS.
Varni, James W; Shulman, Robert J; Self, Mariella M; Nurko, Samuel; Saps, Miguel; Saeed, Shehzad A; Patel, Ashish S; Dark, Chelsea Vaughan; Bendo, Cristiane B; Pohl, John F
2017-04-01
To investigate the patient-reported multidimensional gastrointestinal symptoms predictors of generic health-related quality of life (HRQOL) in pediatric patients with functional gastrointestinal disorders (FGIDs). The Pediatric Quality of Life Inventory™ (PedsQL™) Gastrointestinal Symptoms Scales and PedsQL™ 4.0 Generic Core Scales were completed in a 9-site study by 259 pediatric patients with functional constipation, functional abdominal pain (FAP), or irritable bowel syndrome (IBS). Gastrointestinal Symptoms Scales measuring stomach pain, stomach discomfort when eating, food and drink limits, trouble swallowing, heartburn and reflux, nausea and vomiting, gas and bloating, constipation, blood in poop, and diarrhea were identified as clinically important symptom differentiators from healthy controls based on prior findings, and subsequently tested for bivariate and multivariate linear associations with overall HRQOL. Gastrointestinal symptoms were differentially associated with decreased HRQOL in bivariate analyses for the three FGIDs. In predictive models utilizing hierarchical multiple regression analyses controlling for age, gender, and race/ethnicity, gastrointestinal symptoms differentially accounted for an additional 47, 40, and 60 % of the variance in patient-reported HRQOL for functional constipation, FAP, and IBS, respectively, reflecting large effect sizes. Significant individual gastrointestinal symptoms predictors were identified after controlling for the other gastrointestinal symptoms in the FGID-specific predictive models. Gastrointestinal symptoms represent potentially modifiable predictors of generic HRQOL in pediatric patients with FGIDs. Identifying the condition-specific gastrointestinal symptoms that are the most important predictors from the patient perspective facilitates a patient-centered approach to targeted interventions designed to ameliorate impaired overall HRQOL.
Improving nutrition in home child care: are food costs a barrier?
Monsivais, Pablo; Johnson, Donna B
2015-01-01
Objective Child-care providers have a key role to play in promoting child nutrition, but the higher cost of nutritious foods may pose a barrier. The present study tested the hypothesis that higher nutritional quality of foods served was associated with higher food expenditures in child care homes participating in the Child and Adult Care Food Program (CACFP). Design In this cross-sectional study, nutritional quality of foods served to children and food expenditures were analysed based on 5 d menus and food shopping receipts. Nutritional quality was based on servings of whole grains, fresh whole fruits and vegetables, energy density (kJ/g) and mean nutrient adequacy (mean percentage of dietary reference intake) for seven nutrients of concern for child health. Food expenditures were calculated by linking receipt and menu data. Associations between food expenditures and menu quality were examined using bivariate statistics and multiple linear regression models. Setting USA in 2008–2009. Subjects Sixty child-care providers participating in CACFP in King County, Washington State. Results In bivariate analyses, higher daily food expenditures were associated with higher total food energy and higher nutritional quality of menus. Controlling for energy and other covariates, higher food expenditures were strongly and positively associated with number of portions of whole grains and fresh produce served (P = 0·001 and 0·005, respectively), with lower energy density and with higher mean nutrient adequacy of menus overall (P = 0·003 and 0·032, respectively). Conclusions The results indicate that improving the nutritional quality of foods in child care may require higher food spending. PMID:22014448
Gender differences in compensation, job satisfaction, and other practice patterns in urology
Spencer, E. Sophie; Deal, Allison M.; Pruthi, Nicholas R.; Gonzalez, Chris M.; Kirby, E. Will; Langston, Joshua; McKenna, Patrick H.; McKibben, Maxim J.; Nielsen, Matthew E.; Raynor, Mathew C.; Wallen, Eric M.; Woods, Michael E.; Pruthi, Raj S.; Smith, Angela B.
2016-01-01
Purpose The proportion of women in urology has increased from <0.5% in 1981 to 10% today. Furthermore, 33% of students matching in urology are now female. This analysis sought to characterize the female workforce in urology in comparison to men with regard to income, workload, and job satisfaction. Materials and Methods We collaborated with the American Urologic Association to survey its domestic membership of practicing urologists regarding socioeconomic, workforce, and quality of life issues. 6,511 survey invitations were sent via e-mail. The survey consisted of 26 questions and took approximately 13 minutes to complete. Linear regression models were used to evaluate bivariable and multivariable associations with job satisfaction and compensation. Results A total of 848 responses (n=660 (90%) male, n=73 (10%) female) were collected for a total response rate of 13%. On bivariable analysis, female urologists were younger (p<0.0001), more likely to be fellowship trained (p=0.002), worked in academics (p=0.008), were less likely to be self-employed, and worked fewer hours (p=0.03) compared to males. On multivariable analysis, female gender was a significant predictor of lower compensation (p = 0.001) when controlling for work hours, call frequency, age, practice setting and type, fellowship training, and Advance Practice Provider employment. Adjusted salaries among female urologists were $76,321 less than men. Gender was not a predictor for job satisfaction. Conclusions Female urologists are significantly less compensated compared to males, after adjusting for several factors likely contributing to compensation. There is no difference in job satisfaction between male and female urologists. PMID:26384452
Exploring the effects of coexisting amyloid in subcortical vascular cognitive impairment.
Dao, Elizabeth; Hsiung, Ging-Yuek Robin; Sossi, Vesna; Jacova, Claudia; Tam, Roger; Dinelle, Katie; Best, John R; Liu-Ambrose, Teresa
2015-10-12
Mixed pathology, particularly Alzheimer's disease with cerebrovascular lesions, is reported as the second most common cause of dementia. Research on mixed dementia typically includes people with a primary AD diagnosis and hence, little is known about the effects of co-existing amyloid pathology in people with vascular cognitive impairment (VCI). The purpose of this study was to understand whether individual differences in amyloid pathology might explain variations in cognitive impairment among individuals with clinical subcortical VCI (SVCI). Twenty-two participants with SVCI completed an (11)C Pittsburgh compound B (PIB) position emission tomography (PET) scan to quantify global amyloid deposition. Cognitive function was measured using: 1) MOCA; 2) ADAS-Cog; 3) EXIT-25; and 4) specific executive processes including a) Digits Forward and Backwards Test, b) Stroop-Colour Word Test, and c) Trail Making Test. To assess the effect of amyloid deposition on cognitive function we conducted Pearson bivariate correlations to determine which cognitive measures to include in our regression models. Cognitive variables that were significantly correlated with PIB retention values were entered in a hierarchical multiple linear regression analysis to determine the unique effect of amyloid on cognitive function. We controlled for age, education, and ApoE ε4 status. Bivariate correlation results showed that PIB binding was significantly correlated with ADAS-Cog (p < 0.01) and MOCA (p < 0.01); increased PIB binding was associated with worse cognitive function on both cognitive measures. PIB binding was not significantly correlated with the EXIT-25 or with specific executive processes (p > 0.05). Regression analyses controlling for age, education, and ApoE ε4 status indicated an independent association between PIB retention and the ADAS-Cog (adjusted R-square change of 15.0%, Sig F Change = 0.03). PIB retention was also independently associated with MOCA scores (adjusted R-Square Change of 27.0%, Sig F Change = 0.02). We found that increased global amyloid deposition was significantly associated with greater memory and executive dysfunctions as measured by the ADAS-Cog and MOCA. Our findings point to the important role of co-existing amyloid deposition for cognitive function in those with a primary SVCI diagnosis. As such, therapeutic approaches targeting SVCI must consider the potential role of amyloid for the optimal care of those with mixed dementia. NCT01027858.
Parathyroid Hormone Levels and Cognition
NASA Technical Reports Server (NTRS)
Burnett, J.; Smith, S.M.; Aung, K.; Dyer, C.
2009-01-01
Hyperparathyroidism is a well-recognized cause of impaired cognition due to hypercalcemia. However, recent studies have suggested that perhaps parathyroid hormone itself plays a role in cognition, especially executive dysfunction. The purpose of this study was to explore the relationship of parathyroid hormone levels in a study cohort of elders with impaied cognition. Methods: Sixty community-living adults, 65 years of age and older, reported to Adult Protective Services for self-neglect and 55 controls matched (on age, ethnicity, gender and socio-economic status) consented and participated in this study. The research team conducted in-home comprehensive geriatric assessments which included the Mini-mental state exam (MMSE), the 15-item geriatric depression scale (GDS) , the Wolf-Klein clock test and a comprehensive nutritional panel, which included parathyroid hormone and ionized calcium. Students t tests and linear regression analyses were performed to assess for bivariate associations. Results: Self-neglecters (M = 73.73, sd=48.4) had significantly higher PTH levels compared to controls (M =47.59, sd=28.7; t=3.59, df=98.94, p<.01). There was no significant group difference in ionized calcium levels. Overall, PTH was correlated with the MMSE (r=-.323, p=.001). Individual regression analyses revealed a statistically significant correlation between PTH and MMSE in the self-neglect group (r=-.298, p=.024) and this remained significant after controlling for ionized calcium levels in the regression. No significant associations were revealed in the control group or among any of the other cognitive measures. Conclusion: Parathyroid hormone may be associated with cognitive performance.
Lohr, Kristine M; Clauser, Amanda; Hess, Brian J; Gelber, Allan C; Valeriano-Marcet, Joanne; Lipner, Rebecca S; Haist, Steven A; Hawley, Janine L; Zirkle, Sarah; Bolster, Marcy B
2015-11-01
The American College of Rheumatology (ACR) Adult Rheumatology In-Training Examination (ITE) is a feedback tool designed to identify strengths and weaknesses in the content knowledge of individual fellows-in-training and the training program curricula. We determined whether scores on the ACR ITE, as well as scores on other major standardized medical examinations and competency-based ratings, could be used to predict performance on the American Board of Internal Medicine (ABIM) Rheumatology Certification Examination. Between 2008 and 2012, 629 second-year fellows took the ACR ITE. Bivariate correlation analyses of assessment scores and multiple linear regression analyses were used to determine whether ABIM Rheumatology Certification Examination scores could be predicted on the basis of ACR ITE scores, United States Medical Licensing Examination scores, ABIM Internal Medicine Certification Examination scores, fellowship directors' ratings of overall clinical competency, and demographic variables. Logistic regression was used to evaluate whether these assessments were predictive of a passing outcome on the Rheumatology Certification Examination. In the initial linear model, the strongest predictors of the Rheumatology Certification Examination score were the second-year fellows' ACR ITE scores (β = 0.438) and ABIM Internal Medicine Certification Examination scores (β = 0.273). Using a stepwise model, the strongest predictors of higher scores on the Rheumatology Certification Examination were second-year fellows' ACR ITE scores (β = 0.449) and ABIM Internal Medicine Certification Examination scores (β = 0.276). Based on the findings of logistic regression analysis, ACR ITE performance was predictive of a pass/fail outcome on the Rheumatology Certification Examination (odds ratio 1.016 [95% confidence interval 1.011-1.021]). The predictive value of the ACR ITE score with regard to predicting performance on the Rheumatology Certification Examination supports use of the Adult Rheumatology ITE as a valid feedback tool during fellowship training. © 2015, American College of Rheumatology.
Byg, Blaire; Bazzi, Angela Robertson; Funk, Danielle; James, Bonface; Potter, Jennifer
2016-12-01
Syndemic theory posits that epidemics of multiple physical and psychosocial problems co-occur among disadvantaged groups due to adverse social conditions. Although sexual minority populations are often stigmatized and vulnerable to multiple health problems, the syndemic perspective has been underutilized in understanding chronic disease. To assess the potential utility of this perspective in understanding the management of co-occurring HIV and Type 2 diabetes, we used linear regression to examine glycemic control (A1c) among men who have sex with men (MSM) with both HIV and Type 2 diabetes (n = 88). Bivariable linear regression explored potential syndemic correlates of inadequate glycemic control. Compared to those with adequate glycemic control (A1c ≤ 7.5 %), more men with inadequate glycemic control (A1c > 7.5 %) had hypertension (70 vs. 46 %, p = 0.034), high triglycerides (93 vs. 61 %, p = 0.002), depression (67 vs. 39 %, p = 0.018), current substance abuse (15 vs. 2 %, p = 0.014), and detectable levels of HIV (i.e., viral load ≥75 copies per ml blood; 30 vs. 10 %, p = 0.019). In multivariable regression controlling for age, the factors that were independently associated with higher A1c were high triglycerides, substance use, and detectable HIV viral load, suggesting that chronic disease management among MSM is complex and challenging for patients and providers. Findings also suggest that syndemic theory can be a clarifying lens for understanding chronic disease management among sexual minority stigmatized populations. Interventions targeting single conditions may be inadequate when multiple conditions co-occur; thus, research using a syndemic framework may be helpful in identifying intervention strategies that target multiple co-occurring conditions.
Statistical methods for astronomical data with upper limits. II - Correlation and regression
NASA Technical Reports Server (NTRS)
Isobe, T.; Feigelson, E. D.; Nelson, P. I.
1986-01-01
Statistical methods for calculating correlations and regressions in bivariate censored data where the dependent variable can have upper or lower limits are presented. Cox's regression and the generalization of Kendall's rank correlation coefficient provide significant levels of correlations, and the EM algorithm, under the assumption of normally distributed errors, and its nonparametric analog using the Kaplan-Meier estimator, give estimates for the slope of a regression line. Monte Carlo simulations demonstrate that survival analysis is reliable in determining correlations between luminosities at different bands. Survival analysis is applied to CO emission in infrared galaxies, X-ray emission in radio galaxies, H-alpha emission in cooling cluster cores, and radio emission in Seyfert galaxies.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Qichun; Zhang, Xuesong; Xu, Xingya
Riverine carbon cycling is an important, but insufficiently investigated component of the global carbon cycle. Analyses of environmental controls on riverine carbon cycling are critical for improved understanding of mechanisms regulating carbon processing and storage along the terrestrial-aquatic continuum. Here, we compile and analyze riverine dissolved organic carbon (DOC) concentration data from 1402 United States Geological Survey (USGS) gauge stations to examine the spatial variability and environmental controls of DOC concentrations in the United States (U.S.) surface waters. DOC concentrations exhibit high spatial variability, with an average of 6.42 ± 6.47 mg C/ L (Mean ± Standard Deviation). In general,more » high DOC concentrations occur in the Upper Mississippi River basin and the Southeastern U.S., while low concentrations are mainly distributed in the Western U.S. Single-factor analysis indicates that slope of drainage areas, wetlands, forests, percentage of first-order streams, and instream nutrients (such as nitrogen and phosphorus) pronouncedly influence DOC concentrations, but the explanatory power of each bivariate model is lower than 35%. Analyses based on the general multi-linear regression models suggest DOC concentrations are jointly impacted by multiple factors. Soil properties mainly show positive correlations with DOC concentrations; forest and shrub lands have positive correlations with DOC concentrations, but urban area and croplands demonstrate negative impacts; total instream phosphorus and dam density correlate positively with DOC concentrations. Notably, the relative importance of these environmental controls varies substantially across major U.S. water resource regions. In addition, DOC concentrations and environmental controls also show significant variability from small streams to large rivers, which may be caused by changing carbon sources and removal rates by river orders. In sum, our results reveal that general multi-linear regression analysis of twenty one terrestrial and aquatic environmental factors can partially explain (56%) the DOC concentration variation. In conclusion, this study highlights the complexity of the interactions among these environmental factors in determining DOC concentrations, thus calls for processes-based, non-linear methodologies to constrain uncertainties in riverine DOC cycling.« less
Correlates of early pregnancy serum brain-derived neurotrophic factor in a Peruvian population.
Yang, Na; Levey, Elizabeth; Gelaye, Bizu; Zhong, Qiu-Yue; Rondon, Marta B; Sanchez, Sixto E; Williams, Michelle A
2017-12-01
Knowledge about factors that influence serum brain-derived neurotrophic factor (BDNF) concentrations during early pregnancy is lacking. The aim of the study is to examine the correlates of early pregnancy serum BDNF concentrations. A total of 982 women attending prenatal care clinics in Lima, Peru, were recruited in early pregnancy. Pearson's correlation coefficient was calculated to evaluate the relation between BDNF concentrations and continuous covariates. Analysis of variance and generalized linear models were used to compare the unadjusted and adjusted BDNF concentrations according to categorical variables. Multivariable linear regression models were applied to determine the factors that influence early pregnancy serum BDNF concentrations. In bivariate analysis, early pregnancy serum BDNF concentrations were positively associated with maternal age (r = 0.16, P < 0.001) and early pregnancy body mass index (BMI) (r = 0.17, P < 0.001), but inversely correlated with gestational age at sample collection (r = -0.21, P < 0.001) and C-reactive protein (CRP) concentrations (r = -0.07, P < 0.05). In the multivariable linear regression model, maternal age (β = 0.11, P = 0.001), early pregnancy BMI (β = 1.58, P < 0.001), gestational age at blood collection (β = -0.33, P < 0.001), and serum CRP concentrations (β = -0.57, P = 0.002) were significantly associated with early pregnancy serum BDNF concentrations. Participants with moderate antepartum depressive symptoms (Patient Health Questionnaire-9 (PHQ-9) score ≥ 10) had lower serum BDNF concentrations compared with participants with no/mild antepartum depressive symptoms (PHQ-9 score < 10). Maternal age, early pregnancy BMI, gestational age, and the presence of moderate antepartum depressive symptoms were statistically significantly associated with early pregnancy serum BDNF concentrations in low-income Peruvian women. Biological changes of CRP during pregnancy may affect serum BDNF concentrations.
Mutual information estimation for irregularly sampled time series
NASA Astrophysics Data System (ADS)
Rehfeld, K.; Marwan, N.; Heitzig, J.; Kurths, J.
2012-04-01
For the automated, objective and joint analysis of time series, similarity measures are crucial. Used in the analysis of climate records, they allow for a complimentary, unbiased view onto sparse datasets. The irregular sampling of many of these time series, however, makes it necessary to either perform signal reconstruction (e.g. interpolation) or to develop and use adapted measures. Standard linear interpolation comes with an inevitable loss of information and bias effects. We have recently developed a Gaussian kernel-based correlation algorithm with which the interpolation error can be substantially lowered, but this would not work should the functional relationship in a bivariate setting be non-linear. We therefore propose an algorithm to estimate lagged auto and cross mutual information from irregularly sampled time series. We have extended the standard and adaptive binning histogram estimators and use Gaussian distributed weights in the estimation of the (joint) probabilities. To test our method we have simulated linear and nonlinear auto-regressive processes with Gamma-distributed inter-sampling intervals. We have then performed a sensitivity analysis for the estimation of actual coupling length, the lag of coupling and the decorrelation time in the synthetic time series and contrast our results to the performance of a signal reconstruction scheme. Finally we applied our estimator to speleothem records. We compare the estimated memory (or decorrelation time) to that from a least-squares estimator based on fitting an auto-regressive process of order 1. The calculated (cross) mutual information results are compared for the different estimators (standard or adaptive binning) and contrasted with results from signal reconstruction. We find that the kernel-based estimator has a significantly lower root mean square error and less systematic sampling bias than the interpolation-based method. It is possible that these encouraging results could be further improved by using non-histogram mutual information estimators, like k-Nearest Neighbor or Kernel-Density estimators, but for short (<1000 points) and irregularly sampled datasets the proposed algorithm is already a great improvement.
Abbott, Allan; Ghasemi-Kafash, Elaheh; Dedering, Åsa
2014-10-01
The purpose of this study was to evaluate the validity and preference for assessing pain magnitude with electrocutaneous testing (ECT) compared to the visual analogue scale (VAS) and Borg CR10 scale in men and women with cervical radiculopathy of varying sensory phenotypes. An additional purpose was to investigate ECT sensory and pain thresholds in men and women with cervical radiculopathy of varying sensory phenotypes. This is a cross-sectional study of 34 patients with cervical radiculopathy. Scatterplots and linear regression were used to investigate bivariate relationships between ECT, VAS and Borg CR10 methods of pain magnitude measurement as well as ECT sensory and pain thresholds. The use of the ECT pain magnitude matching paradigm for patients with cervical radiculopathy with normal sensory phenotype shows good linear association with arm pain VAS (R(2) = 0.39), neck pain VAS (R(2) = 0.38), arm pain Borg CR10 scale (R(2) = 0.50) and neck pain Borg CR10 scale (R(2) = 0.49) suggesting acceptable validity of the procedure. For patients with hypoesthesia and hyperesthesia sensory phenotypes, the ECT pain magnitude matching paradigm does not show adequate linear association with rating scale methods rendering the validity of the procedure as doubtful. ECT for sensory and pain threshold investigation, however, provides a method to objectively assess global sensory function in conjunction with sensory receptor specific bedside examination measures.
Idealized models of the joint probability distribution of wind speeds
NASA Astrophysics Data System (ADS)
Monahan, Adam H.
2018-05-01
The joint probability distribution of wind speeds at two separate locations in space or points in time completely characterizes the statistical dependence of these two quantities, providing more information than linear measures such as correlation. In this study, we consider two models of the joint distribution of wind speeds obtained from idealized models of the dependence structure of the horizontal wind velocity components. The bivariate Rice distribution follows from assuming that the wind components have Gaussian and isotropic fluctuations. The bivariate Weibull distribution arises from power law transformations of wind speeds corresponding to vector components with Gaussian, isotropic, mean-zero variability. Maximum likelihood estimates of these distributions are compared using wind speed data from the mid-troposphere, from different altitudes at the Cabauw tower in the Netherlands, and from scatterometer observations over the sea surface. While the bivariate Rice distribution is more flexible and can represent a broader class of dependence structures, the bivariate Weibull distribution is mathematically simpler and may be more convenient in many applications. The complexity of the mathematical expressions obtained for the joint distributions suggests that the development of explicit functional forms for multivariate speed distributions from distributions of the components will not be practical for more complicated dependence structure or more than two speed variables.
A survey of variable selection methods in two Chinese epidemiology journals
2010-01-01
Background Although much has been written on developing better procedures for variable selection, there is little research on how it is practiced in actual studies. This review surveys the variable selection methods reported in two high-ranking Chinese epidemiology journals. Methods Articles published in 2004, 2006, and 2008 in the Chinese Journal of Epidemiology and the Chinese Journal of Preventive Medicine were reviewed. Five categories of methods were identified whereby variables were selected using: A - bivariate analyses; B - multivariable analysis; e.g. stepwise or individual significance testing of model coefficients; C - first bivariate analyses, followed by multivariable analysis; D - bivariate analyses or multivariable analysis; and E - other criteria like prior knowledge or personal judgment. Results Among the 287 articles that reported using variable selection methods, 6%, 26%, 30%, 21%, and 17% were in categories A through E, respectively. One hundred sixty-three studies selected variables using bivariate analyses, 80% (130/163) via multiple significance testing at the 5% alpha-level. Of the 219 multivariable analyses, 97 (44%) used stepwise procedures, 89 (41%) tested individual regression coefficients, but 33 (15%) did not mention how variables were selected. Sixty percent (58/97) of the stepwise routines also did not specify the algorithm and/or significance levels. Conclusions The variable selection methods reported in the two journals were limited in variety, and details were often missing. Many studies still relied on problematic techniques like stepwise procedures and/or multiple testing of bivariate associations at the 0.05 alpha-level. These deficiencies should be rectified to safeguard the scientific validity of articles published in Chinese epidemiology journals. PMID:20920252
Content and Method in the Teaching of Marketing Research Revisited
ERIC Educational Resources Information Center
Wilson, Holt; Neeley, Concha; Niedzwiecki, Kelly
2009-01-01
This paper presents the findings from a survey of marketing research faculty. The study finds SPSS is the most used statistical software, that cross tabulation, single, independent, and dependent t-tests, and ANOVA are among the most important statistical tools according to respondents. Bivariate and multiple regression are also considered…
Organizational Response to Conflict: Future Conflict and Work Outcomes
ERIC Educational Resources Information Center
Meyer, Susan
2004-01-01
The purpose of this study was to examine how on organization's response to conflict affected the amount and intensity of future conflict and negative work outcomes. In this cross-sectional study of 3,374 government service workers, bivariate correlations and multiple regressions revealed associations between managers' conflict-handling style (CHS)…
Pevnick, Joshua M.; Fuller, Garth; Duncan, Ray; Spiegel, Brennan M. R.
2016-01-01
Background Personal fitness trackers (PFT) have substantial potential to improve healthcare. Objective To quantify and characterize early adopters who shared their PFT data with providers. Methods We used bivariate statistics and logistic regression to compare patients who shared any PFT data vs. patients who did not. Results A patient portal was used to invite 79,953 registered portal users to share their data. Of 66,105 users included in our analysis, 499 (0.8%) uploaded data during an initial 37-day study period. Bivariate and regression analysis showed that early adopters were more likely than non-adopters to be younger, male, white, health system employees, and to have higher BMIs. Neither comorbidities nor utilization predicted adoption. Conclusion Our results demonstrate that patients had little intrinsic desire to share PFT data with their providers, and suggest that patients most at risk for poor health outcomes are least likely to share PFT data. Marketing, incentives, and/or cultural change may be needed to induce such data-sharing. PMID:27846287
NASA Astrophysics Data System (ADS)
Winahju, W. S.; Mukarromah, A.; Putri, S.
2015-03-01
Leprosy is a chronic infectious disease caused by bacteria of leprosy (Mycobacterium leprae). Leprosy has become an important thing in Indonesia because its morbidity is quite high. Based on WHO data in 2014, in 2012 Indonesia has the highest number of new leprosy patients after India and Brazil with a contribution of 18.994 people (8.7% of the world). This number makes Indonesia automatically placed as the country with the highest number of leprosy morbidity of ASEAN countries. The province that most contributes to the number of leprosy patients in Indonesia is East Java. There are two kind of leprosy. They consist of pausibacillary and multibacillary. The morbidity of multibacillary leprosy is higher than pausibacillary leprosy. This paper will discuss modeling both of the number of multibacillary and pausibacillary leprosy patients as responses variables. These responses are count variables, so modeling will be conducted by using bivariate poisson regression method. Unit experiment used is in East Java, and predictors involved are: environment, demography, and poverty. The model uses data in 2012, and the result indicates that all predictors influence significantly.
Cognition in patients with burn injury in the inpatient rehabilitation population.
Purohit, Maulik; Goldstein, Richard; Nadler, Deborah; Mathews, Katie; Slocum, Chloe; Gerrard, Paul; DiVita, Margaret A; Ryan, Colleen M; Zafonte, Ross; Kowalske, Karen; Schneider, Jeffrey C
2014-07-01
To analyze potential cognitive impairment in patients with burn injury in the inpatient rehabilitation population. Rehabilitation patients with burn injury were compared with the following impairment groups: spinal cord injury, amputation, polytrauma and multiple fractures, and hip replacement. Differences between the groups were calculated for each cognitive subscale item and total cognitive FIM. Patients with burn injury were compared with the other groups using a bivariate linear regression model. A multivariable linear regression model was used to determine whether differences in cognition existed after adjusting for covariates (eg, sociodemographic factors, facility factors, medical complications) based on previous studies. Inpatient rehabilitation facilities. Data from Uniform Data System for Medical Rehabilitation from 2002 to 2011 for adults with burn injury (N=5347) were compared with other rehabilitation populations (N=668,816). Not applicable. Comparison of total cognitive FIM scores and subscales (memory, verbal comprehension, verbal expression, social interaction, problem solving) for patients with burn injury versus other rehabilitation populations. Adults with burn injuries had an average total cognitive FIM score ± SD of 26.8±7.0 compared with an average FIM score ± SD of 28.7±6.0 for the other groups combined (P<.001). The subscale with the greatest difference between those with burn injury and the other groups was memory (5.1±1.7 compared with 5.6±1.5, P<.001). These differences persisted after adjustment for covariates. Adults with burn injury have worse cognitive FIM scores than other rehabilitation populations. Future research is needed to determine the impact of this comorbidity on patient outcomes and potential interventions for these deficits. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.
Iron status as a covariate in methylmercury-associated neurotoxicity risk.
Fonseca, Márlon de Freitas; De Souza Hacon, Sandra; Grandjean, Philippe; Choi, Anna Lai; Bastos, Wanderley Rodrigues
2014-04-01
Intrauterine methylmercury exposure and prenatal iron deficiency negatively affect offspring's brain development. Since fish is a major source of both methylmercury and iron, occurrence of negative confounding may affect the interpretation of studies concerning cognition. We assessed relationships between methylmercury exposure and iron-status in childbearing females from a population naturally exposed to methylmercury through fish intake (Amazon). We concluded a census (refuse <20%) collecting samples from 274 healthy females (12-49 years) for hair-mercury determination and assessed iron-status through red cell tests and determination of serum ferritin and iron. Reactive C protein and thyroid hormones was used for excluding inflammation and severe thyroid dysfunctions that could affect results. We assessed the association between iron-status and hair-mercury by bivariate correlation analysis and also by different multivariate models: linear regression (to check trends); hierarchical agglomerative clustering method (groups of variables correlated with each other); and factor analysis (to examine redundancy or duplication from a set of correlated variables). Hair-mercury correlated weakly with mean corpuscular volume (r=.141; P=.020) and corpuscular hemoglobin (r=.132; .029), but not with the best biomarker of iron-status, ferritin (r=.037; P=.545). In the linear regression analysis, methylmercury exposure showed weak association with age-adjusted ferritin; age had a significant coefficient (Beta=.015; 95% CI: .003-.027; P=.016) but ferritin did not (Beta=.034; 95% CI: -.147 to .216; P=.711). In the hierarchical agglomerative clustering method, hair-mercury and iron-status showed the smallest similarities. Regarding factor analysis, iron-status and hair-mercury loaded different uncorrelated components. We concluded that iron-status and methylmercury exposure probably occur in an independent way. Copyright © 2013 Elsevier Ltd. All rights reserved.
Fuller, Daniel; Cummins, Steven; Matthews, Stephen A
2013-01-01
A consistent body of research has shown that the neighborhood food environment is associated with fruit and vegetable (F&V) consumption and obesity in deprived neighborhoods in the United States. However, these studies have often neglected to consider how transportation can moderate associations between food accessibility and diet-related outcomes. This study examined associations between distance to primary food store, fruit and vegetable consumption, and BMI and whether mode of transportation to the primary food store moderates this relation. Cross-sectional data from the baseline wave of the Philadelphia Neighborhood Food Environment Study were used. A telephone survey of adult (≥18 y of age) household primary food shoppers residing in 2 Philadelphia neighborhoods was conducted (n = 1440). In a bivariate linear regression analysis, distance to primary food store did not predict F&V consumption (β = 0.04; 95% CI: -0.00, 0.09). Linear regression analysis stratified by transportation mode to the main F&V store showed no difference in F&V consumption between car, public, and multimodal transportation users. Compared with respondents using multimodal transportation, those using public transit had a significantly lower BMI (β = -1.31; 95% CI: -2.50, -0.10), whereas those using an automobile did not (β = -0.41; 95% CI: -1.36, 0.54). The assumption that using an automobile to access food stores results in increased F&V consumption was not confirmed. Significant associations were found for the relation between transportation mode and BMI. Theory-based mechanisms explaining relationships between the primary transportation mode used to access food stores and BMI should be further explored.
Communication skills of tutors and family medicine physician residents in Primary Care clinics.
Valverde Bolívar, Francisco Javier; Pedregal González, Miguel; Pérez Fuentes, María Francisca; Alcalde Molina, María Dolores; Torío Durántez, Jesús; Delgado Rodríguez, Miguel
2016-12-01
To determine the communicative profiles of family physicians and the characteristics associated with an improved level of communication with the patient. A descriptive multicentre study. Primary Healthcare Centres in Almeria, Granada, Jaen and Huelva. 119 family physicians (tutors and 4th year resident physicians) filmed and observed with patients. Demographic and professional characteristics. Analysis of the communication between physicians and patients, using a CICAA (Connect, Identify, Understand, Agree and Assist, in English) scale. A descriptive, bivariate, multiple linear regression analysis was performed. There were 436 valid interviews. Almost 100% of physicians were polite and friendly, facilitating a dialogue with the patient and allowing them to express their doubts. However, few physicians attempted to explore the state of mind of the patient, or enquire about their family situation or any important stressful events, nor did they ask open questions. Furthermore, few physicians summarised the information gathered. The mean score was 21.43±5.91 points (maximum 58). There were no differences in the total score between gender, city, or type of centre. The linear regression verified that the highest scores were obtained from tutors (B: 2.98), from the duration of the consultations (B: 0.63), and from the age of the professionals (B: -0.1). Physicians excel in terms of creating a friendly environment, possessing good listening skills, and providing the patient with information. However the ability to empathise, exploring the psychosocial sphere, carrying out shared decision-making, and asking open questions must be improved. Being a tutor, devoting more time to consultations, and being younger, results in a significant improvement in communication with the patient. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.
Stark, Ken D; Aristizabal Henao, Juan J; Metherel, Adam H; Pilote, Louise
2016-01-01
Specific blood levels of eicosapentaenoic plus docosahexaenoic acid (EPA+DHA, wt% of total) in erythrocytes or "the omega-3 index" have been recommended for cardio-protection, but fatty acids are often measured in different blood fractions. The ability to estimate the % of EPA+DHA in erythrocytes from the fatty acid composition of other blood fractions would enable clinical assessments of omega-3 status when erythrocyte fractions are not available and increase the ability to compare blood levels of omega-3 fatty acids across clinical studies. The fatty acid composition of baseline plasma, erythrocytes and whole blood samples from participants (n=1104) in a prospective, multicenter study examining acute coronary syndrome were determined. The ability to predict the % of EPA+DHA in erythrocytes from other blood fractions were examined using bivariate and multiple linear regression modelling. Concordance analysis was also used to compare the actual erythrocytes EPA+DHA values to values estimated from other blood fractions. EPA+DHA in erythrocytes was significantly (p<0.001) correlated EPA+DHA in plasma (r(2)=0.54) and whole blood (r(2)=0.79). Using multiple linear regression to predict EPA+DHA in erythrocytes resulted in stronger coefficients of determination in both plasma (R(2)=0.70) and whole blood (R(2)=0.84). Concordance analyses indicated agreement between actual and estimated EPA+DHA in erythrocytes, although estimating from plasma fatty acids appears to require translation by categorization rather than by translation as continuous data. This study shows that the fatty acid composition of different blood fractions can be used to estimate erythrocyte EPA+DHA in a population with acute coronary syndrome. Copyright © 2015 Elsevier Ltd. All rights reserved.
Ghaddar, Suad; Brown, Cynthia J; Pagán, José A; Díaz, Violeta
2010-09-01
To explore the relationship between acculturation and healthy lifestyle habits in the largely Hispanic populations living in underserved communities in the United States of America along the U.S.-Mexico border. A cross-sectional study was conducted from April 2006 to June 2008 using survey data from the Alliance for a Healthy Border, a program designed to reduce health disparities in the U.S.-Mexico border region by funding nutrition and physical activity education programs at 12 federally qualified community health centers in Arizona, California, New Mexico, and Texas. The survey included questions on acculturation, diet, exercise, and demographic factors and was completed by 2,381 Alliance program participants, of whom 95.3% were Hispanic and 45.4% were under the U.S. poverty level for 2007. Chi-square (χ2) and Student's t tests were used for bivariate comparisons between acculturation and dietary and physical activity measures. Linear regression and binary logistic regression were used to control for factors associated with nutrition and exercise. Based on univariate tests and confirmed by regression analysis controlling for sociodemographic and health variables, less acculturated survey respondents reported a significantly higher frequency of fruit and vegetable consumption and healthier dietary habits than those who were more acculturated. Adjusted binary logistic regression confirmed that individuals with low language acculturation were less likely to engage in physical activity than those with moderate to high acculturation (odds ratio 0.75, 95% confidence interval 0.59-0.95). Findings confirmed an association between acculturation and healthy lifestyle habits and supported the hypothesis that acculturation in border community populations tends to decrease the practice of some healthy dietary habits while increasing exposure to and awareness of the importance of other healthy behaviors.
Muldoon, Katherine A; King, Rachel; Zhang, Wendy; Birungi, Josephine; Nanfuka, Mastula; Tibengana, Samuel; Afolabi, Omoboade; Moore, David M
2018-06-01
Sexual coercion, especially forced sexual debut, is associated with lifelong adverse health consequences. This is compounded in regions, such as Uganda, where the dual impact of HIV and violence critically shapes women's sexual health risks. Among a sample of women in HIV serodiscordant relationships, we investigated the prevalence and consequences of forced sexual debut. Data for this analysis come from the Highly Active Antiretroviral Treatment as Prevention (HAARP) Study, a cohort of HIV serodiscordant couples in Jinja, Eastern Uganda, and investigates the role of forced sexual debut on two outcomes: age of sexual debut and having more than three lifetime sexual partners. Bivariate and multivariate linear regressions were used to model age at sexual debut using β and adjusted (A) β and 95% confidence intervals (CIs). Bivariate and multivariate logistic regressions were used to model having more than three lifetime sexual partners and used odds ratios (ORs) and adjusted OR (AOR) and 95% CI. A total of 574 women were included in this analysis, median age 35 years, and 241 (41.99%) were living with HIV. A quarter (24.21%) of women experienced forced sexual debut at the median age of 16 years. Forced sexual debut was significantly associated with earlier age of sexual debut (β = -1.17, 95% CI: [-1.64, -0.68]). Forced sexual debut was significantly associated with having more than three sexual partners (AOR: 1.99, 95% CI: [1.33, 2.99]), in addition to older age (AOR: 1.02, 95% CI: [1.01, 1.05]). Speaking Lusoga, the primary language in Jinja (the study site) was associated with lower odds of having more than three sexual partners (AOR: 0.63, 95% CI: [0.43, 0.92]). Forced sexual debut was a common experience significantly associated with younger age of sexual debut and higher number of lifetime sexual partners. Safe and consensual first sexual experiences for young women play an important role in reducing HIV risk and lay the foundation for healthy and safe sexual health.
Predictive spectroscopy and chemical imaging based on novel optical systems
NASA Astrophysics Data System (ADS)
Nelson, Matthew Paul
1998-10-01
This thesis describes two futuristic optical systems designed to surpass contemporary spectroscopic methods for predictive spectroscopy and chemical imaging. These systems are advantageous to current techniques in a number of ways including lower cost, enhanced portability, shorter analysis time, and improved S/N. First, a novel optical approach to predicting chemical and physical properties based on principal component analysis (PCA) is proposed and evaluated. A regression vector produced by PCA is designed into the structure of a set of paired optical filters. Light passing through the paired filters produces an analog detector signal directly proportional to the chemical/physical property for which the regression vector was designed. Second, a novel optical system is described which takes a single-shot approach to chemical imaging with high spectroscopic resolution using a dimension-reduction fiber-optic array. Images are focused onto a two- dimensional matrix of optical fibers which are drawn into a linear distal array with specific ordering. The distal end is imaged with a spectrograph equipped with an ICCD camera for spectral analysis. Software is used to extract the spatial/spectral information contained in the ICCD images and deconvolute them into wave length-specific reconstructed images or position-specific spectra which span a multi-wavelength space. This thesis includes a description of the fabrication of two dimension-reduction arrays as well as an evaluation of the system for spatial and spectral resolution, throughput, image brightness, resolving power, depth of focus, and channel cross-talk. PCA is performed on the images by treating rows of the ICCD images as spectra and plotting the scores of each PC as a function of reconstruction position. In addition, iterative target transformation factor analysis (ITTFA) is performed on the spectroscopic images to generate ``true'' chemical maps of samples. Univariate zero-order images, univariate first-order spectroscopic images, bivariate first-order spectroscopic images, and multivariate first-order spectroscopic images of the temporal development of laser-induced plumes are presented and interpreted. Reconstructed chemical images generated using bivariate and trivariate wavelength techniques, bimodal and trimodal PCA methods, and bimodal and trimodal ITTFA approaches are also included.
Dong, Wei-Feng; Canil, Sarah; Lai, Raymond; Morel, Didier; Swanson, Paul E.; Izevbaye, Iyare
2018-01-01
A new automated MYC IHC classifier based on bivariate logistic regression is presented. The predictor relies on image analysis developed with the open-source ImageJ platform. From a histologic section immunostained for MYC protein, 2 dimensionless quantitative variables are extracted: (a) relative distance between nuclei positive for MYC IHC based on euclidean minimum spanning tree graph and (b) coefficient of variation of the MYC IHC stain intensity among MYC IHC-positive nuclei. Distance between positive nuclei is suggested to inversely correlate MYC gene rearrangement status, whereas coefficient of variation is suggested to inversely correlate physiological regulation of MYC protein expression. The bivariate classifier was compared with 2 other MYC IHC classifiers (based on percentage of MYC IHC positive nuclei), all tested on 113 lymphomas including mostly diffuse large B-cell lymphomas with known MYC fluorescent in situ hybridization (FISH) status. The bivariate classifier strongly outperformed the “percentage of MYC IHC-positive nuclei” methods to predict MYC+ FISH status with 100% sensitivity (95% confidence interval, 94-100) associated with 80% specificity. The test is rapidly performed and might at a minimum provide primary IHC screening for MYC gene rearrangement status in diffuse large B-cell lymphomas. Furthermore, as this bivariate classifier actually predicts “permanent overexpressed MYC protein status,” it might identify nontranslocation-related chromosomal anomalies missed by FISH. PMID:27093450
Quick, Virginia; Byrd-Bredbenner, Carol; White, Adrienne A; Brown, Onikia; Colby, Sarah; Shoff, Suzanne; Lohse, Barbara; Horacek, Tanya; Kidd, Tanda; Greene, Geoffrey
2014-01-01
To examine relationships of sleep, eating, and exercise behaviors; work time pressures; and sociodemographic characteristics by weight status (healthy weight [body mass index or BMI < 25] vs. overweight [BMI ≥ 25]) of young adults. Cross-sectional. Nine U.S. universities. Enrolled college students (N = 1252; 18-24 years; 80% white; 59% female). Survey included the Pittsburgh Sleep Quality Index (PSQI), Three-Factor Eating Questionnaire (TFEQ), Satter Eating Competence Inventory (ecSI), National Cancer Institute Fruit/Vegetable Screener, International Physical Activity Questionnaire, Work Time Pressure items, and sociodemographic characteristics. Chi-square and t-tests determined significant bivariate associations of sociodemographics, sleep behaviors, eating behaviors, physical activity behavior, and work time pressures with weight status (i.e., healthy vs. overweight/obese). Statistically significant bivariate associations with weight status were then entered into a multivariate logistic regression model that estimated associations with being overweight/obese. Sex (female), race (nonwhite), older age, higher Global PSQI score, lower ecSI total score, and higher TFEQ Emotional Eating Scale score were significantly (p < .05) associated with overweight/obesity in bivariate analyses. Multivariate logistic regression analysis showed that sex (female; odds ratio [OR] = 2.05, confidence interval [CI] = 1.54-2.74), older age (OR = 1.35, CI = 1.21-1.50), higher Global PSQI score (OR = 1.07, CI = 1.01-1.13), and lower ecSI score (OR = .96, CI = .94-.98), were significantly (p < .05) associated with overweight/obesity. Findings suggest that obesity prevention interventions for college students should include an education component to emphasize the importance of overall sleep quality and improving eating competence.
Couple Relationship Status and Patterns in Early Parenting Practices
ERIC Educational Resources Information Center
Guzzo, Karen Benjamin; Lee, Helen
2008-01-01
Using data from the Fragile Families and Child Wellbeing Study (N = 3,003), we examine the role of parental relationship status at birth on maternal adherence to current recommendations regarding breastfeeding, corporal punishment, and well-child visits. At the bivariate level, parents' union status is almost linearly related to adherence to…
A Statewide Study of Gang Membership in California Secondary Schools
ERIC Educational Resources Information Center
Estrada, Joey Nuñez, Jr.; Gilreath, Tamika D.; Astor, Ron Avi; Benbenishty, Rami
2016-01-01
To date, there is a paucity of empirical evidence that examines gang membership in schools. Using statewide data of 7th-, 9th-, and 11th-grade students from California, this study focuses on the prevalence of gang membership by county, region, ethnicity, and grade level. Bivariate and multivariate logistic regression analyses were employed with…
General Education Development (GED) Recipients' Life Course Experiences: Humanizing the Findings
ERIC Educational Resources Information Center
Hartigan, Lacey A.
2017-01-01
This study examines a range of GED recipients' life course contexts and experiences and their relationship with long-term outcomes. Using descriptive comparisons, bivariate tests, and propensity-score matched regression models to analyze data from rounds 1-15 of the National Longitudinal Survey of Youth, 1997, analyses aim to examine: (1)…
HIV Risk Behaviors among Rural Stimulant Users: Variation by Gender and Race/Ethnicity
ERIC Educational Resources Information Center
Wright, Patricia B.; Stewart, Katharine E.; Fischer, Ellen P.; Carlson, Robert G.; Falck, Russel; Wang, Jichuan; Leukefeld, Carl G.; Booth, Brenda M.
2007-01-01
We examined data from a community sample of rural stimulant users (n = 691) in three diverse states to identify gender and racial/ethnic differences in HIV risk behaviors. Bivariate and logistic regression analyses were conducted with six risk behaviors as dependent variables: injecting drugs, trading sex to obtain money or drugs, trading money or…
Ciulla, Carlo; Veljanovski, Dimitar; Rechkoska Shikoska, Ustijana; Risteski, Filip A
2015-11-01
This research presents signal-image post-processing techniques called Intensity-Curvature Measurement Approaches with application to the diagnosis of human brain tumors detected through Magnetic Resonance Imaging (MRI). Post-processing of the MRI of the human brain encompasses the following model functions: (i) bivariate cubic polynomial, (ii) bivariate cubic Lagrange polynomial, (iii) monovariate sinc, and (iv) bivariate linear. The following Intensity-Curvature Measurement Approaches were used: (i) classic-curvature, (ii) signal resilient to interpolation, (iii) intensity-curvature measure and (iv) intensity-curvature functional. The results revealed that the classic-curvature, the signal resilient to interpolation and the intensity-curvature functional are able to add additional information useful to the diagnosis carried out with MRI. The contribution to the MRI diagnosis of our study are: (i) the enhanced gray level scale of the tumor mass and the well-behaved representation of the tumor provided through the signal resilient to interpolation, and (ii) the visually perceptible third dimension perpendicular to the image plane provided through the classic-curvature and the intensity-curvature functional.
Ciulla, Carlo; Veljanovski, Dimitar; Rechkoska Shikoska, Ustijana; Risteski, Filip A.
2015-01-01
This research presents signal-image post-processing techniques called Intensity-Curvature Measurement Approaches with application to the diagnosis of human brain tumors detected through Magnetic Resonance Imaging (MRI). Post-processing of the MRI of the human brain encompasses the following model functions: (i) bivariate cubic polynomial, (ii) bivariate cubic Lagrange polynomial, (iii) monovariate sinc, and (iv) bivariate linear. The following Intensity-Curvature Measurement Approaches were used: (i) classic-curvature, (ii) signal resilient to interpolation, (iii) intensity-curvature measure and (iv) intensity-curvature functional. The results revealed that the classic-curvature, the signal resilient to interpolation and the intensity-curvature functional are able to add additional information useful to the diagnosis carried out with MRI. The contribution to the MRI diagnosis of our study are: (i) the enhanced gray level scale of the tumor mass and the well-behaved representation of the tumor provided through the signal resilient to interpolation, and (ii) the visually perceptible third dimension perpendicular to the image plane provided through the classic-curvature and the intensity-curvature functional. PMID:26644943
Negeri, Zelalem F; Shaikh, Mateen; Beyene, Joseph
2018-05-11
Diagnostic or screening tests are widely used in medical fields to classify patients according to their disease status. Several statistical models for meta-analysis of diagnostic test accuracy studies have been developed to synthesize test sensitivity and specificity of a diagnostic test of interest. Because of the correlation between test sensitivity and specificity, modeling the two measures using a bivariate model is recommended. In this paper, we extend the current standard bivariate linear mixed model (LMM) by proposing two variance-stabilizing transformations: the arcsine square root and the Freeman-Tukey double arcsine transformation. We compared the performance of the proposed methods with the standard method through simulations using several performance measures. The simulation results showed that our proposed methods performed better than the standard LMM in terms of bias, root mean square error, and coverage probability in most of the scenarios, even when data were generated assuming the standard LMM. We also illustrated the methods using two real data sets. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Morrison, Lynn A; Sievert, Lynnette L; Brown, Daniel E; Rahberg, Nichole; Reza, Angela
2010-07-01
The objective of this study was to examine the relation of menstrual attitudes to menopausal attitudes and the demographic and health characteristics associated with each. This cross-sectional study consisted of a randomly selected sample of 1,824 respondents aged 16 to 100 years in multi-ethnic Hilo, Hawai'i. Women completed questionnaires for demographic and health information, such as age, ethnicity, education, residency in Hawai'i, menopausal status, exercise, and attitudes toward menstruation and menopause. Women more often chose positive terms, such as "natural," to describe menstruation (60.8%) and menopause (59.4%). In bivariate analyses, post-menopausal women were significantly more likely to have positive menstrual and menopausal attitudes than pre-menopausal women. Factor analyses were used to cluster attitudes followed by linear regression to identify demographic characteristics associated with factor scores. Asian-American ethnicity, higher education, reporting more exercise, and growing up outside of Hawai'i were associated with positive menstrual attitudes. Higher education, older age, post-menopausal status, growing up outside of Hawai'i and having hot flashes were associated with positive menopausal attitudes. Bivariate correlation analyses suggested significant associations between factor scores for menstrual and menopausal attitudes. Both negative and positive menstrual attitudes were positively correlated with the anticipation of menopause, although negative attitudes toward menstruation were negatively correlated with menopause as a positive, natural life event. Demographic variables, specifically education and where one grows up, influenced women's attitudes toward menstruation and menopause and should be considered for inclusion in subsequent multi-ethnic studies. Further research is also warranted in assessing the relationship between menstrual and menopausal attitudes.
Nelson, Karin; Cunningham, William; Andersen, Ron; Harrison, Gail; Gelberg, Lillian
2001-01-01
OBJECTIVES Preliminary studies have shown that among adults with diabetes, food insufficiency has adverse health consequences, including hypoglycemic episodes and increased need for health care services. The purpose of this study was to determine the prevalence of food insufficiency and to describe the association of food insufficiency with health status and health care utilization in a national sample of adults with diabetes. METHODS We analyzed data from adults with diabetes (n = 1,503) interviewed in the Third National Health and Nutrition Examination Survey. Bivariate and multivariate analyses were used to examine the relationship of food insufficiency to self-reported health status and health care utilization. RESULTS Six percent of adults with diabetes reported food insufficiency, representing more than 568,600 persons nationally (95% confidence interval, 368,400 to 768,800). Food insufficiency was more common among those with incomes below the federal poverty level (17% vs 4%, P≤.001). Adults with diabetes who were food insufficient were more likely to report fair or poor health status than those who were not (63% vs 43%; odds ratio, 2.2; P =.05). In a multivariate analysis, fair or poor health status was independently associated with poverty, nonwhite race, low educational achievement, and number of chronic diseases, but not with food insufficiency. Diabetic adults who were food insufficient reported more physician encounters, either in clinic or by phone, than those who were food secure (12 vs 7, P <.05). In a multivariate linear regression, food insufficiency remained independently associated with increased physician utilization among adults with diabetes. There was no association between food insufficiency and hospitalization in bivariate analysis. CONCLUSIONS Food insufficiency is relatively common among low-income adults with diabetes and was associated with higher physician utilization. PMID:11422638
Gender Differences in Compensation, Job Satisfaction and Other Practice Patterns in Urology.
Spencer, E Sophie; Deal, Allison M; Pruthi, Nicholas R; Gonzalez, Chris M; Kirby, E Will; Langston, Joshua; McKenna, Patrick H; McKibben, Maxim J; Nielsen, Matthew E; Raynor, Mathew C; Wallen, Eric M; Woods, Michael E; Pruthi, Raj S; Smith, Angela B
2016-02-01
The proportion of women in urology has increased from less than 0.5% in 1981 to 10% today. Furthermore, 33% of students matching in urology are now female. In this analysis we characterize the female workforce in urology compared to that of men with regard to income, workload and job satisfaction. We collaborated with the American Urological Association to survey its domestic membership of practicing urologists regarding socioeconomic, workforce and quality of life issues. A total of 6,511 survey invitations were sent via e-mail. The survey consisted of 26 questions and took approximately 13 minutes to complete. Linear regression models were used to evaluate bivariable and multivariable associations with job satisfaction and compensation. A total of 848 responses (660 or 90% male, 73 or 10% female) were collected for a total response rate of 13%. On bivariable analysis female urologists were younger (p <0.0001), more likely to be fellowship trained (p=0.002), worked in academics (p=0.008), were less likely to be self-employed and worked fewer hours (p=0.03) compared to male urologists. On multivariable analysis female gender was a significant predictor of lower compensation (p=0.001) when controlling for work hours, call frequency, age, practice setting and type, fellowship training and advance practice provider employment. Adjusted salaries among female urologists were $76,321 less than those of men. Gender was not a predictor of job satisfaction. Female urologists are significantly less compensated compared to male urologists after adjusting for several factors likely contributing to compensation. There is no difference in job satisfaction between male and female urologists. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.
Determinants of job satisfaction for novice nurse managers employed in hospitals.
Djukic, Maja; Jun, Jin; Kovner, Christine; Brewer, Carol; Fletcher, Jason
Numbering close to 300,000 nurse managers represent the largest segment of the health care management workforce. Their effectiveness is, in part, influenced by their job satisfaction. We examined factors associated with job satisfaction of novice frontline nurse managers. We used a cross-sectional, correlational survey design. The sample consisted of responders to the fifth wave of a multiyear study of new nurses in 2013 (N = 1,392; response rate of 69%) who reported working as managers (n = 209). The parent study sample consisted of registered nurses who were licensed for the first time by exam 6-18 months prior in 1 of 51 selected metropolitan statistical areas and 9 rural areas across 34 U.S. states and the District of Columbia. We examined bivariate correlations between job satisfaction and 31 personal and structural variables. All variables significantly related to job satisfaction in bivariate analysis were included in a multivariate linear regression model. In addition, we tested the interaction effects of procedural justice and negative affectivity, autonomy, and organizational constraints on job satisfaction. The Cronbach's alphas for all multi-item scales ranged from .74 to .96. In the multivariate analysis, negative affectivity (β = -.169; p = .006) and procedural justice (β = .210; p = .016) were significantly correlated with job satisfaction. The combination of predictors in the model accounted for half of the variability in job satisfaction ratings (R = .51, adjusted R = .47; p <. 001). Health care executives who want to cultivate an effective novice frontline nurse manager workforce can best ensure their satisfaction by creating an organization with strong procedural justice. This could be achieved by involving managers in decision-making processes and ensuring transparency about how decisions that affect nursing are made.
Iikura, Motoyasu; Yi, Siyan; Ichimura, Yasunori; Hori, Ai; Izumi, Shinyu; Sugiyama, Haruhito; Kudo, Koichiro; Mizoue, Tetsuya; Kobayashi, Nobuyuki
2013-01-01
Background The avoidance of inhaled allergens or tobacco smoke has been known to have favorable effects on asthma control. However, it remains unclear whether other lifestyle-related factors are also related to asthma control. Therefore, a comprehensive study to examine the associations between various lifestyle factors and asthma control was conducted in Japanese asthmatic patients. Methods The study subjects included 437 stable asthmatic patients recruited from our outpatient clinic over a one-year period. A written, informed consent was obtained from each participant. Asthma control was assessed using the asthma control test (ACT), and a structured questionnaire was administered to obtain information regarding lifestyle factors, including tobacco smoking, alcohol drinking, physical exercise, and diet. Both bivariate and multivariate analyses were conducted. Results The proportions of total control (ACT = 25), well controlled (ACT = 20-24), and poorly controlled (ACT < 20) were 27.5%, 48.1%, and 24.5%, respectively. The proportions of patients in the asthma treatment steps as measured by Global Initiative for Asthma 2007 in step 1, step 2, step 3, step 4, and step 5 were 5.5%, 17.4%, 7.6%, 60.2%, and 9.4%, respectively. Body mass index, direct tobacco smoking status and alcohol drinking were not associated with asthma control. On the other hand, younger age (< 65 years old), passive smoking, periodical exercise (> 3 metabolic equivalents-h/week), and raw vegetable intake (> 5 units/week) were significantly associated with good asthma control by bivariate analysis. Younger age, periodical exercise, and raw vegetable intake were significantly associated with good asthma control by multiple linear regression analysis. Conclusions Periodical exercise and raw vegetable intake are associated with good asthma control in Japanese patients. PMID:23874577
Iikura, Motoyasu; Yi, Siyan; Ichimura, Yasunori; Hori, Ai; Izumi, Shinyu; Sugiyama, Haruhito; Kudo, Koichiro; Mizoue, Tetsuya; Kobayashi, Nobuyuki
2013-01-01
The avoidance of inhaled allergens or tobacco smoke has been known to have favorable effects on asthma control. However, it remains unclear whether other lifestyle-related factors are also related to asthma control. Therefore, a comprehensive study to examine the associations between various lifestyle factors and asthma control was conducted in Japanese asthmatic patients. The study subjects included 437 stable asthmatic patients recruited from our outpatient clinic over a one-year period. A written, informed consent was obtained from each participant. Asthma control was assessed using the asthma control test (ACT), and a structured questionnaire was administered to obtain information regarding lifestyle factors, including tobacco smoking, alcohol drinking, physical exercise, and diet. Both bivariate and multivariate analyses were conducted. The proportions of total control (ACT = 25), well controlled (ACT = 20-24), and poorly controlled (ACT < 20) were 27.5%, 48.1%, and 24.5%, respectively. The proportions of patients in the asthma treatment steps as measured by Global Initiative for Asthma 2007 in step 1, step 2, step 3, step 4, and step 5 were 5.5%, 17.4%, 7.6%, 60.2%, and 9.4%, respectively. Body mass index, direct tobacco smoking status and alcohol drinking were not associated with asthma control. On the other hand, younger age (< 65 years old), passive smoking, periodical exercise (> 3 metabolic equivalents-h/week), and raw vegetable intake (> 5 units/week) were significantly associated with good asthma control by bivariate analysis. Younger age, periodical exercise, and raw vegetable intake were significantly associated with good asthma control by multiple linear regression analysis. Periodical exercise and raw vegetable intake are associated with good asthma control in Japanese patients.
Sievert, Lynnette L.; Brown, Daniel E.; Rahberg, Nichole; Reza, Angela
2010-01-01
The objective of this study was to examine the relation of menstrual attitudes to menopausal attitudes and the demographic and health characteristics associated with each. This cross-sectional study consisted of a randomly selected sample of 1824 respondents aged 16 to 100 years in multi-ethnic Hilo, Hawai`i. Women completed questionnaires for demographic and health information, such as age, ethnicity, education, residency in Hawai`i, menopausal status, exercise, and attitudes toward menstruation and menopause. Women more often chose positive terms, such as “natural,” to describe menstruation (60.8%) and menopause (59.4%). In bivariate analyses, post-menopausal women were significantly more likely to have positive menstrual and menopausal attitudes than pre-menopausal women. Factor analyses were used to cluster attitudes followed by linear regression to identify demographic characteristics associated with factor scores. Asian-American ethnicity, higher education, reporting more exercise, and growing up outside of Hawai`i were associated with positive menstrual attitudes. Higher education, older age, post-menopausal status, growing up outside of Hawai`i and having hot flashes were associated with positive menopausal attitudes. Bivariate correlation analyses suggested significant associations between factor scores for menstrual and menopausal attitudes. Both negative and positive menstrual attitudes were positively correlated with the anticipation of menopause, although negative attitudes toward menstruation were negatively correlated with menopause as a positive, natural life event. Demographic variables, specifically education and where one grows up, influenced women’s attitudes toward menstruation and menopause and should be considered for inclusion in subsequent multi-ethnic studies. Further research is also warranted in assessing the relationship between menstrual and menopausal attitudes. PMID:20853216
Bittencourt, Natalia F N; Ocarino, Juliana M; Mendonça, Luciana D M; Hewett, Timothy E; Fonseca, Sergio T
2012-12-01
Cross-sectional. To investigate predictors of increased frontal plane knee projection angle (FPKPA) in athletes. The underlying mechanisms that lead to increased FPKPA are likely multifactorial and depend on how the musculoskeletal system adapts to the possible interactions between its distal and proximal segments. Bivariate and linear analyses traditionally employed to analyze the occurrence of increased FPKPA are not sufficiently robust to capture complex relationships among predictors. The investigation of nonlinear interactions among biomechanical factors is necessary to further our understanding of the interdependence of lower-limb segments and resultant dynamic knee alignment. The FPKPA was assessed in 101 athletes during a single-leg squat and in 72 athletes at the moment of landing from a jump. The investigated predictors were sex, hip abductor isometric torque, passive range of motion (ROM) of hip internal rotation (IR), and shank-forefoot alignment. Classification and regression trees were used to investigate nonlinear interactions among predictors and their influence on the occurrence of increased FPKPA. During single-leg squatting, the occurrence of high FPKPA was predicted by the interaction between hip abductor isometric torque and passive hip IR ROM. At the moment of landing, the shank-forefoot alignment, abductor isometric torque, and passive hip IR ROM were predictors of high FPKPA. In addition, the classification and regression trees established cutoff points that could be used in clinical practice to identify athletes who are at potential risk for excessive FPKPA. The models captured nonlinear interactions between hip abductor isometric torque, passive hip IR ROM, and shank-forefoot alignment.
Sandborgh, Maria; Johansson, Ann-Christin; Söderlund, Anne
2016-01-01
In the fear-avoidance (FA) model social cognitive constructs could add to explaining the disabling process in whiplash associated disorder (WAD). The aim was to exemplify the possible input from Social Cognitive Theory on the FA model. Specifically the role of functional self-efficacy and perceived responses from a spouse/intimate partner was studied. A cross-sectional and correlational design was used. Data from 64 patients with acute WAD were used. Measures were pain intensity measured with a numerical rating scale, the Pain Disability Index, support, punishing responses, solicitous responses, and distracting responses subscales from the Multidimensional Pain Inventory, the Catastrophizing subscale from the Coping Strategies Questionnaire, the Tampa Scale of Kinesiophobia, and the Self-Efficacy Scale. Bivariate correlational, simple linear regression, and multiple regression analyses were used. In the statistical prediction models high pain intensity indicated high punishing responses, which indicated high catastrophizing. High catastrophizing indicated high fear of movement, which indicated low self-efficacy. Low self-efficacy indicated high disability, which indicated high pain intensity. All independent variables together explained 66.4% of the variance in pain disability, p < 0.001. Results suggest a possible link between one aspect of the social environment, perceived punishing responses from a spouse/intimate partner, pain intensity, and catastrophizing. Further, results support a mediating role of self-efficacy between fear of movement and disability in WAD.
Multivariate methods for indoor PM10 and PM2.5 modelling in naturally ventilated schools buildings
NASA Astrophysics Data System (ADS)
Elbayoumi, Maher; Ramli, Nor Azam; Md Yusof, Noor Faizah Fitri; Yahaya, Ahmad Shukri Bin; Al Madhoun, Wesam; Ul-Saufie, Ahmed Zia
2014-09-01
In this study the concentrations of PM10, PM2.5, CO and CO2 concentrations and meteorological variables (wind speed, air temperature, and relative humidity) were employed to predict the annual and seasonal indoor concentration of PM10 and PM2.5 using multivariate statistical methods. The data have been collected in twelve naturally ventilated schools in Gaza Strip (Palestine) from October 2011 to May 2012 (academic year). The bivariate correlation analysis showed that the indoor PM10 and PM2.5 were highly positive correlated with outdoor concentration of PM10 and PM2.5. Further, Multiple linear regression (MLR) was used for modelling and R2 values for indoor PM10 were determined as 0.62 and 0.84 for PM10 and PM2.5 respectively. The Performance indicators of MLR models indicated that the prediction for PM10 and PM2.5 annual models were better than seasonal models. In order to reduce the number of input variables, principal component analysis (PCA) and principal component regression (PCR) were applied by using annual data. The predicted R2 were 0.40 and 0.73 for PM10 and PM2.5, respectively. PM10 models (MLR and PCR) show the tendency to underestimate indoor PM10 concentrations as it does not take into account the occupant's activities which highly affect the indoor concentrations during the class hours.
Denkinger, Michael D; Igl, Wilmar; Lukas, Albert; Bader, Anne; Bailer, Stefanie; Franke, Sebastian; Denkinger, Claudia M; Nikolaus, Thorsten; Jamour, Michael
2010-04-01
To examine the effects of various risk factors on three functional outcomes during rehabilitation. Geriatric inpatient rehabilitation unit. Observational longitudinal study. One hundred sixty-one geriatric rehabilitation inpatients (men, women), mean age 82, who were capable of walking at baseline. Functional status was assessed weekly between admission and discharge and at a follow-up 4 months later at home using the function component of the Short Form-Late Life Function and Disability Instrument, the Barthel Index, and Habitual Gait Speed. Various risk factors, such as falls-related self-efficacy (Falls Efficacy Scale-International), were measured. Associations between predictors and functional status at discharge and follow-up were analyzed using linear regression models and bivariate plots. Fear of falling predicted functioning across all outcomes except for habitual gait speed at discharge and follow-up. Visual comparison of functional trajectories between subgroups confirmed these findings, with different levels of fear of falling across time in linear plots. Thus, superior ability of this measure to discriminate between functional status at baseline across all outcomes and to discriminate between functional change especially with regard to the performance-based outcome was demonstrated. Falls-related self-efficacy is the only parameter that significantly predicts rehabilitation outcome at discharge and follow-up across all outcomes. Therefore, it should be routinely assessed in future studies in (geriatric) rehabilitation and considered to be an important treatment goal.
Correlates of resilience in the face of adversity for Korean women immigrating to the US.
Lee, Hei-Sung; Brown, Stephen L; Mitchell, Mary M; Schiraldi, Glenn R
2008-10-01
To explore the association between resilience and psychosocial variables of theoretical relevance such as self-esteem, optimism, religiousness, cultural interdependency, and belief in higher education in a population of elderly Korean women and their daughters who experienced great adversity. Surveys were conducted with 200 elderly Korean women and 170 of their daughters in several community locations. Both mothers and daughters experienced great adversities in their lives such as psychological and physical losses from war as well as current and past difficulties with relocation. The mothers' bivariate correlations indicate that self-esteem, optimism, religiousness, and cultural interdependency were significantly correlated with resilience. Length of time in the US, age entering the US, physical and psychological war-related adversities, current relocation difficulties, self-esteem, optimism, cultural interdependency, and belief in education were all significantly associated with daughters' resilience. In linear regression, self-esteem and optimism were significant predictors of resilience in both mothers and daughters. Self-esteem and optimism deserve further attention as psychological factors that may increase the likelihood of developing resilience. Implications of these findings for health professionals are discussed.
Kaewboonchoo, Orawan; Isahak, Marzuki; Susilowati, Indri; Phuong, Toai Nguyen; Morioka, Ikuharu; Harncharoen, Kitiphong; Low, Wah Yun; Ratanasiripong, Paul
2016-07-01
Work ability is related to many factors that might influence one's capacity to work. This study aimed to examine the work ability and its related factors among small and medium enterprises (SME) workers in 4 Association of Southeast Asian Nations (ASEAN) countries. The participants in this study included 2098 workers from food and textile industries in Indonesia, Malaysia, Thailand, and Vietnam. A cross-sectional survey of anonymous self-administrated questionnaire was designed to collect information on sociodemographic factors, work environment and ergonomic condition, musculoskeletal disorders, and work ability. Bivariate correlation coefficient and multiple linear regression analyses were used to predict the work ability. Results of this study confirm that work ability in 4 ASEAN countries was similar to that in European countries, and that the sociodemographic factors, work environment and ergonomic condition, and musculoskeletal disorder (MSD) were associated with work ability. These factors are important for considering occupational health and safety policy to promote work ability in food, textile, and other SME workers. © 2016 APJPH.
Statistical analysis of the calibration procedure for personnel radiation measurement instruments
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bush, W.J.; Bengston, S.J.; Kalbeitzer, F.L.
1980-11-01
Thermoluminescent analyzer (TLA) calibration procedures were used to estimate personnel radiation exposure levels at the Idaho National Engineering Laboratory (INEL). A statistical analysis is presented herein based on data collected over a six month period in 1979 on four TLA's located in the Department of Energy (DOE) Radiological and Environmental Sciences Laboratory at the INEL. The data were collected according to the day-to-day procedure in effect at that time. Both gamma and beta radiation models are developed. Observed TLA readings of thermoluminescent dosimeters are correlated with known radiation levels. This correlation is then used to predict unknown radiation doses frommore » future analyzer readings of personnel thermoluminescent dosimeters. The statistical techniques applied in this analysis include weighted linear regression, estimation of systematic and random error variances, prediction interval estimation using Scheffe's theory of calibration, the estimation of the ratio of the means of two normal bivariate distributed random variables and their corresponding confidence limits according to Kendall and Stuart, tests of normality, experimental design, a comparison between instruments, and quality control.« less
Social support network, mental health and quality of life: a cross-sectional study in primary care.
Portugal, Flávia Batista; Campos, Mônica Rodrigues; Correia, Celina Ragoni; Gonçalves, Daniel Almeida; Ballester, Dinarte; Tófoli, Luis Fernando; Mari, Jair de Jesus; Gask, Linda; Dowrick, Christopher; Bower, Peter; Fortes, Sandra
2016-12-22
The objective of this study was to identify the association between emotional distress and social support networks with quality of life in primary care patients. This was a cross-sectional study involving 1,466 patients in the cities of São Paulo and Rio de Janeiro, Brazil, in 2009/2010. The General Health Questionnaire, the Hospital Anxiety and Depression Scale and the brief version of the World Health Organization Quality of Life Instrument were used. The Social Support Network Index classified patients with the highest and lowest index as socially integrated or isolated. A bivariate analysis and four multiple linear regressions were conducted for each quality of life outcome. The means scores for the physical, psychological, social relations, and environment domains were, respectively, 64.7; 64.2; 68.5 and 49.1. In the multivariate analysis, the psychological domain was negatively associated with isolation, whereas the social relations and environment domains were positively associated with integration. Integration and isolation proved to be important factors for those in emotional distress as they minimize or maximize negative effects on quality of life.
Response to comments on "Productivity is a poor predictor of plant species richness"
Grace, James B.; Adler, Peter B.; Seabloom, Eric W.; Borer, Elizabeth T.; Hillebrand, Helmut; Hautier, Yann; Hector, Andy; Harpole, W. Stanley; O'Halloran, Lydia R.; Anderson, T. Michael; Bakker, Jonathan D.; Brown, Cynthia S.; Buckley, Yvonne M.; Collins, Scott L.; Cottingham, Kathryn L.; Crawley, Michael J.; Damschen, Ellen Ingman; Davies, Kendi F.; DeCrappeo, Nicole M.; Fay, Philip A.; Firn, Jennifer; Gruner, Daniel S.; Hagenah, Nicole; Jin, Virginia L.; Kirkman, Kevin P.; Knops, Johannes M.H.; La Pierre, Kimberly J.; Lambrinos, John G.; Melbourne, Brett A.; Mitchell, Charles E.; Moore, Joslin L.; Morgan, John W.; Orrock, John L.; Prover, Suzanne M.; Stevens, Carly J.; Wragg, Peter D.; Yang, Louie H.
2012-01-01
Pan et al. claim that our results actually support a strong linear positive relationship between productivity and richness, whereas Fridley et al. contend that the data support a strong humped relationship. These responses illustrate how preoccupation with bivariate patterns distracts from a deeper understanding of the multivariate mechanisms that control these important ecosystem properties.
ERIC Educational Resources Information Center
Kress, Victoria E.; Newgent, Rebecca A.; Whitlock, Janis; Mease, Laura
2015-01-01
The purpose of this study was to identify factors that may protect or insulate people from engaging in nonsuicidal self-injury (NSSI). College students (N = 14,385) from 8 universities participated in a web-based survey. Results of bivariate correlations and multiple regression revealed that spirituality/religiosity, life satisfaction, and life…
Advanced statistics: linear regression, part I: simple linear regression.
Marill, Keith A
2004-01-01
Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.
Díaz Villegas, Gregory Mishell; Runzer Colmenares, Fernando
2015-01-01
To evaluate the association between calf circumference and gait speed in elderly patients 65 years or older at Geriatric day clinic at Peruvian Centro Médico Naval. Cross-sectional, retrospective study. We assessed 139 participants, 65 years or older at Peruvian Centro Médico Naval including calf circumference, gait speed and Short Physical Performance Battery. With bivariate analyses and logistic regression model we search for association between variables. The age mean was 79.37 years old (SD: 8.71). 59.71% were male, the 30.97% had a slow walking speed and the mean calf circumference was 33.42cm (SD: 5.61). After a bivariate analysis, we found a calf circumference mean of 30.35cm (SD: 3.74) in the slow speed group and, in normal gait group, a mean of 33.51cm (SD: 3.26) with significantly differences. We used logistic regression to analyze association with slow gait speed, founding statistically significant results adjusting model by disability and age. Low calf circumference is associated with slow speed walk in population over 65 years old. Copyright © 2014. Published by Elsevier Espana.
Lead exposure and the 2010 achievement test scores of children in New York counties
2012-01-01
Background Lead is toxic to cognitive and behavioral functioning in children even at levels well below those producing physical symptoms. Continuing efforts in the U.S. since about the 1970s to reduce lead exposure in children have dramatically reduced the incidence of elevated blood lead levels (with elevated levels defined by the current U.S. Centers for Disease Control threshold of 10 μg/dl). The current study examines how much lead toxicity continues to impair the academic achievement of children of New York State, using 2010 test data. Methods This study relies on three sets of data published for the 57 New York counties outside New York City: school achievement data from the New York State Department of Education, data on incidence of elevated blood lead levels from the New York State Department of Health, and data on income from the U.S. Census Bureau. We studied third grade and eighth grade test scores in English Language Arts and mathematics. Using the county as the unit of analysis, we computed bivariate correlations and regression coefficients, with percent of children achieving at the lowest reported level as the dependent variable and the percent of preschoolers in the county with elevated blood lead levels as the independent variable. Then we repeated those analyses using partial correlations to control for possible confounding effects of family income, and using multiple regressions with income included. Results The bivariate correlations between incidence of elevated lead and number of children in the lowest achievement group ranged between 0.38 and 0.47. The partial correlations ranged from 0.29 to 0.40. The regression coefficients, both bivariate and partial (both estimating the increase in percent of children in the lowest achievement group for every percent increase in the children with elevated blood lead levels), ranged from 0.52 to 1.31. All regression coefficients, when rounded to the nearest integer, were approximately 1. Thus, when the percent of children showing elevated lead increases by one percent, the percent of children in the lowest achievement group, according to the regression equations generated, also increases by about one percent. All associations were significant at the 0.05 level. Conclusion Despite public health advances, and despite the imprecision of measures, an association between the incidence of elevated blood lead and achievement in New York counties is still apparent, not attributable to confounding by income. Efforts to reduce lead exposure should persist with vigor. PMID:22269775
Diaphragm and Lung Ultrasound to Predict Weaning Outcome: Systematic Review and Meta-Analysis.
Llamas-Álvarez, Ana M; Tenza-Lozano, Eva M; Latour-Pérez, Jaime
2017-12-01
Deciding the optimal timing for extubation in patients who are mechanically ventilated can be challenging, and traditional weaning predictor tools are not very accurate. The aim of this systematic review and meta-analysis was to assess the accuracy of lung and diaphragm ultrasound for predicting weaning outcomes in critically ill adults. MEDLINE, the Cochrane Library, Web of Science, Scopus, LILACS, Teseo, Tesis Doctorales en Red, and OpenGrey were searched, and the bibliographies of relevant studies were reviewed. Two researchers independently selected studies that met the inclusion criteria and assessed study quality in accordance with the Quality Assessment of Diagnostic Accuracy Studies-2 tool. The summary receiver-operating characteristic curve and pooled diagnostic OR (DOR) were estimated by using a bivariate random effects analysis. Sources of heterogeneity were explored by using predefined subgroup analyses and bivariate meta-regression. Nineteen studies involving 1,071 people were included in the study. For diaphragm thickening fraction, the area under the summary receiver-operating characteristic curve was 0.87, and DOR was 21 (95% CI, 11-40). Regarding diaphragmatic excursion, pooled sensitivity was 75% (95% CI, 65-85); pooled specificity, 75% (95% CI, 60-85); and DOR, 10 (95% CI, 4-24). For lung ultrasound, the area under the summary receiver-operating characteristic curve was 0.77, and DOR was 38 (95% CI, 7-198). Based on bivariate meta-regression analysis, a significantly higher specificity for diaphragm thickening fraction and higher sensitivity for diaphragmatic excursion was detected in studies with applicability concerns. Lung and diaphragm ultrasound can help predict weaning outcome, but its accuracy may vary depending on the patient subpopulation. Copyright © 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.
Garzón-Umerenkova, Angélica; de la Fuente, Jesús; Amate, Jorge; Paoloni, Paola V.; Fadda, Salvatore; Pérez, Javier Fiz
2018-01-01
This research aimed to analyze the linear bivariate correlation and structural relations between self-regulation -as a central construct-, with flow, health, procrastination and academic performance, in an academic context. A total of 363 college students took part, 101 men (27.8%) and 262 women (72.2%). Participants had an average age of 22 years and were between the first and fifth year of studies. They were from five different programs and two universities in Bogotá city (Colombia). A validated ad hoc questionnaire of physical and psychological health was applied along with a battery of tests to measure self-regulation, procrastination, and flourishing. To establish an association relationship, Pearson bivariate correlations were performed using SPSS software (v. 22.0), and structural relationship predictive analysis was performed using an SEM on AMOS software (v. 22.0). Regarding this linear association, it was established that (1) self-regulation has a significant positive association on flourishing and overall health, and a negative effect on procrastination. Regarding the structural relation, it confirmed that (2) self-regulation is a direct and positive predictor of flourishing and health; (3) self-regulation predicts procrastination directly and negatively, and academic performance indirectly and positively; and (4) age and gender have a prediction effect on the analyzed variables. Implications, limitations and future research scope are discussed. PMID:29706922
Garzón-Umerenkova, Angélica; de la Fuente, Jesús; Amate, Jorge; Paoloni, Paola V; Fadda, Salvatore; Pérez, Javier Fiz
2018-01-01
This research aimed to analyze the linear bivariate correlation and structural relations between self-regulation -as a central construct-, with flow, health, procrastination and academic performance, in an academic context. A total of 363 college students took part, 101 men (27.8%) and 262 women (72.2%). Participants had an average age of 22 years and were between the first and fifth year of studies. They were from five different programs and two universities in Bogotá city (Colombia). A validated ad hoc questionnaire of physical and psychological health was applied along with a battery of tests to measure self-regulation, procrastination, and flourishing. To establish an association relationship, Pearson bivariate correlations were performed using SPSS software (v. 22.0), and structural relationship predictive analysis was performed using an SEM on AMOS software (v. 22.0). Regarding this linear association, it was established that (1) self-regulation has a significant positive association on flourishing and overall health, and a negative effect on procrastination. Regarding the structural relation, it confirmed that (2) self-regulation is a direct and positive predictor of flourishing and health; (3) self-regulation predicts procrastination directly and negatively, and academic performance indirectly and positively; and (4) age and gender have a prediction effect on the analyzed variables. Implications, limitations and future research scope are discussed.
Chung, Moo K.; Qiu, Anqi; Seo, Seongho; Vorperian, Houri K.
2014-01-01
We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression framework as a weighted eigenfunction expansion with the heat kernel as the weights. The new kernel regression is mathematically equivalent to isotropic heat diffusion, kernel smoothing and recently popular diffusion wavelets. Unlike many previous partial differential equation based approaches involving diffusion, our approach represents the solution of diffusion analytically, reducing numerical inaccuracy and slow convergence. The numerical implementation is validated on a unit sphere using spherical harmonics. As an illustration, we have applied the method in characterizing the localized growth pattern of mandible surfaces obtained in CT images from subjects between ages 0 and 20 years by regressing the length of displacement vectors with respect to the template surface. PMID:25791435
Allen, Ryan T; Hales, Nicholas M; Baccarelli, Andrea; Jerrett, Michael; Ezzati, Majid; Dockery, Douglas W; Pope, C Arden
2016-08-12
Income, air pollution, obesity, and smoking are primary factors associated with human health and longevity in population-based studies. These four factors may have countervailing impacts on longevity. This analysis investigates longevity trade-offs between air pollution and income, and explores how relative effects of income and air pollution on human longevity are potentially influenced by accounting for smoking and obesity. County-level data from 2,996 U.S. counties were analyzed in a cross-sectional analysis to investigate relationships between longevity and the four factors of interest: air pollution (mean 1999-2008 PM2.5), median income, smoking, and obesity. Two longevity measures were used: life expectancy (LE) and an exceptional aging (EA) index. Linear regression, generalized additive regression models, and bivariate thin-plate smoothing splines were used to estimate the benefits of living in counties with higher incomes or lower PM2.5. Models were estimated with and without controls for smoking, obesity, and other factors. Models which account for smoking and obesity result in substantially smaller estimates of the effects of income and pollution on longevity. Linear regression models without these two variables estimate that a $1,000 increase in median income (1 μg/m(3) decrease in PM2.5) corresponds to a 27.39 (33.68) increase in EA and a 0.14 (0.12) increase in LE, whereas models that control for smoking and obesity estimate only a 12.32 (20.22) increase in EA and a 0.07 (0.05) increase in LE. Nonlinear models and thin-plate smoothing splines also illustrate that, at higher levels of income, the relative benefits of the income-pollution tradeoff changed-the benefit of higher incomes diminished relative to the benefit of lower air pollution exposure. Higher incomes and lower levels of air pollution both correspond with increased human longevity. Adjusting for smoking and obesity reduces estimates of the benefits of higher income and lower air pollution exposure. This adjustment also alters the tradeoff between income and pollution: increases in income become less beneficial relative to a fixed reduction in air pollution-especially at higher levels of income.
Li, Ji; Gray, B.R.; Bates, D.M.
2008-01-01
Partitioning the variance of a response by design levels is challenging for binomial and other discrete outcomes. Goldstein (2003) proposed four definitions for variance partitioning coefficients (VPC) under a two-level logistic regression model. In this study, we explicitly derived formulae for multi-level logistic regression model and subsequently studied the distributional properties of the calculated VPCs. Using simulations and a vegetation dataset, we demonstrated associations between different VPC definitions, the importance of methods for estimating VPCs (by comparing VPC obtained using Laplace and penalized quasilikehood methods), and bivariate dependence between VPCs calculated at different levels. Such an empirical study lends an immediate support to wider applications of VPC in scientific data analysis.
Chung, Moo K; Qiu, Anqi; Seo, Seongho; Vorperian, Houri K
2015-05-01
We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression framework as a weighted eigenfunction expansion with the heat kernel as the weights. The new kernel method is mathematically equivalent to isotropic heat diffusion, kernel smoothing and recently popular diffusion wavelets. The numerical implementation is validated on a unit sphere using spherical harmonics. As an illustration, the method is applied to characterize the localized growth pattern of mandible surfaces obtained in CT images between ages 0 and 20 by regressing the length of displacement vectors with respect to a surface template. Copyright © 2015 Elsevier B.V. All rights reserved.
Yang, Qichun; Zhang, Xuesong; Xu, Xingya; ...
2017-05-29
Riverine carbon cycling is an important, but insufficiently investigated component of the global carbon cycle. Analyses of environmental controls on riverine carbon cycling are critical for improved understanding of mechanisms regulating carbon processing and storage along the terrestrial-aquatic continuum. Here, we compile and analyze riverine dissolved organic carbon (DOC) concentration data from 1402 United States Geological Survey (USGS) gauge stations to examine the spatial variability and environmental controls of DOC concentrations in the United States (U.S.) surface waters. DOC concentrations exhibit high spatial variability, with an average of 6.42 ± 6.47 mg C/ L (Mean ± Standard Deviation). In general,more » high DOC concentrations occur in the Upper Mississippi River basin and the Southeastern U.S., while low concentrations are mainly distributed in the Western U.S. Single-factor analysis indicates that slope of drainage areas, wetlands, forests, percentage of first-order streams, and instream nutrients (such as nitrogen and phosphorus) pronouncedly influence DOC concentrations, but the explanatory power of each bivariate model is lower than 35%. Analyses based on the general multi-linear regression models suggest DOC concentrations are jointly impacted by multiple factors. Soil properties mainly show positive correlations with DOC concentrations; forest and shrub lands have positive correlations with DOC concentrations, but urban area and croplands demonstrate negative impacts; total instream phosphorus and dam density correlate positively with DOC concentrations. Notably, the relative importance of these environmental controls varies substantially across major U.S. water resource regions. In addition, DOC concentrations and environmental controls also show significant variability from small streams to large rivers, which may be caused by changing carbon sources and removal rates by river orders. In sum, our results reveal that general multi-linear regression analysis of twenty one terrestrial and aquatic environmental factors can partially explain (56%) the DOC concentration variation. In conclusion, this study highlights the complexity of the interactions among these environmental factors in determining DOC concentrations, thus calls for processes-based, non-linear methodologies to constrain uncertainties in riverine DOC cycling.« less
The genetic and economic effect of preliminary culling in the seedling orchard
Don E. Riemenschneider
1977-01-01
The genetic and economic effects of two stages of truncation selection in a white spruce seedling orchard were investigated by computer simulation. Genetic effects were computed by assuming a bivariate distribution of juvenile and mature traits and volume was used as the selection criterion. Seed production was assumed to rise in a linear fashion to maturity and then...
Chung, Paul J; Travis, Raphael; Kilpatrick, Shelley D; Elliott, Marc N; Lui, Camillia; Khandwala, Shefali B; Dancel, Theresa M; Vollandt, Lori; Schuster, Mark A
2007-06-01
To examine whether acculturation is associated with parent-adolescent communication about sex in Filipino-American families. Filipino-Americans, the United States' second-largest Asian and Pacific Islander (API) group, have more adolescent pregnancy and HIV infection than other APIs. High-quality parent-adolescent communication about sex has been associated with healthy sexual development, and acculturation has been associated with various increased health risks. Whether acculturation affects parent-adolescent communication is unknown. We surveyed 120 pairs of Filipino-American parents and adolescents at a single large high school. We asked adolescents about their frequency of parent-adolescent communication about sex and measured adolescent acculturation in two ways: disagreement with traditional Asian values and preferential use of English. In bivariate and multivariate regressions, we examined whether adolescent acculturation was associated with adolescent reports of parent-adolescent communication. Few adolescents (22%) reported regularly discussing sex with parents. Although most adolescents (72%) agreed with traditional Asian values, most (63%) preferred using English. In bivariate regressions, less parent-adolescent communication about sex was associated with less adolescent agreement with traditional Asian values (p = .002) and more adolescent English use (p = .009). In multivariate regressions, these associations were largely explained by adolescent perceptions of parent knowledge about their whereabouts and activities. Acculturation may influence Filipino-American parent-adolescent communication about sex and, consequently, Filipino-American adolescent sexual health. Health care and public health providers may need to tailor adolescent sexual health programs based on acculturation or other immigration-related factors.
NASA Astrophysics Data System (ADS)
Marques, R.; Amaral, P.; Zêzere, J. L.; Queiroz, G.; Goulart, C.
2009-04-01
Slope instability research and susceptibility mapping is a fundamental component of hazard assessment and is of extreme importance for risk mitigation, land-use management and emergency planning. Landslide susceptibility zonation has been actively pursued during the last two decades and several methodologies are still being improved. Among all the methods presented in the literature, indirect quantitative probabilistic methods have been extensively used. In this work different linear probabilistic methods, both bi-variate and multi-variate (Informative Value, Fuzzy Logic, Weights of Evidence and Logistic Regression), were used for the computation of the spatial probability of landslide occurrence, using the pixel as mapping unit. The methods used are based on linear relationships between landslides and 9 considered conditioning factors (altimetry, slope angle, exposition, curvature, distance to streams, wetness index, contribution area, lithology and land-use). It was assumed that future landslides will be conditioned by the same factors as past landslides in the study area. The presented work was developed for Ribeira Quente Valley (S. Miguel Island, Azores), a study area of 9,5 km2, mainly composed of volcanic deposits (ash and pumice lapilli) produced by explosive eruptions in Furnas Volcano. This materials associated to the steepness of the slopes (38,9% of the area has slope angles higher than 35°, reaching a maximum of 87,5°), make the area very prone to landslide activity. A total of 1.495 shallow landslides were mapped (at 1:5.000 scale) and included in a GIS database. The total affected area is 401.744 m2 (4,5% of the study area). Most slope movements are translational slides frequently evolving into debris-flows. The landslides are elongated, with maximum length generally equivalent to the slope extent, and their width normally does not exceed 25 m. The failure depth rarely exceeds 1,5 m and the volume is usually smaller than 700 m3. For modelling purposes, the landslides were randomly divided in two sub-datasets: a modelling dataset with 748 events (2,2% of the study area) and a validation dataset with 747 events (2,3% of the study area). The susceptibility algorithms achieved with the different probabilistic techniques, were rated individually using success rate and prediction rate curves. The best model performance was obtained with the logistic regression, although the results from the different methods do not show significant differences neither in success nor in prediction rate curves. These evidences revealed that: (1) the modelling landslide dataset is representative of the entire landslide population characteristics; and (2) the increase of complexity and robustness in the probabilistic methodology did not produce a significant increase in success or prediction rates. Therefore, it was concluded that the resolution and quality of the input variables are much more important than the probabilistic model chosen to assess landslide susceptibility. This work was developed on the behalf of VOLCSOILRISK project (Volcanic Soils Geotechnical Characterization for Landslide Risk Mitigation), supported by Direcção Regional da Ciência e Tecnologia - Governo Regional dos Açores.
Correlation and simple linear regression.
Eberly, Lynn E
2007-01-01
This chapter highlights important steps in using correlation and simple linear regression to address scientific questions about the association of two continuous variables with each other. These steps include estimation and inference, assessing model fit, the connection between regression and ANOVA, and study design. Examples in microbiology are used throughout. This chapter provides a framework that is helpful in understanding more complex statistical techniques, such as multiple linear regression, linear mixed effects models, logistic regression, and proportional hazards regression.
Xie, Weixing; Jin, Daxiang; Ma, Hui; Ding, Jinyong; Xu, Jixi; Zhang, Shuncong; Liang, De
2016-05-01
The risk factors for cement leakage were retrospectively reviewed in 192 patients who underwent percutaneous vertebral augmentation (PVA). To discuss the factors related to the cement leakage in PVA procedure for the treatment of osteoporotic vertebral compression fractures. PVA is widely applied for the treatment of osteoporotic vertebral fractures. Cement leakage is a major complication of this procedure. The risk factors for cement leakage were controversial. A retrospective review of 192 patients who underwent PVA was conducted. The following data were recorded: age, sex, bone density, number of fractured vertebrae before surgery, number of treated vertebrae, severity of the treated vertebrae, operative approach, volume of injected bone cement, preoperative vertebral compression ratio, preoperative local kyphosis angle, intraosseous clefts, preoperative vertebral cortical bone defect, and ratio and type of cement leakage. To study the correlation between each factor and cement leakage ratio, bivariate regression analysis was employed to perform univariate analysis, whereas multivariate linear regression analysis was employed to perform multivariate analysis. The study included 192 patients (282 treated vertebrae), and cement leakage occurred in 100 vertebrae (35.46%). The vertebrae with preoperative cortical bone defects generally exhibited higher cement leakage ratio, and the leakage is typically type C. Vertebrae with intact cortical bones before the procedure tend to experience type S leakage. Univariate analysis showed that patient age, bone density, number of fractured vertebrae before surgery, and vertebral cortical bone were associated with cement leakage ratio (P<0.05). Multivariate analysis showed that the main factors influencing bone cement leakage are bone density and vertebral cortical bone defect, with standardized partial regression coefficients of -0.085 and 0.144, respectively. High bone density and vertebral cortical bone defect are independent risk factors associated with bone cement leakage.
Demographic, socio-economic, and cultural factors affecting fertility differentials in Nepal.
Adhikari, Ramesh
2010-04-28
Traditionally Nepalese society favors high fertility. Children are a symbol of well-being both socially and economically. Although fertility has been decreasing in Nepal since 1981, it is still high compared to many other developing countries. This paper is an attempt to examine the demographic, socio-economic, and cultural factors for fertility differentials in Nepal. This paper has used data from the Nepal Demographic and Health Survey (NDHS 2006). The analysis is confined to ever married women of reproductive age (8,644). Both bivariate and multivariate analyses have been performed to describe the fertility differentials. The bivariate analysis (one-way ANOVA) was applied to examine the association between children ever born and women's demographic, socio-economic, and cultural characteristics. Besides bivariate analysis, the net effect of each independent variable on the dependent variable after controlling for the effect of other predictors has also been measured through multivariate analysis (multiple linear regressions). The mean numbers of children ever born (CEB) among married Nepali women of reproductive age and among women aged 40-49 were three and five children, respectively. There are considerable differentials in the average number of children ever born according to women's demographic, socio-economic, and cultural settings. Regression analysis revealed that age at first marriage, perceived ideal number of children, place of residence, literacy status, religion, mass media exposure, use of family planning methods, household headship, and experience of child death were the most important variables that explained the variance in fertility. Women who considered a higher number of children as ideal (beta = 0.03; p < 0.001), those who resided in rural areas (beta = 0.02; p < 0.05), Muslim women (beta = 0.07; p < 0.001), those who had ever used family planning methods (beta = 0.08; p < 0.001), and those who had a child-death experience (beta = 0.31; p < 0.001) were more likely to have a higher number of CEB compared to their counterparts. On the other hand, those who married at a later age (beta = -0.15; p < 0.001), were literate (beta = -0.05; p < 0.001), were exposed to both (radio/TV) mass media (beta = -0.05; p < 0.001), were richest (beta = -0.12; p < 0.001), and were from female-headed households (beta = -0.02; p < 0.05) had a lower number of children ever born than their counterparts. The average number of children ever born is high among women in Nepal. There are many contributing factors for the high fertility, among which are age at first marriage, perceived ideal number of children, literacy status, mass media exposure, wealth status, and child-death experience by mothers. All of these were strong predictors for CEB. It can be concluded that programs should aim to reduce fertility rates by focusing on these identified factors so that fertility as well as infant and maternal mortality and morbidity will be decreased and the overall well-being of the family maintained and enhanced.
NASA Astrophysics Data System (ADS)
Whitmyer, Charnita P.
This dissertation uses Bolman and Deal's Four Framework approach to reframing an organization to examine science teachers' beliefs on teacher preparation and reform practices for diverse learners. Despite the national emphasis on "science for all students" in the National Science Education Standards (NRC, 2011), some traditionally underserved groups tend to underperform on standardized measures of science learning (Kober, 2001; Darling-Hammond, 2010; Bracey, 2009; Kozol, 2009, 2007; PCAST, 2012); and teachers struggle to meet the needs of these students (Hira, 2010). The literature is replete with calls for a better understanding of teacher quality as an entry point into increased student achievement in science. In the current study, the 2012 National Survey of Science and Mathematics Education (NSSME) was used to gain an understanding of science teacher quality in the United States, and SPSS 22.0 software was used to evaluate descriptive and inferential statistics, including bivariate correlation analysis, simple linear regression, and a multiple regression of the survey responses. The findings indicated that professional development was the most salient predictor of teachers' preparedness to teach diverse learners. Findings further showed that teachers who held favorable perceptions of preparedness to teach diverse learners were more likely to use reform-oriented practices. This study contributes to an emerging area of research on science teacher quality and its influence on instructional reform for diverse learners. The study concludes with a discussion of supports and obstacles that may enable or inhibit the development of these relationships.
Resilience and risk for alcohol use disorders: A Swedish twin study
Long, E.C.; Lönn, S.L.; Ji, J.; Lichtenstein, P.; Sundquist, J.; Sundquist, K.; Kendler, K.S.
2016-01-01
Background Resilience has been shown to be protective against alcohol use disorders (AUD), but the magnitude and nature of the relationship between these two phenotypes is not clear. The aim of this study is to examine the strength of this relationship and the degree to which it results from common genetic or common environmental influences. Methods Resilience was assessed on a nine-point scale during a personal interview in 1,653,721 Swedish men aged 17–25 years. AUD was identified based on Swedish medical, legal, and pharmacy registries. The magnitude of the relationship between resilience and AUD was examined using logistic regression. The extent to which the relationship arises from common genetic or common environmental factors was examined using a bivariate Cholesky decomposition model. Results The five single items that comprised the resilience assessment (social maturity, interest, psychological energy, home environment, and emotional control) all reduced risk for subsequent AUD, with social maturity showing the strongest effect. The linear effect by logistic regression showed that a one-point increase on the resilience scale was associated with a 29% decrease in odds of AUD. The Cholesky decomposition model demonstrated that the resilience-AUD relationship was largely attributable to overlapping genetic and shared environmental factors (57% and 36%, respectively). Conclusion Resilience is strongly associated with a reduction in risk for AUD. This relationship appears to be the result of overlapping genetic and shared environmental influences that impact resilience and risk of AUD, rather than a directly causal relationship. PMID:27918840
Factors associated with intern fatigue.
Friesen, Lindsay D; Vidyarthi, Arpana R; Baron, Robert B; Katz, Patricia P
2008-12-01
Prior data suggest that fatigue adversely affects patient safety and resident well-being. ACGME duty hour limitations were intended, in part, to reduce resident fatigue, but the factors that affect intern fatigue are unknown. To identify factors associated with intern fatigue following implementation of duty hour limitations. Cross-sectional confidential survey of validated questions related to fatigue, sleep, and stress, as well as author-developed teamwork questions. Interns in cognitive specialties at the University of California, San Francisco. Univariate statistics characterized the distribution of responses. Pearson correlations elucidated bivariate relationships between fatigue and other variables. Multivariate linear regression models identified factors independently associated with fatigue, sleep, and stress. Of 111 eligible interns, 66 responded (59%). In a regression analysis including gender, hours worked in the previous week, sleep quality, perceived stress, and teamwork, only poorer quality of sleep and greater perceived stress were significantly associated with fatigue (p < 0.001 and p = 0.02, respectively). To identify factors that may affect sleep, specifically duty hours and stress, a secondary model was constructed. Only greater perceived stress was significantly associated with diminished sleep quality (p = 0.04), and only poorer teamwork was significantly associated with perceived stress (p < 0.001). Working >80 h was not significantly associated with perceived stress, quality of sleep, or fatigue. Simply decreasing the number of duty hours may be insufficient to reduce intern fatigue. Residency programs may need to incorporate programmatic changes to reduce stress, improve sleep quality, and foster teamwork in order to decrease intern fatigue and its deleterious consequences.
Cox, Joanne E; Buman, Matthew; Valenzuela, Jennifer; Joseph, Natalie Pierre; Mitchell, Anna; Woods, Elizabeth R
2008-10-01
To investigate the associations between depressive symptoms in adolescent mothers and their perceived maternal caretaking ability and social support. Subjects were participants enrolled in a parenting program that provided comprehensive multidisciplinary medical care to teen mothers and their children. Baseline data of a prospective cohort study were collected by interview at 2 weeks postpartum and follow-up, and standardized measures on entry into postnatal parenting groups. Demographic data included education, social supports, psychological history, family history and adverse life events. Depressive symptoms were measured with the Center for Epidemiological Studies Depression Scale for Children short version (CES-DC). The Maternal Self-report Inventory (MSRI) measured perceived maternal self-esteem, and Duke-UNC Functional Social Support Questionnaire measured social support. Data were analyzed with bivariate analyses and linear regression modeling focusing on depressive symptoms as the outcome variable. In the 168 teen mothers, mean age 17.6 +/- 1.2 years, African American (50%), Latina (31%) or Biracial (13%), the prevalence of depressive symptoms was 53.6%. In the linear model, controlling for baby's age, teen's age, ethnicity, Temporary Aid for Families with Dependent Children (TAFDC), and previous suicidal gesture, increased depressive symptoms were associated with decreased perceived maternal caretaking ability (P = 0.003) and lower social support (P < 0.001). In a linear model controlling for the same variables, MSRI total score (P = 0.001) and social support (P < 0.001) contributed significantly to the model as did the interaction term (MSRI x Social Support, P = 0.044). Depression is associated with decreased maternal confidence in their ability to parent and decreased perceived maternal social support, with a possible moderating effect of social support on the relationship of maternal self-esteem and depression.
Predictors of workplace sexual health policy at sex work establishments in the Philippines.
Withers, M; Dornig, K; Morisky, D E
2007-09-01
Based on the literature, we identified manager and establishment characteristics that we hypothesized are related to workplace policies that support HIV protective behavior. We developed a sexual health policy index consisting of 11 items as our outcome variable. We utilized both bivariate and multivariate analysis of variance. The significant variables in our bivariate analyses (establishment type, number of employees, manager age, and membership in manager association) were entered into a multivariate regression model. The model was significant (p<.01), and predicted 42) of the variability in the development and management of a workplace sexual health policy supportive of condom use. The significant predictors were number of employees and establishment type. In addition to individually-focused CSW interventions, HIV prevention programs should target managers and establishment policies. Future HIV prevention programs may need to focus on helping smaller establishments, in particular those with less employees, to build capacity and develop sexual health policy guidelines.
Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne
2012-01-01
In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models. PMID:23275882
Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne
2012-12-01
In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models.
Several steps/day indicators predict changes in anthropometric outcomes: HUB City Steps.
Thomson, Jessica L; Landry, Alicia S; Zoellner, Jamie M; Tudor-Locke, Catrine; Webster, Michael; Connell, Carol; Yadrick, Kathy
2012-11-15
Walking for exercise remains the most frequently reported leisure-time activity, likely because it is simple, inexpensive, and easily incorporated into most people's lifestyle. Pedometers are simple, convenient, and economical tools that can be used to quantify step-determined physical activity. Few studies have attempted to define the direct relationship between dynamic changes in pedometer-determined steps/day and changes in anthropometric and clinical outcomes. Hence, the objective of this secondary analysis was to evaluate the utility of several descriptive indicators of pedometer-determined steps/day for predicting changes in anthropometric and clinical outcomes using data from a community-based walking intervention, HUB City Steps, conducted in a southern, African American population. A secondary aim was to evaluate whether treating steps/day data for implausible values affected the ability of these data to predict intervention-induced changes in clinical and anthropometric outcomes. The data used in this secondary analysis were collected in 2010 from 269 participants in a six-month walking intervention targeting a reduction in blood pressure. Throughout the intervention, participants submitted weekly steps/day diaries based on pedometer self-monitoring. Changes (six-month minus baseline) in anthropometric (body mass index, waist circumference, percent body fat [%BF], fat mass) and clinical (blood pressure, lipids, glucose) outcomes were evaluated. Associations between steps/day indicators and changes in anthropometric and clinical outcomes were assessed using bivariate tests and multivariable linear regression analysis which controlled for demographic and baseline covariates. Significant negative bivariate associations were observed between steps/day indicators and the majority of anthropometric and clinical outcome changes (r = -0.3 to -0.2: P < 0.05). After controlling for covariates in the regression analysis, only the relationships between steps/day indicators and changes in anthropometric (not clinical) outcomes remained significant. For example, a 1,000 steps/day increase in intervention mean steps/day resulted in a 0.1% decrease in %BF. Results for the three pedometer datasets (full, truncated, and excluded) were similar and yielded few meaningful differences in interpretation of the findings. Several descriptive indicators of steps/day may be useful for predicting anthropometric outcome changes. Further, manipulating steps/day data to address implausible values has little overall effect on the ability to predict these anthropometric changes.
Haugstvedt, Anne; Wentzel-Larsen, Tore; Rokne, Berit; Graue, Marit
2011-12-20
Being the parents of children with diabetes is demanding. Jay Belsky's determinants of parenting model emphasizes both the personal psychological resources, the characteristics of the child and contextual sources such as parents' work, marital relations and social network support as important determinants for parenting. To better understand the factors influencing parental functioning among parents of children with type 1 diabetes, we aimed to investigate associations between the children's glycated hemoglobin (HbA1c) and 1) variables related to the parents' psychological and contextual resources, and 2) frequency of blood glucose measurement as a marker for diabetes-related parenting behavior. Mothers (n = 103) and fathers (n = 97) of 115 children younger than 16 years old participated in a population-based survey. The questionnaire comprised the Life Orientation Test, the Oslo 3-item Social Support Scale, a single question regarding perceived social limitation because of the child's diabetes, the Relationship Satisfaction Scale and demographic and clinical variables. We investigated associations by using regression analysis. Related to the second aim hypoglycemic events, child age, diabetes duration, insulin regimen and comorbid diseases were included as covariates. The mean HbA1c was 8.1%, and 29% had HbA1c ≤ 7.5%. In multiple regression analysis, lower HbA1c was associated with higher education and stronger perceptions of social limitation among the mothers. A higher frequency of blood glucose measurement was significantly associated with lower HbA1c in bivariate analysis. Higher child age was significantly associated with higher HbA1c both in bivariate and multivariate analysis. A scatterplot indicated this association to be linear. Most families do not reach recommended treatment goals for their child with type 1 diabetes. Concerning contextual sources of stress and support, the families who successfully reached the treatment goals had mothers with higher education and experienced a higher degree of social limitations because of the child's diabetes. The continuous increasing HbA1c by age, also during the years before puberty, may indicate a need for further exploring the associations between child characteristics, context-related variables and parenting behavior such as factors facilitating the transfer of parents' responsibility and motivation for continued frequent treatment tasks to their growing children.
Mota, Natalie; Elias, Brenda; Tefft, Bruce; Medved, Maria; Munro, Garry
2012-01-01
Objectives. We examined individual, friend or family, and community or tribe correlates of suicidality in a representative on-reserve sample of First Nations adolescents. Methods. Data came from the 2002–2003 Manitoba First Nations Regional Longitudinal Health Survey of Youth. Interviews were conducted with adolescents aged 12 to 17 years (n = 1125) from 23 First Nations communities in Manitoba. We used bivariate logistic regression analyses to examine the relationships between a range of factors and lifetime suicidality. We conducted sex-by-correlate interactions for each significant correlate at the bivariate level. A multivariate logistic regression analysis identified those correlates most strongly related to suicidality. Results. We found several variables to be associated with an increased likelihood of suicidality in the multivariate model, including being female, depressed mood, abuse or fear of abuse, a hospital stay, and substance use (adjusted odds ratio range = 2.43–11.73). Perceived community caring was protective against suicidality (adjusted odds ratio = 0.93; 95% confidence interval = 0.88, 0.97) in the same model. Conclusions. Results of this study may be important in informing First Nations and government policy related to the implementation of suicide prevention strategies in First Nations communities. PMID:22676500
Brown, Brandon; Wachowiak-Smolíková, Renata; Spence, Nicholas D.; Wachowiak, Mark P.; Walters, Dan F.
2016-01-01
Securing safe and adequate drinking water is an ongoing issue for many Canadian First Nations communities despite nearly 15 years of reports, studies, policy changes, financial commitments, and regulations. The federal drinking water evaluation scheme is narrowly scoped, ignoring community level social factors, which may play a role in access to safe water in First Nations. This research used the 2006 Aboriginal Affairs and Northern Development Canada First Nations Drinking Water System Risk Survey data and the Community Well-Being Index, including labour force, education, housing, and income, from the 2006 Census. Bivariate analysis was conducted using the Spearman’s correlation, Kendall’s tau correlation, and Pearson’s correlation. Multivariable analysis was conducted using an ordinal (proportional or cumulative odds) regression model. Results showed that the regression model was significant. Community socioeconomic indicators had no relationship with drinking water risk characterization in both the bivariate and multivariable models, with the sole exception of labour force, which had a significantly positive effect on drinking water risk rankings. Socioeconomic factors were not important in explaining access to safe drinking water in First Nations communities. Improvements in the quality of safe water data as well as an examination of other community processes are required to address this pressing policy issue. PMID:27157172
Brown, Brandon; Wachowiak-Smolíková, Renata; Spence, Nicholas D; Wachowiak, Mark P; Walters, Dan F
2016-09-01
Securing safe and adequate drinking water is an ongoing issue for many Canadian First Nations communities despite nearly 15 years of reports, studies, policy changes, financial commitments, and regulations. The federal drinking water evaluation scheme is narrowly scoped, ignoring community level social factors, which may play a role in access to safe water in First Nations. This research used the 2006 Aboriginal Affairs and Northern Development Canada First Nations Drinking Water System Risk Survey data and the Community Well-Being Index, including labour force, education, housing, and income, from the 2006 Census. Bivariate analysis was conducted using the Spearman's correlation, Kendall's tau correlation, and Pearson's correlation. Multivariable analysis was conducted using an ordinal (proportional or cumulative odds) regression model. Results showed that the regression model was significant. Community socioeconomic indicators had no relationship with drinking water risk characterization in both the bivariate and multivariable models, with the sole exception of labour force, which had a significantly positive effect on drinking water risk rankings. Socioeconomic factors were not important in explaining access to safe drinking water in First Nations communities. Improvements in the quality of safe water data as well as an examination of other community processes are required to address this pressing policy issue.
Physical and Sexual Violence and Incident Sexually Transmitted Infections
Anand, Mallika; Redding, Colleen A.; Peipert, Jeffrey F.
2009-01-01
Abstract Objective To investigate whether women aged 13–35 who were victims of interpersonal violence were more likely than nonvictims to experience incident sexually transmitted infections (STIs). Methods We examined 542 women aged 13–35 enrolled in Project PROTECT, a randomized clinical trial that compared two different methods of computer-based intervention to promote the use of dual methods of contraception. Participants completed a baseline questionnaire that included questions about their history of interpersonal violence and were followed for incident STIs over the 2-year study period. We compared the incidence of STIs in women with and without a history of interpersonal violence using bivariate analyses and multiple logistic regression. Results In the bivariate analyses, STI incidence was found to be significantly associated with African American race/ethnicity, a higher number of sexual partners in the past month, and a lower likelihood of avoidance of sexual partners who pressure to have sex without a condom. In both crude and adjusted regression analyses, time to STI incidence was faster among women who reported physical or sexual abuse in the year before study enrollment (HRRadj = 1.68, 95% CI 1.06, 2.65). Conclusions Women with a recent history of abuse are at significantly increased risk of STI incidence than are nonvictims. PMID:19245303
Aggarwal, Neil Krishan; Lam, Peter; Castillo, Enrico; Weiss, Mitchell G.; Diaz, Esperanza; Alarcón, Renato D.; van Dijk, Rob; Rohlof, Hans; Ndetei, David M.; Scalco, Monica; Aguilar-Gaxiola, Sergio; Bassiri, Kavoos; Deshpande, Smita; Groen, Simon; Jadhav, Sushrut; Kirmayer, Laurence J.; Paralikar, Vasudeo; Westermeyer, Joseph; Santos, Filipa; Vega-Dienstmaier, Johann; Anez, Luis; Boiler, Marit; Nicasio, Andel V.; Lewis-Fernández, Roberto
2015-01-01
Objective This study’s objective is to analyze training methods clinicians reported as most and least helpful during the DSM-5 Cultural Formulation Interview field trial, reasons why, and associations between demographic characteristics and method preferences. Method The authors used mixed methods to analyze interviews from 75 clinicians in five continents on their training preferences after a standardized training session and clinicians’ first administration of the Cultural Formulation Interview. Content analysis identified most and least helpful educational methods by reason. Bivariate and logistic regression analysis compared clinician characteristics to method preferences. Results Most frequently, clinicians named case-based behavioral simulations as “most helpful” and video as “least helpful” training methods. Bivariate and logistic regression models, first unadjusted and then clustered by country, found that each additional year of a clinician’s age was associated with a preference for behavioral simulations: OR=1.05 (95% CI: 1.01–1.10; p=0.025). Conclusions Most clinicians preferred active behavioral simulations in cultural competence training, and this effect was most pronounced among older clinicians. Effective training may be best accomplished through a combination of reviewing written guidelines, video demonstration, and behavioral simulations. Future work can examine the impact of clinician training satisfaction on patient symptoms and quality of life. PMID:26449983
Dental avoidance behaviour in parent and child as risk indicators for caries in 5-year-old children.
Wigen, Tove I; Skaret, Erik; Wang, Nina J
2009-11-01
The aim of this study was to explore associations between avoidance behaviour and dental anxiety in both parents and children and caries experience in 5-year-old children. It was hypothesised that parents' dental avoidance behaviour and dental anxiety were related to dental caries in 5-year-old children. Data were collected from dental records and by clinical and radiographic examination of 523 children. The parents completed a questionnaire regarding education, national background, dental anxiety, dental attendance, and behaviour management problems. Bivariate and multivariate logistic regression was conducted. Children having one or more missed dental appointments (OR = 4.7), child behaviour management problems (OR = 3.3), child dental anxiety (OR = 3.1), and parents avoiding dental care (OR = 2.1) were bivariately associated with caries experience at the age of 5 years. In multivariate logistic regression, having one or more missed dental appointments (OR = 4.0) and child behaviour management problems (OR = 2.4) were indicators for dental caries in 5-year-old children, when controlling for parents education and national origin. Parents that avoid bringing their child to scheduled dental appointments and previous experiences of behaviour management problems for the child indicated risk for dental caries in 5-year-old children.
Gonçalves, Hernâni; Pinto, Paula; Silva, Manuela; Ayres-de-Campos, Diogo; Bernardes, João
2016-04-01
Fetal heart rate (FHR) monitoring is used routinely in labor, but conventional methods have a limited capacity to detect fetal hypoxia/acidosis. An exploratory study was performed on the simultaneous assessment of maternal heart rate (MHR) and FHR variability, to evaluate their evolution during labor and their capacity to detect newborn acidemia. MHR and FHR were simultaneously recorded in 51 singleton term pregnancies during the last two hours of labor and compared with newborn umbilical artery blood (UAB) pH. Linear/nonlinear indices were computed separately for MHR and FHR. Interaction between MHR and FHR was quantified through the same indices on FHR-MHR and through their correlation and cross-entropy. Univariate and bivariate statistical analysis included nonparametric confidence intervals and statistical tests, receiver operating characteristic curves and linear discriminant analysis. Progression of labor was associated with a significant increase in most MHR and FHR linear indices, whereas entropy indices decreased. FHR alone and in combination with MHR as FHR-MHR evidenced the highest auROC values for prediction of fetal acidemia, with 0.76 and 0.88 for the UAB pH thresholds 7.20 and 7.15, respectively. The inclusion of MHR on bivariate analysis achieved sensitivity and specificity values of nearly 100 and 89.1%, respectively. These results suggest that simultaneous analysis of MHR and FHR may improve the identification of fetal acidemia compared with FHR alone, namely during the last hour of labor.
Elevated blood pressure, race/ethnicity, and C-reactive protein levels in children and adolescents.
Lande, Marc B; Pearson, Thomas A; Vermilion, Roger P; Auinger, Peggy; Fernandez, Isabel D
2008-12-01
Adult hypertension is independently associated with elevated C-reactive protein levels, after controlling for obesity and other cardiovascular risk factors. The objective of this study was to determine, with a nationally representative sample of children, whether the relationship between elevated blood pressure and C-reactive protein levels may be evident before adulthood. Cross-sectional data for children 8 to 17 years of age who participated in the National Health and Nutrition Examination Survey between 1999 and 2004 were analyzed. Bivariate analyses compared children with C-reactive protein levels of >3 mg/L versus
Dexter, Franklin; Epstein, Richard H
2018-03-01
Diagnosis-related group (DRG) based reimbursement creates incentives for reduction in hospital length of stay (LOS). Such reductions might be accomplished by lesser incidences of discharges to home. However, we previously reported that, while controlling for DRG, each 1-day decrease in hospital median LOS was associated with lesser odds of transfer to a postacute care facility (P = .0008). The result, though, was limited to elective admissions, 15 common surgical DRGs, and the 2013 US National Readmission Database. We studied the same potential relationship between decreased LOS and postacute care using different methodology and over 2 different years. The observational study was performed using summary measures from the 2008 and 2014 US National Inpatient Sample, with 3 types of categories (strata): (1) Clinical Classifications Software's classes of procedures (CCS), (2) DRGs including a major operating room procedure during hospitalization, or (3) CCS limiting patients to those with US Medicare as the primary payer. Greater reductions in the mean LOS were associated with smaller percentages of patients with disposition to postacute care. Analyzed using 72 different CCSs, 174 DRGs, or 70 CCSs limited to Medicare patients, each pairwise reduction in the mean LOS by 1 day was associated with an estimated 2.6% ± 0.4%, 2.3% ± 0.3%, or 2.4% ± 0.3% (absolute) pairwise reduction in the mean incidence of use of postacute care, respectively. These 3 results obtained using bivariate weighted least squares linear regression were all P < .0001, as were the corresponding results obtained using unweighted linear regression or the Spearman rank correlation. In the United States, reductions in hospital LOS, averaged over many surgical procedures, are not accomplished through a greater incidence of use of postacute care.
Variable selection and model choice in geoadditive regression models.
Kneib, Thomas; Hothorn, Torsten; Tutz, Gerhard
2009-06-01
Model choice and variable selection are issues of major concern in practical regression analyses, arising in many biometric applications such as habitat suitability analyses, where the aim is to identify the influence of potentially many environmental conditions on certain species. We describe regression models for breeding bird communities that facilitate both model choice and variable selection, by a boosting algorithm that works within a class of geoadditive regression models comprising spatial effects, nonparametric effects of continuous covariates, interaction surfaces, and varying coefficients. The major modeling components are penalized splines and their bivariate tensor product extensions. All smooth model terms are represented as the sum of a parametric component and a smooth component with one degree of freedom to obtain a fair comparison between the model terms. A generic representation of the geoadditive model allows us to devise a general boosting algorithm that automatically performs model choice and variable selection.
Jetelina, Katelyn K; Jennings, Wesley G; Bishopp, Stephen A; Piquero, Alex R; Reingle Gonzalez, Jennifer M
2017-07-01
To examine how sublethal use-of-force patterns vary across officer-civilian race/ethnicity while accounting for officer-, civilian-, and situational-level factors. We extracted cross-sectional data from 5630 use-of-force reports from the Dallas Police Department in 2014 and 2015. We categorized each officer-civilian interaction into race/ethnicity dyads. We used multilevel, mixed logistic regression models to evaluate the relationship between race/ethnicity dyads and the types of use of force. Forty-eight percent of use-of-force interactions occurred between a White officer and a non-White civilian (White-non-White). In bivariate models, the odds of hard-empty hand control and intermediate weapon use were significantly higher among White-Black dyads compared with White-White dyads. The bivariate odds of intermediate weapon use were also significantly higher among Black-Black, Hispanic-White, Black-Hispanic, and Hispanic-Black dyads compared with White-White dyads. However, after we controlled for individual and situational factors, the relationship between race/ethnicity dyad and hard-empty hand control was no longer significant. Although we observed significant bivariate relationships between race/ethnicity dyads and use of force, these relationships largely dissipated after we controlled for other factors.
NASA Astrophysics Data System (ADS)
Yilmaz, Işik; Marschalko, Marian; Bednarik, Martin
2013-04-01
The paper presented herein compares and discusses the use of bivariate, multivariate and soft computing techniques for collapse susceptibility modelling. Conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) models representing the bivariate, multivariate and soft computing techniques were used in GIS based collapse susceptibility mapping in an area from Sivas basin (Turkey). Collapse-related factors, directly or indirectly related to the causes of collapse occurrence, such as distance from faults, slope angle and aspect, topographical elevation, distance from drainage, topographic wetness index (TWI), stream power index (SPI), Normalized Difference Vegetation Index (NDVI) by means of vegetation cover, distance from roads and settlements were used in the collapse susceptibility analyses. In the last stage of the analyses, collapse susceptibility maps were produced from the models, and they were then compared by means of their validations. However, Area Under Curve (AUC) values obtained from all three models showed that the map obtained from soft computing (ANN) model looks like more accurate than the other models, accuracies of all three models can be evaluated relatively similar. The results also showed that the conditional probability is an essential method in preparation of collapse susceptibility map and highly compatible with GIS operating features.
Pellecchia, Melanie; Connell, James E; Kerns, Connor M; Xie, Ming; Marcus, Steven C; Mandell, David S
2016-04-01
This study examined the extent to which clinical and demographic characteristics predicted outcome for children with autism spectrum disorder. Participants included 152 students with autism spectrum disorder in 53 kindergarten-through-second-grade autism support classrooms in a large urban public school district. Associations between child characteristics (including age, language ability, autism severity, social skills, adaptive behavior, co-occurring psychological symptoms, and restrictive and repetitive behavior) and outcome, as measured by changes in cognitive ability following one academic year of an intervention standardized across the sample were evaluated using linear regression with random effects for classroom. While several scales and subscales had statistically significant bivariate associations with outcome, in adjusted analysis, only age and the presence of symptoms associated with social anxiety, such as social avoidance and social fearfulness, as measured through the Child Symptom Inventory-4, were associated with differences in outcome. The findings regarding the role of social anxiety are new and have important implications for treatment. Disentangling the construct of social anxiety to differentiate between social fearfulness and social motivation has important implications for shifting the focus of early treatment for children with autism spectrum disorder. © The Author(s) 2015.
Auditory dysfunction associated with solvent exposure
2013-01-01
Background A number of studies have demonstrated that solvents may induce auditory dysfunction. However, there is still little knowledge regarding the main signs and symptoms of solvent-induced hearing loss (SIHL). The aim of this research was to investigate the association between solvent exposure and adverse effects on peripheral and central auditory functioning with a comprehensive audiological test battery. Methods Seventy-two solvent-exposed workers and 72 non-exposed workers were selected to participate in the study. The test battery comprised pure-tone audiometry (PTA), transient evoked otoacoustic emissions (TEOAE), Random Gap Detection (RGD) and Hearing-in-Noise test (HINT). Results Solvent-exposed subjects presented with poorer mean test results than non-exposed subjects. A bivariate and multivariate linear regression model analysis was performed. One model for each auditory outcome (PTA, TEOAE, RGD and HINT) was independently constructed. For all of the models solvent exposure was significantly associated with the auditory outcome. Age also appeared significantly associated with some auditory outcomes. Conclusions This study provides further evidence of the possible adverse effect of solvents on the peripheral and central auditory functioning. A discussion of these effects and the utility of selected hearing tests to assess SIHL is addressed. PMID:23324255
Predicting Aggression among Male Adolescents: an Application of the Theory of Planned Behavior
ZinatMotlagh, Fazel; Ataee, Mari; Jalilian, Farzad; MirzaeiAlavijeh, Mehdi; Aghaei, Abbas; Karimzadeh Shirazi, Kambiz
2013-01-01
Background: Aggressive behaviorin adolescencecan be expressed asa predictorfor crime, substanceabuse, depression and academic failure. The purpose of this study was to determine the prediction of aggression among Iranian adolescent based on theory of planned behavior (TPB) as a theoretical framework. Methods: In this cross-sectional study, conducted in Yasuj County, south of Iran, during 2011, a total of 256 male adolescents, were randomly enrolled. Participants filled out a self-administered questionnaire. Data were analyzed by SPSS version 21 using bivariate correlations, and linear regression statistical tests at 95% significant level. Result:The three predictor variables of 1) attitude, 2) subjective norms, and 3) perceived behavioral control, accounted for 40% of the variation in the outcome measure of the aggression intention. Besides, intention accounted for 15% of the variation in the outcome measure of the aggression behavior. There was a significant correlation between drug abuse and alcohol consumption, have friend drug user, unprotect sex and parents divorced with aggression (P< 0.05). Conclusions: Designing intervention to reduction positive attitude and subjective norms toward aggressive behavior among adolescents could be usefulness result to aggression prevention. PMID:24688977
Emotional and cognitive health correlates of leisure activities in older Latino and Caucasian women
Herrera, Angelica P.; Meeks, Thomas W.; Dawes, Sharron E.; Hernandez, Dominique M.; Thompson, Wesley K.; Sommerfeld, David H.; Allison, Matthew A.; Jeste, Dilip V.
2011-01-01
This study examined differences in the frequency of leisure activity participation and relationships to depressive symptom burden and cognition in Latino and Caucasian women. Cross-sectional data were obtained from a demographically matched subsample of Latino and Caucasian (n = 113 each) post-menopausal women (age ≥60), interviewed in 2004–06 for a multi-ethnic cohort study of successful aging in San Diego County. Frequencies of engagement in 16 leisure activities and associations between objective cognitive performance and depressive symptom burden by ethnicity were identified using bivariate and linear regression, adjusted for physical functioning and demographic covariates. Compared to Caucasian women, Latinas were significantly more likely to be caregivers and used computers less often. Engaging in organized social activity was associated with fewer depressive symptoms in both groups. Listening to the radio was positively correlated with lower depressive symptom burden for Latinas, and better cognitive functioning in Caucasians. Cognitive functioning was better in Latinas who read and did puzzles. Housework was negatively associated with Latinas’ emotional health and Caucasians’ cognitive functioning. Latino and Caucasian women participate in different patterns of leisure activities. Additionally, ethnicity significantly affects the relationship between leisure activities and both emotional and cognitive health. PMID:21391135
Suh, Yoojin; Weikert, Madeline; Dlugonski, Deirdre; Sandroff, Brian; Motl, Robert W
2012-01-01
The present study examined the pattern of associations among physical activity, social support, mobility disability, perceived stress, and depressive symptoms in relapsing-remitting MS (RRMS). Persons (N = 218) with RRMS completed a battery of questionnaires that was sent and returned through the United States Postal Service (USPS). Bivariate correlation analysis indicated that physical activity and social support were both inversely associated with depressive symptoms (r's = -0.288 and -0.386, p ≤ 0.05, respectively). Multiple linear regression analysis indicated that physical activity (β = -0.21, p = 0.002) and social support (β = -0.37, p = 0.0001) were independently associated with depressive symptoms. Path analysis confirmed that the associations between physical activity and social support with depressive symptoms were indirect via mobility disability and perceived stress. Collectively, the evidence indicates that physical activity and social support are independently and indirectly associated with depression via mobility disability and perceived stress in relapsing-remitting MS. This supports the design of interventions and programs that target physical activity and social support for reducing depressive symptoms among persons with MS.
Factors associated with the patient safety climate at a teaching hospital1
Luiz, Raíssa Bianca; Simões, Ana Lúcia de Assis; Barichello, Elizabeth; Barbosa, Maria Helena
2015-01-01
Objectives: to investigate the association between the scores of the patient safety climate and socio-demographic and professional variables. Methods: an observational, sectional and quantitative study, conducted at a large public teaching hospital. The Safety Attitudes Questionnaire was used, translated and validated for Brazil. Data analysis used the software Statistical Package for Social Sciences. In the bivariate analysis, we used Student's t-test, analysis of variance and Spearman's correlation of (α=0.05). To identify predictors for the safety climate scores, multiple linear regression was used, having the safety climate domain as the main outcome (α=0.01). Results: most participants were women, nursing staff, who worked in direct care to adult patients in critical areas, without a graduate degree and without any other employment. The average and median total score of the instrument corresponded to 61.8 (SD=13.7) and 63.3, respectively. The variable professional performance was found as a factor associated with the safety environment for the domain perception of service management and hospital management (p=0.01). Conclusion: the identification of factors associated with the safety environment permits the construction of strategies for safe practices in the hospitals. PMID:26487138
Hendrick, C Emily; Cohen, Alison K; Deardorff, Julianna; Cance, Jessica D
2016-03-01
Lifetime educational attainment is an important predictor of health and well-being for women in the United States. In this study, we examine the roles of sociocultural factors in youth and an understudied biological life event, pubertal timing, in predicting women's lifetime educational attainment. Using data from the National Longitudinal Survey of Youth 1997 cohort (N = 3889), we conducted sequential multivariate linear regression analyses to investigate the influences of macro-level and family-level sociocultural contextual factors in youth (region of country, urbanicity, race/ethnicity, year of birth, household composition, mother's education, and mother's age at first birth) and early menarche, a marker of early pubertal development, on women's educational attainment after age 24. Pubertal timing and all sociocultural factors in youth, other than year of birth, predicted women's lifetime educational attainment in bivariate models. Family factors had the strongest associations. When family factors were added to multivariate models, geographic region in youth, and pubertal timing were no longer significant. Our findings provide additional evidence that family factors should be considered when developing comprehensive and inclusive interventions in childhood and adolescence to promote lifetime educational attainment among girls. © 2016, American School Health Association.
Law, Tameeka L; Katikaneni, Lakshmi D; Taylor, Sarah N; Korte, Jeffrey E; Ebeling, Myla D; Wagner, Carol L; Newman, Roger B
2012-07-01
Compare customized versus population-based growth curves for identification of small-for-gestational-age (SGA) and body fat percent (BF%) among preterm infants. Prospective cohort study of 204 preterm infants classified as SGA or appropriate-for-gestational-age (AGA) by population-based and customized growth curves. BF% was determined by air-displacement plethysmography. Differences between groups were compared using bivariable and multivariable linear and logistic regression analyses. Customized curves reclassified 30% of the preterm infants as SGA. SGA infants identified by customized method only had significantly lower BF% (13.8 ± 6.0) than the AGA (16.2 ± 6.3, p = 0.02) infants and similar to the SGA infants classified by both methods (14.6 ± 6.7, p = 0.51). Customized growth curves were a significant predictor of BF% (p = 0.02), whereas population-based growth curves were not a significant independent predictor of BF% (p = 0.50) at term corrected gestational age. Customized growth potential improves the differentiation of SGA infants and low BF% compared with a standard population-based growth curve among a cohort of preterm infants.
Vijay, Aishwarya; Earnshaw, Valerie A; Tee, Ying Chew; Pillai, Veena; White Hughto, Jaclyn M; Clark, Kirsty; Kamarulzaman, Adeeba; Altice, Frederick L; Wickersham, Jeffrey A
2018-01-01
Transgender people are frequent targets of discrimination. Discrimination against transgender people in the context of healthcare can lead to poor health outcomes and facilitate the growth of health disparities. This study explores factors associated with medical doctors' intentions to discriminate against transgender people in Malaysia. A total of 436 physicians at two major university medical centers in Kuala Lumpur, Malaysia, completed an online survey. Sociodemographic characteristics, stigma-related constructs, and intentions to discriminate against transgender people were measured. Bivariate and multivariate linear regression were used to evaluate independent covariates of discrimination intent. Medical doctors who felt more fearful of transgender people and more personal shame associated with transgender people expressed greater intention to discriminate against transgender people, whereas doctors who endorsed the belief that transgender people deserve good care reported lower discrimination intent. Stigma-related constructs accounted for 42% of the variance and 8% was accounted for by sociodemographic characteristics. Constructs associated with transgender stigma play an important role in medical doctors' intentions to discriminate against transgender patients. Development of interventions to improve medical doctors' knowledge about and attitudes toward transgender people are necessary to reduce discriminatory intent in healthcare settings.
Warsini, Sri; Buettner, Petra; Mills, Jane; West, Caryn; Usher, Kim
2015-06-01
The Mount Merapi volcanic eruption in October 2010 was one of Indonesia's largest and most recent natural disasters. A cross-sectional study was undertaken to measure the psychosocial impact of the eruption on survivors in two locations in Yogyakarta, Java, Indonesia. The Impact of Event Scale Revised was used to assess participants' symptoms of post-traumatic stress disorder. Post-Traumatic Stress Disorder responses and demographic characteristics were compared in both locations by conducting bivariate analysis using Mann-Whitney and t tests. The relative contributions of demographic variables and psychosocial impact were examined using multiple linear regression analyses. Two years after the eruption, survivors from the area closest to the eruption had significantly higher Impact of Event Scale Revised scores than those in the comparison area. In particular, females, adults between the ages of 18 and 59, and people who owned their own home experienced the highest levels of psychosocial impact. Nurses and other health professionals need to be aware of the impact of natural disasters on survivors and develop interventions to help people adjust to the psychosocial impact of these events. © 2014 Wiley Publishing Asia Pty Ltd.
Unger, Jennifer B.; Yaroch, Amy L.; Cockburn, Myles G.; Baezconde-Garbanati, Lourdes; Reynolds, Kim D.
2009-01-01
Objectives. We examined the relationship between acculturation and sun safety among US Latinos. Methods. We used linear regression models to analyze data from 496 Latino respondents to the 2005 Health Information National Trends Survey. Using sunscreen, seeking shade, and wearing protective clothing were the primary outcomes and were assessed by frequency scales. Acculturation was assessed with a composite index. Results. In bivariate models, acculturation was negatively associated with use of shade and protective clothing and positively associated with sunscreen use (all, P < .004). In adjusted models, acculturation was negatively associated with seeking shade and wearing protective clothing across gender and region of residence (all, P < .05). Conclusions. Our results demonstrated both adverse and beneficial effects of acculturation on Latinos’ risk behaviors relating to skin cancer. Education about sun safety is needed for all Latinos and should be tailored to different levels of acculturation. Initiatives for Latinos who are not yet acculturated could focus on reinforcing existing sun-safe behaviors and presenting new ones, such as use of sunscreen; initiatives for highly acculturated Latinos might require more resources because the objective is behavior modification. PMID:19150918
Yazdani, Farzaneh; Carstensen, Tove; Bonsaksen, Tore
2017-03-01
The Intentional Relationship Model is specifically focused on the relational aspect of therapy. The model describes six therapeutic modes; these represent different types of interaction for the therapist. However, preferences for therapeutic mode use are under researched. This study aims to describe preferences for therapeutic modes in undergraduate occupational therapy students, as well as to explore factors associated to each of the therapeutic modes. A sample of 96 occupational therapy students, based at two different Norwegian universities, participated in the study. They completed the Norwegian Self-Assessment of Modes Questionnaire along with sociodemographic information. Descriptive analysis, bivariate correlation and linear regression analysis were employed. The problem-solving mode was most frequently endorsed. There were generally weak associations between the variables, but female sex and being a student in the education program in Trondheim were associated with higher preference for collaboration. There is diversity in students' preferences for the modes, but the problem-solving mode was the most preferred. Students need to be aware of the mode they feel more comfortable with and make sure they use modes that fit with the specific client. The occupational therapy education programs need to incorporate raising awareness about therapeutic modes.
Portugal, Flávia Batista; Campos, Mônica Rodrigues; Gonçalves, Daniel Almeida; Mari, Jair de Jesus; Fortes, Sandra Lúcia Correia Lima
2016-02-01
Quality of life (QoL) is a subjective construct, which can be negatively associated with factors such as mental disorders and stressful life events (SLEs). This article seeks to identify the association between socioeconomic and demographic variables, common mental disorders, symptoms suggestive of depression and anxiety, SLEs with QoL in patients attended in Primary Care (PC). It is a transversal study, conducted with 1,466 patients attended in PC centers in the cities of São Paulo and Rio de Janeiro in 2009 and 2010. Bivariate analysis was performed using the T-test and four multiple linear regressions for each QoL domain. The scores for the physical, psychological, social relations and environment domains were, respectively, 64.7; 64.2; 68.5 and 49.1. By means of multivariate analysis, associations of the physical domain were found with health problems and discrimination; of the psychological domain with discrimination; of social relations with financial/structural problems; of external causes and health problems; and of the environment with financial/structural problems, external causes and discrimination. Mental health variables, health problems and financial/structural problems were the factors negatively associated with QoL.
López-Martínez, Catalina; Frías-Osuna, Antonio; Del-Pino-Casado, Rafael
2017-11-23
To analyze the relationship between the sense of coherence and subjective overload, anxiety and depression in caregivers of dependent elderly relatives. Cross-sectional study in an area of the province of Jaén (Andalusia, Spain) with a probabilistic sample of 132 caregivers of dependent elderly. sense of coherence (Life Orientation Questionnaire), subjective burden (Caregiver Strain Index), anxiety and depression (Goldberg Scale), objective burden (Dedication to Care Scale), sex and kinship. Main analyses: bivariate analysis using the Pearson correlation coefficient and multivariate analysis using multiple linear regression. Most of the caregivers studied were women (86.4%), daughter or son of the care recipient (74.2%) and shared home with the latter (69.7%). When controlling for objective burden, sex and kinship, we found that the sense of coherence was inversely related to subjective burden (β = -0.46; p <0.001), anxiety (β = -0.57; p = 0.001) and depression (β = -0.66; p <0.001). The sense of coherence might be an important protective factor of subjective burden, anxiety and depression in caregivers of dependent elderly relatives. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.
Vijay, Aishwarya; Earnshaw, Valerie A.; Tee, Ying Chew; Pillai, Veena; White Hughto, Jaclyn M.; Clark, Kirsty; Kamarulzaman, Adeeba; Altice, Frederick L.
2018-01-01
Abstract Purpose: Transgender people are frequent targets of discrimination. Discrimination against transgender people in the context of healthcare can lead to poor health outcomes and facilitate the growth of health disparities. This study explores factors associated with medical doctors' intentions to discriminate against transgender people in Malaysia. Methods: A total of 436 physicians at two major university medical centers in Kuala Lumpur, Malaysia, completed an online survey. Sociodemographic characteristics, stigma-related constructs, and intentions to discriminate against transgender people were measured. Bivariate and multivariate linear regression were used to evaluate independent covariates of discrimination intent. Results: Medical doctors who felt more fearful of transgender people and more personal shame associated with transgender people expressed greater intention to discriminate against transgender people, whereas doctors who endorsed the belief that transgender people deserve good care reported lower discrimination intent. Stigma-related constructs accounted for 42% of the variance and 8% was accounted for by sociodemographic characteristics. Conclusions: Constructs associated with transgender stigma play an important role in medical doctors' intentions to discriminate against transgender patients. Development of interventions to improve medical doctors' knowledge about and attitudes toward transgender people are necessary to reduce discriminatory intent in healthcare settings. PMID:29227183
Late Life Immigration and Quality of Life among Asian Indian Older Adults.
Mukherjee, Anita J; Diwan, Sadhna
2016-09-01
Late-life immigration among seniors for purposes of family reunification is a growing phenomenon in developed countries. Using the World Health Organization's Quality of Life instrument short form (WHOQOL-BREF) and other psychosocial measures related to the political/legal context of immigration, and personal and environmental autonomy (mastery, immigration status, access to transportation, and language barrier), this study examined quality of life (QoL) in Asian Indian seniors (N = 109), who immigrated to the United States to reunite with their adult children. The sample scores on Overall QoL and QoL domains (physical and psychological health, social relationships, and environment) were similar to established norms. Although all QoL domains correlated significantly with Overall QoL at the bivariate level, multivariate analysis showed that only environmental domain contributed significantly to Overall QoL. Linear regressions indicated: Mastery contributed significantly to Overall QoL and all QoL domains; access to transport contributed to Overall QoL, physical health, and environmental QoL; immigration status (a proxy for political/legal context) contributed to environmental QoL whereas language barrier contributed to none. Implications for improving perceptions of QoL, mastery, access to transport and other services are discussed.
Zhou, Yunping; Tian, Changwei; Jia, Chongqi
2012-08-01
Results from observational studies on the association of fish and n-3 fatty acid consumption with type 2 diabetes mellitus (T2DM) risk are conflicting. Hence, a meta-analysis was performed to investigate this association from cohort studies. A comprehensive search was then conducted to identify cohort studies on the association of fish and/or n-3 fatty acid intake with T2DM risk. In the highest v. lowest categorical analyses, the fixed or random-effect model was selected based on the homogeneity test among studies. Linear and non-linear dose-response relationships were also assessed by univariate and bivariate random-effect meta-regression with restricted maximum likelihood estimation. In the highest v. lowest categorical analyses, the pooled relative risk (RR) of T2DM for intake of fish and n-3 fatty acid was 1·146 (95 % CI 0·975, 1·346) and 1·076 (95 % CI 0·955, 1·213), respectively. In the linear dose-response relationship, the pooled RR for an increment of one time (about 105 g)/week of fish intake (four times/month) and of 0·1 g/d of n-3 fatty acid intake was 1·042 (95 % CI 1·026, 1·058) and 1·057 (95 % CI 1·042, 1·073), respectively. The significant non-linear dose-response associations of fish and n-3 fatty acid intake with T2DM risk were not observed. The present evidence from observational studies suggests that the intake of both fish and n-3 fatty acids might be weakly positively associated with the T2DM risk. Further studies are needed to confirm these results.
Pogorzelska-Maziarz, Monika
2015-10-01
Sharps disposal containers are ubiquitous in health care facilities; however, there is paucity of data on their potential role in pathogen transmission. This study assessed the relationship between use of single-use versus reusable sharps containers and rates of Clostridium difficile infections in a national sample of hospitals. A 2013 survey of 1,990 hospitals collected data on the use of sharps containers. Responses were linked to the 2012 Medicare Provider Analysis and Review dataset. Bivariate and multivariable negative binomial regression were conducted to examine differences in C difficile rates between hospitals using single-use versus reusable containers. There were 604 hospitals who completed the survey; of these, 539 provided data on use of sharps containers in 2012 (27% response rate). Hospitals had, on average, 289 beds (SD ± 203) and were predominantly non-for-profit (67%) and nonteaching (63%). Most used reusable sharps containers (72%). In bivariate regression, hospitals using single-use containers had significantly lower rates of C difficile versus hospitals using reusable containers (incidence rate ratio [IRR] = 0.846, P = .001). This relationship persisted in multivariable regression (IRR = 0.870, P = .003) after controlling for other hospital characteristics. This is the first study to show a link between use of single-use sharps containers and lower C difficile rates. Future research should investigate the potential for environmental contamination of reusable containers and the role they may play in pathogen transmission. Copyright © 2015 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.
Determinants of adolescent suicidal ideation: rural versus urban.
Murphy, Sean M
2014-01-01
The existing literature on disparities between rural and urban adolescents as they pertain to suicidal behavior is limited; identifying these distinctions could be pivotal in the decision of how to efficiently allocate scarce resources to reduce youth suicide rates. This study aimed to identify dissimilarities in predictors of suicidal ideation across the rural/urban threshold, as ideation is one of the most important predictors of suicide. Given that substance abuse is generally considered one of the strongest risk factors for suicidal behavior, a secondary aim was the isolation of the differences in usage of particular substances between rural and urban adolescents, and their effects on the likelihood of suicidal ideation, which is something that previous studies have had difficulty addressing. A global test determined that individual predictors of suicidal ideation differed across rural and urban adolescents, and simply including a rural/urban indicator in a multiple regression would result in biased estimates. Therefore, this paper assessed rural/urban differences among a comprehensive list of traditionally perceived risk and protective factors via bivariate analyses and separate multiple full-information-maximum-likelihood regressions, which account for missing data. Somewhat contrary to the extant literature, the findings indicate important differences among predictors of suicidal ideation for rural and urban youths. These differences should be taken into consideration when developing plans to combat adolescent suicide. The results further indicate that analyzing potential predictors of suicidal ideation for rural and urban adolescents via bivariate analyses alone, or a rural/urban indicator in a multiple regression, is not sufficient. © 2013 National Rural Health Association.
Shah, Kalpit N; Defroda, Steven F; Wang, Bo; Weiss, Arnold-Peter C
2017-12-01
The first carpometacarpal (CMC) joint is a common site of osteoarthritis, with arthroplasty being a common procedure to provide pain relief and improve function with low complications. However, little is known about risk factors that may predispose a patient for postoperative complications. All CMC joint arthroplasty from 2005 to 2015 in the prospectively collected American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database were identified. Bivariate testing and multiple logistic regressions were performed to determine which patient demographics, surgical variables and medical comorbidities were significant predictors for complications. These included wound related, cardiopulmonary, neurological and renal complications, return to the operating room (OR) and readmission. A total of 3344 patients were identified from the database. Of those, 45 patients (1.3%) experienced a complication including wound issues (0.66%), return to the OR (0.15%) and readmission (0.27%) amongst others. When performing bivariate analysis, age over 65, American Society of Anesthesiologists (ASA) Class, diabetes and renal dialysis were significant risk factors. Multiple logistic regression after adjusting for confounding factors demonstrated that insulin-dependent diabetes and ASA Class 4 had a strong trend while renal dialysis was a significant risk factor. CMC arthroplasty has a very low overall complication rate of 1.3% and wound complication rate of 0.66%. Diabetes requiring insulin and ASA Class 4 trended towards significance while renal dialysis was found to be a significant risk factors in logistic regression. This information may be useful for preoperative counseling and discussion with patients who have these risk factors.
Kumar, K Vasanth
2007-04-02
Kinetic experiments were carried out for the sorption of safranin onto activated carbon particles. The kinetic data were fitted to pseudo-second order model of Ho, Sobkowsk and Czerwinski, Blanchard et al. and Ritchie by linear and non-linear regression methods. Non-linear method was found to be a better way of obtaining the parameters involved in the second order rate kinetic expressions. Both linear and non-linear regression showed that the Sobkowsk and Czerwinski and Ritchie's pseudo-second order models were the same. Non-linear regression analysis showed that both Blanchard et al. and Ho have similar ideas on the pseudo-second order model but with different assumptions. The best fit of experimental data in Ho's pseudo-second order expression by linear and non-linear regression method showed that Ho pseudo-second order model was a better kinetic expression when compared to other pseudo-second order kinetic expressions.
Symmetric co-movement between Malaysia and Japan stock markets
NASA Astrophysics Data System (ADS)
Razak, Ruzanna Ab; Ismail, Noriszura
2017-04-01
The copula approach is a flexible tool known to capture linear, nonlinear, symmetric and asymmetric dependence between two or more random variables. It is often used as a co-movement measure between stock market returns. The information obtained from copulas such as the level of association of financial market during normal and bullish and bearish markets phases are useful for investment strategies and risk management. However, the study of co-movement between Malaysia and Japan markets are limited, especially using copulas. Hence, we aim to investigate the dependence structure between Malaysia and Japan capital markets for the period spanning from 2000 to 2012. In this study, we showed that the bivariate normal distribution is not suitable as the bivariate distribution or to present the dependence between Malaysia and Japan markets. Instead, Gaussian or normal copula was found a good fit to represent the dependence. From our findings, it can be concluded that simple distribution fitting such as bivariate normal distribution does not suit financial time series data, whose characteristics are often leptokurtic. The nature of the data is treated by ARMA-GARCH with heavy tail distributions and these can be associated with copula functions. Regarding the dependence structure between Malaysia and Japan markets, the findings suggest that both markets co-move concurrently during normal periods.
Inci, Ercan; Ekizoglu, Oguzhan; Turkay, Rustu; Aksoy, Sema; Can, Ismail Ozgur; Solmaz, Dilek; Sayin, Ibrahim
2016-10-01
Morphometric analysis of the mandibular ramus (MR) provides highly accurate data to discriminate sex. The objective of this study was to demonstrate the utility and accuracy of MR morphometric analysis for sex identification in a Turkish population.Four hundred fifteen Turkish patients (18-60 y; 201 male and 214 female) who had previously had multidetector computed tomography scans of the cranium were included in the study. Multidetector computed tomography images were obtained using three-dimensional reconstructions and a volume-rendering technique, and 8 linear and 3 angular values were measured. Univariate, bivariate, and multivariate discriminant analyses were performed, and the accuracy rates for determining sex were calculated.Mandibular ramus values produced high accuracy rates of 51% to 95.6%. Upper ramus vertical height had the highest rate at 95.6%, and bivariate analysis showed 89.7% to 98.6% accuracy rates with the highest ratios of mandibular flexure upper border and maximum ramus breadth. Stepwise discrimination analysis gave a 99% accuracy rate for all MR variables.Our study showed that the MR, in particular morphometric measures of the upper part of the ramus, can provide valuable data to determine sex in a Turkish population. The method combines both anthropological and radiologic studies.
A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield
NASA Astrophysics Data System (ADS)
Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan
2018-04-01
In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.
Anderson, Carl A; McRae, Allan F; Visscher, Peter M
2006-07-01
Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.
Waqas, Ahmed; Rehman, Abdul; Malik, Aamenah; Muhammad, Umer; Khan, Sarah; Mahmood, Nadia
2015-09-30
Ego defense mechanisms are unconscious psychological processes that help an individual to prevent anxiety when exposed to a stressful situation. These mechanisms are important in psychiatric practice to assess an individual's personality dynamics, psychopathologies, and modes of coping with stressful situations, and hence, to design appropriate individualized treatment. Our study delineates the relationship of ego defense mechanisms with anxiety, depression, and academic performance of Pakistani medical students. This cross-sectional study was done at CMH Lahore Medical College and Fatima Memorial Hospital Medical and Dental College, both in Lahore, Pakistan, from December 1, 2014 to January 15, 2015. Convenience sampling was used and only students who agreed to take part in this study were included. The questionnaire consisted of three sections: 1) Demographics, documenting demographic data and academic scores on participants' most recent exams; 2) Hospital Anxiety and Depression Scale (HADS); and 3) Defense Style Questionnaire-40 (DSQ-40). The data were analyzed with SPSS v. 20. Mean scores and frequencies were calculated for demographic variables and ego defense mechanisms. Bivariate correlations, one-way ANOVA, and multiple linear regression were used to identify associations between academic scores, demographics, ego defense mechanisms, anxiety, and depression. A total of 409 medical students participated, of whom 286 (70%) were females and 123 (30%) were males. Mean percentage score on the most recent exams was 75.6% in medical students. Bivariate correlation revealed a direct association between mature and neurotic ego defense mechanisms and academic performance, and an indirect association between immature mechanisms and academic performance. One-way ANOVA showed that moderate levels of anxiety (P < .05) and low levels of depression (P < .05) were associated with higher academic performance. There was a significant association between academic performance and ego defense mechanisms, anxiety, and depression levels in our sample of Pakistani medical students.
Prophylactic Dextrose Gel Does Not Prevent Neonatal Hypoglycemia: A Quasi-Experimental Pilot Study.
Coors, Sarah M; Cousin, Joshua J; Hagan, Joseph L; Kaiser, Jeffrey R
2018-07-01
To test the hypothesis that prophylactic dextrose gel administered to newborn infants at risk for hypoglycemia will increase the initial blood glucose concentration after the first feeding and decrease neonatal intensive care unit (NICU) admissions for treatment of asymptomatic neonatal hypoglycemia compared with feedings alone. This quasi-experimental study allocated asymptomatic at-risk newborn infants (late preterm, birth weight <2500 or >4000 g, and infants of mothers with diabetes) to receive prophylactic dextrose gel (Insta-Glucose; Valeant Pharmaceuticals North America LLC, Bridgewater, New Jersey); other at-risk infants formed the control group. After the initial feeding, the prophylactic group received dextrose gel (0.5 mL/kg) rubbed into the buccal mucosa. The blood glucose concentration was checked 30 minutes later. Initial glucose concentrations and rate of NICU admissions were compared between the prophylactic group and controls using bivariate analyses. A multivariable linear regression compared first glucose concentrations between groups, adjusting for at-risk categories and age at first glucose concentration. There were 236 subjects (72 prophylactic, 164 controls). The first glucose concentration was not different between the prophylactic and control groups in bivariate analysis (52.1 ± 17.1 vs 50.5 ± 15.3 mg/dL, P = .69) and after adjusting for covariates (P = .18). Rates of NICU admission for treatment of transient neonatal hypoglycemia were 9.7% and 14.6%, respectively (P = .40). Prophylactic dextrose gel did not reduce transient neonatal hypoglycemia or NICU admissions for hypoglycemia. The carbohydrate concentration of Insta-Glucose (77%) may have caused a hyperinsulinemic response, or alternatively, exogenous enteral dextrose influences glucose homeostasis minimally during the first few hours when counter-regulatory mechanisms are especially active. ClinicalTrials.gov: NCT02523222. Copyright © 2018 Elsevier Inc. All rights reserved.
Lifestyle Markers Predict Cognitive Function.
Masley, Steven C; Roetzheim, Richard; Clayton, Gwendolyn; Presby, Angela; Sundberg, Kelley; Masley, Lucas V
2017-01-01
Rates of mild cognitive impairment and Alzheimer's disease are increasing rapidly. None of the current treatment regimens for Alzheimer's disease are effective in arresting progression. Lifestyle choices may prevent cognitive decline. This study aims to clarify which factors best predict cognitive function. This was a prospective cross-sectional analysis of 799 men and women undergoing health and cognitive testing every 1 to 3 years at an outpatient center. This study utilizes data collected from the first patient visit. Participant ages were 18 to 88 (mean = 50.7) years and the sample was 26.6% female and 73.4% male. Measurements were made of body composition, fasting laboratory and anthropometric measures, strength and aerobic fitness, nutrient and dietary intake, and carotid intimal media thickness (IMT). Each participant was tested with a computerized neurocognitive test battery. Cognitive outcomes were assessed in bivariate analyses using t-tests and correlation coefficients and in multivariable analysis (controlling for age) using multiple linear regression. The initial bivariate analyses showed better Neurocognitive Index (NCI) scores with lower age, greater fitness scores (push-up strength, VO 2 max, and exercise duration during treadmill testing), and lower fasting glucose levels. Better cognitive flexibility scores were also noted with younger age, lower systolic blood pressure, lower body fat, lower carotid IMT scores, greater fitness, and higher alcohol intake. After controlling for age, factors that remained associated with better NCI scores include no tobacco use, lower fasting glucose levels, and better fitness (aerobic and strength). Higher cognitive flexibility scores remained associated with greater aerobic and strength fitness, lower body fat, and higher intake of alcohol. Modifiable biomarkers that impact cognitive performance favorably include greater aerobic fitness and strength, lower blood sugar levels, greater alcohol intake, lower body fat, and avoidance of tobacco. Further studies are warranted to study whether modifying these lifestyle factors improves cognitive function and slows cognitive decline.
Waqas, Ahmed; Malik, Aamenah; Muhammad, Umer; Khan, Sarah; Mahmood, Nadia
2015-01-01
Background: Ego defense mechanisms are unconscious psychological processes that help an individual to prevent anxiety when exposed to a stressful situation. These mechanisms are important in psychiatric practice to assess an individual’s personality dynamics, psychopathologies, and modes of coping with stressful situations, and hence, to design appropriate individualized treatment. Our study delineates the relationship of ego defense mechanisms with anxiety, depression, and academic performance of Pakistani medical students. Methods: This cross-sectional study was done at CMH Lahore Medical College and Fatima Memorial Hospital Medical and Dental College, both in Lahore, Pakistan, from December 1, 2014 to January 15, 2015. Convenience sampling was used and only students who agreed to take part in this study were included. The questionnaire consisted of three sections: 1) Demographics, documenting demographic data and academic scores on participants’ most recent exams; 2) Hospital Anxiety and Depression Scale (HADS); and 3) Defense Style Questionnaire-40 (DSQ-40). The data were analyzed with SPSS v. 20. Mean scores and frequencies were calculated for demographic variables and ego defense mechanisms. Bivariate correlations, one-way ANOVA, and multiple linear regression were used to identify associations between academic scores, demographics, ego defense mechanisms, anxiety, and depression. Results: A total of 409 medical students participated, of whom 286 (70%) were females and 123 (30%) were males. Mean percentage score on the most recent exams was 75.6% in medical students. Bivariate correlation revealed a direct association between mature and neurotic ego defense mechanisms and academic performance, and an indirect association between immature mechanisms and academic performance. One-way ANOVA showed that moderate levels of anxiety (P < .05) and low levels of depression (P < .05) were associated with higher academic performance. Conclusion: There was a significant association between academic performance and ego defense mechanisms, anxiety, and depression levels in our sample of Pakistani medical students. PMID:26543695
Sutton, Madeline Y.; Gray, Simone C.; Elmore, Kim; Gaul, Zaneta
2017-01-01
HIV infection disproportionately affects Blacks in the southern United States (U.S.), a region where legal policies that may unintentionally impede earlier HIV detection and treatment are prevalent. Historically Black Colleges and Universities (HBCUs) have historically facilitated social change in communities of color and have been underexplored as partners for HIV prevention. We describe geographic and social determinants of health (SDH) in the southern U.S. to inform potential HBCU-public health partnerships that might improve HIV health equity. We evaluated the relationship between county-level HIV prevalences (2013), HBCU geographic coordinates, and SDH variables in the southern counties with HBCUs. U.S. Census-derived SDH variables included race/ethnicity (i.e., Black, White, Hispanic), unemployment, female head of household, poverty, percent owner-occupied housing units, urbanicity, and primary care provider rates. Associations were assessed using bivariate and multivariable linear regression. Of 104 HBCUs in the contiguous U.S., 100 (96%) were located in 69 southern counties with average Black populations of 40% and an average HIV prevalence of 615. 5 per 100,000, over two times the national rate (295.1 per 100,000). In bivariable analyses, higher HIV rates in these counties were associated with higher percent Black population, unemployment, female head of household, poverty, fewer owner-occupied housing units, and greater urbanicity (p < 0.05). In multivariable analyses, counties with higher HIV rates had higher percentages of Blacks, greater urbanicity, fewer owner-occupied housing units, and more female heads of households (p < 0.05). The southern U.S. is disproportionately affected by HIV, and many HBCUs are located in affected southern counties. HBCUs may be important public health partners for helping to develop structural interventions that strengthen HIV policies in support of health equity in these southern, mostly urban counties. PMID:28107532
Sutton, Madeline Y; Gray, Simone C; Elmore, Kim; Gaul, Zaneta
2017-01-01
HIV infection disproportionately affects Blacks in the southern United States (U.S.), a region where legal policies that may unintentionally impede earlier HIV detection and treatment are prevalent. Historically Black Colleges and Universities (HBCUs) have historically facilitated social change in communities of color and have been underexplored as partners for HIV prevention. We describe geographic and social determinants of health (SDH) in the southern U.S. to inform potential HBCU-public health partnerships that might improve HIV health equity. We evaluated the relationship between county-level HIV prevalences (2013), HBCU geographic coordinates, and SDH variables in the southern counties with HBCUs. U.S. Census-derived SDH variables included race/ethnicity (i.e., Black, White, Hispanic), unemployment, female head of household, poverty, percent owner-occupied housing units, urbanicity, and primary care provider rates. Associations were assessed using bivariate and multivariable linear regression. Of 104 HBCUs in the contiguous U.S., 100 (96%) were located in 69 southern counties with average Black populations of 40% and an average HIV prevalence of 615. 5 per 100,000, over two times the national rate (295.1 per 100,000). In bivariable analyses, higher HIV rates in these counties were associated with higher percent Black population, unemployment, female head of household, poverty, fewer owner-occupied housing units, and greater urbanicity (p < 0.05). In multivariable analyses, counties with higher HIV rates had higher percentages of Blacks, greater urbanicity, fewer owner-occupied housing units, and more female heads of households (p < 0.05). The southern U.S. is disproportionately affected by HIV, and many HBCUs are located in affected southern counties. HBCUs may be important public health partners for helping to develop structural interventions that strengthen HIV policies in support of health equity in these southern, mostly urban counties.
Song, Yun-Mi; Lee, Kayoung
2018-05-02
The longitudinal associations between serum uric acid (UA) levels and metabolic syndrome (MetS) and its components, as well as the shared genetic and environmental correlations between these traits, were evaluated. In a total of 1803 participants (675 men and 1128 women; 695 monozygotic twin individuals, 159 dizygotic twin individuals, and 949 non-twin family members; 44.3 ± 12.8 years old) and 321 monozygotic twin pairs with data on UA levels and MetS components at baseline and follow-up, mixed linear model, conditional logistic regression, and bivariate variance component analysis were conducted. After 3.7 ± 1.4 years, the incident and persistent prevalence of MetS were 5.3% and 11.6%, respectively. UA was positively associated with the concurrent and future number of MetS criteria, blood pressure (BP), and triglyceride (TG) levels, whereas an inverse association was observed between UA and future high-density lipoprotein cholesterol (HDL-C) levels after adjusting for twin and household effects, demographics, health behaviors at baseline, and other confounders according to outcome variables. In the adjusted bivariate analysis, UA had genetic and environmental correlations with the concurrent and future number of MetS criteria, and had genetic correlations with concurrent BP and TG levels and future diastolic BP and HDL-C levels. In the adjusted co-twin control analysis, twins with a higher UA level were more likely to have concurrent MetS [odds ratio (95% confidence interval) 1.59 (1.00-2.53)], high blood glucose levels [1.84 (1.06-3.17)], future MetS [2.35 (1.19-4.64)], and high TG levels [1.52 (1.03-2.24)] than co-twins with a lower UA level. Genetic and environmental factors affect the concurrent and longitudinal associations between UA and MetS as well as some of its components.
Linear regression crash prediction models : issues and proposed solutions.
DOT National Transportation Integrated Search
2010-05-01
The paper develops a linear regression model approach that can be applied to : crash data to predict vehicle crashes. The proposed approach involves novice data aggregation : to satisfy linear regression assumptions; namely error structure normality ...
Comparison between Linear and Nonlinear Regression in a Laboratory Heat Transfer Experiment
ERIC Educational Resources Information Center
Gonçalves, Carine Messias; Schwaab, Marcio; Pinto, José Carlos
2013-01-01
In order to interpret laboratory experimental data, undergraduate students are used to perform linear regression through linearized versions of nonlinear models. However, the use of linearized models can lead to statistically biased parameter estimates. Even so, it is not an easy task to introduce nonlinear regression and show for the students…
The Application of the Cumulative Logistic Regression Model to Automated Essay Scoring
ERIC Educational Resources Information Center
Haberman, Shelby J.; Sinharay, Sandip
2010-01-01
Most automated essay scoring programs use a linear regression model to predict an essay score from several essay features. This article applied a cumulative logit model instead of the linear regression model to automated essay scoring. Comparison of the performances of the linear regression model and the cumulative logit model was performed on a…
Modeling continuous covariates with a "spike" at zero: Bivariate approaches.
Jenkner, Carolin; Lorenz, Eva; Becher, Heiko; Sauerbrei, Willi
2016-07-01
In epidemiology and clinical research, predictors often take value zero for a large amount of observations while the distribution of the remaining observations is continuous. These predictors are called variables with a spike at zero. Examples include smoking or alcohol consumption. Recently, an extension of the fractional polynomial (FP) procedure, a technique for modeling nonlinear relationships, was proposed to deal with such situations. To indicate whether or not a value is zero, a binary variable is added to the model. In a two stage procedure, called FP-spike, the necessity of the binary variable and/or the continuous FP function for the positive part are assessed for a suitable fit. In univariate analyses, the FP-spike procedure usually leads to functional relationships that are easy to interpret. This paper introduces four approaches for dealing with two variables with a spike at zero (SAZ). The methods depend on the bivariate distribution of zero and nonzero values. Bi-Sep is the simplest of the four bivariate approaches. It uses the univariate FP-spike procedure separately for the two SAZ variables. In Bi-D3, Bi-D1, and Bi-Sub, proportions of zeros in both variables are considered simultaneously in the binary indicators. Therefore, these strategies can account for correlated variables. The methods can be used for arbitrary distributions of the covariates. For illustration and comparison of results, data from a case-control study on laryngeal cancer, with smoking and alcohol intake as two SAZ variables, is considered. In addition, a possible extension to three or more SAZ variables is outlined. A combination of log-linear models for the analysis of the correlation in combination with the bivariate approaches is proposed. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
NASA Astrophysics Data System (ADS)
Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong; Ding, Yinghui
2014-07-01
The linear regression parameters between two time series can be different under different lengths of observation period. If we study the whole period by the sliding window of a short period, the change of the linear regression parameters is a process of dynamic transmission over time. We tackle fundamental research that presents a simple and efficient computational scheme: a linear regression patterns transmission algorithm, which transforms linear regression patterns into directed and weighted networks. The linear regression patterns (nodes) are defined by the combination of intervals of the linear regression parameters and the results of the significance testing under different sizes of the sliding window. The transmissions between adjacent patterns are defined as edges, and the weights of the edges are the frequency of the transmissions. The major patterns, the distance, and the medium in the process of the transmission can be captured. The statistical results of weighted out-degree and betweenness centrality are mapped on timelines, which shows the features of the distribution of the results. Many measurements in different areas that involve two related time series variables could take advantage of this algorithm to characterize the dynamic relationships between the time series from a new perspective.
Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong; Ding, Yinghui
2014-07-01
The linear regression parameters between two time series can be different under different lengths of observation period. If we study the whole period by the sliding window of a short period, the change of the linear regression parameters is a process of dynamic transmission over time. We tackle fundamental research that presents a simple and efficient computational scheme: a linear regression patterns transmission algorithm, which transforms linear regression patterns into directed and weighted networks. The linear regression patterns (nodes) are defined by the combination of intervals of the linear regression parameters and the results of the significance testing under different sizes of the sliding window. The transmissions between adjacent patterns are defined as edges, and the weights of the edges are the frequency of the transmissions. The major patterns, the distance, and the medium in the process of the transmission can be captured. The statistical results of weighted out-degree and betweenness centrality are mapped on timelines, which shows the features of the distribution of the results. Many measurements in different areas that involve two related time series variables could take advantage of this algorithm to characterize the dynamic relationships between the time series from a new perspective.
Turiho, Andrew Kampikaho; Muhwezi, Wilson Winston; Okello, Elialilia Sarikiaeli; Tumwesigye, Nazarius Mbona; Banura, Cecil; Katahoire, Anne Ruhweza
2015-01-01
The purpose of the study was to investigate the influence of human papillomavirus (HPV) vaccination on adolescent girls' knowledge of HPV and HPV vaccine, perception of sexual risk and intentions for sexual debut. This cross-sectional comparative study was conducted in Ibanda and Mbarara districts. Data was collected using a standardized self-administered questionnaire and analyzed using the Statistical Package for the Social Sciences computer software. Univariate, bivariate, and logistic regression analyses were conducted with significance level set at p < .05. Results showed that HPV vaccination was associated with being knowledgeable (Crude OR: 5.26, CI: 2.32-11.93; p = 0.000). Vaccination against HPV did not predict perception of sexual risk. Knowledge was low (only 87/385 or 22.6% of vaccinated girls were knowledgeable), but predicted perception of a high sexual risk (Adjusted OR: 3.12, CI: 1.37-3.63; p = 0.008). HPV vaccination, knowledge and perceived sexual risk did not predict sexual behaviour intentions. High parental communication was associated with adolescent attitudes that support postponement of sexual debut in both bivariate and multiple regression analyses. In conclusion, findings of this study suggest that HPV vaccination is not likely to encourage adolescent sexual activity. Influence of knowledge on sexual behaviour intentions was not definitively explained. Prospective cohort studies were proposed to address the emerging questions.
Falck, Ryan S; Wilcox, Sara; Best, John R; Chandler, Jessica L; Liu-Ambrose, Teresa
2017-01-01
Mobility and executive functions (EFs) decline with age, although associations between mobility and EFs are less clear. This study examined relationships between different mobility measures and EFs among rural older adults. This cross-sectional study recruited 56 older adults (60+ years) in rural South Carolina. Mobility was assessed via gait speed, timed up-and-go, chair stand, and as a composite physical performance score (PPS). EFs was assessed via Trail Making Test, semantic fluency, and phonemic fluency. Bivariate analyses were performed and regressions were calculated controlling for appropriate covariates, with PPS as the independent variable and each EF test as the dependent variable. Mean age was 74.22 years (SD = 8.02), 80.40% were female and 64.71% were white. Bivariate analysis revealed associations between gait speed and Trail Making Test (r = -.33; p = .03), between timed up-and-go and Trail Making Test (r = .34; p = .01), and between PPS and Trail Making Test (r = -.33; p = .03). The regression models indicated higher PPS was associated with better performance on Trail Making Test (β = -1.12; p < 0.01), phonemic fluency (β = 0.68; p = .01), and semantic fluency (β = 0.81; p = .02). In a rural setting, mobility is associated with multiple EF processes. Higher mobility and physical ability are desired for maintaining EFs capability.
Predictors for living at home after geriatric inpatient rehabilitation: A prospective cohort study.
Kool, Jan; Oesch, Peter; Bachmann, Stefan
2017-01-31
To evaluate patient characteristics predicting living at home after geriatric rehabilitation. Prospective cohort study. A total of 210 patients aged 65 years or older receiving inpatient rehabilitation. Candidate predictors evaluated during rehabilitation were: age, vulnerability (Vulnerable Elders Survey), multimorbidity (Cumulative Illness Rating Scale), cognition (Mini-Mental State Examination), depression (Hospital Anxiety and Depression Scale), living alone, previous independence in activities of daily living, fall risk, and mobility at discharge (Timed Up and Go test). Multiple imputation data-sets, bivariate and multiple regression were used to build a predictive model for living at home, which was evaluated at 3-month follow-up. A total of 210 patients (mean age 76.0 years, 46.2% women) were included in the study. Of these, 87.6% had been admitted to geriatric rehabilitation directly from acute hospital care. Follow-up was complete in 75.2% of patients. The strongest predictor for living at home was better mobility at discharge (Timed Up and Go test < 20 s), followed by lower multimorbidity, better cognition, and not living alone. In bivariate regression, living at home was also associated with age, fall risk, vulnerability, depression, and previous independence in activities of daily living. Mobility is the most important predictive factor for living at home after geriatric rehabilitation. Assessment and training of mobility are therefore key aspects in geriatric rehabilitation.
Ahonen, Emily Q; Nebot, Manel; Giménez, Emmanuel
2007-01-01
Poor mental health is a common problem in adolescence. Little information is available, however, about the factors influencing negative mood states in otherwise healthy adolescents. We aimed to describe the mood states and related factors in a sample of adolescents in the city of Barcelona (Spain). We administered a health survey to a sample of 2,727 students from public, subsidized, and private schools in Barcelona, aged approximately 14, 16, and 18 years old. To analyze the associations among moods and related factors, we used bivariate logistic regression, and fitted multivariate logistic regressions using the statistically significant variables from the bivariate analysis. To examine the possible group effects of the school on individual students, we employed multilevel analysis. The frequencies of negative mood states increased with age, with girls consistently reporting more frequent negative mood states than boys. The factors associated with negative mood states were problematic alcohol use, perceived mistreatment or abuse, antisocial behavior, intention to use or current use of illegal drugs (not including cannabis), lower perceived academic performance, and feeling isolated. Mood states are influenced by lifestyle and social factors, about which there is little local information. To plan and implement appropriate public health interventions, more complete information about the possible areas of influence is required. To complement the information obtained from studies such as the present study, longitudinal and qualitative studies would be desirable.
Datamining approaches for modeling tumor control probability.
Naqa, Issam El; Deasy, Joseph O; Mu, Yi; Huang, Ellen; Hope, Andrew J; Lindsay, Patricia E; Apte, Aditya; Alaly, James; Bradley, Jeffrey D
2010-11-01
Tumor control probability (TCP) to radiotherapy is determined by complex interactions between tumor biology, tumor microenvironment, radiation dosimetry, and patient-related variables. The complexity of these heterogeneous variable interactions constitutes a challenge for building predictive models for routine clinical practice. We describe a datamining framework that can unravel the higher order relationships among dosimetric dose-volume prognostic variables, interrogate various radiobiological processes, and generalize to unseen data before when applied prospectively. Several datamining approaches are discussed that include dose-volume metrics, equivalent uniform dose, mechanistic Poisson model, and model building methods using statistical regression and machine learning techniques. Institutional datasets of non-small cell lung cancer (NSCLC) patients are used to demonstrate these methods. The performance of the different methods was evaluated using bivariate Spearman rank correlations (rs). Over-fitting was controlled via resampling methods. Using a dataset of 56 patients with primary NCSLC tumors and 23 candidate variables, we estimated GTV volume and V75 to be the best model parameters for predicting TCP using statistical resampling and a logistic model. Using these variables, the support vector machine (SVM) kernel method provided superior performance for TCP prediction with an rs=0.68 on leave-one-out testing compared to logistic regression (rs=0.4), Poisson-based TCP (rs=0.33), and cell kill equivalent uniform dose model (rs=0.17). The prediction of treatment response can be improved by utilizing datamining approaches, which are able to unravel important non-linear complex interactions among model variables and have the capacity to predict on unseen data for prospective clinical applications.
Arrow, P
2013-09-01
Published reports suggest that children with enamel defects, especially where enamel is missing or breaking down, experience considerable discomfort and are generally more fearful of dental treatment. However, children's oral health-related quality of life in relation to enamel defects has not been reported. The aim of this study was to examine the association between oral health-related quality of life among children (COHQoL) with enamel defects of the first permanent molars and deciduous caries experience. Children attending pre-primary schools in metropolitan Perth, Western Australia, were recruited and classified for enamel defects using the modified Developmental Defects of Enamel index. Caries experience of deciduous molars and canines was also recorded. Parents completed a child oral health-related quality of life questionnaire. Data were analysed using Kruskal-Wallis, Spearman's rank correlation, chi-square, multiple linear regression and ordered logistic regression to test the factors for their influence on the COHQoL. From the 550 children assessed (mean age 7.2 years) 522 COHQoL questionnaires were returned. Mean COHQoL score was 8.9 (sd 8.8). Bivariate tests showed no association of COHQoL with enamel defect status of the first permanent molars. COHQoL was associated with dmft (mean dmft 1.96, sd 2.62). Higher caries experience children had poorer reported oral health-related quality of life. The presence of enamel defects in the first permanent molars did not affect the children's oral health-related quality of life.
Koorevaar, A M L; Hegeman, J M; Lamers, F; Dhondt, A D F; van der Mast, R C; Stek, M L; Comijs, H C
2017-12-01
This study examined the associations of personality characteristics with both subtypes and symptom dimensions of depression in older adults. Three hundred and seventy-eight depressed older adults participated in the Netherlands Study of Depression in Older Persons. Personality characteristics were assessed by the NEO-Five Factor Inventory. Subtypes and symptom dimensions of depression were determined using the Composite International Diagnostic Interview and the Inventory of Depressive Symptomatology (IDS). Multinomial logistic regression analyses were performed to examine the associations between personality and atypical, melancholic, and unspecified subtypes of major depression. Linear regression analyses examined the associations between personality and the IDS mood, somatic, and motivation symptom dimensions. The analyses were adjusted for confounders and additionally adjusted for depression severity. Neuroticism, Extraversion, Conscientiousness, and Agreeableness were associated with specified (atypical or melancholic) major depression compared with unspecified major depression in the bivariate analyses but lost their significance after adjustments for functional limitations and severity of depression. Neuroticism was positively associated with the IDS mood and motivation symptom dimensions, also in the adjusted models. Further, Extraversion and Agreeableness were negatively associated with the IDS mood symptom dimension, and Extraversion and Conscientiousness were negatively associated with the IDS motivation symptom dimension. None was associated with the IDS somatic symptom dimension. This study demonstrated the association of personality characteristics with mood and motivational symptoms of late-life depression. The lacking ability of personality to differentiate between melancholic and atypical depression seems to be largely explained by severity of depressive symptoms. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Career-Success Scale – A new instrument to assess young physicians' academic career steps
Buddeberg-Fischer, Barbara; Stamm, Martina; Buddeberg, Claus; Klaghofer, Richard
2008-01-01
Background Within the framework of a prospective cohort study of Swiss medical school graduates, a Career-Success Scale (CSS) was constructed in a sample of young physicians choosing different career paths in medicine. Furthermore the influence of personality factors, the participants' personal situation, and career related factors on their career success was investigated. Methods 406 residents were assessed in terms of career aspired to, and their career progress. The Career-Success Scale, consisting of 7 items, was developed and validated, addressing objective criteria of academic career advancement. The influence of gender and career aspiration was investigated by a two-factorial analysis of variance, the relationships between personality factors, personal situation, career related factors and the Career-Success Scale by a multivariate linear regression analysis. Results The unidimensional Career-Success Scale has an internal consistency of 0.76. It is significantly correlated at the bivariate level with gender, instrumentality, and all career related factors, particularly with academic career and received mentoring. In multiple regression, only gender, academic career, surgery as chosen specialty, and received mentoring are significant predictors. The highest values were observed in participants aspiring to an academic career, followed by those pursuing a hospital career and those wanting to run a private practice. Independent of the career aspired to, female residents have lower scores than their male colleagues. Conclusion The Career-Success Scale proved to be a short, reliable and valid instrument to measure career achievements. As mentoring is an independent predictor of career success, mentoring programs could be an important instrument to specifically enhance careers of female physicians in academia. PMID:18518972
Career-success scale - a new instrument to assess young physicians' academic career steps.
Buddeberg-Fischer, Barbara; Stamm, Martina; Buddeberg, Claus; Klaghofer, Richard
2008-06-02
Within the framework of a prospective cohort study of Swiss medical school graduates, a Career-Success Scale (CSS) was constructed in a sample of young physicians choosing different career paths in medicine. Furthermore the influence of personality factors, the participants' personal situation, and career related factors on their career success was investigated. 406 residents were assessed in terms of career aspired to, and their career progress. The Career-Success Scale, consisting of 7 items, was developed and validated, addressing objective criteria of academic career advancement. The influence of gender and career aspiration was investigated by a two-factorial analysis of variance, the relationships between personality factors, personal situation, career related factors and the Career-Success Scale by a multivariate linear regression analysis. The unidimensional Career-Success Scale has an internal consistency of 0.76. It is significantly correlated at the bivariate level with gender, instrumentality, and all career related factors, particularly with academic career and received mentoring. In multiple regression, only gender, academic career, surgery as chosen specialty, and received mentoring are significant predictors. The highest values were observed in participants aspiring to an academic career, followed by those pursuing a hospital career and those wanting to run a private practice. Independent of the career aspired to, female residents have lower scores than their male colleagues. The Career-Success Scale proved to be a short, reliable and valid instrument to measure career achievements. As mentoring is an independent predictor of career success, mentoring programs could be an important instrument to specifically enhance careers of female physicians in academia.
Factors Associated with Intern Fatigue
Vidyarthi, Arpana R.; Baron, Robert B.; Katz, Patricia P.
2008-01-01
ABSTRACT BACKGROUND Prior data suggest that fatigue adversely affects patient safety and resident well-being. ACGME duty hour limitations were intended, in part, to reduce resident fatigue, but the factors that affect intern fatigue are unknown. OBJECTIVE To identify factors associated with intern fatigue following implementation of duty hour limitations. DESIGN Cross-sectional confidential survey of validated questions related to fatigue, sleep, and stress, as well as author-developed teamwork questions. SUBJECTS Interns in cognitive specialties at the University of California, San Francisco. MEASUREMENTS Univariate statistics characterized the distribution of responses. Pearson correlations elucidated bivariate relationships between fatigue and other variables. Multivariate linear regression models identified factors independently associated with fatigue, sleep, and stress. RESULTS Of 111 eligible interns, 66 responded (59%). In a regression analysis including gender, hours worked in the previous week, sleep quality, perceived stress, and teamwork, only poorer quality of sleep and greater perceived stress were significantly associated with fatigue (p < 0.001 and p = 0.02, respectively). To identify factors that may affect sleep, specifically duty hours and stress, a secondary model was constructed. Only greater perceived stress was significantly associated with diminished sleep quality (p = 0.04), and only poorer teamwork was significantly associated with perceived stress (p < 0.001). Working >80 h was not significantly associated with perceived stress, quality of sleep, or fatigue. CONCLUSIONS Simply decreasing the number of duty hours may be insufficient to reduce intern fatigue. Residency programs may need to incorporate programmatic changes to reduce stress, improve sleep quality, and foster teamwork in order to decrease intern fatigue and its deleterious consequences. PMID:18807096
Korany, Mohamed A; Gazy, Azza A; Khamis, Essam F; Ragab, Marwa A A; Kamal, Miranda F
2018-06-01
This study outlines two robust regression approaches, namely least median of squares (LMS) and iteratively re-weighted least squares (IRLS) to investigate their application in instrument analysis of nutraceuticals (that is, fluorescence quenching of merbromin reagent upon lipoic acid addition). These robust regression methods were used to calculate calibration data from the fluorescence quenching reaction (∆F and F-ratio) under ideal or non-ideal linearity conditions. For each condition, data were treated using three regression fittings: Ordinary Least Squares (OLS), LMS and IRLS. Assessment of linearity, limits of detection (LOD) and quantitation (LOQ), accuracy and precision were carefully studied for each condition. LMS and IRLS regression line fittings showed significant improvement in correlation coefficients and all regression parameters for both methods and both conditions. In the ideal linearity condition, the intercept and slope changed insignificantly, but a dramatic change was observed for the non-ideal condition and linearity intercept. Under both linearity conditions, LOD and LOQ values after the robust regression line fitting of data were lower than those obtained before data treatment. The results obtained after statistical treatment indicated that the linearity ranges for drug determination could be expanded to lower limits of quantitation by enhancing the regression equation parameters after data treatment. Analysis results for lipoic acid in capsules, using both fluorimetric methods, treated by parametric OLS and after treatment by robust LMS and IRLS were compared for both linearity conditions. Copyright © 2018 John Wiley & Sons, Ltd.
Sexual and Nonsexual Homicide in Scotland: Is There a Difference?
Skott, Sara; Beauregard, Eric; Darjee, Rajan
2018-05-01
While a number of previous studies have compared sexual homicides to nonlethal sexual offenses, there have been few studies comparing sexual and nonsexual homicides. This study examines whether sexual homicide offenders differ from nonsexual homicide offenders in Scotland regarding characteristics of the offender, the victim, and the homicide incident. Unlike previous studies, only homicides committed by males against females were examined. Data from a national police database were used to compare 89 male sexual homicide offenders who killed adult females with 306 male nonsexual homicide offenders who had also killed adult females using bivariate and multivariate (logistic regression) analyses. The findings revealed not only some similarities between the two groups, particularly regarding some victim variables, but also significant bivariate and multivariate differences. Sexual homicides appeared to be associated with indicators of instrumentality and sexual deviance. We conclude that sexual homicide offenders might be considered a distinct group of homicide offenders, more similar to sexual offenders than to other homicide offenders.
Kapadia, F; Siconolfi, D E; Barton, S; Olivieri, B; Lombardo, L; Halkitis, P N
2013-06-01
Associations between social support network characteristics and sexual risk among racially/ethnically diverse young men who have sex with men (YMSM) were examined using egocentric network data from a prospective cohort study of YMSM (n = 501) recruited in New York City. Bivariate and multivariable logistic regression analyses examined associations between social support network characteristics and sexual risk taking behaviors in Black, Hispanic/Latino, and White YMSM. Bivariate analyses indicated key differences in network size, composition, communication frequency and average relationship duration by race/ethnicity. In multivariable analyses, controlling for individual level sociodemographic, psychosocial and relationship factors, having a sexual partner in one's social support network was associated with unprotected sexual behavior for both Hispanic/Latino (AOR = 3.90) and White YMSM (AOR = 4.93). Further examination of key network characteristics across racial/ethnic groups are warranted in order to better understand the extant mechanisms for provision of HIV prevention programming to racially/ethnically diverse YMSM at risk for HIV.
Costa, Andréa A; Serra-Negra, Júnia M; Bendo, Cristiane B; Pordeus, Isabela A; Paiva, Saul M
2016-01-01
To investigate the impact of wearing a fixed orthodontic appliance on oral health-related quality of life (OHRQoL) among adolescents. A case-control study (1 ∶ 2) was carried out with a population-based randomized sample of 327 adolescents aged 11 to 14 years enrolled at public and private schools in the City of Brumadinho, southeast of Brazil. The case group (n = 109) was made up of adolescents with a high negative impact on OHRQoL, and the control group (n = 218) was made up of adolescents with a low negative impact. The outcome variable was the impact on OHRQoL measured by the Brazilian version of the Child Perceptions Questionnaire (CPQ 11-14) - Impact Short Form (ISF:16). The main independent variable was wearing fixed orthodontic appliances. Malocclusion and the type of school were identified as possible confounding variables. Bivariate and multiple conditional logistic regressions were employed in the statistical analysis. A multiple conditional logistic regression model demonstrated that adolescents wearing fixed orthodontic appliances had a 4.88-fold greater chance of presenting high negative impact on OHRQoL (95% CI: 2.93-8.13; P < .001) than those who did not wear fixed orthodontic appliances. A bivariate conditional logistic regression demonstrated that malocclusion was significantly associated with OHRQoL (P = .017), whereas no statistically significant association was found between the type of school and OHRQoL (P = .108). Adolescents who wore fixed orthodontic appliances had a greater chance of reporting a negative impact on OHRQoL than those who did not wear such appliances.
Jin, Meihua; Yang, Zhongrong; Dong, Zhengquan; Han, Jiankang
2013-12-01
There is growing evidence that men who have sex with men (MSM) are currently a group at high risk of HIV infection in China. Our study aims to know the factors affecting consistent condom use among MSM recruited through the internet in Huzhou city. An anonymous cross-sectional study was conducted by recruiting 410 MSM living in Huzhou city via the Internet. The socio-demographic profiles (age, education level, employment status, etc.) and sexual risk behaviors of the respondents were investigated. Bivariate logistic regression analyses were performed to compare the differences between consistent condom users and inconsistent condom users. Variables with significant bivariate between groups' differences were used as candidate variables in a stepwise multivariate logistic regression model. All statistical analyses were performed using SPSS for Windows 17.0, and a p value < 0.05 was considered to be statistically significant. According to their condom use, sixty-eight respondents were classified into two groups. One is consistent condom users, and the other is inconsistent condom users. Multivariate logistic regression showed that respondents who had a comprehensive knowledge of HIV (OR = 4.08, 95% CI: 1.85-8.99), who had sex with male sex workers (OR = 15.30, 95% CI: 5.89-39.75) and who had not drunk alcohol before sex (OR = 3.10, 95% CI: 1.38-6.95) were more likely to be consistent condom users. Consistent condom use among MSM was associated with comprehensive knowledge of HIV and a lack of alcohol use before sexual contact. As a result, reducing alcohol consumption and enhancing education regarding the risks of HIV among sexually active MSM would be effective in preventing of HIV transmission.
Trends and Correlation Estimation in Climate Sciences: Effects of Timescale Errors
NASA Astrophysics Data System (ADS)
Mudelsee, M.; Bermejo, M. A.; Bickert, T.; Chirila, D.; Fohlmeister, J.; Köhler, P.; Lohmann, G.; Olafsdottir, K.; Scholz, D.
2012-12-01
Trend describes time-dependence in the first moment of a stochastic process, and correlation measures the linear relation between two random variables. Accurately estimating the trend and correlation, including uncertainties, from climate time series data in the uni- and bivariate domain, respectively, allows first-order insights into the geophysical process that generated the data. Timescale errors, ubiquitious in paleoclimatology, where archives are sampled for proxy measurements and dated, poses a problem to the estimation. Statistical science and the various applied research fields, including geophysics, have almost completely ignored this problem due to its theoretical almost-intractability. However, computational adaptations or replacements of traditional error formulas have become technically feasible. This contribution gives a short overview of such an adaptation package, bootstrap resampling combined with parametric timescale simulation. We study linear regression, parametric change-point models and nonparametric smoothing for trend estimation. We introduce pairwise-moving block bootstrap resampling for correlation estimation. Both methods share robustness against autocorrelation and non-Gaussian distributional shape. We shortly touch computing-intensive calibration of bootstrap confidence intervals and consider options to parallelize the related computer code. Following examples serve not only to illustrate the methods but tell own climate stories: (1) the search for climate drivers of the Agulhas Current on recent timescales, (2) the comparison of three stalagmite-based proxy series of regional, western German climate over the later part of the Holocene, and (3) trends and transitions in benthic oxygen isotope time series from the Cenozoic. Financial support by Deutsche Forschungsgemeinschaft (FOR 668, FOR 1070, MU 1595/4-1) and the European Commission (MC ITN 238512, MC ITN 289447) is acknowledged.
Han, Dong-Hun; Kim, Mi-Sun; Shin, Hye-Sun; Park, Kyung Pyo; Kim, Hyun-Duck
2013-06-01
Nitric oxide (NO) is known to play an important role in many biologic systems, although the relationship between NO metabolites and periodontitis remains controversial. Moreover, little evidence of an association between salivary NO (S-NO) and periodontitis in the general population has been reported. This study aims to investigate the relationship between S-NO and periodontitis in an elderly Korean population. A cross-sectional study was conducted using participants and salivary samples from Sunchang Elderly Cohort Study. The total number of final participants was 242 (91 males and 151 females; 48 to 93 years old). Periodontitis was determined by a clinical attachment loss of >6 mm at six probe points on 12 index teeth. NO was measured in unstimulated saliva via the Griess reaction. Sociodemographic status, general/oral health, and health-related behaviors were investigated as confounders. Bivariate analysis and multivariable linear regression analyses including confounders were applied. After controlling for age, sex, education, salivary flow rate, number of teeth, smoking status, physical activity, hypertension, and diabetes, three metabolites of S-NO (total NO, nitrite, and nitrate) were independently associated with the percentage of probe points exhibiting periodontitis. Of these linear associations, total NO was found to have the strongest correlation with periodontitis (partial r = 0.181, P = 0.009). These associations were most pronounced in females (except for nitrate), non-smokers, those without hypertension, and those without diabetes. Our data suggest that high concentrations of S-NO are associated with severe periodontitis. Thus, S-NO may serve as a potential biologic marker for detecting and monitoring periodontitis.
Jenkins, Kristi Rahrig
2014-08-01
The present study uses a focused approach to compare self-reported versus administratively recorded measures of absences related to health or illness. To date, the few studies that focus on this topic produced mixed results. To help shed light on this issue, the present research has 2 related objectives: (1) examine how highly correlated self-reported and administratively recorded measures of absences related to health or illness might be, and (2) how each measure predicts various aspects of health. Using data from the 2012 StayWell® Health Management health risk appraisal (HRA) and 1 year (2011) of administratively recorded timekeeping data, bivariate analyses for continuous variables and generalized linear modeling for variables with greater than 2 response categories were used. For the multivariate analyses, linear regression models controlling for sex, age, race, income, job status, and campus location were calculated for the continuous outcomes (ie, self-rated health and chronic conditions). Results indicate that self-reported and administratively recorded absences related to health or illness were moderately correlated (correlation coefficient of 0.47). In addition, each measure functioned similarly (in direction and magnitude) to predict health outcomes. Both greater self-reported and recorded illness-related absenteeism was associated with poorer self-rated health and greater numbers of chronic conditions. These results suggest that self-rated illness-related absenteeism may be a reasonable way to assess various program outcomes meaningful to employers, particularly if administratively recorded measures are unavailable or too time consuming or expensive to analyze.
Do 360-degree feedback survey results relate to patient satisfaction measures?
Hageman, Michiel G J S; Ring, David C; Gregory, Paul J; Rubash, Harry E; Harmon, Larry
2015-05-01
There is evidence that feedback from 360-degree surveys-combined with coaching-can improve physician team performance and quality of patient care. The Physicians Universal Leadership-Teamwork Skills Education (PULSE) 360 is one such survey tool that is used to assess work colleagues' and coworkers' perceptions of a physician's leadership, teamwork, and clinical practice style. The Clinician & Group-Consumer Assessment of Healthcare Providers and System (CG-CAHPS), developed by the US Department of Health and Human Services to serve as the benchmark for quality health care, is a survey tool for patients to provide feedback that is based on their recent experiences with staff and clinicians and soon will be tied to Medicare-based compensation of participating physicians. Prior research has indicated that patients and coworkers often agree in their assessment of physicians' behavioral patterns. The goal of the current study was to determine whether 360-degree, also called multisource, feedback provided by coworkers could predict patient satisfaction/experience ratings. A significant relationship between these two forms of feedback could enable physicians to take a more proactive approach to reinforce their strengths and identify any improvement opportunities in their patient interactions by reviewing feedback from team members. An automated 360-degree software process may be a faster, simpler, and less resource-intensive approach than telephoning and interviewing patients for survey responses, and it potentially could facilitate a more rapid credentialing or quality improvement process leading to greater fiscal and professional development gains for physicians. Our primary research question was to determine if PULSE 360 coworkers' ratings correlate with CG-CAHPS patients' ratings of overall satisfaction, recommendation of the physician, surgeon respect, and clarity of the surgeon's explanation. Our secondary research questions were to determine whether CG-CAHPS scores correlate with additional composite scores from the Quality PULSE 360 (eg, insight impact score, focus concerns score, leadership-teamwork index score, etc). We retrospectively analyzed existing quality improvement data from CG-CAHPS patient surveys as well as from a department quality improvement initiative using 360-degree survey feedback questionnaires (Quality PULSE 360 with coworkers). Bivariate analyses were conducted to identify significant relationships for inclusion of research variables in multivariate linear analyses (eg, stepwise regression to determine the best fitting predictive model for CG-CAHPS ratings). In all higher order analyses, CG-CAHPS ratings were treated as the dependent variables, whereas PULSE 360 scores served as independent variables. This approach led to the identification of the most predictive linear model for each CG-CAHPS' performance rating (eg, [1] overall satisfaction; [2] recommendation of the physician; [3] surgeon respect; and [4] clarity of the surgeon's explanation) regressed on all PULSE scores with which there was a significant bivariate relationship. Backward stepwise regression was then used to remove unnecessary predictors from the linear model based on changes in the variance explained by the model with or without inclusion of the predictor. The Quality PULSE 360 insight impact score correlated with patient satisfaction (0.50, p = 0.01), patient recommendation (0.58, p = 0.002), patient rating of surgeon respect (0.74, p < 0.001), and patient impression of clarity of the physician explanation (0.69, p < 0.001). Additionally, leadership-teamwork index also correlated with patient rating of surgeon respect (0.46, p = 0.019) and patient impression of clarity of the surgeon's explanation (0.39, p = 0.05). Multivariate analyses supported retention of insight impact as a predictor of patient overall satisfaction, patient recommendation of the surgeon, and patient rating of surgeon respect. Both insight impact and leadership-teamwork index were retained as predictors of patient impression of explanation. Several other PULSE 360 variables were correlated with CG-CAHPS ratings, but none were retained in the linear models post stepwise regression. The relationship between Quality PULSE 360 feedback scores and measures of patient satisfaction reaffirm that feedback from work team members may provide helpful information into how patients may be perceiving their physicians' behavior and vice versa. Furthermore, the findings provide tentative support for the use of team-based feedback to improve the quality of relationships with both coworkers and patients. The 360-degree survey process may offer an effective tool for physicians to obtain feedback about behavior that could directly impact practice reimbursement and reputation or potentially be used for bonuses to incentivize better team professionalism and patient satisfaction, ie, "pay-for-professionalism." Further research is needed to expand on this line of inquiry, determine which interventions can improve 360-degree and patient satisfaction scores, and explain the shared variance in physician performance that is captured in the perceptions of patients and coworkers.
1974-01-01
REGRESSION MODEL - THE UNCONSTRAINED, LINEAR EQUALITY AND INEQUALITY CONSTRAINED APPROACHES January 1974 Nelson Delfino d’Avila Mascarenha;? Image...Report 520 DIGITAL IMAGE RESTORATION UNDER A REGRESSION MODEL THE UNCONSTRAINED, LINEAR EQUALITY AND INEQUALITY CONSTRAINED APPROACHES January...a two- dimensional form adequately describes the linear model . A dis- cretization is performed by using quadrature methods. By trans
Element enrichment factor calculation using grain-size distribution and functional data regression.
Sierra, C; Ordóñez, C; Saavedra, A; Gallego, J R
2015-01-01
In environmental geochemistry studies it is common practice to normalize element concentrations in order to remove the effect of grain size. Linear regression with respect to a particular grain size or conservative element is a widely used method of normalization. In this paper, the utility of functional linear regression, in which the grain-size curve is the independent variable and the concentration of pollutant the dependent variable, is analyzed and applied to detrital sediment. After implementing functional linear regression and classical linear regression models to normalize and calculate enrichment factors, we concluded that the former regression technique has some advantages over the latter. First, functional linear regression directly considers the grain-size distribution of the samples as the explanatory variable. Second, as the regression coefficients are not constant values but functions depending on the grain size, it is easier to comprehend the relationship between grain size and pollutant concentration. Third, regularization can be introduced into the model in order to establish equilibrium between reliability of the data and smoothness of the solutions. Copyright © 2014 Elsevier Ltd. All rights reserved.
Who Will Win?: Predicting the Presidential Election Using Linear Regression
ERIC Educational Resources Information Center
Lamb, John H.
2007-01-01
This article outlines a linear regression activity that engages learners, uses technology, and fosters cooperation. Students generated least-squares linear regression equations using TI-83 Plus[TM] graphing calculators, Microsoft[C] Excel, and paper-and-pencil calculations using derived normal equations to predict the 2004 presidential election.…
The microcomputer scientific software series 2: general linear model--regression.
Harold M. Rauscher
1983-01-01
The general linear model regression (GLMR) program provides the microcomputer user with a sophisticated regression analysis capability. The output provides a regression ANOVA table, estimators of the regression model coefficients, their confidence intervals, confidence intervals around the predicted Y-values, residuals for plotting, a check for multicollinearity, a...
Wang, D Z; Wang, C; Shen, C F; Zhang, Y; Zhang, H; Song, G D; Xue, X D; Xu, Z L; Zhang, S; Jiang, G H
2017-05-10
We described the time trend of acute myocardial infarction (AMI) from 1999 to 2013 in Tianjin incidence rate with Cochran-Armitage trend (CAT) test and linear regression analysis, and the results were compared. Based on actual population, CAT test had much stronger statistical power than linear regression analysis for both overall incidence trend and age specific incidence trend (Cochran-Armitage trend P value
Yang, Ruiqi; Wang, Fei; Zhang, Jialing; Zhu, Chonglei; Fan, Limei
2015-05-19
To establish the reference values of thalamus, caudate nucleus and lenticular nucleus diameters through fetal thalamic transverse section. A total of 265 fetuses at our hospital were randomly selected from November 2012 to August 2014. And the transverse and length diameters of thalamus, caudate nucleus and lenticular nucleus were measured. SPSS 19.0 statistical software was used to calculate the regression curve of fetal diameter changes and gestational weeks of pregnancy. P < 0.05 was considered as having statistical significance. The linear regression equation of fetal thalamic length diameter and gestational week was: Y = 0.051X+0.201, R = 0.876, linear regression equation of thalamic transverse diameter and fetal gestational week was: Y = 0.031X+0.229, R = 0.817, linear regression equation of fetal head of caudate nucleus length diameter and gestational age was: Y = 0.033X+0.101, R = 0.722, linear regression equation of fetal head of caudate nucleus transverse diameter and gestational week was: R = 0.025 - 0.046, R = 0.711, linear regression equation of fetal lentiform nucleus length diameter and gestational week was: Y = 0.046+0.229, R = 0.765, linear regression equation of fetal lentiform nucleus diameter and gestational week was: Y = 0.025 - 0.05, R = 0.772. Ultrasonic measurement of diameter of fetal thalamus caudate nucleus, and lenticular nucleus through thalamic transverse section is simple and convenient. And measurements increase with fetal gestational weeks and there is linear regression relationship between them.
Local Linear Regression for Data with AR Errors.
Li, Runze; Li, Yan
2009-07-01
In many statistical applications, data are collected over time, and they are likely correlated. In this paper, we investigate how to incorporate the correlation information into the local linear regression. Under the assumption that the error process is an auto-regressive process, a new estimation procedure is proposed for the nonparametric regression by using local linear regression method and the profile least squares techniques. We further propose the SCAD penalized profile least squares method to determine the order of auto-regressive process. Extensive Monte Carlo simulation studies are conducted to examine the finite sample performance of the proposed procedure, and to compare the performance of the proposed procedures with the existing one. From our empirical studies, the newly proposed procedures can dramatically improve the accuracy of naive local linear regression with working-independent error structure. We illustrate the proposed methodology by an analysis of real data set.
Orthogonal Regression: A Teaching Perspective
ERIC Educational Resources Information Center
Carr, James R.
2012-01-01
A well-known approach to linear least squares regression is that which involves minimizing the sum of squared orthogonal projections of data points onto the best fit line. This form of regression is known as orthogonal regression, and the linear model that it yields is known as the major axis. A similar method, reduced major axis regression, is…
Practical Session: Simple Linear Regression
NASA Astrophysics Data System (ADS)
Clausel, M.; Grégoire, G.
2014-12-01
Two exercises are proposed to illustrate the simple linear regression. The first one is based on the famous Galton's data set on heredity. We use the lm R command and get coefficients estimates, standard error of the error, R2, residuals …In the second example, devoted to data related to the vapor tension of mercury, we fit a simple linear regression, predict values, and anticipate on multiple linear regression. This pratical session is an excerpt from practical exercises proposed by A. Dalalyan at EPNC (see Exercises 1 and 2 of http://certis.enpc.fr/~dalalyan/Download/TP_ENPC_4.pdf).
Using bivariate signal analysis to characterize the epileptic focus: the benefit of surrogates.
Andrzejak, R G; Chicharro, D; Lehnertz, K; Mormann, F
2011-04-01
The disease epilepsy is related to hypersynchronous activity of networks of neurons. While acute epileptic seizures are the most extreme manifestation of this hypersynchronous activity, an elevated level of interdependence of neuronal dynamics is thought to persist also during the seizure-free interval. In multichannel recordings from brain areas involved in the epileptic process, this interdependence can be reflected in an increased linear cross correlation but also in signal properties of higher order. Bivariate time series analysis comprises a variety of approaches, each with different degrees of sensitivity and specificity for interdependencies reflected in lower- or higher-order properties of pairs of simultaneously recorded signals. Here we investigate which approach is best suited to detect putatively elevated interdependence levels in signals recorded from brain areas involved in the epileptic process. For this purpose, we use the linear cross correlation that is sensitive to lower-order signatures of interdependence, a nonlinear interdependence measure that integrates both lower- and higher-order properties, and a surrogate-corrected nonlinear interdependence measure that aims to specifically characterize higher-order properties. We analyze intracranial electroencephalographic recordings of the seizure-free interval from 29 patients with an epileptic focus located in the medial temporal lobe. Our results show that all three approaches detect higher levels of interdependence for signals recorded from the brain hemisphere containing the epileptic focus as compared to signals recorded from the opposite hemisphere. For the linear cross correlation, however, these differences are not significant. For the nonlinear interdependence measure, results are significant but only of moderate accuracy with regard to the discriminative power for the focal and nonfocal hemispheres. The highest significance and accuracy is obtained for the surrogate-corrected nonlinear interdependence measure.
Using bivariate signal analysis to characterize the epileptic focus: The benefit of surrogates
NASA Astrophysics Data System (ADS)
Andrzejak, R. G.; Chicharro, D.; Lehnertz, K.; Mormann, F.
2011-04-01
The disease epilepsy is related to hypersynchronous activity of networks of neurons. While acute epileptic seizures are the most extreme manifestation of this hypersynchronous activity, an elevated level of interdependence of neuronal dynamics is thought to persist also during the seizure-free interval. In multichannel recordings from brain areas involved in the epileptic process, this interdependence can be reflected in an increased linear cross correlation but also in signal properties of higher order. Bivariate time series analysis comprises a variety of approaches, each with different degrees of sensitivity and specificity for interdependencies reflected in lower- or higher-order properties of pairs of simultaneously recorded signals. Here we investigate which approach is best suited to detect putatively elevated interdependence levels in signals recorded from brain areas involved in the epileptic process. For this purpose, we use the linear cross correlation that is sensitive to lower-order signatures of interdependence, a nonlinear interdependence measure that integrates both lower- and higher-order properties, and a surrogate-corrected nonlinear interdependence measure that aims to specifically characterize higher-order properties. We analyze intracranial electroencephalographic recordings of the seizure-free interval from 29 patients with an epileptic focus located in the medial temporal lobe. Our results show that all three approaches detect higher levels of interdependence for signals recorded from the brain hemisphere containing the epileptic focus as compared to signals recorded from the opposite hemisphere. For the linear cross correlation, however, these differences are not significant. For the nonlinear interdependence measure, results are significant but only of moderate accuracy with regard to the discriminative power for the focal and nonfocal hemispheres. The highest significance and accuracy is obtained for the surrogate-corrected nonlinear interdependence measure.
Neuropsychologic assessment of a population-based sample of Gulf War veterans.
Wallin, Mitchell T; Wilken, Jeffrey; Alfaro, Mercedes H; Rogers, Catherine; Mahan, Clare; Chapman, Julie C; Fratto, Timothy; Sullivan, Cynthia; Kang, Han; Kane, Robert
2009-09-01
The objective of this project was to compare neuropsychologic performance and quality of life in a population-based sample of deployed Gulf War (GW) veterans with and without multisymptom complaints. The study participants were obtained from the 30,000 member population-based National Health Survey of GW-era veterans conducted in 1995. Cases (N=25) were deployed to the year 1990 and 1991 GW and met Center for Disease Control and Prevention criteria for multisymptom GW illness (GWI). Controls (N=16) were deployed to the 1990 and 1991 GW but did not meet Center for Disease Control and Prevention criteria for GWI. There were no significant differences in composite scores on the traditional and computerized neuropsychologic battery (automated neuropsychologic assessment metrics) between GW cases and controls using bivariate techniques. Multiple linear regression analyses controlling for demographic and clinical variables revealed composite automated neuropsychologic assessment metrics scores were associated with age (b=-7.8; P=0.084), and education (b=22.9; P=0.0012), but not GW case or control status (b=-63.9; P=0.22). Compared with controls, GW cases had significantly more impairment on the Personality Assessment Inventory and the short form-36. Compared with GW controls, GW cases meeting criteria for GWI had preserved cognition function but had significant psychiatric symptoms and lower quality of life.
Gagnon, Dany H; Roy, Audrey; Gabison, Sharon; Duclos, Cyril; Verrier, Molly C; Nadeau, Sylvie
2016-01-01
Objectives. To quantify the association between performance-based manual wheelchair propulsion tests (20 m propulsion test, slalom test, and 6 min propulsion test), trunk and upper extremity (U/E) strength, and seated reaching capability and to establish which ones of these variables best predict performance at these tests. Methods. 15 individuals with a spinal cord injury (SCI) performed the three wheelchair propulsion tests prior to discharge from inpatient SCI rehabilitation. Trunk and U/E strength and seated reaching capability with unilateral hand support were also measured. Bivariate correlation and multiple linear regression analyses allowed determining the best determinants and predictors, respectively. Results. The performance at the three tests was moderately or strongly correlated with anterior and lateral flexion trunk strength, anterior seated reaching distance, and the shoulder, elbow, and handgrip strength measures. Shoulder adductor strength-weakest side explained 53% of the variance on the 20-meter propulsion test-maximum velocity. Shoulder adductor strength-strongest side and forward seated reaching distance explained 71% of the variance on the slalom test. Handgrip strength explained 52% of the variance on the 6-minute propulsion test. Conclusion. Performance at the manual wheelchair propulsion tests is explained by a combination of factors that should be considered in rehabilitation.
Food Insecurity and Rural Adolescent Personal Health, Home, and Academic Environments.
Shanafelt, Amy; Hearst, Mary O; Wang, Qi; Nanney, Marilyn S
2016-06-01
Food-insecure (FIS) adolescents struggle in school and with health and mental health more often than food-secure (FS) adolescents. Rural communities experience important disparities in health, but little is known about rural FIS adolescents. This study aims to describe select characteristics of rural adolescents by food-security status. Baseline analysis using data from a randomized trial to increase school breakfast participation (SBP) in rural Minnesota high schools. Students completed a survey regarding food security, characteristics, and home and school environments. Schools provided academic data and staff measured height and weight. Food security was dichotomized as FS vs FIS. Bivariate analysis, multivariate linear/logistic regression, and testing for interaction of food security and sex were performed. Food-insecure adolescents reported poorer health, less exercise, had lower grades, and higher SBP (p < .01). Food-insecure adolescents reported marginally fewer barriers (p = .06) and more benefits of breakfast (p = .05). All associations except reported benefits remained significant after adjustment. Interactions were identified with girls' grade point average and with boys' caloric and added sugar intake. Negative associations among food insecurity and positive youth development are identified in our sample. Policy and environmental strategies should address the complexities of these associations, including exploration of the role of school meals. © 2016, American School Health Association.
Paiva, Michelle Helena Pereira de; Pegorari, Maycon Sousa; Nascimento, Janaína Santos; Santos, Álvaro da Silva
2016-11-01
This study sought to establish the socioeconomic and health factors associated with quality of life among the elderly in the community. An analytical study with a cross-sectional and quantitative approach was conducted in 2012 and 2013 with 3430 senior citizens in 24 municipalities in the Southern Triangle Macro-region of the State of Minas Gerais in Brazil. A structured questionnaire was used for socioeconomic and health variables, as well as the Katz scale, the World Health Organization Quality of Life-Bref (WHOQOL-BREF) and the World Health Organization Quality of Life Assessment for Older Adults (WHOQOL-OLD). Descriptive, bivariate statistical analysis was performed and a multiple linear regression model (p < 0.05) was created. Lower quality of life (QoL) scores were found in the environment and autonomy domains associated with advanced age, lack of schooling and income, a negative perception of health and functional disability. The salient key factor was negative health perception. The conclusion drawn was that socioeconomic and health factors were associated with the quality of life of the elderly, highlighting the lowest scores in the environmental domain and from the aspect of autonomy, a key influencing factor being negative health perception.
Hendrick, C. Emily; Cohen, Alison K.; Deardorff, Julianna
2015-01-01
BACKGROUND Lifetime educational attainment is an important predictor of health and well-being for women in the United States. In the current study, we examine the roles of socio-cultural factors in youth and an understudied biological life event, pubertal timing, in predicting women’s lifetime educational attainment. METHODS Using data from the National Longitudinal Survey of Youth 1997 cohort (N = 3889), we conducted sequential multivariate linear regression analyses to investigate the influences of macro-level and family-level socio-cultural contextual factors in youth (region of country, urbanicity, race/ethnicity, year of birth, household composition, mother’s education, mother’s age at first birth) and early menarche, a marker of early pubertal development, on women’s educational attainment after age 24. RESULTS Pubertal timing and all socio-cultural factors in youth, other than year of birth, predicted women’s lifetime educational attainment in bivariate models. Family factors had the strongest associations. When family factors were added to multivariate models, geographic region in youth and pubertal timing were no longer significant. CONCLUSION Our findings provide additional evidence that family factors should be considered when developing comprehensive and inclusive interventions in childhood and adolescence to promote lifetime educational attainment among girls. PMID:26830508
Trevino, Kelly M.; Fasciano, Karen; Prigerson, Holly G.
2013-01-01
Purpose Patients who develop a strong alliance with their health care providers have been shown to have higher levels of psychosocial well-being and rates of treatment adherence. Young adults with cancer have lower levels of psychosocial well-being and treatment adherence relative to patients with cancer in other age groups. This study sought to evaluate the relationships between the patient-oncologist alliance, psychosocial well-being, and treatment adherence in young adults with advanced cancer. Patients and Methods Ninety-five young adults (age 20 to 40 years) with advanced cancer were administered measures of alliance, psychosocial well-being, willingness to adhere to treatment, and treatment adherence. Relationships between alliance and psychosocial well-being were examined bivariately. Multiple linear regression models examined the relationship between alliance and adherence, controlling for confounding influences (eg, psychosocial well-being). Results Alliance was significantly (P ≤ .01) and positively associated with greater perceived social support and less severe illness-related grief. After controlling for significant confounding influences (ie, metastases, appraised support, and grief), alliance remained significantly (P ≤ .01) associated with greater willingness to adhere to treatment and greater adherence to oral medication. Conclusion By developing a strong alliance, oncologists may enhance psychosocial well-being and increase treatment adherence in young adult patients with advanced cancer. PMID:23530105
Carvalhal, Adriana; Gill, M John; Letendre, Scott L; Rachlis, Anita; Bekele, Tsegaye; Raboud, Janet; Burchell, Ann; Rourke, Sean B
2016-06-01
Since the introduction of combination antiretroviral therapy (cART), the incidence of severe HIV-associated neurocognitive impairment has declined significantly, whereas the prevalence of the milder forms has increased. Studies suggest that better distribution of cART drugs into the CNS may be important in reducing viral replication in the CNS and in reducing HIV-related brain injury. Correlates of neuropsychological (NP) performance were determined in 417 participants of the Ontario HIV Treatment Cohort Study (OCS). All participants were on three cART drugs for at least 90 days prior to assessment. Multiple logistic and linear regression methods were used. Most participants were Caucasian men with mean age of 47 years. About two thirds had a nadir CD4+ T-cell count below 200 cells/μL and 92 % had an undetectable plasma HIV viral load. The median CNS penetration effectiveness (CPE) score was 7. Sixty percent of participants had neuropsychological impairment. Higher CPE values significantly correlated with lower prevalence of impairment in bivariate and multivariate analyses. In this cross-sectional analysis of HIV+ adults who had a low prevalence of comorbidities and were taking three-drug cART regimens, greater estimated distribution of cART drugs into the CNS was associated with better NP performance.
War, forced displacement and growth in Laotian adults.
Clarkin, Patrick F
2012-01-01
Evidence from several populations suggests that war negatively impacts civilian nutrition, physical growth and overall health. This effect is often enduring or permanent, particularly if experienced early in life. To assess whether the number of lifetime displacement experiences and being displaced in infancy were associated with adult height, sitting height, leg length and the sitting height ratio. Retrospective questionnaires on displacement and resettlement experiences and anthropometric data were collected from a sample of Laotian adult refugees (ethnic Hmong and Lao; n = 365). All were born in Laos or Thailand and had resettled in French Guiana or the US. Many had been displaced several times by military conflict in Laos. In bivariate analyses, being displaced in infancy and the number of lifetime displacement experiences one had were negatively associated with final adult height and leg length in both sexes. The association was stronger in females, particularly Hmong females. There was no significant association between total displacement experiences and the sitting height ratio. In multiple regression analyses, linear growth in males was negatively associated with being displaced in infancy; in females, the number of lifetime displacement experiences was a significant predictor. Forced displacement from war appears to have a lasting effect on final adult height, sitting height and leg length, although not necessarily on the sitting height ratio in this sample.
Microcredit participation and women's health: results from a cross-sectional study in Peru.
Hamad, Rita; Fernald, Lia C H
2015-08-05
Social and economic conditions are powerful determinants of women's health status. Microcredit, which involves the provision of small loans to low-income women in the hopes of improving their living conditions, is an increasingly popular intervention to improve women's socioeconomic status. Studies examining the health effects of microcredit programs have had mixed results. We conduct a cross-sectional study among female clients of a non-profit microcredit program in Peru (N = 1,593). The predictor variable is length of microcredit participation. We conduct bivariate and multivariate linear regressions to examine the associations between length of microcredit participation and a variety of measures of women's health. We control for participants' sociodemographic characteristics. We find that longer participation is associated with decreased depressive symptoms, increased social support, and increased perceived control, but these differences are attenuated with the inclusion of covariates. We find no association between length of participation and contraception use, cancer screening, or self-reported days sick. These results demonstrate a positive association between length of microcredit participation and measures of women's psychological health, but not physical health. These findings contribute to the discussion on the potential of microcredit programs to address the socioeconomic determinants of health, and suggest that addressing socioeconomic status may be a key way to improve women's health worldwide.
Kenyon, Chris R; Buyze, Jozefien
2015-01-01
The prevalence of both gender inequality and HIV prevalence vary considerably both within all developing countries and within those in sub-Saharan Africa. We test the hypothesis that the extent of gender inequality is associated with national peak HIV prevalence. Linear regression was used to test the association between national peak HIV prevalence and three markers of gender equality - the gender-related development index (GDI), the gender empowerment measure (GEM), and the gender inequality index (GII). No evidence was found of a positive relationship between gender inequality and HIV prevalence, either in the analyses of all developing countries or those limited to Africa. In the bivariate analyses limited to Africa, there was a positive association between the two measures of gender "equality" and peak HIV prevalence (GDI: coefficient 28, 95% confidence interval (CI) 9.1-46.8; GEM: coefficient 54.8, 95% CI 20.5-89.1). There was also a negative association between the marker of gender "inequality" and peak HIV prevalence (GII: coefficient -66.9, 95% CI -112.8 to -21.0). These associations all disappeared on multivariate analyses. We could not find any evidence to support the hypothesis that variations in the extent of gender inequality explain variations in HIV prevalence in developing countries.
Kerns, Jennifer L; Mengesha, Biftu; McNamara, Blair C; Cassidy, Arianna; Pearlson, Geffan; Kuppermann, Miriam
2018-06-01
We sought to explore the relationship between counseling quality, measured by shared decision making and decision satisfaction, and psychological outcomes (anxiety, grief, and posttraumatic stress) after second-trimester abortion for pregnancy complications. We conducted a cross-sectional study of women who underwent second-trimester abortion for complications. We recruited participants from Facebook and online support groups and surveyed them about counseling experiences and psychosocial issues. We used multivariate linear regression to evaluate relationships between counseling quality and psychological outcomes. We analyzed data from 145 respondents. Shared decision making and decision satisfaction scores were positively and strongly correlated in bivariate analysis (r=0.7, p<.0001), as were posttraumatic stress and grief scores (r=0.7, p<.0001). In the adjusted analysis, higher decision satisfaction was associated with lower grief and posttraumatic stress scores (p=.02 and p=.01, respectively) and higher shared decision making was associated with lower posttraumatic stress scores (p=.01). Decision satisfaction and shared decision making have a positive effect on psychological outcomes after second-trimester abortion for pregnancy complications. Counseling quality may be especially important in this setting given the sensitive nature of decisions regarding pregnancy termination for complications. These results highlight the importance of patient-centered counseling for women seeking pregnancy termination. Copyright © 2018. Published by Elsevier Inc.
Colón-Ramos, Uriyoán; Racette, Susan B.; Ganiban, Jody; Nguyen, Thuy G.; Kocak, Mehmet; Carroll, Kecia N.; Völgyi, Eszter; Tylavsky, Frances A.
2015-01-01
Despite increased interest in promoting nutrition during pregnancy, the association between maternal dietary patterns and birth outcomes has been equivocal. We examined maternal dietary patterns during pregnancy as a determinant of offspring’s birth weight-for-length (WLZ), weight-for-age (WAZ), length-for-age (LAZ), and head circumference (HCZ) Z-scores in Southern United States (n = 1151). Maternal diet during pregnancy was assessed by seven dietary patterns. Multivariable linear regression models described the association of WLZ, WAZ, LAZ, and HCZ with diet patterns controlling for other maternal and child characteristics. In bivariate analyses, WAZ and HCZ were significantly lower for processed and processed-Southern compared to healthy dietary patterns, whereas LAZ was significantly higher for these patterns. In the multivariate models, mothers who consumed a healthy-processed dietary pattern had children with significantly higher HCZ compared to the ones who consumed a healthy dietary pattern (HCZ β: 0.36; p = 0.019). No other dietary pattern was significantly associated with any of the birth outcomes. Instead, the major outcome determinants were: African American race, pre-pregnancy BMI, and gestational weight gain. These findings justify further investigation about socio-environmental and genetic factors related to race and birth outcomes in this population. PMID:25690420
Income inequality and obesity prevalence among OECD countries.
Su, Dejun; Esqueda, Omar A; Li, Lifeng; Pagán, José A
2012-07-01
Using recent pooled data from the World Health Organization Global Infobase and the World Factbook compiled by the Central Intelligence Agency of the United States, this study assesses the relation between income inequality and obesity prevalence among 31 OECD countries through a series of bivariate and multivariate linear regressions. The United States and Mexico well lead OECD countries in both obesity prevalence and income inequality. A sensitivity analysis suggests that the inclusion or exclusion of these two extreme cases can fundamentally change the findings. When the two countries are included, the results reveal a positive correlation between income inequality and obesity prevalence. This correlation is more salient among females than among males. Income inequality alone is associated with 16% and 35% of the variations in male and female obesity rates, respectively, across OECD countries in 2010. Higher levels of income inequality in the 2005-2010 period were associated with a more rapid increase in obesity prevalence from 2002 to 2010. These associations, however, virtually disappear when the US and Mexico have been excluded from the analysis. Findings from this study underscore the importance of assessing the impact of extreme cases on the relation between income inequality and health outcomes. The potential pathways from income inequality to the alarmingly high rates of obesity in the cases of the US and Mexico warrant further research.
Morse Code, Scrabble, and the Alphabet
ERIC Educational Resources Information Center
Richardson, Mary; Gabrosek, John; Reischman, Diann; Curtiss, Phyliss
2004-01-01
In this paper we describe an interactive activity that illustrates simple linear regression. Students collect data and analyze it using simple linear regression techniques taught in an introductory applied statistics course. The activity is extended to illustrate checks for regression assumptions and regression diagnostics taught in an…
Advanced statistics: linear regression, part II: multiple linear regression.
Marill, Keith A
2004-01-01
The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.
NASA Astrophysics Data System (ADS)
Kang, Pilsang; Koo, Changhoi; Roh, Hokyu
2017-11-01
Since simple linear regression theory was established at the beginning of the 1900s, it has been used in a variety of fields. Unfortunately, it cannot be used directly for calibration. In practical calibrations, the observed measurements (the inputs) are subject to errors, and hence they vary, thus violating the assumption that the inputs are fixed. Therefore, in the case of calibration, the regression line fitted using the method of least squares is not consistent with the statistical properties of simple linear regression as already established based on this assumption. To resolve this problem, "classical regression" and "inverse regression" have been proposed. However, they do not completely resolve the problem. As a fundamental solution, we introduce "reversed inverse regression" along with a new methodology for deriving its statistical properties. In this study, the statistical properties of this regression are derived using the "error propagation rule" and the "method of simultaneous error equations" and are compared with those of the existing regression approaches. The accuracy of the statistical properties thus derived is investigated in a simulation study. We conclude that the newly proposed regression and methodology constitute the complete regression approach for univariate linear calibrations.
A comparison of methods for the analysis of binomial clustered outcomes in behavioral research.
Ferrari, Alberto; Comelli, Mario
2016-12-01
In behavioral research, data consisting of a per-subject proportion of "successes" and "failures" over a finite number of trials often arise. This clustered binary data are usually non-normally distributed, which can distort inference if the usual general linear model is applied and sample size is small. A number of more advanced methods is available, but they are often technically challenging and a comparative assessment of their performances in behavioral setups has not been performed. We studied the performances of some methods applicable to the analysis of proportions; namely linear regression, Poisson regression, beta-binomial regression and Generalized Linear Mixed Models (GLMMs). We report on a simulation study evaluating power and Type I error rate of these models in hypothetical scenarios met by behavioral researchers; plus, we describe results from the application of these methods on data from real experiments. Our results show that, while GLMMs are powerful instruments for the analysis of clustered binary outcomes, beta-binomial regression can outperform them in a range of scenarios. Linear regression gave results consistent with the nominal level of significance, but was overall less powerful. Poisson regression, instead, mostly led to anticonservative inference. GLMMs and beta-binomial regression are generally more powerful than linear regression; yet linear regression is robust to model misspecification in some conditions, whereas Poisson regression suffers heavily from violations of the assumptions when used to model proportion data. We conclude providing directions to behavioral scientists dealing with clustered binary data and small sample sizes. Copyright © 2016 Elsevier B.V. All rights reserved.
Vajargah, Kianoush Fathi; Sadeghi-Bazargani, Homayoun; Mehdizadeh-Esfanjani, Robab; Savadi-Oskouei, Daryoush; Farhoudi, Mehdi
2012-01-01
The objective of the present study was to assess the comparable applicability of orthogonal projections to latent structures (OPLS) statistical model vs traditional linear regression in order to investigate the role of trans cranial doppler (TCD) sonography in predicting ischemic stroke prognosis. The study was conducted on 116 ischemic stroke patients admitted to a specialty neurology ward. The Unified Neurological Stroke Scale was used once for clinical evaluation on the first week of admission and again six months later. All data was primarily analyzed using simple linear regression and later considered for multivariate analysis using PLS/OPLS models through the SIMCA P+12 statistical software package. The linear regression analysis results used for the identification of TCD predictors of stroke prognosis were confirmed through the OPLS modeling technique. Moreover, in comparison to linear regression, the OPLS model appeared to have higher sensitivity in detecting the predictors of ischemic stroke prognosis and detected several more predictors. Applying the OPLS model made it possible to use both single TCD measures/indicators and arbitrarily dichotomized measures of TCD single vessel involvement as well as the overall TCD result. In conclusion, the authors recommend PLS/OPLS methods as complementary rather than alternative to the available classical regression models such as linear regression.
Quality of life in breast cancer patients--a quantile regression analysis.
Pourhoseingholi, Mohamad Amin; Safaee, Azadeh; Moghimi-Dehkordi, Bijan; Zeighami, Bahram; Faghihzadeh, Soghrat; Tabatabaee, Hamid Reza; Pourhoseingholi, Asma
2008-01-01
Quality of life study has an important role in health care especially in chronic diseases, in clinical judgment and in medical resources supplying. Statistical tools like linear regression are widely used to assess the predictors of quality of life. But when the response is not normal the results are misleading. The aim of this study is to determine the predictors of quality of life in breast cancer patients, using quantile regression model and compare to linear regression. A cross-sectional study conducted on 119 breast cancer patients that admitted and treated in chemotherapy ward of Namazi hospital in Shiraz. We used QLQ-C30 questionnaire to assessment quality of life in these patients. A quantile regression was employed to assess the assocciated factors and the results were compared to linear regression. All analysis carried out using SAS. The mean score for the global health status for breast cancer patients was 64.92+/-11.42. Linear regression showed that only grade of tumor, occupational status, menopausal status, financial difficulties and dyspnea were statistically significant. In spite of linear regression, financial difficulties were not significant in quantile regression analysis and dyspnea was only significant for first quartile. Also emotion functioning and duration of disease statistically predicted the QOL score in the third quartile. The results have demonstrated that using quantile regression leads to better interpretation and richer inference about predictors of the breast cancer patient quality of life.
Interpretation of commonly used statistical regression models.
Kasza, Jessica; Wolfe, Rory
2014-01-01
A review of some regression models commonly used in respiratory health applications is provided in this article. Simple linear regression, multiple linear regression, logistic regression and ordinal logistic regression are considered. The focus of this article is on the interpretation of the regression coefficients of each model, which are illustrated through the application of these models to a respiratory health research study. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.
Rowe, A Shaun; Rinehart, Derrick R; Lezatte, Stephanie; Langdon, J Russell
2018-03-07
The objective of this study was to evaluate and identify the risk factors for developing a new or enlarged intracranial hemorrhage (ICH) after the placement of an external ventricular drain. A single center, nested case-control study of individuals who received an external ventricular drain from June 1, 2011 to June 30, 2014 was conducted at a large academic medical center. A bivariate analysis was conducted to compare those individuals who experienced a post-procedural intracranial hemorrhage to those who did not experience a new bleed. The variables identified as having a p-value less than 0.15 in the bivariate analysis were then evaluated using a multivariate logistic regression model. Twenty-seven of the eighty-one study participants experienced a new or enlarged intracranial hemorrhage after the placement of an external ventricular drain. Of these twenty-seven patients, 6 individuals received an antiplatelet within ninety-six hours of external ventricular drain placement (p = 0.024). The multivariate logistic regression model identified antiplatelet use within 96 h of external ventricular drain insertion as an independent risk factor for post-EVD ICH (OR 13.1; 95% CI 1.95-88.6; p = 0.008). Compared to those study participants who did not receive an antiplatelet within 96 h of external ventricular drain placement, those participants who did receive an antiplatelet were 13.1 times more likely to exhibit a new or enlarged intracranial hemorrhage.
Zacarias, Antonio Eugenio; Macassa, Gloria; Soares, Joaquim JF; Svanström, Leif; Antai, Diddy
2012-01-01
Background Little knowledge exists in Mozambique and sub-Saharan Africa about the mental health (symptoms of depression, anxiety, and somatization) of women victims and perpetrators of intimate partner violence (IPV) by type of abuse (psychological aggression, physical assault without/with injury, and sexual coercion). This study scrutinizes factors associated with mental health among women victims and perpetrators of IPV over the 12 months prior to the study. Methods and materials Mental health data were analyzed with bivariate and multiple regression methods for 1442 women aged 15–49 years who contacted Forensic Services at Maputo Central Hospital (Maputo City, Mozambique) for IPV victimization between April 1, 2007 and March 31, 2008. Results In bivariate analyses, victims and perpetrators of IPVs scored higher on symptoms of mental health than their unaffected counterparts. Multiple regressions revealed that controlling behaviors, mental health comorbidity, social support, smoking, childhood abuse, sleep difficulties, age, and lack of education were more important in explaining symptoms of mental health than demographics/socioeconomics or life-style factors. Victimization and perpetration across all types of IPV were not associated with symptoms of mental health. Conclusion In our sample, victimization and perpetration were not important factors in explaining mental ill health, contrary to previous findings. More research into the relationship between women’s IPV victimization and perpetration and mental health is warranted as well as the influence of controlling behaviors on mental health. PMID:23071419
Scannapieco, Frank A; Ho, Alex W; DiTolla, Maris; Chen, Casey; Dentino, Andrew R
2004-03-01
To determine if the prevalence of respiratory disease among dental students and dental residents varies with their exposure to the clinical dental environment. A detailed questionnaire was administered to 817 students at 3 dental schools. The questionnaire sought information concerning demographic characteristics, school year, exposure to the dental environment and dental procedures, and history of respiratory disease. The data obtained were subjected to bivariate and multiple logistic regression analysis. Respondents reported experiencing the following respiratory conditions during the previous year: asthma (26 cases), bronchitis (11 cases), chronic lung disease (6 cases), pneumonia (5 cases) and streptococcal pharyngitis (50 cases). Bivariate statistical analyses indicated no significant associations between the prevalence of any of the respiratory conditions and year in dental school, except for asthma, for which there was a significantly higher prevalence at 1 school compared to the other 2 schools. When all cases of respiratory disease were combined as a composite variable and subjected to multivariate logistic regression analysis controlling for age, sex, race, dental school, smoking history and alcohol consumption, no statistically significant association was observed between respiratory condition and year in dental school or exposure to the dental environment as a dental patient. No association was found between the prevalence of respiratory disease and a student's year in dental school or previous exposure to the dental environment as a patient. These results suggest that exposure to the dental environment does not increase the risk for respiratory infection in healthy dental health care workers.
Atteraya, Madhu Sudhan; Ebrahim, Nasser B; Gnawali, Shreejana
2018-02-01
We examined the prevalence of child maltreatment as measured by the level of physical (moderate to severe) and emotional abuse and child labor, and the associated household level determinants of child maltreatment in Nepal. We used a nationally representative data set from the fifth round of the Nepal Multiple Indicator Cluster Survey (the 2014 NMICS). The main independent variables were household level characteristics. Dependent variables included child experience of moderate to severe physical abuse, emotional abuse, and child labor (domestic work and economic activities). Bivariate analyses and logistic regressions were used to examine the associations between independent and dependent variables. The results showed that nearly half of the children (49.8%) had experienced moderate physical abuse, 21.5% experienced severe physical abuse, and 77.3% experienced emotional abuse. About 27% of the children had engaged in domestic work and 46.7% in various economic activities. At bivariate level, educational level of household's head and household wealth status had shown significant statistical association with child maltreatment (p<0.001). Results from multivariate logistic regressions showed that higher education levels and higher household wealth status protected children from moderate to severe physical abuse, emotional abuse and child labor. In general, child maltreatment is a neglected social issue in Nepal and the high rates of child maltreatment calls for mass awareness programs focusing on parents, and involving all stakeholders including governments, local, and international organizations. Copyright © 2017 Elsevier Ltd. All rights reserved.
Determinants of modern contraceptive use among sexually active men in Kenya.
Ochako, Rhoune; Temmerman, Marleen; Mbondo, Mwende; Askew, Ian
2017-04-27
Research in Kenya has focussed on family planning from women's perspectives, with the aim of helping reduce the burden of unintended pregnancies. As such, the determinants of modern contraceptive use among sexually active women are well documented. However, the perspectives of men should be considered not only as women's partners, but also as individuals with distinct reproductive histories and desires of their own. This study seeks to understand the determinants of modern contraceptive use among sexually active men, by exploring factors that are correlated with modern contraceptive use. The data source is the nationally representative 2014 Kenya Demographic and Health Survey (DHS) of men aged 15-54 years. The analysis is restricted to 9,514 men who reported being sexually active in the past 12 months prior to the survey, as they were likely to report either doing something or not to avoid or delay pregnancy. We use bivariate and multinomial logistic regression to assess factors that influence modern contraceptive use among sexually active men. Findings from the bivariate and multinomial logistic regression indicate that region of residence, marital status, religion, wealth, interaction with a health care provider, fertility preference, number of sexual partners and access to media were all significantly associated with modern contraceptive use among sexually active men. Provider-client interaction as well as dissemination of information through mass media has the potential to increase knowledge and uptake of modern contraceptives. Similar efforts targeting segments of the population where contraceptive uptake is low are recommended.
Truthmann, Julia; Mensink, Gert B M; Bosy-Westphal, Anja; Hapke, Ulfert; Scheidt-Nave, Christa; Schienkiewitz, Anja
2017-06-10
This study examined sex-specific differences in physical health-related quality of life (HRQoL) across subgroups of metabolic health and obesity. We specifically asked whether (1) obesity is related to lower HRQoL independent of metabolic health status and potential confounders, and (2) whether associations are similar in men and women. We used cross-sectional data from the German Health Interview and Examination Survey 2008-11. Physical HRQoL was measured using the Short Form-36 version 2 physical component summary (PCS) score. Based on harmonized ATPIII criteria for the definition of the metabolic health and a body mass index ≥ 30 kg/m 2 to define obesity, individuals were classified as metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO). Sex-specific analyses including multivariable linear regression analyses were based on PCS as the dependent variable, metabolic health and obesity category as the independent variable with three categories and MHNO as the reference, and age, education, lifestyle and comorbidities as confounders. This study included 6860 participants (3298 men, 3562 women). Compared to MHNO, all other metabolic health and obesity categories had significantly lower PCS in both sexes. As reflected by the beta coefficients [95% confidence interval] from bivariable linear regression models, a significant inverse association with PCS was strongest for MUO (men: -7.0 [-8.2; -5.8]; women: -9.0 [-10.2; -7.9]), intermediate for MUNO (men: -4.2 [-5.3; -3.1]; women: -5.6 [-6.8; -4.4]) and least pronounced for MHO (men: -2.2 [-3.6; -0.8]; women -3.9 [-5.4; -2.5]). Differences in relation to MHNO remained statistically significant for all groups after adjusting for confounders, but decreased in particular for MUNO (men:-1.3 [-2.3; -0.3]; women: -1.5 [-2.7; -0.3]. Obesity was significantly related to lower physical HRQoL, independent of metabolic health status. Potential confounders including age, educational status, health-related behaviors, and comorbidities explained parts of the inverse relationship. Associations were evident in both sexes and consistently more pronounced among women than men.
Association between filial responsibility when caring for parents and the caregivers overload.
Aires, Marinês; Mocellin, Duane; Fengler, Fernanda Laís; Rosset, Idiane; Santos, Naiana Oliveira Dos; Machado, Diani de Oliveira; Day, Carolina Baltar; Paskulin, Lisiane Manganelli Girardi
2017-01-01
To analyze the association between filial responsibility and the overload of the children when caring for their older parents. Cross-sectional study with 100 caregiver children of older adults. Filial liability was assessed by the attitudes of the responsible child (scale of expectation and filial duty) and by care behaviors (assistance in activities of daily living, emotional and financial support, and keeping company). The overload was assessed by the Caregiver Burden Inventory. To assess the associations, the correlation coefficients of Pearson and Spearman, Kruskal-Wallis Test, and Mann-Whitney were employed. Variables that presented p-value<0.20 in the bivariate analysis were inserted in a multivariate linear regression model. The factors associated with overload were: formal employment (p=0.002), feelings regarding family life (p<0.001), financial support (p=0.027), and assistance with Activities of Daily Living (ADLs) (p<0.001). Children who were more involved with the ADLs and provided financial support showed higher levels of overload. Analisar a associação entre a responsabilidade filial e a sobrecarga dos filhos cuidadores de pessoas idosas. Estudo transversal com 100 filhos cuidadores de pessoas idosas. A responsabilidade filial foi avaliada pelas atitudes de responsabilidade filial (escala de expectativa e dever filial) e pelos comportamentos de cuidar (auxílio nas atividades de vida diária, apoio emocional, financeiro e companhia). A sobrecarga foi avaliada pelo Inventário de Sobrecarga do Cuidador. Para avaliar as associações utilizaram-se os coeficientes de correlação de Pearson e Spearman, Teste de Kruskal-Wallis e Mann-whitney. Variáveis que apresentaram valor de p<0,20 na análise bivariada foram inseridas em um modelo multivariado de regressão linear. Os fatores associados com a sobrecarga foram: emprego formal (p=0,002), sentimentos na vida familiar (p<0,001), apoio financeiro (p=0,027) e ajuda nas Atividades da Vida Diária (AVDs) (p<0,001). Os filhos que mais auxiliavam nas AVDs e prestavam apoio financeiro apresentaram maiores níveis de sobrecarga.
Webb, Travis P; Paul, Jasmeet; Treat, Robert; Codner, Panna; Anderson, Rebecca; Redlich, Philip
2014-01-01
A protected block curriculum (PBC) with postcurriculum examinations for all surgical residents has been provided to assure coverage of core curricular topics. Biannual assessment of resident competency will soon be required by the Next Accreditation System. To identify opportunities for early medical knowledge assessment and interventions, we examined whether performance in postcurriculum multiple-choice examinations (PCEs) is predictive of performance in the American Board of Surgery In-Training Examination (ABSITE) and clinical service competency assessments. Retrospective single-institutional education research study. Academic general surgery residency program. A total of 49 surgical residents. Data for PGY1 and PGY2 residents participating in the 2008 to 2012 PBC are included. Each resident completed 6 PCEs during each year. The results of 6 examinations were correlated to percentage-correct ABSITE scores and clinical assessments based on the 6 Accreditation Council for Graduate Medical Education core competencies. Individual ABSITE performance was compared between PGY1 and PGY2. Statistical analysis included multivariate linear regression and bivariate Pearson correlations. A total of 49 residents completed the PGY1 PBC and 36 completed the PGY2 curriculum. Linear regression analysis of percentage-correct ABSITE and PCE scores demonstrated a statistically significant correlation between the PGY1 PCE 1 score and the subsequent PGY1 ABSITE score (p = 0.037, β = 0.299). Similarly, the PGY2 PCE 1 score predicted performance in the PGY2 ABSITE (p = 0.015, β = 0.383). The ABSITE scores correlated between PGY1 and PGY2 with statistical significance, r = 0.675, p = 0.001. Performance on the 6 Accreditation Council for Graduate Medical Education core competencies correlated between PGY1 and PGY2, r = 0.729, p = 0.001, but did not correlate with PCE scores during either years. Within a mature PBC, early performance in a PGY1 and PGY2 PCE is predictive of performance in the respective ABSITE. This information can be used for formative assessment and early remediation of residents who are predicted to be at risk for poor performance in the ABSITE. Copyright © 2014 Association of Program Directors in Surgery. All rights reserved.
Use of probabilistic weights to enhance linear regression myoelectric control
NASA Astrophysics Data System (ADS)
Smith, Lauren H.; Kuiken, Todd A.; Hargrove, Levi J.
2015-12-01
Objective. Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Approach. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts’ law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Main results. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p < 0.05) by preventing extraneous movement at additional DOFs. Similar results were seen in experiments with two transradial amputees. Though goodness-of-fit evaluations suggested that the EMG feature distributions showed some deviations from the Gaussian, equal-covariance assumptions used in this experiment, the assumptions were sufficiently met to provide improved performance compared to linear regression control. Significance. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.
Simplified large African carnivore density estimators from track indices.
Winterbach, Christiaan W; Ferreira, Sam M; Funston, Paul J; Somers, Michael J
2016-01-01
The range, population size and trend of large carnivores are important parameters to assess their status globally and to plan conservation strategies. One can use linear models to assess population size and trends of large carnivores from track-based surveys on suitable substrates. The conventional approach of a linear model with intercept may not intercept at zero, but may fit the data better than linear model through the origin. We assess whether a linear regression through the origin is more appropriate than a linear regression with intercept to model large African carnivore densities and track indices. We did simple linear regression with intercept analysis and simple linear regression through the origin and used the confidence interval for ß in the linear model y = αx + ß, Standard Error of Estimate, Mean Squares Residual and Akaike Information Criteria to evaluate the models. The Lion on Clay and Low Density on Sand models with intercept were not significant ( P > 0.05). The other four models with intercept and the six models thorough origin were all significant ( P < 0.05). The models using linear regression with intercept all included zero in the confidence interval for ß and the null hypothesis that ß = 0 could not be rejected. All models showed that the linear model through the origin provided a better fit than the linear model with intercept, as indicated by the Standard Error of Estimate and Mean Square Residuals. Akaike Information Criteria showed that linear models through the origin were better and that none of the linear models with intercept had substantial support. Our results showed that linear regression through the origin is justified over the more typical linear regression with intercept for all models we tested. A general model can be used to estimate large carnivore densities from track densities across species and study areas. The formula observed track density = 3.26 × carnivore density can be used to estimate densities of large African carnivores using track counts on sandy substrates in areas where carnivore densities are 0.27 carnivores/100 km 2 or higher. To improve the current models, we need independent data to validate the models and data to test for non-linear relationship between track indices and true density at low densities.
[From clinical judgment to linear regression model.
Palacios-Cruz, Lino; Pérez, Marcela; Rivas-Ruiz, Rodolfo; Talavera, Juan O
2013-01-01
When we think about mathematical models, such as linear regression model, we think that these terms are only used by those engaged in research, a notion that is far from the truth. Legendre described the first mathematical model in 1805, and Galton introduced the formal term in 1886. Linear regression is one of the most commonly used regression models in clinical practice. It is useful to predict or show the relationship between two or more variables as long as the dependent variable is quantitative and has normal distribution. Stated in another way, the regression is used to predict a measure based on the knowledge of at least one other variable. Linear regression has as it's first objective to determine the slope or inclination of the regression line: Y = a + bx, where "a" is the intercept or regression constant and it is equivalent to "Y" value when "X" equals 0 and "b" (also called slope) indicates the increase or decrease that occurs when the variable "x" increases or decreases in one unit. In the regression line, "b" is called regression coefficient. The coefficient of determination (R 2 ) indicates the importance of independent variables in the outcome.
Hemmila, April; McGill, Jim; Ritter, David
2008-03-01
To determine if changes in fingerprint infrared spectra linear with age can be found, partial least squares (PLS1) regression of 155 fingerprint infrared spectra against the person's age was constructed. The regression produced a linear model of age as a function of spectrum with a root mean square error of calibration of less than 4 years, showing an inflection at about 25 years of age. The spectral ranges emphasized by the regression do not correspond to the highest concentration constituents of the fingerprints. Separate linear regression models for old and young people can be constructed with even more statistical rigor. The success of the regression demonstrates that a combination of constituents can be found that changes linearly with age, with a significant shift around puberty.
Gimelfarb, A.; Willis, J. H.
1994-01-01
An experiment was conducted to investigate the offspring-parent regression for three quantitative traits (weight, abdominal bristles and wing length) in Drosophila melanogaster. Linear and polynomial models were fitted for the regressions of a character in offspring on both parents. It is demonstrated that responses by the characters to selection predicted by the nonlinear regressions may differ substantially from those predicted by the linear regressions. This is true even, and especially, if selection is weak. The realized heritability for a character under selection is shown to be determined not only by the offspring-parent regression but also by the distribution of the character and by the form and strength of selection. PMID:7828818
Variable-Domain Functional Regression for Modeling ICU Data.
Gellar, Jonathan E; Colantuoni, Elizabeth; Needham, Dale M; Crainiceanu, Ciprian M
2014-12-01
We introduce a class of scalar-on-function regression models with subject-specific functional predictor domains. The fundamental idea is to consider a bivariate functional parameter that depends both on the functional argument and on the width of the functional predictor domain. Both parametric and nonparametric models are introduced to fit the functional coefficient. The nonparametric model is theoretically and practically invariant to functional support transformation, or support registration. Methods were motivated by and applied to a study of association between daily measures of the Intensive Care Unit (ICU) Sequential Organ Failure Assessment (SOFA) score and two outcomes: in-hospital mortality, and physical impairment at hospital discharge among survivors. Methods are generally applicable to a large number of new studies that record a continuous variables over unequal domains.
Impact of hospital market competition on endovascular aneurysm repair adoption and outcomes.
Sethi, Rosh K V; Henry, Antonia J; Hevelone, Nathanael D; Lipsitz, Stuart R; Belkin, Michael; Nguyen, Louis L
2013-09-01
The share of total abdominal aortic aneurysm (AAA) repairs performed by endovascular aneurysm repair (EVAR) increased rapidly from 32% in 2001 to 65% in 2006 with considerable variation between states. We hypothesized that hospitals in competitive markets were early EVAR adopters and had improved AAA repair outcomes. Nationwide Inpatient Sample and linked Hospital Market Structure (HMS) data was queried for patients who underwent repair for nonruptured AAA in 2003. In HMS, the Herfindahl Hirschman Index (HHI, range 0-1) is a validated and widely accepted economic measure of competition. Hospital markets were defined using a variable geographic radius that encompassed 90% of discharged patients. We conducted bivariate and multivariable linear and logistic regression analyses for the dependent variable of EVAR use. A propensity score-adjusted multivariable logistic regression model was used to control for treatment bias in the assessment of competition on AAA repair outcomes. A weighted total of 21,600 patients was included in our analyses. Patients at more competitive hospitals (lower HHI) were at increased odds of undergoing EVAR vs open repair (odds ratio, 1.127 per 0.1 decrease in HHI; P < .0127) after adjusting for patient demographics, comorbidities, and hospital level factors (bed size, teaching status, AAA repair volume, and ownership). Competition was not associated with differences in in-hospital mortality or vascular, neurologic, or other minor postoperative complications. Greater hospital competition is significantly associated with increased EVAR adoption at a time when diffusion of this technology passed its tipping point. Hospital competition does not influence post-AAA repair outcomes. These results suggest that adoption of novel vascular technology is not solely driven by clinical indications but may also be influenced by market forces. Copyright © 2013 Society for Vascular Surgery. Published by Mosby, Inc. All rights reserved.
How Important Are Health Care Expenditures for Life Expectancy? A Comparative, European Analysis.
van den Heuvel, Wim J A; Olaroiu, Marinela
2017-03-01
The relationship between health care expenditures and health care outcomes, such as life expectancy and mortality, is complex. Research outcomes show different and contradictory results on this relationship. How and why health care expenditures affect health outcomes is not clear. A causal link between the two is not proven. Without such knowledge, effects of increase/decrease in health care expenses on health outcomes may be overestimated/underestimated. This study analyzes the relationship between life expectancy at birth and expenditures on health care, taking into account expenditures of social production and education, as well as the quantity and quality of health care provisions and lifestyles. This is a cross-sectional study, analyzing national data of 31 European countries. First, the bivariate correlation between the dependent variable and independent variables are calculated and described. Next a forward linear regression analysis is applied. The data are derived from standardized, comparative data bases as available in the Organisation for Economic Co-operation and Development and Eurostat. Health care expenditures are assessed as a percentage of the Gross Domestic Product (GDP). Health care expenditures are not the main determinant of life expectancy at birth, but social protection expenditures are. The regression analysis shows that in countries that spend a high percentage of their GDP on social protection, that have fewer curative beds and low infant mortality, whose citizens report fewer unmet health care needs and drink less alcohol, citizens have a significant longer life expectancy. To realize high life expectancy of citizens, policy measures have to be directed on investment in social protection expenditures, on improving quality of care, and on promoting a healthy life style. Copyright © 2016 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.
Merker, Vanessa L; Bredella, Miriam A; Cai, Wenli; Kassarjian, Ara; Harris, Gordon J; Muzikansky, Alona; Nguyen, Rosa; Mautner, Victor F; Plotkin, Scott R
2014-06-01
Patients with neurofibromatosis 1 (NF1), NF2, and schwannomatosis share a predisposition to develop multiple nerve sheath tumors. Previous studies have demonstrated that patients with NF1 and NF2 have reduced quality of life (QOL), but no studies have examined the relationship between whole-body tumor burden and QOL in these patients. We administered a QOL questionnaire (the SF-36) and a visual analog pain scale (VAS) to a previously described cohort of adult neurofibromatosis patients undergoing whole-body MRI. One-sample t-tests were used to compare norm-based SF-36 scores to weighted population means. Spearman correlation coefficients and multiple linear regression analyses controlling for demographic and disease-specific clinical variable were used to relate whole-body tumor volume to QOL scales. Two hundred forty-five patients (142 NF1, 53 NF2, 50 schwannomatosis) completed the study. Subjects showed deficits in selected subscales of the SF-36 compared to adjusted general population means. In bivariate analysis, increased tumor volume was significantly associated with pain in schwannomatosis patients, as measured by the SF-36 bodily pain subscale (rho = -0.287, P = 0.04) and VAS (rho = 0.34, P = 0.02). Regression models for NF2 patients showed a positive relationship between tumor burden and increased pain, as measured by the SF-36 (P = 0.008). Patients with NF1, NF2, and schwannomatosis suffer from reduced QOL, although only pain shows a clear relationship to patient's overall tumor burden. These findings suggest that internal tumor volume is not a primary contributor to QOL and emphasize the need for comprehensive treatment approaches that go beyond tumor-focused therapies such as surgery by including psychosocial interventions. © 2014 Wiley Periodicals, Inc.
Faculty motivations to use active learning among pharmacy educators.
Rockich-Winston, Nicole; Train, Brian C; Rudolph, Michael J; Gillette, Chris
2018-03-01
Faculty motivations to use active learning have been limited to surveys evaluating faculty perceptions within active learning studies. Our objective in this study was to evaluate the relationship between faculty intrinsic motivation, extrinsic motivation, and demographic variables and the extent of active learning use in the classroom. An online survey was administered to individual faculty members at 137 colleges and schools of pharmacy across the United States. The survey assessed intrinsic and extrinsic motivations, active learning strategies, classroom time dedicated to active learning, and faculty development resources. Bivariate associations and multivariable stepwise linear regression were used to analyze the results. In total, 979 faculty members completed the questionnaire (23.6% response rate). All motivation variables were significantly correlated with percent active learning use (p < 0.001). Intrinsic motivation demonstrated the highest correlation (r = 0.447) followed by current extrinsic motivations (r = 0.245) and ideal extrinsic motivations (r = 0.291). Variables associated with higher intrinsic motivation included the number of resources used (r = 0.233, p < 0.001) and the number of active learning methods used in the last year (r = 0.259, p < 0.001). Years of teaching experience was negatively associated with intrinsic motivation (r = -0.177, p < 0.001). Regression analyses confirmed the importance of intrinsic and extrinsic motivations in predicting active learning use. Our results suggest that faculty members who are intrinsically motivated to use active learning are more likely to dedicate additional class time to active learning. Furthermore, intrinsic motivation may be positively associated with encouraging faculty members to attend active learning workshops and supporting faculty to use various active learning strategies in the classroom. Copyright © 2017 Elsevier Inc. All rights reserved.
Gadegbeku, Crystal A; Stillman, Phyllis Kreger; Huffman, Mark D; Jackson, James S; Kusek, John W; Jamerson, Kenneth A
2008-11-01
Recruitment of diverse populations into clinical trials remains challenging but is needed to fully understand disease processes and benefit the general public. Greater knowledge of key factors among ethnic and racial minority populations associated with the decision to participate in clinical research studies may facilitate recruitment and enhance the generalizibility of study results. Therefore, during the recruitment phase of the African American Study of Kidney Disease and Hypertension (AASK) trial, we conducted a telephone survey, using validated questions, to explore potential facilitators and barriers of research participation among eligible candidates residing in seven U.S. locations. Survey responses included a range of characteristics and perceptions among participants and non-participants and were compared using bivariate and step-wise logistic regression analyses. One-hundred forty-one respondents in the one-hundred forty (70 trial participants and 71 non-participants) completed the survey. Trial participants and non-participants were similar in multiple demographic characteristics and shared similar views on discrimination, physician mistrust, and research integrity. Key group differences were related to their perceptions of the impact of their research participation. Participants associated enrollment with personal and societal health benefits, while non-participants were influenced by the health risks. In a step-wise linear regression analysis, the most powerful significant positive predictors of participation were acknowledgement of health status as important in the enrollment decision (OR=4.54, p=0.006), employment (OR=3.12, p = 0.05) and healthcare satisfaction (OR=2.12, p<0.01). Racially-based mistrust did not emerge as a negative predictor and subjects' decisions were not influenced by the race of the research staff. In conclusion, these results suggest that health-related factors, and not psychosocial perceptions, have predominant influence on research participation among African Americans.
Gielen, M; Hageman, G; Pachen, D; Derom, C; Vlietinck, R; Zeegers, M P
2014-10-01
In contrast to the postnatal period, little is known about telomere length (TL) during prenatal life. The decrease in placental TL remains unknown, although intra uterine growth retardation and preeclampsia are associated with shorter placental TL. The aim of this study is to assess the decrease of placental TL during the third trimester of gestation and to explore the role of potential "growth influencing factors". The study sample consisted of 329 live-born twins from the East Flanders Prospective Twin Survey. TL was determined using a multiplex quantitative PCR method. Gestational age, sex, birth order, placental characteristics, parity, maternal and paternal age, diabetes, hypertension, smoking, alcohol use, and socio economic status (SES) were considered "growth influencing factors". Bivariable multilevel regression analysis with "growth influencing factors" was performed. Placental TL ranged from 4.3 kbp to 84.4 kbp with a median of 10.8 kbp. Ln(TL) decreased in a linear fashion with an estimated TL decreasing from 13.98 kbp at 28 weeks to 10.56 kbp at 42 weeks. The regression coefficient of gestational age became smaller if considered together with SES (b = -0.017; p = 0.08) or diabetes (b = -0.018; p = 0.07) and bigger if considered together with parity (b = -0.022; p = 0.02), indicating that part of the association between gestational age and telomere length is explained by these three confounding factors. Placental TL decreases during the third trimester of gestation of live-born twins with approximately 25% indicating that telomere shortening may play a role in aging of the placenta. Copyright © 2014 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Verkade, J. S.; Brown, J. D.; Reggiani, P.; Weerts, A. H.
2013-09-01
The ECMWF temperature and precipitation ensemble reforecasts are evaluated for biases in the mean, spread and forecast probabilities, and how these biases propagate to streamflow ensemble forecasts. The forcing ensembles are subsequently post-processed to reduce bias and increase skill, and to investigate whether this leads to improved streamflow ensemble forecasts. Multiple post-processing techniques are used: quantile-to-quantile transform, linear regression with an assumption of bivariate normality and logistic regression. Both the raw and post-processed ensembles are run through a hydrologic model of the river Rhine to create streamflow ensembles. The results are compared using multiple verification metrics and skill scores: relative mean error, Brier skill score and its decompositions, mean continuous ranked probability skill score and its decomposition, and the ROC score. Verification of the streamflow ensembles is performed at multiple spatial scales: relatively small headwater basins, large tributaries and the Rhine outlet at Lobith. The streamflow ensembles are verified against simulated streamflow, in order to isolate the effects of biases in the forcing ensembles and any improvements therein. The results indicate that the forcing ensembles contain significant biases, and that these cascade to the streamflow ensembles. Some of the bias in the forcing ensembles is unconditional in nature; this was resolved by a simple quantile-to-quantile transform. Improvements in conditional bias and skill of the forcing ensembles vary with forecast lead time, amount, and spatial scale, but are generally moderate. The translation to streamflow forecast skill is further muted, and several explanations are considered, including limitations in the modelling of the space-time covariability of the forcing ensembles and the presence of storages.
Physicians' anxiety due to uncertainty and use of race in medical decision making.
Cunningham, Brooke A; Bonham, Vence L; Sellers, Sherrill L; Yeh, Hsin-Chieh; Cooper, Lisa A
2014-08-01
The explicit use of race in medical decision making is contested. Researchers have hypothesized that physicians use race in care when they are uncertain. The aim of this study was to investigate whether physician anxiety due to uncertainty (ADU) is associated with a higher propensity to use race in medical decision making. This study included a national cross-sectional survey of general internists. A national sample of 1738 clinically active general internists drawn from the SK&A physician database were included in the study. ADU is a 5-item measure of emotional reactions to clinical uncertainty. Bonham and Sellers Racial Attributes in Clinical Evaluation (RACE) scale includes 7 items that measure self-reported use of race in medical decision making. We used bivariate regression to test for associations between physician characteristics, ADU, and RACE. Multivariate linear regression was performed to test for associations between ADU and RACE while adjusting for potential confounders. The mean score on ADU was 19.9 (SD=5.6). Mean score on RACE was 13.5 (SD=5.6). After adjusting for physician demographics, physicians with higher levels of ADU scored higher on RACE (+β=0.08 in RACE, P=0.04, for each 1-point increase in ADU), as did physicians who understood "race" to mean biological or genetic ancestral, rather than sociocultural, group. Physicians who graduated from a US medical school, completed fellowship, and had more white patients scored lower on RACE. This study demonstrates positive associations between physicians' ADU, meanings attributed to race, and self-reported use of race in medical decision making. Future research should examine the potential impact of these associations on patient outcomes and health care disparities.
Zhu, Chunyan; Yang, Hongling; Geng, Qingshan; Ma, Qingling; Long, Yan; Zhou, Cheng; Chen, Ming
2015-01-01
Objective The relationship between gestational diabetes mellitus (GDM) and oxidative stress has not been fully elucidated. This study examined the association between biomarkers of oxidative stress and GDM. Methods We conducted a case-control study which included 36 women presenting with GDM and 36 asymptomatic matched control subjects who visited Guangzhou Women and Children’s Medical Centre, China, from June 2012 to December 2012. Pregnant women were prospectively recruited to the study, and blood samples were collected at the time of a routine oral glucose tolerance test. These samples were then analyzed for levels of endocrine and surrogate markers of oxidative stress. Results Compared to control subjects, women with GDM exhibited elevated values for plasma glucose, insulin, and insulin resistance (IR), and showed reduced HOMA pancreatic β-cell function (HOMA-B), insulin sensitivity index (ISI), insulinogenic index, and corrected insulin response at 24–28 weeks gestation. A bivariate logistic regression analysis showed that levels of high-sensitivity C reactive protein (hs-CRP) and high fluorescence reticulocytes at fasting, and hs-CRP in a 1-h OGTT, were significantly associated with GDM. A linear regression analysis showed that levels of hs-CRP (P = 0.003) and reticulocytes (P = 0.029) at fasting were associated with IR, and levels of hs-CRP (P = 0.002) and monocytes (P = 0.006) in a 1-h OGTT were associated with ISI. Conclusions Pregnant women with GDM developed a pathological IR and exhibited β-cell dysfunction. Their decreased ability to compensate for oxidative stress was associated with increased IR and a reduced ISI, which might be important factors in GDM. PMID:25915047
Hughes, Sheryl O.; Power, Thomas G.; O’Connor, Teresia M.; Fisher, Jennifer Orlet
2016-01-01
The purpose of the present study was to examine relationships between child eating self-regulation, child non-eating self-regulation, and child BMIz in a low-income sample of Hispanic families with preschoolers. The eating in the absence of hunger task as well as parent-report of child satiety responsiveness and food responsiveness were used to assess child eating self-regulation. Two laboratory tasks assessing executive functioning, a parent questionnaire assessing child effortful control (a temperament dimension related to executive functioning), and the delay of gratification and gift delay tasks assessing child emotion regulation were used to assess child non-eating self-regulation. Bivariate correlations were run among all variables in the study. Hierarchical linear regression analyses assessed: 1) child eating self-regulation associations with the demographic, executive functioning, effortful control, and emotion regulation measures; and 2) child BMI z-scores associations with executive functioning, effortful control, emotion regulation measures, and eating self-regulation measures. Within child eating self-regulation, only the two parent-report measures were related. Low to moderate positive correlations were found between measures of executive functioning, effortful control, and emotion regulation. Only three relationships were found between child eating self-regulation and other forms of child self-regulation: eating in the absence of hunger was positively associated with delay of gratification, and poor regulation on the gift delay task was associated positively with maternal reports of food responsiveness and negatively with parent-reports of satiety responsiveness. Regression analyses showed that child eating self-regulation was associated with child BMIz but other forms of child self-regulation were not. Implications for understanding the role of self-regulation in the development of child obesity are discussed. PMID:25596501
Prevalence and associated factors for decreased appetite among patients with stable heart failure.
Andreae, Christina; Strömberg, Anna; Årestedt, Kristofer
2016-06-01
To explore the prevalence of decreased appetite and factors associated with appetite among patients with stable heart failure. Decreased appetite is an important factor for the development of undernutrition among patients with heart failure, but there are knowledge gaps about prevalence and the factors related to appetite in this patient group. Observational, cross-sectional study. A total of 186 patients with mild to severe heart failure were consecutively recruited from three heart failure outpatient clinics. Data were obtained from medical records (heart failure diagnosis, comorbidity and medical treatment) and self-rated questionnaires (demographics, appetite, self-perceived health, symptoms of depression and sleep). Blood samples were taken to determine myocardial stress and nutrition status. Heart failure symptoms and cognitive function were assessed by clinical examinations. The Council on Nutrition Appetite Questionnaire was used to assess self-reported appetite. Bivariate correlations and multivariate linear regression analyses were conducted to explore factors associated with appetite. Seventy-one patients (38%) experienced a loss of appetite with a significant risk of developing weight loss. The final multiple regression model showed that age, symptoms of depression, insomnia, cognitive function and pharmacological treatment were associated with appetite, explaining 27% of the total variance. In this cross-sectional study, a large share of patients with heart failure was affected by decreased appetite, associated with demographic, psychosocial and medical factors. Loss of appetite is a prevalent problem among patients with heart failure that may lead to undernutrition. Health care professionals should routinely assess appetite and discuss patients' experiences of appetite, nutrition intake and body weight and give appropriate nutritional advice with respect to individual needs. © 2016 John Wiley & Sons Ltd.
Staland-Nyman, Carin; Alexanderson, Kristina; Hensing, Gunnel
2008-01-01
The aim of this study was to analyse the association between strain in domestic work and self-rated health among employed women in Sweden, using two different methods of measuring strain in domestic work. Questionnaire data were collected on health and living conditions in paid and unpaid work for employed women (n=1,417), aged 17-64 years. "Domestic job strain'' was an application of the demand-control model developed by Karasek and Theorell, and "Domestic work equity and marital satisfaction'' was measured by questions on the division of and responsibility for domestic work and relationship with spouse/cohabiter. Self-rated health was measured using the SF-36 Health Survey. Associations were analysed by bivariate and multivariate linear regression analyses, and reported as standardized regression coefficients. Higher strain in domestic work was associated with lower self-rated health, also after controlling for potential confounders and according to both strain measures. "Domestic work equity and marital satisfaction'' showed for example negative associations with mental health beta -0.211 (p<0.001), vitality beta -0.195 (p<0.001), social function -0.132 (p<0.01) and physical role beta -0.115 (p<0.01). The highest associations between "Domestic job strain'' and SF-36 were found for vitality beta -0.156 (p<0.001), mental health beta -0.123 (p<0.001). Strain in domestic work, including perceived inequity in the relationship and lack of a satisfactory relationship with a spouse/cohabiter, was associated with lower self-rated health in this cross-sectional study. Future research needs to address the specific importance of strain in domestic work as a contributory factor to women's ill-health.
Pousa, Esther; Ochoa, Susana; Cobo, Jesús; Nieto, Lourdes; Usall, Judith; Gonzalez, Beatriz; Garcia-Ribera, Carles; Pérez Solà, Victor; Ruiz, Ada-I; Baños, Iris; Cobo, Jesús; García-Ribera, Carles; González, Beatriz; Massons, Carmina; Nieto, Lourdes; Monserrat, Clara; Ochoa, Susana; Pousa, Esther; Ruiz, Ada-Inmaculada; Ruiz, Isabel; Sanchez-Cabezudo, Dolores; Usall, Judith
2017-11-01
1. To describe insight in a large sample of schizophrenia subjects from a multidimensional point of view, including unawareness of general insight dimensions as well as unawareness and misattribution of particular symptoms. 2. To explore the relationship between unawareness and clinical and socio-demographic variables. 248 schizophrenia patients were assessed with the Positive and Negative Syndrome Scale (PANSS, five factor model of Lindenmayer) and the full Scale of Unawareness of Mental Disorder (SUMD). Bivariate associations and multiple linear regression analyses were used to investigate the relationship between unawareness, symptoms and socio-demographic variables. Around 40% of the sample showed unawareness of mental disorder, of the need for medication and of the social consequences. Levels of unawareness and misattribution of particular symptoms varied considerably. General unawareness dimensions showed small significant correlations with positive, cognitive and excitement factors of psychopathology, whereas these symptom factors showed higher correlations with unawareness of particular symptoms. Similarly, regression models showed a small significant predictive value of positive symptoms in the three general unawareness dimensions while a moderate one in the prediction of particular symptoms. Misattribution showed no significant correlations with any symptom factors. Results confirm that insight in schizophrenia is a multi-phased phenomenon and that unawareness into particular symptoms varies widely. The overlap between unawareness dimensions and psychopathology is small and seems to be restricted to positive and cognitive symptoms, supporting the accounts from cognitive neurosciences that suggest that besides basic cognition poor insight may be in part a failure of self-reflection or strategic metacognition. Copyright © 2017 Elsevier B.V. All rights reserved.
Physicians’ Anxiety Due to Uncertainty and Use of Race in Medical Decision-Making
Cunningham, Brooke A.; Bonham, Vence L.; Sellers, Sherrill L.; Yeh, Hsin-Chieh; Cooper, Lisa A.
2014-01-01
Background The explicit use of race in medical decision-making is contested. Researchers have hypothesized that physicians use race in care when they are uncertain. Objectives To investigate whether physician anxiety due to uncertainty is associated with a higher propensity to use race in medical decision-making. Research Design A national cross-sectional survey of general internists Subjects A national sample of 1738 clinically active general internists drawn from the SK&A physician database Measures Anxiety Due to Uncertainty (ADU) is a 5-item measure of emotional reactions to clinical uncertainty. Bonham and Sellers Racial Attributes in Clinical Evaluation (RACE) scale includes 7 items that measure self-reported use of race in medical decision-making. We used bivariate regression to test for associations between physician characteristics, ADU and RACE. Multivariate linear regression was performed to test for associations between ADU and RACE while adjusting for potential confounders. Results The mean score on ADU was 19.9 (SD=5.6). Mean score on RACE was 13.5 (SD=5.6). After adjusting for physician demographics, physicians with higher levels of ADU scored higher on RACE (+β=0.08 in RACE, p=0.04, for each 1-point increase in ADU), as did physicians who understand “race” to mean biological or genetic ancestral, rather than sociocultural, group. Physicians who graduated from a US medical school, completed fellowship, and had more white patients, scored lower on RACE. Conclusions This study demonstrates positive associations between physicians’ anxiety due to uncertainty, meanings attributed to race, and self-reported use of race in medical decision-making. Future research should examine the potential impact of these associations on patient outcomes and healthcare disparities. PMID:25025871
Hughes, Sheryl O; Power, Thomas G; O'Connor, Teresia M; Orlet Fisher, Jennifer
2015-06-01
The purpose of the present study was to examine relationships between child eating self-regulation, child non-eating self-regulation, and child BMIz in a low-income sample of Hispanic families with preschoolers. The eating in the absence of hunger task as well as parent-report of child satiety responsiveness and food responsiveness were used to assess child eating self-regulation. Two laboratory tasks assessing executive functioning, a parent questionnaire assessing child effortful control (a temperament dimension related to executive functioning), and the delay of gratification and gift delay tasks assessing child emotion regulation were used to assess child non-eating self-regulation. Bivariate correlations were run among all variables in the study. Hierarchical linear regression analyses assessed: (1) child eating self-regulation associations with the demographic, executive functioning, effortful control, and emotion regulation measures; and (2) child BMI z-score associations with executive functioning, effortful control, emotion regulation measures, and eating self-regulation measures. Within child eating self-regulation, only the two parent-report measures were related. Low to moderate positive correlations were found between measures of executive functioning, effortful control, and emotion regulation. Only three relationships were found between child eating self-regulation and other forms of child self-regulation: eating in the absence of hunger was positively associated with delay of gratification, and poor regulation on the gift delay task was associated positively with maternal reports of food responsiveness and negatively with parent-reports of satiety responsiveness. Regression analyses showed that child eating self-regulation was associated with child BMIz but other forms of child self-regulation were not. Implications for understanding the role of self-regulation in the development of child obesity are discussed. Copyright © 2015 Elsevier Ltd. All rights reserved.
Yang, Lili; Taylor, Elizabeth; Winslow, Betty; Pothier, Patricia
2018-05-22
To examine associations among blood pressure, personal and illness characteristics, illness perception and medication and self-management adherence among adults with hypertension in rural mainland China. Despite the high prevalence of hypertension in China, the control rate is only 20%. Identifying factors associated with blood pressure control is critical. Cross-sectional survey. Data were collected from 163 hypertensive adults in two rural villages in mainland China. Measures included a demographic questionnaire, the Chinese Illness-Perception Questionnaire-Revised, Medication Adherence Inventory and the Inventory of Adherence to Self-management. Height, weight and blood pressure were also measured using standard approaches. Hierarchical linear regression was used to assess the association between blood pressure and significant variables identified in bivariate analysis. The mean systolic pressure observed in this sample was147 mmHg and the diastolic mean was 81 mmHg. None of the variables analyzed were associated with systolic blood pressure. Gender, age and household annual income were associated with diastolic blood pressure, explaining 23% of the variance in the regression model. Illness coherence contributed an additional 2%. These findings suggest: (a) healthcare providers should focus on educating rural hypertensive adults about healthful diets and behaviors to manage hypertension, especially for those with high household income; (b) knowledge-based health education alone is not adequate; (c) illness perception may not be directly associated with blood pressure and; (d) the Chinese Illness-Perception Questionnaire-Revised and the Inventory of Adherence to Self-management require validation and potential revision for use with rural Chinese populations. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Linear and nonlinear regression techniques for simultaneous and proportional myoelectric control.
Hahne, J M; Biessmann, F; Jiang, N; Rehbaum, H; Farina, D; Meinecke, F C; Muller, K-R; Parra, L C
2014-03-01
In recent years the number of active controllable joints in electrically powered hand-prostheses has increased significantly. However, the control strategies for these devices in current clinical use are inadequate as they require separate and sequential control of each degree-of-freedom (DoF). In this study we systematically compare linear and nonlinear regression techniques for an independent, simultaneous and proportional myoelectric control of wrist movements with two DoF. These techniques include linear regression, mixture of linear experts (ME), multilayer-perceptron, and kernel ridge regression (KRR). They are investigated offline with electro-myographic signals acquired from ten able-bodied subjects and one person with congenital upper limb deficiency. The control accuracy is reported as a function of the number of electrodes and the amount and diversity of training data providing guidance for the requirements in clinical practice. The results showed that KRR, a nonparametric statistical learning method, outperformed the other methods. However, simple transformations in the feature space could linearize the problem, so that linear models could achieve similar performance as KRR at much lower computational costs. Especially ME, a physiologically inspired extension of linear regression represents a promising candidate for the next generation of prosthetic devices.
Unitary Response Regression Models
ERIC Educational Resources Information Center
Lipovetsky, S.
2007-01-01
The dependent variable in a regular linear regression is a numerical variable, and in a logistic regression it is a binary or categorical variable. In these models the dependent variable has varying values. However, there are problems yielding an identity output of a constant value which can also be modelled in a linear or logistic regression with…
An Expert System for the Evaluation of Cost Models
1990-09-01
contrast to the condition of equal error variance, called homoscedasticity. (Reference: Applied Linear Regression Models by John Neter - page 423...normal. (Reference: Applied Linear Regression Models by John Neter - page 125) Click Here to continue -> Autocorrelation Click Here for the index - Index...over time. Error terms correlated over time are said to be autocorrelated or serially correlated. (REFERENCE: Applied Linear Regression Models by John
Winters, Eric R; Petosa, Rick L; Charlton, Thomas E
2003-06-01
To examine whether knowledge of high school students' actions of self-regulation, and perceptions of self-efficacy to overcome exercise barriers, social situation, and outcome expectation will predict non-school related moderate and vigorous physical exercise. High school students enrolled in introductory Physical Education courses completed questionnaires that targeted selected Social Cognitive Theory variables. They also self-reported their typical "leisure-time" exercise participation using a standardized questionnaire. Bivariate correlation statistic and hierarchical regression were conducted on reports of moderate and vigorous exercise frequency. Each predictor variable was significantly associated with measures of moderate and vigorous exercise frequency. All predictor variables were significant in the final regression model used to explain vigorous exercise. After controlling for the effects of gender, the psychosocial variables explained 29% of variance in vigorous exercise frequency. Three of four predictor variables were significant in the final regression equation used to explain moderate exercise. The final regression equation accounted for 11% of variance in moderate exercise frequency. Professionals who attempt to increase the prevalence of physical exercise through educational methods should focus on the psychosocial variables utilized in this study.
Kapadia, F; Siconolfi, DE; Barton, S; Olivieri, B; Lombardo, L; Halkitis, PN
2013-01-01
Associations between social support network characteristics and sexual risk among racially/ethnically diverse young men who have sex with men (YMSM) were examined using egocentric network data from a prospective cohort study of YMSM (n=501) recruited in New York City. Bivariate and multivariable logistic regression analyses examined associations between social support network characteristics and sexual risk taking behaviors in Black, Hispanic/Latino, and White YMSM. Bivariate analyses indicated key differences in network size, composition, communication frequency and average relationship duration by race/ethnicity. In multivariable analyses, controlling for individual level sociodemographic, psychosocial and relationship factors, having a sexual partner in one’s social support network was associated with unprotected sexual behavior for both Hispanic/Latino (AOR=3.90) and White YMSM (AOR=4.93). Further examination of key network characteristics across racial/ethnic groups are warranted in order to better understand the extant mechanisms for provision of HIV prevention programming to racially/ethnically diverse YMSM at risk for HIV. PMID:23553346
Lusk, S L; Kerr, M J; Kauffman, S A
1998-07-01
The purpose of this study was to describe construction workers' use of hearing protection devices (HPDs) and determine their perceptions of noise exposure and hearing loss. Operating engineers, carpenters, and plumbers/pipe fitters in the Midwest (n = 400) completed a written questionnaire regarding their use of HPDs and their perceptions of noise exposure and hearing loss. Subjects were recruited through their trade union groups. Mean reported use of HPDs and mean perceived noise exposure were compared across trade groups. Bivariate and multivariate analysis techniques were used to assess relationships between use of HPDs and trade category, education, age, years of employment, noise exposure, and hearing loss. Bivariate analyses identified significant differences in mean use of HPDs by age, years of employment, and trade group. Multivariate logistic regression assessing the independent effects of these variables found significant differences only by trade group. Results indicate a need for significant improvement in all three trade groups' use of HPDs, and suggest a need to consider use and exposure levels, demographics, and trade group membership in designing hearing conservation programs.
Tickle, M; Moulding, G; Milsom, K; Blinkhorn, A
2000-10-14
To measure the relationship between tooth decay, contact with dental services and deprivation at electoral ward level. The study was carried out in 1998 in Ellesmere Port in the North West of England. All children younger than six years resident in Ellesmere Port registered with GDS services and those using CDS services were matched against the HA population register to identify unregistered children. Rates for children aged 3-5 years 'in contact' with primary dental care services, whether CDS or GDS, were calculated at ward level. One calibrated examiner examined all 5-year-old children in Ellesmere Port and dmft scores were calculated at ward level. Ward deprivation was measured using the Jarman score. Bivariate linear regressions at ward level were performed in turn between: dmft and Jarman score; rates for 3-5-year-olds in contact with dental services and Jarman score; and dmft and rates for 3-5-year-olds in contact with dental services. A significant linear relationship was observed between dmft and Jarman score (P=0.02, R2 = 0.43). Significant inverse relationships were found between rates for 3-5-year-olds in contact with dental services and Jarman score (P=0.001, R2 = 0.67), and also between dmft and rates for 3-5-year-olds in contact with dental services (P=0.002, R2 = 0.65). A strong inverse relationship was found between dental caries and contact with primary dental care services at electoral ward level. This relationship needs to be explored over a wider geographical area to establish if it is consistent and independent of deprivation.
Lee, Juyeon; Bahk, Jinwook; Kim, Ikhan; Kim, Yeon-Yong; Yun, Sung-Cheol; Kang, Hee-Yeon; Lee, Jeehye; Park, Jong Heon; Shin, Soon-Ae; Khang, Young-Ho
2018-03-01
Little is known about within-country variation in morbidity and mortality of cerebrovascular diseases (CVDs). Geographic differences in CVD morbidity and mortality have yet to be properly examined. This study examined geographic variation in morbidity and mortality of CVD, neighborhood factors for CVD morbidity and mortality, and the association between CVD morbidity and mortality across the 245 local districts in Korea during 2011-2015. District-level health care utilization and mortality data were obtained to estimate age-standardized CVD morbidity and mortality. The bivariate Pearson correlation was used to examine the linear relationship between district-level CVD morbidity and mortality Z-scores. Simple linear regression and multivariate analyses were conducted to investigate the associations of area characteristics with CVD morbidity, mortality, and discrepancies between morbidity and mortality. Substantial variation was found in CVD morbidity and mortality across the country, with 1074.9 excess CVD inpatients and 73.8 excess CVD deaths per 100,000 between the districts with the lowest and highest CVD morbidity and mortality, respectively. Higher rates of CVD admissions and deaths were clustered in the noncapital regions. A moderate geographic correlation between CVD morbidity and mortality was found (Pearson correlation coefficient = .62 for both genders). Neighborhood level indicators for socioeconomic disadvantages, undersupply of health care resources, and unhealthy behaviors were positively associated with CVD morbidity and mortality and the relative standing of CVD mortality vis-à-vis morbidity. Policy actions targeting life-course socioeconomic conditions, equitable distribution of health care resources, and behavioral risk factors may help reduce geographic differences in CVD morbidity and mortality in Korea. Copyright © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved.
Liu, Zuyun; Wu, Di; Huang, Jiapin; Qian, Degui; Chen, Fei; Xu, Jun; Li, Shilin; Jin, Li; Wang, Xiaofeng
2016-01-01
Sensory impairment affects an increasing number of elderly adults, with a negative psychological impact. Our objective was to examine the associations of visual and hearing impairment with subjective well-being (SWB), an important psychological concept defined by life satisfaction [LS], positive affect [PA], negative affect [NA], and affect balance [AB] among long-lived individuals (LLIs) over 95 years of age. Data on 442 LLIs from the Rugao longevity cohort, a population-based study in Rugao, China, were analyzed. Graded classifications of visual and hearing impairment (none, mild, moderate, and severe) were constructed from self-reported items. Bivariate correlation and multiple regression analysis were performed to test the associations. Approximately 66.1% and 87.3% of the subjects reported varying degrees of visual and hearing impairment. Following the degree of vision impairment, LS, PA, and AB decreased linearly, whereas NA increased linearly (all p for trend<0.05). Vision was significantly related to LS (r=0.238, p<0.001), PA (r=0.142, p<0.01), NA (r=-0.157, p<0.001), and AB (r=0.206, p<0.001). After adjustment for multiple variables including functional ability, an important factor of SWB, the associations of vision impairment with LS, NA, and AB, while diminished, still existed. Visual impairment, but not hearing impairment, was independently associated with low SWB among LLIs, and functional ability may play a mediating role in the observed relationship. The findings indicate that rehabilitation targeted for those with reduced vision and functioning in long-lived populations may be important for promoting well-being and quality of life. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Compound Identification Using Penalized Linear Regression on Metabolomics
Liu, Ruiqi; Wu, Dongfeng; Zhang, Xiang; Kim, Seongho
2014-01-01
Compound identification is often achieved by matching the experimental mass spectra to the mass spectra stored in a reference library based on mass spectral similarity. Because the number of compounds in the reference library is much larger than the range of mass-to-charge ratio (m/z) values so that the data become high dimensional data suffering from singularity. For this reason, penalized linear regressions such as ridge regression and the lasso are used instead of the ordinary least squares regression. Furthermore, two-step approaches using the dot product and Pearson’s correlation along with the penalized linear regression are proposed in this study. PMID:27212894
NASA Astrophysics Data System (ADS)
Baiyegunhi, Christopher; Liu, Kuiwu; Gwavava, Oswald
2017-11-01
Grain size analysis is a vital sedimentological tool used to unravel the hydrodynamic conditions, mode of transportation and deposition of detrital sediments. In this study, detailed grain-size analysis was carried out on thirty-five sandstone samples from the Ecca Group in the Eastern Cape Province of South Africa. Grain-size statistical parameters, bivariate analysis, linear discriminate functions, Passega diagrams and log-probability curves were used to reveal the depositional processes, sedimentation mechanisms, hydrodynamic energy conditions and to discriminate different depositional environments. The grain-size parameters show that most of the sandstones are very fine to fine grained, moderately well sorted, mostly near-symmetrical and mesokurtic in nature. The abundance of very fine to fine grained sandstones indicate the dominance of low energy environment. The bivariate plots show that the samples are mostly grouped, except for the Prince Albert samples that show scattered trend, which is due to the either mixture of two modes in equal proportion in bimodal sediments or good sorting in unimodal sediments. The linear discriminant function analysis is dominantly indicative of turbidity current deposits under shallow marine environments for samples from the Prince Albert, Collingham and Ripon Formations, while those samples from the Fort Brown Formation are lacustrine or deltaic deposits. The C-M plots indicated that the sediments were deposited mainly by suspension and saltation, and graded suspension. Visher diagrams show that saltation is the major process of transportation, followed by suspension.
Control Variate Selection for Multiresponse Simulation.
1987-05-01
M. H. Knuter, Applied Linear Regression Mfodels, Richard D. Erwin, Inc., Homewood, Illinois, 1983. Neuts, Marcel F., Probability, Allyn and Bacon...1982. Neter, J., V. Wasserman, and M. H. Knuter, Applied Linear Regression .fodels, Richard D. Erwin, Inc., Homewood, Illinois, 1983. Neuts, Marcel F...Aspects of J%,ultivariate Statistical Theory, John Wiley and Sons, New York, New York, 1982. dY Neter, J., W. Wasserman, and M. H. Knuter, Applied Linear Regression Mfodels
ERIC Educational Resources Information Center
Kobrin, Jennifer L.; Sinharay, Sandip; Haberman, Shelby J.; Chajewski, Michael
2011-01-01
This study examined the adequacy of a multiple linear regression model for predicting first-year college grade point average (FYGPA) using SAT[R] scores and high school grade point average (HSGPA). A variety of techniques, both graphical and statistical, were used to examine if it is possible to improve on the linear regression model. The results…
High correlations between MRI brain volume measurements based on NeuroQuant® and FreeSurfer.
Ross, David E; Ochs, Alfred L; Tate, David F; Tokac, Umit; Seabaugh, John; Abildskov, Tracy J; Bigler, Erin D
2018-05-30
NeuroQuant ® (NQ) and FreeSurfer (FS) are commonly used computer-automated programs for measuring MRI brain volume. Previously they were reported to have high intermethod reliabilities but often large intermethod effect size differences. We hypothesized that linear transformations could be used to reduce the large effect sizes. This study was an extension of our previously reported study. We performed NQ and FS brain volume measurements on 60 subjects (including normal controls, patients with traumatic brain injury, and patients with Alzheimer's disease). We used two statistical approaches in parallel to develop methods for transforming FS volumes into NQ volumes: traditional linear regression, and Bayesian linear regression. For both methods, we used regression analyses to develop linear transformations of the FS volumes to make them more similar to the NQ volumes. The FS-to-NQ transformations based on traditional linear regression resulted in effect sizes which were small to moderate. The transformations based on Bayesian linear regression resulted in all effect sizes being trivially small. To our knowledge, this is the first report describing a method for transforming FS to NQ data so as to achieve high reliability and low effect size differences. Machine learning methods like Bayesian regression may be more useful than traditional methods. Copyright © 2018 Elsevier B.V. All rights reserved.
Quantile Regression in the Study of Developmental Sciences
Petscher, Yaacov; Logan, Jessica A. R.
2014-01-01
Linear regression analysis is one of the most common techniques applied in developmental research, but only allows for an estimate of the average relations between the predictor(s) and the outcome. This study describes quantile regression, which provides estimates of the relations between the predictor(s) and outcome, but across multiple points of the outcome’s distribution. Using data from the High School and Beyond and U.S. Sustained Effects Study databases, quantile regression is demonstrated and contrasted with linear regression when considering models with: (a) one continuous predictor, (b) one dichotomous predictor, (c) a continuous and a dichotomous predictor, and (d) a longitudinal application. Results from each example exhibited the differential inferences which may be drawn using linear or quantile regression. PMID:24329596
Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L
2018-01-01
Aims A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R2), using R2 as the primary metric of assay agreement. However, the use of R2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. Methods We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Results Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. Conclusions The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. PMID:28747393
A SEMIPARAMETRIC BAYESIAN MODEL FOR CIRCULAR-LINEAR REGRESSION
We present a Bayesian approach to regress a circular variable on a linear predictor. The regression coefficients are assumed to have a nonparametric distribution with a Dirichlet process prior. The semiparametric Bayesian approach gives added flexibility to the model and is usefu...
Balzer, K; Kremer, L; Junghans, A; Halfens, R J G; Dassen, T; Kottner, J
2014-05-01
Nurses' clinical judgement plays a vital role in pressure ulcer risk assessment, but evidence is lacking which patient characteristics are important for nurses' perception of patients' risk exposure. To explore which patient characteristics nurses employ when assessing pressure ulcer risk without use of a risk assessment scale. Mixed methods design triangulating observational data from the control group of a quasi-experimental trial and data from semi-structured interviews with nurses. Two traumatological wards at a university hospital. Quantitative data: A consecutive sample of 106 patients matching the eligibility criteria (age ≥ 18 years, no pressure ulcers category ≥ 2 at admission and ≥ 5 days expected length of stay). Qualitative data: A purposive sample of 16 nurses. Quantitative data: Predictor variables for pressure ulcer risk were measured by study assistants at the bedside each second day. Concurrently, nurses documented their clinical judgement on patients' pressure ulcer risk by means of a 4-step global judgement scale. Bivariate correlations between predictor variables and nurses' risk estimates were established. Qualitative data: In interviews, nurses were asked to assess fictitious patients' pressure ulcer risk and to justify their risk estimates. Patient characteristics perceived as relevant for nurses' judements were thematically clustered. Triangulation: Firstly, predictors of nurses' risk estimates identified in bivariate analysis were cross-mapped with interview findings. Secondly, three models to predict nurses' risk estimates underwent multiple linear regression analysis. Nurses consider multiple patient characteristics for pressure ulcer risk assessment, but regard some conditions more important than others. Triangulation showed that these are measures reflecting patients' exposure to pressure or overall care dependency. Qualitative data furthermore indicate that nurses are likely to trade off risk-enhancing conditions against conditions perceived to be protective. Here, patients' mental capabilities like willingness to engage in one owns care seem to be particularly important. Due to missing information on these variables in the quantitative data, they could not be incorporated into triangulation. Nurses' clinical judgement draws on well-known aetiological factors, and tends to expand conditions covered by risk assessment scales. Patients' care dependency and self-care abilities seem to be core concepts for nurses' risk assessment. Copyright © 2013 Elsevier Ltd. All rights reserved.
Tang, Derek H; Colayco, Danielle C; Khalaf, Kristin M; Piercy, James; Patel, Vaishali; Globe, Denise; Ginsberg, David
2014-03-01
To evaluate the impact of urinary incontinence (UI) on healthcare resource utilization (HRU), health-related quality of life (HRQoL) and productivity measures in patients with overactive bladder (OAB). This retrospective, cross-sectional study used data from the Adelphi OAB/UI Disease Specific Programme, a multinational survey of patient- and physician-reported data, fielded between November 2010 and February 2011. The primary patient groups of interest were those with OAB, both with and without UI. Health-related quality of life and productivity measures were derived from the EuroQoL-5D, the Incontinence Quality of Life questionnaire, the Overactive Bladder Questionnaire, and the Work Productivity and Activity Impairment Questionnaire. Measures of HRU included OAB-related surgeries, OAB-related hospitalizations, incontinence pads, anticholinergic use and physician visits. Multivariate linear regression models and literature-based minimal clinically important differences were used to assess statistically significant and clinically meaningful differences in HRQoL and productivity measures between patients with OAB with UI and those without UI. A total of 1 730 patients were identified, with a mean age of 60.7 years, and 77.0% of them were women, 84.2% were non-Hispanic whites, and 71% were incontinent. Bivariate analyses showed that HRU was significantly higher among patients with OAB with UI than among those without UI in all categories except for the number of OAB-related physician visits. In both bivariate and multivariate analyses, incontinent patients presented with clinically and statistically significantly lower HRQoL and productivity measures with respect to all study endpoints, except for percentage of work time missed due to their OAB/UI. Urinary incontinence was associated with significantly higher HRU and lower HRQoL and productivity in this population of patients with OAB from five different countries. In addition to clinical considerations, the economic and humanistic impact of UI should be taken into account when evaluating treatment options for patients with OAB. © 2013 The Authors. BJU International © 2013 BJU International.
The connection between nursing diagnosis and the use of healthcare resources.
Company-Sancho, María Consuelo; Estupiñán-Ramírez, Marcos; Sánchez-Janáriz, Hilda; Tristancho-Ajamil, Rita
The health service invests up to 75% of its resources on chronic care where the focus should be on caring rather than curing. Nursing staff focuses their work on such care. Care requires being redorded in health histories through the standardized languages. These records enable useful analyses to organisational and healthcare decision-making. Our proposal is to know the association of between nursing diagnosis and a higher total expenditure on health. An observational cross-sectional analytical study was performed based on data from electronic health records in Primary Care (Drago-AP), hospital discharges (CMBD-AH) and prescriptions (REC-SCS) of patients over 50 from 2012-2013 in the Canary Islands. A descriptive, bivariate and multivariate analysis was undertaken to create a predictive model on the use of resources. Sociodemographic (age, sex, type of health-care affiliation, type of prescription charge) and nursing diagnosis (ND) recorded in late 2012. Dependent variables: Resources consumed in 2013. 582,171 patients met the criteria for inclusion. 53.0% of them were women with an average age of 64.3 years (SD 10.8years). 53.2% were pensioners. 49% of the included population had an ND, with an average of 2.1ND per patient. The average costs per patient were 1824.62€ (with a median of 827.5€) 25 and 27 percentiles of 264.1€ and 1824.7€, respectively. The bivariate analysis showed a significant correlation between these expenses and all the demographic variables; the expenses increased when a nursing diagnosis has been made (Spearman's rank=0.37: the more diagnoses, the more expenses). In the multivariate analysis, a first linear regression with the sociodemographic variables as independent variables explains 13.7% of the variability of the logarithm of the full costs (R 2 =0.137). If we add to this model the presence of nursing diagnoses, the explanatory capacity reaches 19.77% (R 2 =0.1977). Compared with a model that only consists of sociodemographic variables, nursing diagnoses can enhance the explanatory capacity of the use of healthcare resources. Copyright © 2017 Elsevier España, S.L.U. All rights reserved.
Siegrist, Karin; Millier, Aurelie; Amri, Ikbal; Aballéa, Samuel; Toumi, Mondher
2015-12-30
The lack of social contacts may be an important element in the presumed vicious circle aggravating, or at least stabilising negative symptoms in patients with schizophrenia. A European 2-year cohort study collected negative symptom scores, psychosocial functioning scores, objective social contact frequency scores and quality of life scores every 6 months. Bivariate analyses, correlation analyses, multivariate regressions and random effects regressions were conducted to describe relations between social contact and outcomes of interest and to gain a better understanding of this relation over time. Using data from 1208 patients with schizophrenia, a link between social contact frequency and negative symptom scores, functioning and quality of life at baseline was established. Regression models confirmed the significant association between social contact and negative symptoms as well as psychosocial functioning. This study aimed at demonstrating the importance of social contact for deficient behavioural aspects of schizophrenia. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.
Kumar, K Vasanth; Sivanesan, S
2006-08-25
Pseudo second order kinetic expressions of Ho, Sobkowsk and Czerwinski, Blanachard et al. and Ritchie were fitted to the experimental kinetic data of malachite green onto activated carbon by non-linear and linear method. Non-linear method was found to be a better way of obtaining the parameters involved in the second order rate kinetic expressions. Both linear and non-linear regression showed that the Sobkowsk and Czerwinski and Ritchie's pseudo second order model were the same. Non-linear regression analysis showed that both Blanachard et al. and Ho have similar ideas on the pseudo second order model but with different assumptions. The best fit of experimental data in Ho's pseudo second order expression by linear and non-linear regression method showed that Ho pseudo second order model was a better kinetic expression when compared to other pseudo second order kinetic expressions. The amount of dye adsorbed at equilibrium, q(e), was predicted from Ho pseudo second order expression and were fitted to the Langmuir, Freundlich and Redlich Peterson expressions by both linear and non-linear method to obtain the pseudo isotherms. The best fitting pseudo isotherm was found to be the Langmuir and Redlich Peterson isotherm. Redlich Peterson is a special case of Langmuir when the constant g equals unity.
2015-07-15
Long-term effects on cancer survivors’ quality of life of physical training versus physical training combined with cognitive-behavioral therapy ...COMPARISON OF NEURAL NETWORK AND LINEAR REGRESSION MODELS IN STATISTICALLY PREDICTING MENTAL AND PHYSICAL HEALTH STATUS OF BREAST...34Comparison of Neural Network and Linear Regression Models in Statistically Predicting Mental and Physical Health Status of Breast Cancer Survivors
Prediction of the Main Engine Power of a New Container Ship at the Preliminary Design Stage
NASA Astrophysics Data System (ADS)
Cepowski, Tomasz
2017-06-01
The paper presents mathematical relationships that allow us to forecast the estimated main engine power of new container ships, based on data concerning vessels built in 2005-2015. The presented approximations allow us to estimate the engine power based on the length between perpendiculars and the number of containers the ship will carry. The approximations were developed using simple linear regression and multivariate linear regression analysis. The presented relations have practical application for estimation of container ship engine power needed in preliminary parametric design of the ship. It follows from the above that the use of multiple linear regression to predict the main engine power of a container ship brings more accurate solutions than simple linear regression.
ERIC Educational Resources Information Center
Li, Deping; Oranje, Andreas
2007-01-01
Two versions of a general method for approximating standard error of regression effect estimates within an IRT-based latent regression model are compared. The general method is based on Binder's (1983) approach, accounting for complex samples and finite populations by Taylor series linearization. In contrast, the current National Assessment of…
Ernst, Anja F; Albers, Casper J
2017-01-01
Misconceptions about the assumptions behind the standard linear regression model are widespread and dangerous. These lead to using linear regression when inappropriate, and to employing alternative procedures with less statistical power when unnecessary. Our systematic literature review investigated employment and reporting of assumption checks in twelve clinical psychology journals. Findings indicate that normality of the variables themselves, rather than of the errors, was wrongfully held for a necessary assumption in 4% of papers that use regression. Furthermore, 92% of all papers using linear regression were unclear about their assumption checks, violating APA-recommendations. This paper appeals for a heightened awareness for and increased transparency in the reporting of statistical assumption checking.
Ernst, Anja F.
2017-01-01
Misconceptions about the assumptions behind the standard linear regression model are widespread and dangerous. These lead to using linear regression when inappropriate, and to employing alternative procedures with less statistical power when unnecessary. Our systematic literature review investigated employment and reporting of assumption checks in twelve clinical psychology journals. Findings indicate that normality of the variables themselves, rather than of the errors, was wrongfully held for a necessary assumption in 4% of papers that use regression. Furthermore, 92% of all papers using linear regression were unclear about their assumption checks, violating APA-recommendations. This paper appeals for a heightened awareness for and increased transparency in the reporting of statistical assumption checking. PMID:28533971
Estimating linear temporal trends from aggregated environmental monitoring data
Erickson, Richard A.; Gray, Brian R.; Eager, Eric A.
2017-01-01
Trend estimates are often used as part of environmental monitoring programs. These trends inform managers (e.g., are desired species increasing or undesired species decreasing?). Data collected from environmental monitoring programs is often aggregated (i.e., averaged), which confounds sampling and process variation. State-space models allow sampling variation and process variations to be separated. We used simulated time-series to compare linear trend estimations from three state-space models, a simple linear regression model, and an auto-regressive model. We also compared the performance of these five models to estimate trends from a long term monitoring program. We specifically estimated trends for two species of fish and four species of aquatic vegetation from the Upper Mississippi River system. We found that the simple linear regression had the best performance of all the given models because it was best able to recover parameters and had consistent numerical convergence. Conversely, the simple linear regression did the worst job estimating populations in a given year. The state-space models did not estimate trends well, but estimated population sizes best when the models converged. We found that a simple linear regression performed better than more complex autoregression and state-space models when used to analyze aggregated environmental monitoring data.
Angore, Banchalem Nega; Tufa, Efrata Girma; Bisetegen, Fithamlak Solomon
2018-04-19
Reducing maternal mortality and improving maternal health care through increased utilization of postnatal care utilization is a global and local priority. However studies that have been carried out in Ethiopia regarding determinants are limited. So This study aims to assess the magnitude of postnatal care utilization and its determinants in Debre Birhan Town, North Ethiopia. A community-based cross-sectional study was conducted from March 1 to April 25, 2015, in Debre Birhan Town. Data were collected through face-to-face interviews using structured pre-tested questionnaires. The data were entered and cleaned in Epi Info version 3.5 and analyzed using SPSS version 20. Bivariate and multiple logistic regression analyses were used. Variable with p value less than or equal to 0.2 at bivariate analysis were entered into multiple logistic regression. Significance was declared at 0.05 in multiple logistic regressions and considered to be an independent factor. From the total respondents, we found that 327 (83.3%) mothers utilized the postnatal care services. Single mothers were less likely to utilize postnatal care services than those mothers who are married and live together [adjusted odds ratio (AOR) = 0.06, 95% CI (0.01, 0.45)]. This study revealed that respondent's knowledge about postnatal care services is an important predictor of postnatal care utilization [AOR = 0.03, 95% CI (0.00, 0.44)] and mothers who delivered in a health care facility were more likely to receive PNC than mothers who did not deliver in a health care facility [AOR = 0.65, 95% CI (0.58, 0.94)]. The postnatal care utilization rate in Debre Birhan town was 83.3%. Marital status, maternal knowledge, and place of delivery were predictors of postnatal care service utilization. So specific attention should be directed towards the improvement of women's education since the perception of the need for PNC services were positively correlated with the mother's education.
Jegan, Nikita Roman A; Brugger, Markus; Viniol, Annika; Strauch, Konstantin; Barth, Jürgen; Baum, Erika; Leonhardt, Corinna; Becker, Annette
2017-03-20
Utilizing psychological resources when dealing with chronic low back pain might aid the prevention of disability. The observational study at hand examined the longitudinal impact of resilience and coping resources on disability in addition to established risk factors. Four hundred eighty four patients with chronic low back pain (>3 months) were recruited in primary care practices and followed up for one year. Resilience, coping, depression, somatization, pain and demographic variables were measured at baseline. At follow-up (participation rate 89%), data on disability was collected. We first calculated bivariate correlations of all the predictors with each other and with follow-up disability. We then used a multiple regression to evaluate the impact of all the predictors on disability together. More than half of the followed up sample showed a high degree of disability at baseline (53.7%) and had suffered for more than 10 years from pain (50.4%). Besides gender all of the predictors were bivariately associated with follow-up disability. However in the main analysis (multiple regression), disability at follow up was only predicted by baseline disability, age and somatization. There was no relationship between resilience and disability, nor between coping resources and disability. Although it is known that there are cross-sectional relationships between resilience/coping resources and disability we were not able to replicate it in the multiple regression. This can have several reasons: a) the majority of patients in our sample were much more disabled and suffered for a longer time than in other studies. Therefore our results might be limited to this specific population and resilience and coping resources might still have a protective influence in acute or subacute populations. b) We used a rather broad operationalization of resilience. There is emerging evidence that focusing on more concrete sub facets like (pain) self-efficacy and acceptance might be more beneficial. German Clinical Trial Register, DRKS00003123 (June 28th 2011).
Dental Workforce Availability and Dental Services Utilization in Appalachia: A Geospatial Analysis
Feng, Xue; Sambamoorthi, Usha; Wiener, R. Constance
2016-01-01
Objectives There is considerable variation in dental services utilization across Appalachian counties, and a plausible explanation is that individuals in some geographical areas do not utilize dental care due to dental workforce shortage. We conducted an ecological study on dental workforce availability and dental services utilization in Appalachia. Methods We derived county-level (n = 364) data on demographic, socio-economic characteristics and dental services utilization in Appalachia from the 2010 Behavioral Risk Factor Surveillance System (BRFSS) using person-level data. We obtained county-level dental workforce availability and physician-to-population ratio estimates from Area Health Resource File, and linked them to the county-level BRFSS data. The dependent variable was the proportion using dental services within the last year in each county (ranging from 16.6% to 91.0%). We described the association between dental workforce availability and dental services utilization using ordinary least squares regression and spatial regression techniques. Spatial analyses consisted of bivariate Local Indicators of Spatial Association (LISA) and geographically weighted regression (GWR). Results Bivariate LISA showed that counties in the central and southern Appalachian regions had significant (p < .05) low-low spatial clusters (low dental workforce availability, low percent dental services utilization). GWR revealed considerable local variations in the association between dental utilization and dental workforce availability. In the multivariate GWR models, 8.5% (t-statistics >1.96) and 13.45% (t-statistics >1.96) of counties showed positive and statistically significant relationships between the dental services utilization and workforce availability of dentists and dental hygienists, respectively. Conclusions Dental workforce availability was associated with dental services utilization in the Appalachian region; however, this association was not statistically significant in all counties. The findings suggest that program and policy efforts to improve dental services utilization need to focus on factors other than increasing the dental workforce availability for many counties in Appalachia. PMID:27957773
A case-control study of determinants for high and low dental caries prevalence in Nevada youth
2010-01-01
Background The main purpose of this study was to compare the 30% of Nevada Youth who presented with the highest Decayed Missing and Filled Teeth (DMFT) index to a cohort who were caries free and to national NHANES data. Secondly, to explore the factors associated with higher caries prevalence in those with the highest DMFT scores compared to the caries-free group. Methods Over 4000 adolescents between ages 12 and 19 (Case Group: N = 2124; Control Group: N = 2045) received oral health screenings conducted in public/private middle and high schools in Nevada in 2008/2009 academic year. Caries prevalence was computed (Untreated decay scores [D-Score] and DMFT scores) for the 30% of Nevada Youth who presented with the highest DMFT score (case group) and compared to the control group (caries-free) and to national averages. Bivariate and multivariate logistic regression was used to analyze the relationship between selected variables and caries prevalence. Results A majority of the sample was non-Hispanic (62%), non-smokers (80%), and had dental insurance (70%). With the exception of gender, significant differences in mean D-scores were found in seven of the eight variables. All variables produced significant differences between the case and control groups in mean DMFT Scores. With the exception of smoking status, there were significant differences in seven of the eight variables in the bivariate logistic regression. All of the independent variables remained in the multivariate logistic regression model contributing significantly to over 40% of the variation in the increased DMFT status. The strongest predictors for the high DMFT status were racial background, age, fluoridated community, and applied sealants respectively. Gender, second hand smoke, insurance status, and tobacco use were significant, but to a lesser extent. Conclusions Findings from this study will aid in creating educational programs and other primary and secondary interventions to help promote oral health for Nevada youth, especially focusing on the subgroup that presents with the highest mean DMFT scores. PMID:21067620
Comparing The Effectiveness of a90/95 Calculations (Preprint)
2006-09-01
Nachtsheim, John Neter, William Li, Applied Linear Statistical Models , 5th ed., McGraw-Hill/Irwin, 2005 5. Mood, Graybill and Boes, Introduction...curves is based on methods that are only valid for ordinary linear regression. Requirements for a valid Ordinary Least-Squares Regression Model There... linear . For example is a linear model ; is not. 2. Uniform variance (homoscedasticity
Correlation and simple linear regression.
Zou, Kelly H; Tuncali, Kemal; Silverman, Stuart G
2003-06-01
In this tutorial article, the concepts of correlation and regression are reviewed and demonstrated. The authors review and compare two correlation coefficients, the Pearson correlation coefficient and the Spearman rho, for measuring linear and nonlinear relationships between two continuous variables. In the case of measuring the linear relationship between a predictor and an outcome variable, simple linear regression analysis is conducted. These statistical concepts are illustrated by using a data set from published literature to assess a computed tomography-guided interventional technique. These statistical methods are important for exploring the relationships between variables and can be applied to many radiologic studies.
Non-medical use of prescription opioids among Ontario adults: data from the 2008/2009 CAMH Monitor.
Shield, Kevin D; Ialomiteanu, Anca; Fischer, Benedikt; Mann, Robert E; Rehm, Jürgen
2011-01-01
There are indications that non-medical prescription opioid analgesics use (NMPOU) in the general population has increased in Canada in recent years; however, existing estimates have limitations. Thus our objectives are to determine prevalence and associated demographics of 1) prescription opioid analgesics (PO) use, 2) NMPOU, and 3) use of PO for intoxication purposes in the adult population in Ontario. Prevalence and the associations between sex, age, region, income, cigarette smoking, binge drinking, cannabis use and psychological distress with the above-noted types of PO use were assessed using data from the 2008 and 2009 samples (n = 2030) of the CAMH Monitor. The statistical significance of the associations for all types of PO use was tested through bivariate associations using chi-square tests, and a two-step logistic regression was performed to test if demographics are associated with NMPOU. The prevalence of PO use was 21.3% (95% CI 19.1-23.4), and the prevalence of NMPOU was 2.0% (95% CI 1.2-2.8) of Ontario adults. There were no significant differences between men and women for either PO use or NMPOU. Bivariate associations indicated that NMPOU was associated with tobacco and cannabis use and psychological distress in men. Logistic regression showed a significant association between NMPOU and each of age, cannabis use, and psychological distress in men. NMPOU is an emerging epidemic in Canada across all income and age groups, and is associated with other substance use and mental health problems. Improved survey designs are required for more accurate population estimates of NMPOU.
A comparison of unemployed job-seekers with and without social anxiety
Himle, Joseph A; Weaver, Addie; Bybee, Deborah; O'Donnell, Lisa; Vlnka, Sarah; Laviolette, Wayne; Steinberger, Edward; Zipora, Golenberg; Levine, Debra Siegel
2014-01-01
Objective Literature consistently demonstrates that social anxiety disorder has substantial negative impacts on occupational functioning. However, to date, no identified empirical work has focused on understanding the specific nature of vocational problems among persons with social anxiety disorder. This study examines the association between employment-related factors (i.e., barriers to employment; skills related to employment; and job aspirations) and social anxiety among a sample of adults seeking vocational rehabilitation services. Methods Data from intake assessments, including a screen for social anxiety disorder, of 265 low-income, unemployed adults who initiated vocational rehabilitation services in urban Michigan was examined to assess differences in barriers to employment, employment skills, job aspirations, and demographic characteristics among participants who screened positive for social anxiety disorder compared to those who did not. Bivariate and multiple logistic regression analyses were performed. Results Multiple logistic regression analysis revealed that greater perceived experience and skill barriers to employment, fewer skills related to social-type occupations, and less education were significantly associated with social anxiety, after adjusting for other factors. Bivariate analysis also suggested that participants who screened positive for social anxiety disorder were significantly less likely to aspire to social jobs. Conclusions Employment-related factors likely impacting occupational functioning were significantly different between persons with and without social anxiety problems. Identifying these differences in employment barriers, skills, and job aspirations offer potentially important functional targets for psychosocial interventions aimed at social anxiety disorder and suggest the need for vocational service professionals to assess and address social anxiety among their clients. PMID:24733524
Prevalence of cognitive and functional impairment in a community sample in Ribeirão Preto, Brazil.
Lopes, Marcos A; Hototian, Sergio R; Bustamante, Sonia E Z; Azevedo, Dionísio; Tatsch, Mariana; Bazzarella, Mário C; Litvoc, Júlio; Bottino, Cássio M C
2007-08-01
This study aimed at estimating the prevalence of cognitive and functional impairment (CFI) in a community sample in Ribeirão Preto, Brazil, evaluating its distribution in relation to various socio-demographic and clinical factors. The population was a representative sample aged 60 and older, from three different socio-economic classes. Cluster sampling was applied. Instruments used to select CFI (a syndromic category that does not exclude dementia): 'Mini Mental State Examination' (MMSE), 'Fuld Object Memory Evaluation' (FOME), 'Informant Questionnaire on Cognitive Decline in the Elderly' (IQCODE), 'Bayer Activities of Daily Living Scale' (B-ADL) and clinical interviews. The data obtained were submitted to bivariate and logistic regression analysis. A sample of 1.145 elderly persons was evaluated, with a mean age of 70.9 years (60-100; DP: 7.7); 63.4% were female, and 52.8% had up to 4 years of schooling. CFI prevalence was 18.9% (n = 217). Following logistic regression analysis, higher age, low education, stroke, epilepsy and depression were associated with CFI. Female sex, widowhood, low social class and head trauma were associated with CFI only on bivariate analysis. CFI prevalence results were similar to those found by studies in Brazil, Puerto Rico and Malaysia. Cognitive and functional impairment is a rather heterogeneous condition which may be associated with various clinical conditions found in the elderly population. Due to its high prevalence and association with higher mortality and disability rates, this clinical syndrome should receive more attention on public health intervention planning.
Cooper, Denise C; Ziegler, Michael G; Milic, Milos S; Ancoli-Israel, Sonia; Mills, Paul J; Loredo, José S; Von Känel, Roland; Dimsdale, Joel E
2014-02-01
Endothelial function typically precedes clinical manifestations of cardiovascular disease and provides a potential mechanism for the associations observed between cardiovascular disease and sleep quality. This study examined how subjective and objective indicators of sleep quality relate to endothelial function, as measured by brachial artery flow-mediated dilation (FMD). In a clinical research centre, 100 non-shift working adults (mean age: 36 years) completed FMD testing and the Pittsburgh Sleep Quality Index, along with a polysomnography assessment to obtain the following measures: slow wave sleep, percentage rapid eye movement (REM) sleep, REM sleep latency, total arousal index, total sleep time, wake after sleep onset, sleep efficiency and apnea-hypopnea index. Bivariate correlations and follow-up multiple regressions examined how FMD related to subjective (i.e., Pittsburgh Sleep Quality Index scores) and objective (i.e., polysomnography-derived) indicators of sleep quality. After FMD showed bivariate correlations with Pittsburgh Sleep Quality Index scores, percentage REM sleep and REM latency, further examination with separate regression models indicated that these associations remained significant after adjustments for sex, age, race, hypertension, body mass index, apnea-hypopnea index, smoking and income (Ps < 0.05). Specifically, as FMD decreased, scores on the Pittsburgh Sleep Quality Index increased (indicating decreased subjective sleep quality) and percentage REM sleep decreased, while REM sleep latency increased (Ps < 0.05). Poorer subjective sleep quality and adverse changes in REM sleep were associated with diminished vasodilation, which could link sleep disturbances to cardiovascular disease. © 2013 European Sleep Research Society.
[Bone mineral density in overweight and obese adolescents].
Cobayashi, Fernanda; Lopes, Luiz A; Taddei, José Augusto de A C
2005-01-01
To study bone density as a concomitant factor for obesity in post-pubertal adolescents, controlling for other variables that may interfere in such a relation. Study comprising 83 overweight and obese adolescents (BMI > or = P85) and 89 non obese ones (P5 < or = BMI < or = P85). Cases and controls were selected out of 1,420 students (aged 14-19) from a public school in the city of São Paulo. The bone mineral density of the lumbar spine (L2-L4 in g/cm2) was assessed by dual-energy x-ray absorptiometry (LUNARtrade mark DPX-L). The variable bone density was dichotomized using 1.194 g/cm2 as cutoff point. Bivariate analyses were conducted considering the prevalence of overweight and obesity followed by multivariate analysis (logistic regression) according to a hierarchical conceptual model. The prevalence of bone density above the median was twice more frequent among cases (69.3%) than among controls (32.1%). In the bivariate analysis such prevalence resulted in an odds ratio (OR) of 4.78. The logistic regression model showed that the association between obesity and mineral density is yet more intense with an OR of 6.65 after the control of variables related to sedentary lifestyle and intake of milk and dairy products. Obese and overweight adolescents in the final stages of sexual maturity presented higher bone mineral density in relation to their normal-weight counterparts; however, cohort studies will be necessary to evaluate the influence of such characteristic on bone resistance in adulthood and, consequently, on the incidence of osteopenia and osteoporosis at older ages.
Wartberg, Lutz; Kriston, Levente; Kammerl, Rudolf
2017-07-01
Internet Gaming Disorder (IGD) has been included in the current edition of the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-5). In the present study, the relationship among social support, friends only known through the Internet, health-related quality of life, and IGD in adolescence was explored for the first time. For this purpose, 1,095 adolescents aged from 12 to 14 years were surveyed with a standardized questionnaire concerning IGD, self-perceived social support, proportion of friends only known through the Internet, and health-related quality of life. The authors conducted unpaired t-tests, a chi-square test, as well as correlation and logistic regression analyses. According to the statistical analyses, adolescents with IGD reported lower self-perceived social support, more friends only known through the Internet, and a lower health-related quality of life compared with the group without IGD. Both in bivariate and multivariate logistic regression models, statistically significant associations between IGD and male gender, a higher proportion of friends only known through the Internet, and a lower health-related quality of life (multivariate model: Nagelkerke's R 2 = 0.37) were revealed. Lower self-perceived social support was related to IGD in the bivariate model only. In summary, quality of life and social aspects seem to be important factors for IGD in adolescence and therefore should be incorporated in further (longitudinal) studies. The findings of the present survey may provide starting points for the development of prevention and intervention programs for adolescents affected by IGD.
Resnick, Cory M; Dentino, Kelley; Katz, Eliot; Mulliken, John B; Padwa, Bonnie L
2016-09-01
Tongue-lip adhesion (TLA) is commonly used to relieve obstructive sleep apnea (OSA) in infants with Robin sequence (RS), but few studies have evaluated its efficacy with objective measures. The purpose of this study was to measure TLA outcomes using polysomnography. Our hypothesis was that TLA relieves OSA in most infants. This is a retrospective study of infants with RS who underwent TLA from 2011 to 2014 and had at least a postoperative polysomnogram. Predictor variables included demographic and birth characteristics, surgeon, syndromic diagnosis, GILLS score, preoperative OSA severity, and clinical course. A successful outcome was defined as minimal OSA (apnea-hypopnea index score < 5) on postoperative polysomnogram and no need for additional airway intervention. Descriptive, bivariate, and regression statistics were computed, and statistical significance was set at P < .05. Eighteen subjects who had TLA at a mean age of 28 ± 4.7 days were included. Thirteen (72.2%) had a confirmed or suspected syndrome, and the mean GILLS score was 3 ± 0.3. All parameters trended toward improvement from the preoperative to postoperative polysomnograms, and improvement in OSA severity, oxygen saturation nadir, and arousals per hour was statistically significant (P < .02). This effect was significant across categories of surgeon, syndrome, and GILLS score. Nine subjects (50%) met the criteria for a successful outcome. Bivariate and regression analyses did not demonstrate a significant relationship between success and any predictor variable. TLA improved airway obstruction in all infants with RS but resolved OSA in only nine patients, and success was unpredictable.
Determinants of use of health facility for childbirth in rural Hadiya zone, Southern Ethiopia.
Asseffa, Netsanet Abera; Bukola, Fawole; Ayodele, Arowojolu
2016-11-16
Maternal mortality remains a major global public health concern despite many international efforts. Facility-based childbirth increases access to appropriate skilled attendance and emergency obstetric care services as the vast majority of obstetric complications occur during delivery. The purpose of the study was to determine the proportion of facility delivery and assess factors influencing utilization of health facility for childbirth. A cross-sectional study was conducted in two rural districts of Hadiya zone, southern Ethiopia. Participants who delivered within three years of the survey were selected by stratified random sampling. Trained interviewers administered a pre-tested semi-structured questionnaire. We employed bivariate analysis and logistic regression to identify determinants of facility-based delivery. Data from 751 participants showed that 26.9% of deliveries were attended in health facilities. In bivariate analysis, maternal age, education, husband's level of education, possession of radio, antenatal care, place of recent ANC attended, planned pregnancy, wealth quintile, parity, birth preparedness and complication readiness, being a model family and distance from the nearest health facility were associated with facility delivery. On multiple logistic regression, age, educational status, antenatal care, distance from the nearest health facility, wealth quintile, being a model family, planned pregnancy and place of recent ANC attended were the determinants of facility-based childbirth. Efforts to improve institutional deliveries in the region must strengthen initiatives that promote female education, opportunities for wealth creation, female empowerment and increased uptake of family planning among others. Service related barriers and cultural influences on the use of health facility for childbirth require further evaluation.
Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L
2018-02-01
A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R 2 ), using R 2 as the primary metric of assay agreement. However, the use of R 2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
2017-10-01
ENGINEERING CENTER GRAIN EVALUATION SOFTWARE TO NUMERICALLY PREDICT LINEAR BURN REGRESSION FOR SOLID PROPELLANT GRAIN GEOMETRIES Brian...author(s) and should not be construed as an official Department of the Army position, policy, or decision, unless so designated by other documentation...U.S. ARMY ARMAMENT RESEARCH, DEVELOPMENT AND ENGINEERING CENTER GRAIN EVALUATION SOFTWARE TO NUMERICALLY PREDICT LINEAR BURN REGRESSION FOR SOLID
Linear regression in astronomy. II
NASA Technical Reports Server (NTRS)
Feigelson, Eric D.; Babu, Gutti J.
1992-01-01
A wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.
A Constrained Linear Estimator for Multiple Regression
ERIC Educational Resources Information Center
Davis-Stober, Clintin P.; Dana, Jason; Budescu, David V.
2010-01-01
"Improper linear models" (see Dawes, Am. Psychol. 34:571-582, "1979"), such as equal weighting, have garnered interest as alternatives to standard regression models. We analyze the general circumstances under which these models perform well by recasting a class of "improper" linear models as "proper" statistical models with a single predictor. We…
On the design of classifiers for crop inventories
NASA Technical Reports Server (NTRS)
Heydorn, R. P.; Takacs, H. C.
1986-01-01
Crop proportion estimators that use classifications of satellite data to correct, in an additive way, a given estimate acquired from ground observations are discussed. A linear version of these estimators is optimal, in terms of minimum variance, when the regression of the ground observations onto the satellite observations in linear. When this regression is not linear, but the reverse regression (satellite observations onto ground observations) is linear, the estimator is suboptimal but still has certain appealing variance properties. In this paper expressions are derived for those regressions which relate the intercepts and slopes to conditional classification probabilities. These expressions are then used to discuss the question of classifier designs that can lead to low-variance crop proportion estimates. Variance expressions for these estimates in terms of classifier omission and commission errors are also derived.
The impact of professional identity on role stress in nursing students: A cross-sectional study.
Sun, Li; Gao, Ying; Yang, Juan; Zang, Xiao-Ying; Wang, Yao-Gang
2016-11-01
As newcomers to the clinical workplace, nursing students will encounter a high degree of role stress, which is an important predictor of burnout and engagement. Professional identity is theorised to be a key factor in providing high-quality care to improve patient outcomes and is thought to mediate the negative effects of a high-stress workplace and improve clinical performance and job retention. To investigate the level of nursing students' professional identity and role stress at the end of the first sub-internship, and to explore the impact of the nursing students' professional identity and other characteristics on role stress. A cross-sectional study. Three nursing schools in China. Nursing students after a 6-month sub-internship in a general hospital (n=474). The Role Stress Scale (score range: 12-60) and the Professional Identity Questionnaire for Nursing students (score range: 17-85) were used to investigate the levels of nursing students' role stress and professional identity. Higher scores indicated higher levels of role stress and professional identity. Basic demographic information about the nursing students was collected. The Pearson correlation, point-biserial correlation and multiple linear regression analysis were used to analyse the data. The mean total scores of the Role Stress Scale and Professional Identity Questionnaire for Nursing Students were 34.04 (SD=6.57) and 57.63 (SD=9.63), respectively. In the bivariate analyses, the following independent variables were found to be significantly associated with the total score of the Role Stress Scale: the total score of the Professional Identity Questionnaire for Nursing Students (r=-0.295, p<0.01), age (r=0.145, p<0.01), whether student was an only child or not (r=-0.114, p<0.05), education level (r=0.295, p<0.01) and whether student had experience in community organisations or not (r=0.151, p<0.01). In the multiple linear regression analysis, the total score of the Professional Identity Questionnaire for Nursing Students (standardised coefficient Beta: -0.260, p<0.001), education level (standardised coefficient Beta: 0.212, p<0.001) and whether or not student had experience in community organisations (standardised coefficient Beta: 0.107, p<0.016) were the factors significantly associated with the total score of the Role Stress Scale. The multiple linear regression model explained 18.2% (adjusted R 2 scores 16.5%) of the Role Stress Scale scores variance. The nursing students' level of role stress at the end of the first sub-internship was high. The students with higher professional identity values had lower role stress levels. Compared with other personal characteristics, professional identity and education level had the strongest impact on the nursing students' level of role stress. This is a new perspective that shows that developing and improving professional identity may prove helpful for nursing students in managing role stress. Copyright © 2016 Elsevier Ltd. All rights reserved.
Sanchez-Moreno, J; Bonnin, C M; González-Pinto, A; Amann, B L; Solé, B; Balanzá-Martinez, V; Arango, C; Jiménez, E; Tabarés-Seisdedos, R; Garcia-Portilla, M P; Ibáñez, A; Crespo, J M; Ayuso-Mateos, J L; Martinez-Aran, A; Torrent, C; Vieta, E
2018-05-03
The current investigation aimed at studying the sociodemographic, clinical, and neuropsychological variables related to functional outcome in a sample of euthymic patients with bipolar disorder(BD) presenting moderate-severe levels of functional impairment. Two-hundred and thirty-nine participants with BD disorders and with Functioning Assessment Short Test(FAST) scores equal or above 18 were administered a clinical and diagnostic interview, and the administration of mood measure scales and a comprehensive neuropsychological battery. Analyses involved preliminary Pearson bivariate correlations to identify sociodemographic and clinical variables associated with the FAST total score. Regarding neuropsychological variables, a principal component analysis (PCA) was performed to group the variables in orthogonal factors. Finally, a hierarchical multiple regression was run. The best fitting model for the variables associated with functioning was a linear combination of gender, age, estimated IQ, Hamilton Depression Rating Scale (HAM-D), number of previous manic episodes, Factor 1 and Factor 2 extracted from the PCA. The model, including all these previous variables, explained up to 29.4% of the observed variance. Male gender, older age, lower premorbid IQ, subdepressive symptoms, higher number of manic episodes, and lower performance in verbal memory, working memory, verbal fluency, and processing speed were associated with lower functioning in patients with BD. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Roy, Audrey; Gabison, Sharon; Verrier, Molly C.
2016-01-01
Objectives. To quantify the association between performance-based manual wheelchair propulsion tests (20 m propulsion test, slalom test, and 6 min propulsion test), trunk and upper extremity (U/E) strength, and seated reaching capability and to establish which ones of these variables best predict performance at these tests. Methods. 15 individuals with a spinal cord injury (SCI) performed the three wheelchair propulsion tests prior to discharge from inpatient SCI rehabilitation. Trunk and U/E strength and seated reaching capability with unilateral hand support were also measured. Bivariate correlation and multiple linear regression analyses allowed determining the best determinants and predictors, respectively. Results. The performance at the three tests was moderately or strongly correlated with anterior and lateral flexion trunk strength, anterior seated reaching distance, and the shoulder, elbow, and handgrip strength measures. Shoulder adductor strength-weakest side explained 53% of the variance on the 20-meter propulsion test-maximum velocity. Shoulder adductor strength-strongest side and forward seated reaching distance explained 71% of the variance on the slalom test. Handgrip strength explained 52% of the variance on the 6-minute propulsion test. Conclusion. Performance at the manual wheelchair propulsion tests is explained by a combination of factors that should be considered in rehabilitation. PMID:27635262
Social determinants of leprosy in a hyperendemic State in North Brazil
Monteiro, Lorena Dias; Mota, Rosa Maria Salani; Martins-Melo, Francisco Rogerlândio; Alencar, Carlos Henrique; Heukelbach, Jorg
2017-01-01
ABSTRACT OBJECTIVE To identify the socioeconomic, demographic, operational, and health service-related factors associated with the occurrence of leprosy in a hyperendemic State in North Brazil. METHODS This is an ecological study based on secondary data from the Sistema de Informações de Agravos de Notificação in municipalities of the State of Tocantins from 2001 to 2012. Units of analysis were the 139 municipalities of the State. Negative binomial log linear regression models were used to estimate incidence rate ratios. RESULTS In bivariate analysis, the incidence rate ratios were significantly higher for municipalities with higher income ratio of the poorest 20.0% (1.47; 95%CI 1.19–1.81) and better Municipal Human Development Index (1.53; 95%CI 1.14–2.06). In multivariate analysis, the incidence rate ratios were significantly higher in municipalities with higher proportion of immigrants (1.31; 95%CI 1.11–1.55) and higher proportion of households with waste collection (1.37; 95%CI 1.11–1.69). There was a significant reduction in the incidence rate ratio with increased coverage of the Bolsa Família Program (0.98; 95%CI 0.96–0.99). CONCLUSIONS Control programs need to focus on activities in municipalities of greater social vulnerability with intersectoral investment for the improvement of the living conditions of the population. PMID:28746575
Association of Personality Traits with Elder Self-Neglect in a Community Dwelling Population
Dong, XinQi; Simon, Melissa; Wilson, Robert; Beck, Todd; McKinell, Kelly; Evans, Denis
2010-01-01
Objective Elder self-neglect is an important public health issue. However, little is known about the association between personality traits and risk of elder self-neglect among community-dwelling populations. The objectives of this study are: 1) to examine the association of personality traits with elder self-neglect and 2) to examine the association of personality traits with elder self-neglect severity. Methods Population-based study conducted from 1993–2005 of community-dwelling older adults (N=9,056) participating in the Chicago Health Aging Project (CHAP). Subsets of the CHAP participants (N=1,820) were identified for suspected self-neglect by social services agency, which assessed the severity. Personality traits assessed included neuroticism, extraversion, rigidity and information processing. Logistic and linear regressions were used to assess these associations. Results In the bivariate analyses, personality traits (neuroticism, extraversion, information processing, and rigidity) were significantly associated with increased risk of elder self-neglect. However, after adjusting for potential confounders, the above associations were no longer statistically significant. In addition, personality traits were not associated with increased risk of greater self-neglect severity. Furthermore, interaction term analyses of personality traits with health and psychosocial factors were not statistically significant with elder self-neglect outcomes. Conclusion Neuroticism, extraversion, rigidity and information processing were not associated with significantly increased risk of elder self-neglect after consideration of potential confounders. PMID:21788924
Ozdemir-Karatas, Meltem; Balik, Ali; Evlioglu, Gülümser; Uysal, Ömer; Peker, Kadriye
2018-03-01
The aim of this study was to determine the sociodemographic, behavioral, and clinical factors affecting obturator function and satisfaction using the obturator functioning scale (OFS) in maxillectomy patients rehabilitated with obturator prostheses. The study sample consisted of 41 maxillectomy patients. The OFS was translated into Turkish and adapted for assessing obturator functioning and patient satisfaction among Turkish patients. Data were collected from patients' medical records and self-completed questionnaires, including the Turkish version of the OFS, sociodemographic and behavioral characteristics. Descriptive statistics, Mann-Whitney U test, Spearman's correlation coefficient, and backward stepwise multiple linear regression were used for data analysis. Internal consistency (Cronbach's alpha = 0.85) and test-retest reliability (intraclass correlation coefficient = 0.86) were acceptable for the OFS. The most frequently reported problem was "difficulty chewing." Bivariate analysis revealed significant differences in total OFS scores in terms of surgery type, defect size, and education level, except for the other clinical and sociodemographic characteristics and behavioral factors. Education level and surgery type were found to be the most important predictors of patient satisfaction and functioning of the obturator. The Turkish version of the OFS might be a useful tool for clinicians to identify patients who are at risk for poor functioning of the obturator, lack of satisfaction, and unmet needs. Copyright © 2017 Elsevier Inc. All rights reserved.
Serum BDNF Is Positively Associated With Negative Symptoms in Older Adults With Schizophrenia.
Binford, Sasha S; Hubbard, Erin M; Flowers, Elena; Miller, Bruce L; Leutwyler, Heather
2018-01-01
Older adults with chronic schizophrenia are at greater risk for functional disability and poorer health outcomes than those without serious mental illness. These individuals comprise 1-2% of the elderly population in the United States and are projected to number approximately 15 million by 2030. The symptoms of schizophrenia can be disabling for individuals, significantly reducing quality of life. Often, the negative symptoms (NS) are the most resistant to treatment and are considered a marker of illness severity, though they are challenging to measure objectively. Biomarkers can serve as objective indicators of health status. Brain-derived neurotrophic factor (BDNF) is a potential biomarker for schizophrenia and may serve as an important indicator of illness severity. A cross-sectional study with 30 older adults with chronic schizophrenia. Participants were assessed on serum levels of BDNF and psychiatric symptoms (Positive and Negative Syndrome Scale). Pearson's bivariate correlations (two-tailed) and linear regression models were used. A significant positive association ( p < .05) was found between higher serum levels of BDNF and greater severity for the NS items of passive, apathetic, social withdrawal, and emotional withdrawal. In multivariate analyses, the association remained significant. Although the association between BDNF and NS was not in the expected direction, the data corroborate findings from previous work in patients with schizophrenia. It is possible that higher serum levels of BDNF reflect compensatory neuronal mechanisms resulting from neurodevelopmental dysfunction.
Energy content of municipal solid waste bales.
Ozbay, Ismail; Durmusoglu, Ertan
2013-07-01
Baling technology is a preferred method for temporary storage of municipal solid waste (MSW) prior to final disposal. If incineration is intended for final disposal of the bales, the energy content of the baled MSW gains importance. In this study, nine cylindrical bales containing a mix of different waste materials were constructed and several parameters, including total carbon (TC), total organic carbon (TOC), total Kjeldahl nitrogen, moisture content, loss on ignition, gross calorific value and net calorific value (NCV) were determined before the baling and at the end of 10 months of storage. In addition, the relationships between the waste materials and the energy contents of the bales were investigated by the bivariate correlation analyses. At the end, linear regression models were developed in order to forecast the decrease of energy content during storage. While the NCVs of the waste materials before the baling ranged between 6.2 and 23.7 MJ kg(-1) dry basis, they ranged from 1.0 to 16.4 MJ kg(-1) dry basis at the end of the storage period. Moreover, food wastes exhibited the highest negative correlation with NCVs, whereas plastics have significant positive correlation with both NCVs and TCs. Similarly, TOCs and carbon/nitrogen ratios decreased with the increase in food amounts inside the bales. In addition, textile, wood and yard wastes increase the energy content of the bales slightly over the storage period.
DBH Prediction Using Allometry Described by Bivariate Copula Distribution
NASA Astrophysics Data System (ADS)
Xu, Q.; Hou, Z.; Li, B.; Greenberg, J. A.
2017-12-01
Forest biomass mapping based on single tree detection from the airborne laser scanning (ALS) usually depends on an allometric equation that relates diameter at breast height (DBH) with per-tree aboveground biomass. The incapability of the ALS technology in directly measuring DBH leads to the need to predict DBH with other ALS-measured tree-level structural parameters. A copula-based method is proposed in the study to predict DBH with the ALS-measured tree height and crown diameter using a dataset measured in the Lassen National Forest in California. Instead of exploring an explicit mathematical equation that explains the underlying relationship between DBH and other structural parameters, the copula-based prediction method utilizes the dependency between cumulative distributions of these variables, and solves the DBH based on an assumption that for a single tree, the cumulative probability of each structural parameter is identical. Results show that compared with the bench-marking least-square linear regression and the k-MSN imputation, the copula-based method obtains better accuracy in the DBH for the Lassen National Forest. To assess the generalization of the proposed method, prediction uncertainty is quantified using bootstrapping techniques that examine the variability of the RMSE of the predicted DBH. We find that the copula distribution is reliable in describing the allometric relationship between tree-level structural parameters, and it contributes to the reduction of prediction uncertainty.
Breastfeeding, comnlementarv food introduction and overweight in preschool children.
Lopes, Amanda Forster; Rocha, Elida Mara Braga; da Silva, Janaina Paula Costa; Nascimento, Viviane Gabriela; Bertoli, Ciro; Leone, Claudio
2016-09-01
Growing phenomenon, which involves high morbidity and consequently high costs for health systems, obesity has been found also among the pediatric population and is currently considered a public health problem. The aim of this study was to verify if in children in the early preschool age we can see the prevalence of overweight and if introducing complementary feeding as well as the type of food introduced, are associated with this condition in this age group. It is an observational analytic study with children born in 2011-2012 that attended public schools in Taubat6 -SP during 2014. In addition to the weight and height of children, information about the history of feeding and birth were collectedusing a standardized questionnaire.The nutritional status was defined as having overweight children with z-scores for body mass index (zIMC) > 1.We conducted bivariate analysis and then linear regression analysis of multiple variables.The prevalence of overweight was elevated (27.5%). Only birth weight showed significant correlation with respect to zIMC (r = 0.22, p < 0.0001). The multivariable analysis showed no relationship with the various foods, but showed birth weightas a high risk factor, the male and the total duration of breastfeeding as protective factors. As a result, we conclude that the early introduction of new foods is not a risk factor for the development of overweight at the beginning of pre-school age.
Escobar, A L; Coimbra, C E A; Camacho, L A B; Santos, R V
2004-01-01
To investigate the characteristics of tuberculin skin test reactivity in the Pakaanóva Indians, in Amazonia, Brazil, after revaccination of all study participants with bacille Calmette-Guerin (BCG). The investigation was designed as a post-BCG vaccination purified protein derivative (PPD) survey. Data included PPD readings, age, sex, nutritional status, place of residence, previous tuberculosis, physical examinations and BCG status. Bivariate and multivariate logistic regression analyses were conducted. About 90% (n = 505) of the total population participated. One third (32.1%) of the subjects presented induration > or = 10 mm at 72 h. Induration sizes showed weak linear correlation with age; differences between sexes were not observed. Skin reaction was not associated with nutritional status. Individuals with a history of tuberculosis were six times more likely to test positive. History of tuberculosis, age, and previous BCG vaccination were significantly associated with PPD reactivity in the multivariate analyses. The Pakaanóva showed a high proportion (58.4%) of non-reactors, even with a recent BCG booster. Sex differences in PPD reactivity were either not present or could not be demonstrated. The association between age and PPD reactivity resembles that observed in other Amazonian populations. The authors discuss the potential of PPD testing as a screening tool to enhance tuberculosis detection, especially in indigenous populations in Amazonia with limited access to health services.
Adams-Chapman, Ira; Bann, Carla M; Vaucher, Yvonne E; Stoll, Barbara J
2013-09-01
To evaluate the relationship between abnormal feeding patterns and language performance on the Bayley Scales of Infant Development-Third Edition at 18-22 months adjusted age among a cohort of extremely premature infants. This is a descriptive analysis of 1477 preterm infants born ≤ 26 weeks gestation or enrolled in a clinical trial between January 1, 2006 and March 18, 2008 at a National Institute of Child Health and Human Development Neonatal Research Network center who completed the 18-month neurodevelopmental follow-up assessment. At 18-22 months adjusted age, a comprehensive neurodevelopmental evaluation was performed by certified examiners including the Receptive and Expressive Language Subscales of the Bayley Scales of Infant Development-Third Edition and a standardized adjusted age feeding behaviors and nutritional intake. Data were analyzed using bivariate and multilevel linear and logistic regression modeling. Abnormal feeding behaviors were reported in 193 (13%) of these infants at 18-22 months adjusted age. Abnormal feeding patterns, days of mechanical ventilation, hearing impairment, and Gross Motor Functional Classification System level ≥ 2 each independently predicted lower composite language scores. At 18 months adjusted age, premature infants with a history of feeding difficulties are more likely to have language delay. Neuromotor impairment and days of mechanical ventilation are both important risk factors associated with these outcomes. Copyright © 2013 Mosby, Inc. All rights reserved.
Media use, cancer knowledge and lifestyle choices: a cross-sectional analysis.
Nelissen, Sara; Beullens, Kathleen; Lemal, Marijke; Van den Bulck, Jan
2015-10-01
Both media use and cancer knowledge have been identified as important predictors of a healthy lifestyle. However, little is known about the interplay between these two variables, and about differences between cancer diagnosed and non-diagnosed consumers of media and knowledge. This study investigated the relationship between media use (television and internet exposure) and lifestyle choices of cancer diagnosed and non-diagnosed individuals, and looked at the influence of cancer knowledge on this relationship. A cross-sectional, quantitative survey (the Leuven Cancer Information Survey) was administered to 621 cancer diagnosed and 1387 non-diagnosed individuals, aged 16-88 years old in Flanders (Belgium). Bivariate analyses, hierarchical linear regression analyses and advanced moderation and mediation analyses were conducted. Internet exposure was not a predictor of lifestyle choices. Television exposure, however, was a negative predictor of healthy lifestyle choices. Moreover, television exposure was a direct negative predictor of cancer knowledge, which in turn positively predicted lifestyle choices. However, no differences were found in the investigated relationships between the two subsamples. These results indicate that higher levels of television exposure coincide with less cancer knowledge and with less healthy lifestyle choices. It offers a pathway for intervention by suggesting that improving cancer knowledge through television might positively affect lifestyle choices. © The Author 2015. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.
Harris, Gabrielle M; Collins-McNeil, Janice; Yang, Qing; Nguyen, Vu Q C; Hirsch, Mark A; Rhoads, Charles F; Guerrier, Tami; Thomas, J George; Pugh, Terrence M; Hamm, Deanna; Pereira, Carol; Prvu Bettger, Janet
2017-01-01
To examine the prevalence of poststroke depression (PSD) among African American stroke survivors and the association of depression with functional status at inpatient rehabilitation facility (IRF) discharge. Secondary data analysis was conducted of a patient cohort who received care at 3 IRFs in the United States from 2009 to 2011. Functional status was measured by the Functional Independence Measure (FIM). Multiple linear regression models were used to examine associations of PSD and FIM motor and cognitive scores. Of 458 African American stroke survivors, 48.5% were female, 84% had an ischemic stroke, and the mean age was 60.8 ± 13.6 years. Only 15.4% (n = 71) had documentation of PSD. Bivariate analyses to identify factors associated with depression identified a higher percentage of patients with depression than without who were retired due to disability (17.1% versus 11.6%) or employed (31.4% versus 19.6%) prestroke (P = .041). Dysphagia, cognitive deficits, and a lower admission motor FIM score were also significantly more common among those with depression. There was no significant relationship between depression and functional status after adjusting for patient characteristics. In this study, 15% of the African Americans who received rehabilitation after a stroke had documentation of PSD but this was not associated with functional status at discharge. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.
College Women's Responses to a Celebrity Health Disclosure.
Drizin, Julia H; Malcarne, Vanessa L; Schiaffino, Melody K; Wells, Kristen J
2017-08-18
Celebrities can have a powerful influence on people's health-related attitudes and behaviors, often by publicly disclosing their own personal health decisions. In May 2013, Angelina Jolie, an internationally recognized actress, director, and author, wrote an op-ed for the New York Times disclosing her decision to undergo a prophylactic double mastectomy to reduce her risk of breast cancer after learning that she carried the BRCA1 gene mutation. This cross-sectional study examined whether exposure to Angelina Jolie and her mastectomy disclosure and parasocial involvement (PSI) with Angelina Jolie were related to female college students' perceived risk of breast cancer and breast cancer screening intentions. Participants were 198 female undergraduate college students. Data were collected anonymously via an online questionnaire and analyzed using bivariate correlations and hierarchical linear regression analyses. Neither exposure to Angelina and her disclosure nor PSI with Angelina Jolie was related to participants' attitudes or behaviors related to breast cancer. However, having a family history of cancer was associated with more exposure to Angelina Jolie and her disclosure. Findings suggest that exposure to and PSI with a celebrity who has disclosed a health-related message may not be sufficient to motivate young women to change their health-related attitudes and behaviors. Future studies should explore how celebrities disclosing different types of health issues might influence the attitudes and behaviors of young women.
Cognitive Psychophysiological Substrates of Affective Temperaments.
Poyraz, Burç Çağrı; Sakallı Kani, Ayşe; Aksoy Poyraz, Cana; Öcek Baş, Tuba; Arıkan, Mehmet Kemal
2017-03-01
Affective temperaments are the subclinical manifestations or phenotypes of mood states and hypothetically represent one healthy end of the mood disorder spectrum. However, there is a scarcity of studies investigating the neurobiological basis of affective temperaments. One fundamental aspect of temperament is the behavioral reactivity to environmental stimuli, which can be effectively evaluated by use of cognitive event-related potentials (ERPs) reflecting the diversity of information processing. The aim of the present study is to explore the associations between P300 and the affective temperamental traits in healthy individuals. We recorded the P300 ERP waves using an auditory oddball paradigm in 50 medical student volunteers (23 females, 27 males). Participants' affective temperaments were evaluated using the Temperament Evaluation of Memphis, Pisa, Paris, and San Diego-auto questionnaire version (TEMPS-A). In bivariate analyses, depressive temperament score was significantly correlated with P300 latency ( r s = 0.37, P < .01). In a multiple linear regression analysis, P300 latency showed a significant positive correlation with scores of depressive temperament (β = 0.40, P < .01) and a significant negative one with scores of cyclothymic temperament (β = -0.29, P = .03). Affective temperament scores were not associated with P300 amplitude and reaction times. These results indicate that affective temperaments are related to information processing in the brain. Depressive temperament may be characterized by decreased physiological arousal and slower information processing, while the opposite was observed for cyclothymic temperament.
Zhang, Bo; Zhang, Zhi-ying; Xu, De-zhong; Sun, Zhi-dong; Zhou, Xiao-nong; Gong, Zi-li; Liu, Shi-jun; Liu, Cheng; Xu, Bin; Zhou, Yun
2003-04-01
To analyze the relationship between the normalized difference vegetation index (NDVI) and the snail distribution in marshland of Jiangning county in Jiangsu province, and to explore the utility of Terra-MODIS image map in the small scale snail habitats surveillance. NDVI were extracted from MODIS image by vector chart of the snail distribution using ArcView 8.1 and ERDAS 8.5 software. The relationship between NDVI and the snail distribution were Investigated using Bivariate correlations and stepwise linear regression. The snail density on marshland was positively correlated with the mean NDVI in the first ten-day of May and the maximum NDVI (N(20max)) in the last ten-day of May. Incidence of pixel with the live snail on marshland was positively correlated with the mean NDVI (N(2mean)) in the first ten-day of May. An equation Y(1) = 0.009 47 x N(20max) (R(2) = 0.73), Y(2) = 0.018 6 x N(2mean) (R(2) = 0.906) was established. This study showed that the Terra-MODIS satellite images reflecting the status of the vegetation on marshland in Jiangning county could be applied to the study to supervise the snail habitat. The results suggested that MODIS images could be used to survey the small scale snail habitats on marshland.
Bowen, Stephen R; Chappell, Richard J; Bentzen, Søren M; Deveau, Michael A; Forrest, Lisa J; Jeraj, Robert
2012-01-01
Purpose To quantify associations between pre-radiotherapy and post-radiotherapy PET parameters via spatially resolved regression. Materials and methods Ten canine sinonasal cancer patients underwent PET/CT scans of [18F]FDG (FDGpre), [18F]FLT (FLTpre), and [61Cu]Cu-ATSM (Cu-ATSMpre). Following radiotherapy regimens of 50 Gy in 10 fractions, veterinary patients underwent FDG PET/CT scans at three months (FDGpost). Regression of standardized uptake values in baseline FDGpre, FLTpre and Cu-ATSMpre tumour voxels to those in FDGpost images was performed for linear, log-linear, generalized-linear and mixed-fit linear models. Goodness-of-fit in regression coefficients was assessed by R2. Hypothesis testing of coefficients over the patient population was performed. Results Multivariate linear model fits of FDGpre to FDGpost were significantly positive over the population (FDGpost~0.17 FDGpre, p=0.03), and classified slopes of RECIST non-responders and responders to be different (0.37 vs. 0.07, p=0.01). Generalized-linear model fits related FDGpre to FDGpost by a linear power law (FDGpost~FDGpre0.93, p<0.001). Univariate mixture model fits of FDGpre improved R2 from 0.17 to 0.52. Neither baseline FLT PET nor Cu-ATSM PET uptake contributed statistically significant multivariate regression coefficients. Conclusions Spatially resolved regression analysis indicates that pre-treatment FDG PET uptake is most strongly associated with three-month post-treatment FDG PET uptake in this patient population, though associations are histopathology-dependent. PMID:22682748
Linear regression analysis of survival data with missing censoring indicators.
Wang, Qihua; Dinse, Gregg E
2011-04-01
Linear regression analysis has been studied extensively in a random censorship setting, but typically all of the censoring indicators are assumed to be observed. In this paper, we develop synthetic data methods for estimating regression parameters in a linear model when some censoring indicators are missing. We define estimators based on regression calibration, imputation, and inverse probability weighting techniques, and we prove all three estimators are asymptotically normal. The finite-sample performance of each estimator is evaluated via simulation. We illustrate our methods by assessing the effects of sex and age on the time to non-ambulatory progression for patients in a brain cancer clinical trial.
An Analysis of COLA (Cost of Living Adjustment) Allocation within the United States Coast Guard.
1983-09-01
books Applied Linear Regression [Ref. 39], and Statistical Methods in Research and Production [Ref. 40], or any other book on regression. In the event...Indexes, Master’s Thesis, Air Force Institute of Technology, Wright-Patterson AFB, 1976. 39. Weisberg, Stanford, Applied Linear Regression , Wiley, 1980. 40
Testing hypotheses for differences between linear regression lines
Stanley J. Zarnoch
2009-01-01
Five hypotheses are identified for testing differences between simple linear regression lines. The distinctions between these hypotheses are based on a priori assumptions and illustrated with full and reduced models. The contrast approach is presented as an easy and complete method for testing for overall differences between the regressions and for making pairwise...
Teaching the Concept of Breakdown Point in Simple Linear Regression.
ERIC Educational Resources Information Center
Chan, Wai-Sum
2001-01-01
Most introductory textbooks on simple linear regression analysis mention the fact that extreme data points have a great influence on ordinary least-squares regression estimation; however, not many textbooks provide a rigorous mathematical explanation of this phenomenon. Suggests a way to fill this gap by teaching students the concept of breakdown…
Estimating monotonic rates from biological data using local linear regression.
Olito, Colin; White, Craig R; Marshall, Dustin J; Barneche, Diego R
2017-03-01
Accessing many fundamental questions in biology begins with empirical estimation of simple monotonic rates of underlying biological processes. Across a variety of disciplines, ranging from physiology to biogeochemistry, these rates are routinely estimated from non-linear and noisy time series data using linear regression and ad hoc manual truncation of non-linearities. Here, we introduce the R package LoLinR, a flexible toolkit to implement local linear regression techniques to objectively and reproducibly estimate monotonic biological rates from non-linear time series data, and demonstrate possible applications using metabolic rate data. LoLinR provides methods to easily and reliably estimate monotonic rates from time series data in a way that is statistically robust, facilitates reproducible research and is applicable to a wide variety of research disciplines in the biological sciences. © 2017. Published by The Company of Biologists Ltd.
Locally linear regression for pose-invariant face recognition.
Chai, Xiujuan; Shan, Shiguang; Chen, Xilin; Gao, Wen
2007-07-01
The variation of facial appearance due to the viewpoint (/pose) degrades face recognition systems considerably, which is one of the bottlenecks in face recognition. One of the possible solutions is generating virtual frontal view from any given nonfrontal view to obtain a virtual gallery/probe face. Following this idea, this paper proposes a simple, but efficient, novel locally linear regression (LLR) method, which generates the virtual frontal view from a given nonfrontal face image. We first justify the basic assumption of the paper that there exists an approximate linear mapping between a nonfrontal face image and its frontal counterpart. Then, by formulating the estimation of the linear mapping as a prediction problem, we present the regression-based solution, i.e., globally linear regression. To improve the prediction accuracy in the case of coarse alignment, LLR is further proposed. In LLR, we first perform dense sampling in the nonfrontal face image to obtain many overlapped local patches. Then, the linear regression technique is applied to each small patch for the prediction of its virtual frontal patch. Through the combination of all these patches, the virtual frontal view is generated. The experimental results on the CMU PIE database show distinct advantage of the proposed method over Eigen light-field method.
Victimization and health risk factors among weapon-carrying youth.
Stayton, Catherine; McVeigh, Katharine H; Olson, E Carolyn; Perkins, Krystal; Kerker, Bonnie D
2011-11-01
To compare health risks of 2 subgroups of weapon carriers: victimized and nonvictimized youth. 2003-2007 NYC Youth Risk Behavior Surveys were analyzed using bivariate analyses and multinomial logistic regression. Among NYC teens, 7.5% reported weapon carrying without victimization; 6.9% reported it with victimization. Both subgroups were more likely than non-weapon carriers to binge drink, use marijuana, smoke, fight, and have multiple sex partners; weapon carriers with victimization also experienced persistent sadness and attempted suicide. Subgroups of weapon carriers have distinct profiles. Optimal response should pair disciplinary action with screening for behavioral and mental health concerns and victimization.
Jagger, Pamela; Shively, Gerald
Using data from 433 firms operating along Uganda's charcoal and timber supply chains we investigate patterns of bribe payment and tax collection between supply chain actors and government officials responsible for collecting taxes and fees. We examine the factors associated with the presence and magnitude of bribe and tax payments using a series of bivariate probit and Tobit regression models. We find empirical support for a number of hypotheses related to payments, highlighting the role of queuing, capital-at-risk, favouritism, networks, and role in the supply chain. We also find that taxes crowd-in bribery in the charcoal market.
Jagger, Pamela; Shively, Gerald
2016-01-01
Using data from 433 firms operating along Uganda’s charcoal and timber supply chains we investigate patterns of bribe payment and tax collection between supply chain actors and government officials responsible for collecting taxes and fees. We examine the factors associated with the presence and magnitude of bribe and tax payments using a series of bivariate probit and Tobit regression models. We find empirical support for a number of hypotheses related to payments, highlighting the role of queuing, capital-at-risk, favouritism, networks, and role in the supply chain. We also find that taxes crowd-in bribery in the charcoal market. PMID:27274568
A general framework for the use of logistic regression models in meta-analysis.
Simmonds, Mark C; Higgins, Julian Pt
2016-12-01
Where individual participant data are available for every randomised trial in a meta-analysis of dichotomous event outcomes, "one-stage" random-effects logistic regression models have been proposed as a way to analyse these data. Such models can also be used even when individual participant data are not available and we have only summary contingency table data. One benefit of this one-stage regression model over conventional meta-analysis methods is that it maximises the correct binomial likelihood for the data and so does not require the common assumption that effect estimates are normally distributed. A second benefit of using this model is that it may be applied, with only minor modification, in a range of meta-analytic scenarios, including meta-regression, network meta-analyses and meta-analyses of diagnostic test accuracy. This single model can potentially replace the variety of often complex methods used in these areas. This paper considers, with a range of meta-analysis examples, how random-effects logistic regression models may be used in a number of different types of meta-analyses. This one-stage approach is compared with widely used meta-analysis methods including Bayesian network meta-analysis and the bivariate and hierarchical summary receiver operating characteristic (ROC) models for meta-analyses of diagnostic test accuracy. © The Author(s) 2014.
Taulaniemi, Annika; Kuusinen, Lotta; Tokola, Kari; Kankaanpää, Markku; Suni, Jaana H
2017-08-31
To investigate associations of various bio-psychosocial factors with bodily pain, physical func-tioning, and ability to work in low back pain. Cross-sectional study. A total of 219 female healthcare workers with recurrent non-specific low back pain. Associations between several physical and psychosocial factors and: (i) bodily pain, (ii) physical functioning and (iii) ability to work were studied. Variables with statistically significant associations (p < 0.05) in bivariate analysis were set within a generalized linear model to analyse their relationship with each dependent variable. In generalized linear model analysis, perceived work-induced lumbar exertion (p < 0.001), multi-site pain (p <0.001) and work-related fear-avoidance beliefs (FAB-W) (p = 0.02) best explained bodily pain. Multi-site pain (p < 0.001), lumbar exertion (p = 0.005), FAB-W (p = 0.01) and physical performance in figure-of-eight running (p = 0.01) and modified push-ups (p = 0.05) best explained physical functioning; FAB-W (p <0.001), lumbar exertion (p = 0.003), depression (p = 0.01) and recovery after work (p = 0.03) best explained work ability. In bivariate analysis lumbar exertion was associated with poor physical performance. FAB-W and work-induced lumbar exertion were associated with levels of pain, physical functioning and ability to work. Poor physical performance capacity was associated with work-induced lumbar exertion. Interventions that aim to reduce fear-avoidance and increase fitness capacity might be beneficial.
Saraf, Sanatan; Mathew, Thomas; Roy, Anindya
2015-01-01
For the statistical validation of surrogate endpoints, an alternative formulation is proposed for testing Prentice's fourth criterion, under a bivariate normal model. In such a setup, the criterion involves inference concerning an appropriate regression parameter, and the criterion holds if the regression parameter is zero. Testing such a null hypothesis has been criticized in the literature since it can only be used to reject a poor surrogate, and not to validate a good surrogate. In order to circumvent this, an equivalence hypothesis is formulated for the regression parameter, namely the hypothesis that the parameter is equivalent to zero. Such an equivalence hypothesis is formulated as an alternative hypothesis, so that the surrogate endpoint is statistically validated when the null hypothesis is rejected. Confidence intervals for the regression parameter and tests for the equivalence hypothesis are proposed using bootstrap methods and small sample asymptotics, and their performances are numerically evaluated and recommendations are made. The choice of the equivalence margin is a regulatory issue that needs to be addressed. The proposed equivalence testing formulation is also adopted for other parameters that have been proposed in the literature on surrogate endpoint validation, namely, the relative effect and proportion explained.
Effect of Malmquist bias on correlation studies with IRAS data base
NASA Technical Reports Server (NTRS)
Verter, Frances
1993-01-01
The relationships between galaxy properties in the sample of Trinchieri et al. (1989) are reexamined with corrections for Malmquist bias. The linear correlations are tested and linear regressions are fit for log-log plots of L(FIR), L(H-alpha), and L(B) as well as ratios of these quantities. The linear correlations for Malmquist bias are corrected using the method of Verter (1988), in which each galaxy observation is weighted by the inverse of its sampling volume. The linear regressions are corrected for Malmquist bias by a new method invented here in which each galaxy observation is weighted by its sampling volume. The results of correlation and regressions among the sample are significantly changed in the anticipated sense that the corrected correlation confidences are lower and the corrected slopes of the linear regressions are lower. The elimination of Malmquist bias eliminates the nonlinear rise in luminosity that has caused some authors to hypothesize additional components of FIR emission.
An Affine Invariant Bivariate Version of the Sign Test.
1987-06-01
words: affine invariance, bivariate quantile, bivariate symmetry, model,. generalized median, influence function , permutation test, normal efficiency...calculate a bivariate version of the influence function , and the resulting form is bounded, as is the case for the univartate sign test, and shows the...terms of a blvariate analogue of IHmpel’s (1974) influence function . The latter, though usually defined as a von-Mises derivative of certain
A primer for biomedical scientists on how to execute model II linear regression analysis.
Ludbrook, John
2012-04-01
1. There are two very different ways of executing linear regression analysis. One is Model I, when the x-values are fixed by the experimenter. The other is Model II, in which the x-values are free to vary and are subject to error. 2. I have received numerous complaints from biomedical scientists that they have great difficulty in executing Model II linear regression analysis. This may explain the results of a Google Scholar search, which showed that the authors of articles in journals of physiology, pharmacology and biochemistry rarely use Model II regression analysis. 3. I repeat my previous arguments in favour of using least products linear regression analysis for Model II regressions. I review three methods for executing ordinary least products (OLP) and weighted least products (WLP) regression analysis: (i) scientific calculator and/or computer spreadsheet; (ii) specific purpose computer programs; and (iii) general purpose computer programs. 4. Using a scientific calculator and/or computer spreadsheet, it is easy to obtain correct values for OLP slope and intercept, but the corresponding 95% confidence intervals (CI) are inaccurate. 5. Using specific purpose computer programs, the freeware computer program smatr gives the correct OLP regression coefficients and obtains 95% CI by bootstrapping. In addition, smatr can be used to compare the slopes of OLP lines. 6. When using general purpose computer programs, I recommend the commercial programs systat and Statistica for those who regularly undertake linear regression analysis and I give step-by-step instructions in the Supplementary Information as to how to use loss functions. © 2011 The Author. Clinical and Experimental Pharmacology and Physiology. © 2011 Blackwell Publishing Asia Pty Ltd.
ERIC Educational Resources Information Center
Rocconi, Louis M.
2013-01-01
This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least squares (OLS) regression. To illustrate this point, this study examined the influences of seniors' self-reported critical thinking abilities three ways: (1) an OLS regression with the student…
Dental services utilization by women of childbearing age by socioeconomic status.
Kaylor, Mary B; Polivka, Barbara J; Chaudry, Rosemary; Salsberry, Pamela; Wee, Alvin G
2010-04-01
For women of childbearing age, oral health not only affects their physical and psychological well-being but also that of their children. This study used the 2003-2004 Ohio Family Health Survey (N = 9,819) to examine dental need and utilization by women in Ohio. Predisposing, enabling, and need variables were examined as they effect dental health service utilization by women of childbearing age at different socioeconomic status (SES) levels. The proportion of women in the low SES group self reporting a dental need (18%) was 3 times that of the proportion of women in the higher SES group with a self reported need (6%). Results of bivariate analysis showed that having a dental visit in the past year varied significantly by SES, race, insurance status, provider density, and need. A racial disparity in dental service utilization was noted in the bivariate analysis of the middle SES group. While dental need and type of dental coverage varied by SES, both were significantly associated with utilization of dental services within all 3 SES categories in the logistic regressions. These results suggest that measures need to be implemented to meet the goal of increasing access and utilization of dental health services by low-income populations.
Epidemiology of mixed martial arts and youth violence in an ethnically diverse sample.
Hishinuma, Earl S; Umemoto, Karen N; Nguyen, Toan Gia; Chang, Janice Y; Bautista, Randy Paul M
2012-01-01
Mixed martial arts' (MMAs) growing international popularity has rekindled the discussion on the advantages (e.g., exercise) and disadvantages (e.g., possible injury) of contact sports. This study was the first of its kind to examine the psychosocial aspects of MMA and youth violence using an epidemiologic approach with an Asian American and Pacific Islander (AAPI) adolescent sample (N = 881). The results were consistent with the increased popularity of MMA with 52% (adolescent males = 73%, adolescent females = 39%) enjoying watching MMA and 24% (adolescent males = 39%, adolescent females = 13%) practicing professional fight moves with friends. Although statistically significant ethnic differences were found for the two MMA items on a bivariate level, these findings were not statistically significant when considering other variables in the model. The bivariate results revealed a cluster of risk-protective factors. Regarding the multiple regression findings, although enjoying watching MMA remained associated with positive attitudes toward violence and practicing fight moves remained associated with negative out-group orientation, the MMA items were not associated with unique variances of youth violence perpetration and victimization. Implications included the need for further research that includes other diverse samples, more comprehensive and objective MMA and violence measures, and observational and intervention longitudinal studies.
Shared etiology of phonological memory and vocabulary deficits in school-age children.
Peterson, Robin L; Pennington, Bruce F; Samuelsson, Stefan; Byrne, Brian; Olson, Richard K
2013-08-01
The goal of this study was to investigate the etiologic basis for the association between deficits in phonological memory (PM) and vocabulary in school-age children. Children with deficits in PM or vocabulary were identified within the International Longitudinal Twin Study (ILTS; Samuelsson et al., 2005). The ILTS includes 1,045 twin pairs (between the ages of 5 and 8 years) from the United States, Australia, and Scandinavia. The authors applied the DeFries-Fulker ( DeFries & Fulker, 1985, 1988) regression method to determine whether problems in PM and vocabulary tend to co-occur because of overlapping genes, overlapping environmental risk factors, or both. Among children with isolated PM deficits, the authors found significant bivariate heritability of PM and vocabulary weaknesses both within and across time. However, when probands were selected for a vocabulary deficit, there was no evidence for bivariate heritability. In this case, it appears that the PM-vocabulary relationship is caused by common shared environmental experiences. The findings are consistent with previous research on the heritability of specific language impairment and suggest that there are etiologic subgroups of children with low vocabulary for different reasons, 1 being more influenced by genes and another being more influenced by environment.
ERIC Educational Resources Information Center
Rocconi, Louis M.
2011-01-01
Hierarchical linear models (HLM) solve the problems associated with the unit of analysis problem such as misestimated standard errors, heterogeneity of regression and aggregation bias by modeling all levels of interest simultaneously. Hierarchical linear modeling resolves the problem of misestimated standard errors by incorporating a unique random…
ERIC Educational Resources Information Center
Preacher, Kristopher J.; Curran, Patrick J.; Bauer, Daniel J.
2006-01-01
Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests and plotting the…
Classical Testing in Functional Linear Models.
Kong, Dehan; Staicu, Ana-Maria; Maity, Arnab
2016-01-01
We extend four tests common in classical regression - Wald, score, likelihood ratio and F tests - to functional linear regression, for testing the null hypothesis, that there is no association between a scalar response and a functional covariate. Using functional principal component analysis, we re-express the functional linear model as a standard linear model, where the effect of the functional covariate can be approximated by a finite linear combination of the functional principal component scores. In this setting, we consider application of the four traditional tests. The proposed testing procedures are investigated theoretically for densely observed functional covariates when the number of principal components diverges. Using the theoretical distribution of the tests under the alternative hypothesis, we develop a procedure for sample size calculation in the context of functional linear regression. The four tests are further compared numerically for both densely and sparsely observed noisy functional data in simulation experiments and using two real data applications.
Classical Testing in Functional Linear Models
Kong, Dehan; Staicu, Ana-Maria; Maity, Arnab
2016-01-01
We extend four tests common in classical regression - Wald, score, likelihood ratio and F tests - to functional linear regression, for testing the null hypothesis, that there is no association between a scalar response and a functional covariate. Using functional principal component analysis, we re-express the functional linear model as a standard linear model, where the effect of the functional covariate can be approximated by a finite linear combination of the functional principal component scores. In this setting, we consider application of the four traditional tests. The proposed testing procedures are investigated theoretically for densely observed functional covariates when the number of principal components diverges. Using the theoretical distribution of the tests under the alternative hypothesis, we develop a procedure for sample size calculation in the context of functional linear regression. The four tests are further compared numerically for both densely and sparsely observed noisy functional data in simulation experiments and using two real data applications. PMID:28955155
Musuku, Adrien; Tan, Aimin; Awaiye, Kayode; Trabelsi, Fethi
2013-09-01
Linear calibration is usually performed using eight to ten calibration concentration levels in regulated LC-MS bioanalysis because a minimum of six are specified in regulatory guidelines. However, we have previously reported that two-concentration linear calibration is as reliable as or even better than using multiple concentrations. The purpose of this research is to compare two-concentration with multiple-concentration linear calibration through retrospective data analysis of multiple bioanalytical projects that were conducted in an independent regulated bioanalytical laboratory. A total of 12 bioanalytical projects were randomly selected: two validations and two studies for each of the three most commonly used types of sample extraction methods (protein precipitation, liquid-liquid extraction, solid-phase extraction). When the existing data were retrospectively linearly regressed using only the lowest and the highest concentration levels, no extra batch failure/QC rejection was observed and the differences in accuracy and precision between the original multi-concentration regression and the new two-concentration linear regression are negligible. Specifically, the differences in overall mean apparent bias (square root of mean individual bias squares) are within the ranges of -0.3% to 0.7% and 0.1-0.7% for the validations and studies, respectively. The differences in mean QC concentrations are within the ranges of -0.6% to 1.8% and -0.8% to 2.5% for the validations and studies, respectively. The differences in %CV are within the ranges of -0.7% to 0.9% and -0.3% to 0.6% for the validations and studies, respectively. The average differences in study sample concentrations are within the range of -0.8% to 2.3%. With two-concentration linear regression, an average of 13% of time and cost could have been saved for each batch together with 53% of saving in the lead-in for each project (the preparation of working standard solutions, spiking, and aliquoting). Furthermore, examples are given as how to evaluate the linearity over the entire concentration range when only two concentration levels are used for linear regression. To conclude, two-concentration linear regression is accurate and robust enough for routine use in regulated LC-MS bioanalysis and it significantly saves time and cost as well. Copyright © 2013 Elsevier B.V. All rights reserved.
A Linear Regression and Markov Chain Model for the Arabian Horse Registry
1993-04-01
as a tax deduction? Yes No T-4367 68 26. Regardless of previous equine tax deductions, do you consider your current horse activities to be... (Mark one...E L T-4367 A Linear Regression and Markov Chain Model For the Arabian Horse Registry Accesion For NTIS CRA&I UT 7 4:iC=D 5 D-IC JA" LI J:13tjlC,3 lO...the Arabian Horse Registry, which needed to forecast its future registration of purebred Arabian horses . A linear regression model was utilized to
Cross-sectional survey of knowledge of obstetric danger signs among women in rural Madagascar.
Salem, Ania; Lacour, Oriane; Scaringella, Stefano; Herinianasolo, Josea; Benski, Anne Caroline; Stancanelli, Giovanna; Vassilakos, Pierre; Petignat, Patrick; Schmidt, Nicole Christine
2018-02-05
Antenatal care (ANC) has the potential to identify and manage obstetric complications, educate women about risks during pregnancy and promote skilled birth attendance during childbirth. The aim of this study was to assess women's knowledge of obstetric danger signs and factors associated with this knowledge in Ambanja, Madagascar. It also sought to evaluate whether the participation in a mobile health (mHealth) project that aimed to provide comprehensive ANC to pregnant women in remote areas influenced women's knowledge of obstetric danger signs. From April to October 2015, a non-random, convenience sample of 372 women in their first year postpartum were recruited, including 161 who had participated in the mHealth project. Data were analyzed using bivariate and multivariate logistic regression. Knowledge of at least one danger sign varied from 80.9% of women knowing danger sign(s) in pregnancy, to 51.9%, 50.8% and 53.2% at delivery, postpartum and in the newborn, respectively. Participation in the mHealth intervention, higher household income, and receipt of information about danger signs during pregnancy were associated with knowledge of danger signs during delivery, in bivariate analysis; only higher household income and mHealth project participation were independently associated. Higher educational attainment and receipt of information about danger signs in antenatal care were associated with significantly higher odds of knowing danger sign(s) for the newborn in both bivariate and multivariate analysis. Knowledge of obstetric danger signs is low. Information provision during pregnancy and with mHealth is promising. This trial was retrospectively registered at the International Standard Randomized Controlled Trial Register (identifier ISRCTN15798183 ; August 22, 2015).
Colle, Romain; Segawa, Tomoyuki; Chupin, Marie; Tran Dong, Minh Ngoc Thien Kim; Hardy, Patrick; Falissard, Bruno; Colliot, Olivier; Ducreux, Denis; Corruble, Emmanuelle
2017-02-15
Three studies assessed the association of early life adversity (ELA) and hippocampal volumes in depressed patients, of which one was negative and the two others did not control for several potential confounding variables. Since the association of ELA and hippocampal volumes differ in male and female healthy volunteers, we investigated the association of ELA and hippocampal volumes in depressed patients, while focusing specifically on sex and controlling for several relevant socio-demographic and clinical variables. Sixty-three depressed in-patients treated in a psychiatric setting, with a current Major Depressive Episode (MDE) and a Major Depressive Disorder (MDD) were included and assessed for ELA. Hippocampal volumes were measured with brain magnetic resonance imaging (MRI) and automatic segmentation. They were compared between patients with (n = 28) or without (n = 35) ELA. After bivariate analyses, multivariate regression analyses tested the interaction of sex and ELA on hippocampal volume and were adjusted for several potential confounding variables. The subgroups of men (n = 26) and women (n = 37) were assessed separately. Patients with ELA had a smaller hippocampus than those without ELA (4.65 (±1.11) cm 3 versus 5.25 (±1.01) cm 3 ), bivariate: p = 0.03, multivariate: HR = 0.40, 95%CI [0.23;0.71], p = 0.002), independently from other factors. This association was found in men (4.43 (±1.22) versus 5.67 (±0.77) cm 3 ), bivariate: p = 0.006, multivariate HR = 0.23, 95%CI [0.06;0.82], p = 0.03) but not in women. ELA is associated with a smaller hippocampus in male but not female depressed in-patients. The reasons for this association should be investigated in further studies.
An improved multiple linear regression and data analysis computer program package
NASA Technical Reports Server (NTRS)
Sidik, S. M.
1972-01-01
NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.
Psychosocial factors influencing smokeless tobacco use by teen-age military dependents.
Lee, S; Raker, T; Chisick, M C
1994-02-01
Using bivariate and logistic regression analysis, we explored psychosocial correlates of smokeless tobacco (SLT) use in a sample of 2,257 teenage military dependents. We built separate regression models for males and females to explain triers and users of SLT. Results show female and male triers share five factors regarding SLT use--parental and peer approval, trying smoking, relatives using SLT, and athletic team membership. Male trial of SLT was additionally associated with race, difficulty in purchasing SLT, relatives who smoke, current smoking, and belief that SLT can cause mouth cancer. Male use of SLT was associated with race, seeing a dentist regularly, SLT counseling by a dentist, parental approval, trying and current smoking, and grade level. In all models, trying smoking was the strongest explanatory variable. Relatives and peers exert considerable influence on SLT use. Few triers or users had received SLT counseling from their dentist despite high dental utilization rates.
Personal growth, symptoms, and uncertainty in community-residing adults with heart failure.
Overbaugh, Kristen J; Parshall, Mark B
Personal growth has not been studied extensively in heart failure (HF). To characterize personal growth in HF and its relationships with symptom burden, uncertainty, and demographic and clinical factors. Associations among personal growth, uncertainty, symptom burden, and clinical and demographic variables were examined in adult outpatients with HF using bivariate correlations and multiple regressions. Participants (N = 103; 76% male, mean age = 74 years, 97% New York Heart Association classes II and III) reported moderate levels of personal growth, uncertainty, and symptom burden. Personal growth was weakly correlated with age and symptom burden but not with other study variables. In a regression model, age, sex, ethnicity, disease severity, time since diagnosis, symptom burden, and uncertainty were not significant independent correlates of personal growth. Community-residing patients with HF report moderate personal growth that is not explained by uncertainty, symptom burden, or demographic and clinical variables. Copyright © 2016 Elsevier Inc. All rights reserved.
Linking family dynamics and the mental health of Colombian dementia caregivers.
Sutter, Megan; Perrin, Paul B; Chang, Yu-Ping; Hoyos, Guillermo Ramirez; Buraye, Jaqueline Arabia; Arango-Lasprilla, Juan Carlos
2014-02-01
This cross-sectional, quantitative, self-report study examined the relationship between family dynamics (cohesion, flexibility, pathology/ functioning, communication, family satisfaction, and empathy) and mental health (depression, burden, stress, and satisfaction with life [SWL]) in 90 dementia caregivers from Colombia. Hierarchical multiple regressions controlling for caregiver demographics found that family dynamics were significantly associated with caregiver depression, stress, and SWL and marginally associated with burden. Within these regressions, empathy was uniquely associated with stress; flexibility with depression and marginally with SWL; and family communication marginally with burden and stress. Nearly all family dynamic variables were bivariately associated with caregiver mental health variables, such that caregivers had stronger mental health when their family dynamics were healthy. Family-systems interventions in global regions with high levels of familism like that in the current study may improve family empathy, flexibility, and communication, thereby producing better caregiver mental health and better informal care for people with dementia.
High-level language ability in healthy individuals and its relationship with verbal working memory.
Antonsson, Malin; Longoni, Francesca; Einald, Christina; Hallberg, Lina; Kurt, Gabriella; Larsson, Kajsa; Nilsson, Tina; Hartelius, Lena
2016-01-01
The aims of the study were to investigate healthy subjects' performance on a clinical test of high-level language (HLL) and how it is related to demographic characteristics and verbal working memory (VWM). One hundred healthy subjects (20-79 years old) were assessed with the Swedish BeSS test (Laakso, Brunnegård, Hartelius, & Ahlsén, 2000) and two digit span tasks. Relationships between the demographic variables, VWM and BeSS were investigated both with bivariate correlations and multiple regression analysis. The results present the norms for BeSS. The correlations and multiple regression analysis show that demographic variables had limited influence on test performance. Measures of VWM were moderately related to total BeSS score and weakly to moderately correlated with five of the seven subtests. To conclude, education has an influence on the test as a whole but measures of VWM stood out as the most robust predictor of HLL.
Use of antidementia drugs in frontotemporal lobar degeneration.
López-Pousa, Secundino; Calvó-Perxas, Laia; Lejarreta, Saioa; Cullell, Marta; Meléndez, Rosa; Hernández, Erélido; Bisbe, Josep; Perkal, Héctor; Manzano, Anna; Roig, Anna Maria; Turró-Garriga, Oriol; Vilalta-Franch, Joan; Garre-Olmo, Josep
2012-06-01
Clinical evidence indicates that acetylcholinesterase inhibitors (AChEIs) are not efficacious to treat frontotemporal lobar degeneration (FTLD). The British Association for Psychopharmacology recommends avoiding the use of AChEI and memantine in patients with FTLD. Cross-sectional design using 1092 cases with Alzheimer's disease (AD) and 64 cases with FTLD registered by the Registry of Dementias of Girona. Bivariate analyses were performed, and binary logistic regressions were used to detect variables associated with antidementia drugs consumption. The AChEIs were consumed by 57.6% and 42.2% of the patients with AD and FTLD, respectively. Memantine was used by 17.2% and 10.9% of patients with AD and FTLD, respectively. Binary logistic regressions yielded no associations with antidementia drugs consumption. There is a discrepancy regarding clinical practice and the recommendations based upon clinical evidence. The increased central nervous system drug use detected in FTLD requires multicentric studies aiming at finding the best means to treat these patients.
Wali, Behram; Khattak, Asad J; Xu, Jingjing
2018-01-01
The main objective of this study is to simultaneously investigate the degree of injury severity sustained by drivers involved in head-on collisions with respect to fault status designation. This is complicated to answer due to many issues, one of which is the potential presence of correlation between injury outcomes of drivers involved in the same head-on collision. To address this concern, we present seemingly unrelated bivariate ordered response models by analyzing the joint injury severity probability distribution of at-fault and not-at-fault drivers. Moreover, the assumption of bivariate normality of residuals and the linear form of stochastic dependence implied by such models may be unduly restrictive. To test this, Archimedean copula structures and normal mixture marginals are integrated into the joint estimation framework, which can characterize complex forms of stochastic dependencies and non-normality in residual terms. The models are estimated using 2013 Virginia police reported two-vehicle head-on collision data, where exactly one driver is at-fault. The results suggest that both at-fault and not-at-fault drivers sustained serious/fatal injuries in 8% of crashes, whereas, in 4% of the cases, the not-at-fault driver sustained a serious/fatal injury with no injury to the at-fault driver at all. Furthermore, if the at-fault driver is fatigued, apparently asleep, or has been drinking the not-at-fault driver is more likely to sustain a severe/fatal injury, controlling for other factors and potential correlations between the injury outcomes. While not-at-fault vehicle speed affects injury severity of at-fault driver, the effect is smaller than the effect of at-fault vehicle speed on at-fault injury outcome. Contrarily, and importantly, the effect of at-fault vehicle speed on injury severity of not-at-fault driver is almost equal to the effect of not-at-fault vehicle speed on injury outcome of not-at-fault driver. Compared to traditional ordered probability models, the study provides evidence that copula based bivariate models can provide more reliable estimates and richer insights. Practical implications of the results are discussed. Published by Elsevier Ltd.
Takeshita, Hajime; Ikebe, Kazunori; Kagawa, Ryosuke; Okada, Tadashi; Gondo, Yasuyuki; Nakagawa, Takeshi; Ishioka, Yoshiko; Inomata, Chisato; Tada, Sayaka; Matsuda, Ken-ichi; Kurushima, Yuko; Enoki, Kaori; Kamide, Kei; Masui, Yukie; Takahashi, Ryutaro; Arai, Yasumichi; Maeda, Yoshinobu
2015-03-01
Oral health-related quality of life (OHRQoL) is being increasingly used in epidemiologic studies of dentistry. However, patient-reported OHRQoL does not always coincide with clinical measures. Previous studies have shown a relationship between OHRQoL and personality, but did not concomitantly investigate oral function. We aimed to examine the association among personality traits, oral function, and OHRQoL using a large sample of community-dwelling Japanese elderly. The participants (n = 938; age, 69-71 years) were drawn from a complete enumeration of an urban area and a rural area of both the Tokyo metropolitan area and Hyogo Prefecture. The self-perceived impact of OHRQoL was measured using the Geriatric Oral Health Assessment Index (GOHAI). The oral status and socioeconomic characteristics were recorded in each participant, and personality traits (neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness) were assessed with the NEO-five-factor inventory. Multiple linear regression analysis was performed to examine the relationships between OHRQoL and other factors, with p < 0.05 considered to be statistically significant. Neuroticism was negatively associated with the GOHAI score in bivariate analyses (Spearman rank-order correlation coefficient (rs )= -0.20), whereas extraversion was positively associated (rs = 0.17). In the regression analyses, neuroticism (standardized partial regression coefficient (β) = -0.179) and extraversion (β=0.094) were significantly associated with the GOHAI scores independently of the number of teeth, maximal occlusal force, and financial status. Personality traits are associated with OHRQoL independently of objective measures of oral health status in community-dwelling elderly Japanese. This study showed personality traits are associated with OHRQoL independently of dental status and oral function in old Japanese people. As elderly patients undergo increasingly complex dental treatments, there is a need to evaluate patient personality traits prior to dental treatment and predict patient expectations and responses to planned treatment. This is advantageous in determining the most appropriate therapy. Copyright © 2015 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Kutzbach, L.; Schneider, J.; Sachs, T.; Giebels, M.; Nykänen, H.; Shurpali, N. J.; Martikainen, P. J.; Alm, J.; Wilmking, M.
2007-07-01
Closed (non-steady state) chambers are widely used for quantifying carbon dioxide (CO2) fluxes between soils or low-stature canopies and the atmosphere. It is well recognised that covering a soil or vegetation by a closed chamber inherently disturbs the natural CO2 fluxes by altering the concentration gradients between the soil, the vegetation and the overlying air. Thus, the driving factors of CO2 fluxes are not constant during the closed chamber experiment, and no linear increase or decrease of CO2 concentration over time within the chamber headspace can be expected. Nevertheless, linear regression has been applied for calculating CO2 fluxes in many recent, partly influential, studies. This approach was justified by keeping the closure time short and assuming the concentration change over time to be in the linear range. Here, we test if the application of linear regression is really appropriate for estimating CO2 fluxes using closed chambers over short closure times and if the application of nonlinear regression is necessary. We developed a nonlinear exponential regression model from diffusion and photosynthesis theory. This exponential model was tested with four different datasets of CO2 flux measurements (total number: 1764) conducted at three peatland sites in Finland and a tundra site in Siberia. The flux measurements were performed using transparent chambers on vegetated surfaces and opaque chambers on bare peat surfaces. Thorough analyses of residuals demonstrated that linear regression was frequently not appropriate for the determination of CO2 fluxes by closed-chamber methods, even if closure times were kept short. The developed exponential model was well suited for nonlinear regression of the concentration over time c(t) evolution in the chamber headspace and estimation of the initial CO2 fluxes at closure time for the majority of experiments. CO2 flux estimates by linear regression can be as low as 40% of the flux estimates of exponential regression for closure times of only two minutes and even lower for longer closure times. The degree of underestimation increased with increasing CO2 flux strength and is dependent on soil and vegetation conditions which can disturb not only the quantitative but also the qualitative evaluation of CO2 flux dynamics. The underestimation effect by linear regression was observed to be different for CO2 uptake and release situations which can lead to stronger bias in the daily, seasonal and annual CO2 balances than in the individual fluxes. To avoid serious bias of CO2 flux estimates based on closed chamber experiments, we suggest further tests using published datasets and recommend the use of nonlinear regression models for future closed chamber studies.
Danel, T; Vilain, J; Roelandt, J L; Salleron, J; Vaiva, G; Amariei, A; Amarie, A; Plancke, L; Plance, L; Duhamel, A
2010-01-01
The Santé Mentale en Population Générale Survey (Mental Health in General Population Survey (MHGP)) is a multicentre international research and action project initiated by the World Health Organisation Collaboration Centre for research and training in mental health. Its aims are to assess the prevalence of the major mental health disorders in the general adult population and from this to record perceptions associated with "mental illness", "madness" and "depression" together with different means of assistance and specialist or lay care. In this work we present the analysis of data on risks of suicide and past history of suicide attempts in the Nord pas de Calais region. We present the qualitative features of these phenomena and correlations with socio-economic, cultural and psychopathological factors, which are discussed in terms of both protective and vulnerability factors. Risk of suicide is present in 15% of the Nord pas de Calais population and is divided into 10.44% slight risk, 2.37% moderate risk and 2.2% high risk. A comparison with data from the MHGP survey in other regions reveals the high risk of suicide in the NPDC region. A risk of suicide is present is 13% of the population in other SMPG survey regions, broken down into 9.1% low risk, 2.1% medium risk and 1.7% high risk. Compared to the 2.2% high risk figure for NPDC, the population in this category is 21% larger. In terms of risk and protective factors, a bivariate analysis of socio-economic and cultural factors confirms the classical risk factors of sex, marital, occupational and educational status and income. The odds-ratio for these socio-economic and cultural factors can be calculated from logistic regression and the protective factors ranked in decreasing order from religion (Muslim versus other religions), martial status (marked versus separated), age (over 58 years old), occupational status (working or retired versus unemployed), income (more than 1300 euros versus less than 840 euros), sex (men versus women) and immigration. For mental illness, the bivariate analysis confirms that the risk of suicide is significantly higher regardless of the mental disorder in question. Logistic regression categorises the mental illnesses as risk factors in the following order: depression, psychotic disorders, anxiety, alcohol abuse disorders, other drugs and insomnia. Suicide attempts have been made by 9.7% of the study population. This figure should be compared with the 8% of the study population in other regions in the survey and represents 29% more attempts. For the risk and protective factors the results of the bivariate analysis of socio-economic on cultural and psychopathological factors are superimposeable on those found for risk of suicide. The ranking of protective factors obtained from logistic regression places age in first position followed in decreasing order by religion, martial status, income, employment status and finally sex and immigration. The same ranking of mental illnesses by logistic regression places depression as the greatest risk factor followed by anxiety, psychotic disorders, alcohol abuse disorders, drugs and insomnia. Copyright 2010 L’Encéphale. Published by Elsevier Masson SAS.. All rights reserved.
Determining Directional Dependency in Causal Associations
Pornprasertmanit, Sunthud; Little, Todd D.
2014-01-01
Directional dependency is a method to determine the likely causal direction of effect between two variables. This article aims to critique and improve upon the use of directional dependency as a technique to infer causal associations. We comment on several issues raised by von Eye and DeShon (2012), including: encouraging the use of the signs of skewness and excessive kurtosis of both variables, discouraging the use of D’Agostino’s K2, and encouraging the use of directional dependency to compare variables only within time points. We offer improved steps for determining directional dependency that fix the problems we note. Next, we discuss how to integrate directional dependency into longitudinal data analysis with two variables. We also examine the accuracy of directional dependency evaluations when several regression assumptions are violated. Directional dependency can suggest the direction of a relation if (a) the regression error in population is normal, (b) an unobserved explanatory variable correlates with any variables equal to or less than .2, (c) a curvilinear relation between both variables is not strong (standardized regression coefficient ≤ .2), (d) there are no bivariate outliers, and (e) both variables are continuous. PMID:24683282
Montes, Alejandro; Pazos, Gustavo
2016-02-01
Identifying children at risk of failing the National Developmental Screening Test by combining prevalences of children suspected of having inapparent developmental disorders (IDDs) and associated risk factors (RFs) would allow to save resources. 1. To estimate the prevalence of children suspected of having IDDs. 2. To identify associated RFs. 3. To assess three methods developed based on observed RFs and propose a pre-screening procedure. The National Developmental Screening Test was administered to 60 randomly selected children aged between 2 and 4 years old from a socioeconomically disadvantaged area from Puerto Madryn. Twenty-four biological and socioenvironmental outcome measures were assessed in order to identify potential RFs using bivariate and multivariate analyses. The likelihood of failing the screening test was estimated as follows: 1. a multivariate logistic regression model was developed; 2. a relationship was established between the number of RFs present in each child and the percentage of children who failed the test; 3. these two methods were combined. The prevalence of children suspected of having IDDs was 55.0% (95% confidence interval: 42.4%-67.6%). Six RFs were initially identified using the bivariate approach. Three of them (maternal education, number of health checkups and Z scores for height-for-age, and maternal age) were included in the logistic regression model, which has a greater explanatory power. The third method included in the assessment showed greater sensitivity and specificity (85% and 79%, respectively). The estimated prevalence of children suspected of having IDDs was four times higher than the national standards. Seven RFs were identified. Combining the analysis of risk factor accumulation and a multivariate model provides a firm basis for developing a sensitive, specific and practical pre-screening procedure for socioeconomically disadvantaged areas. Sociedad Argentina de Pediatría.
Mannava, Priya; Geibel, Scott; King'ola, Nzioki; Temmerman, Marleen; Luchters, Stanley
2013-01-01
To investigate self-report of heterosexual anal intercourse among male sex workers who sell sex to men, and to identify the socio-demographic characteristics associated with practice of the behavior. Two cross-sectional surveys of male sex workers who sell sex to men in Mombasa, Kenya. Male sex workers selling sex to men were invited to participate in surveys undertaken in 2006 and 2008. A structured questionnaire administered by trained interviewers was used to collect information on socio-demographic characteristics, sexual behaviors, HIV and STI knowledge, and health service usage. Data were analyzed through descriptive and inferential statistics. Bivariate logistic regression, after controlling for year of survey, was used to identify socio-demographic characteristics associated with heterosexual anal intercourse. From a sample of 867 male sex workers, 297 men had sex with a woman during the previous 30 days - of whom 45% did so with a female client and 86% with a non-paying female partner. Within these groups, 66% and 43% of male sex workers had anal intercourse with a female client and non-paying partner respectively. Factors associated with reporting recent heterosexual anal intercourse in bivariate logistic regression after controlling for year of survey participation were being Muslim, ever or currently married, living with wife only, living with a female partner only, living with more than one sexual partner, self-identifying as basha/king/bisexual, having one's own children, and lower education. We found unexpectedly high levels of self-reported anal sex with women by male sex workers, including selling sex to female clients as well as with their own partners. Further investigation among women in Mombasa is needed to understand heterosexual anal sex practices, and how HIV programming may respond.
A Facebook Follow-Up Strategy for Rural Drug-Using Women.
Dickson, Megan F; Staton-Tindall, Michele; Smith, Kirsten E; Leukefeld, Carl; Webster, J Matthew; Oser, Carrie B
2017-06-01
Facebook (FB) use has grown exponentially over the past decade, including in rural areas. Despite its popularity, FB has been underutilized as a research follow-up approach to maintain contact with research participants and may have advantages in less densely populated areas and among more hard-to-reach, at-risk groups. The overall goal of this study was to examine FB as a supplemental follow-up approach to other follow-up strategies with rural drug-using women. Face-to-face interviews were conducted with randomly selected women who completed baseline interviews in 3 rural jails in 1 state. Analyses focus on participants who were released from jail and were eligible for 3-month follow-up (n = 284). Bivariate analyses were used to examine differences between FB users and nonusers, and multivariate logistic regression models examined predictors of 3-month follow-up participation and being located for follow-up using FB. About two-thirds (64.4%) of participants were regular FB users. Bivariate analyses indicated that FB users were younger, more educated, and more likely to have used alcohol in the 30 days before incarceration but less likely to have a chronic health problem. Regression analyses indicated that rural FB users had more than 5 times the odds of being located for the 3-month follow-up interview, even after controlling for other variables. There were no significant predictors of being followed up using FB. Findings suggest that FB is widely used and well accepted among rural drug-using women. Among hard-to-reach populations, including those in rural, geographically isolated regions, FB serves as a method to improve participant follow-up. © 2016 National Rural Health Association.
Kesler, Maya A; Kaul, Rupert; Loutfy, Mona; Myers, Ted; Brunetta, Jason; Remis, Robert S; Gesink, Dionne
2018-01-01
Non-disclosure criminal prosecutions among gay, bisexual and other men who have sex with men (MSM) are increasing, even though transmission risk is low when effective antiretroviral treatment (ART) is used. Reduced HIV testing may reduce the impact of HIV "test and treat" strategies. We aimed to quantify the potential impact of non-disclosure prosecutions on HIV testing and transmission among MSM. MSM attending an HIV and primary care clinic in Toronto completed an audio computer-assisted self-interview questionnaire. HIV-negative participants were asked concern over non-disclosure prosecution altered their likelihood of HIV testing. Responses were characterized using cross-tabulations and bivariate logistic regressions. Flow charts modelled how changes in HIV testing behaviour impacted HIV transmission rates controlling for ART use, condom use and HIV status disclosure. 150 HIV-negative MSM were recruited September 2010 to June 2012. 7% (9/124) were less or much less likely to be tested for HIV due to concern over future prosecution. Bivariate regression showed no obvious socio/sexual demographic characteristics associated with decreased willingness of HIV testing to due concern about prosecution. Subsequent models estimated that this 7% reduction in testing could cause an 18.5% increase in community HIV transmission, 73% of which was driven by the failure of HIV-positive but undiagnosed MSM to access care and reduce HIV transmission risk by using ART. Fear of prosecution over HIV non-disclosure was reported to reduce HIV testing willingness by a minority of HIV-negative MSM in Toronto; however, this reduction has the potential to significantly increase HIV transmission at the community level which has important public health implications.
Predicting Subnational Ebola Virus Disease Epidemic Dynamics from Sociodemographic Indicators
Valeri, Linda; Patterson-Lomba, Oscar; Gurmu, Yared; Ablorh, Akweley; Bobb, Jennifer; Townes, F. William; Harling, Guy
2016-01-01
Background The recent Ebola virus disease (EVD) outbreak in West Africa has spread wider than any previous human EVD epidemic. While individual-level risk factors that contribute to the spread of EVD have been studied, the population-level attributes of subnational regions associated with outbreak severity have not yet been considered. Methods To investigate the area-level predictors of EVD dynamics, we integrated time series data on cumulative reported cases of EVD from the World Health Organization and covariate data from the Demographic and Health Surveys. We first estimated the early growth rates of epidemics in each second-level administrative district (ADM2) in Guinea, Sierra Leone and Liberia using exponential, logistic and polynomial growth models. We then evaluated how these growth rates, as well as epidemic size within ADM2s, were ecologically associated with several demographic and socio-economic characteristics of the ADM2, using bivariate correlations and multivariable regression models. Results The polynomial growth model appeared to best fit the ADM2 epidemic curves, displaying the lowest residual standard error. Each outcome was associated with various regional characteristics in bivariate models, however in stepwise multivariable models only mean education levels were consistently associated with a worse local epidemic. Discussion By combining two common methods—estimation of epidemic parameters using mathematical models, and estimation of associations using ecological regression models—we identified some factors predicting rapid and severe EVD epidemics in West African subnational regions. While care should be taken interpreting such results as anything more than correlational, we suggest that our approach of using data sources that were publicly available in advance of the epidemic or in real-time provides an analytic framework that may assist countries in understanding the dynamics of future outbreaks as they occur. PMID:27732614
Colón-López, Vivian; Ortiz, Ana P; Banerjee, Geetanjoli; Gertz, Alida M; García, Hermes
2013-03-01
This study aimed to assess the demographic, behavioral, and clinical factors associated with HIV and syphilis infection among a sample of men attending a sexually transmitted infection clinic during 2009 to 2010 in San Juan, Puerto Rico (PR). A sample of 350 clinical records from men visiting the clinic for the first time during 2009 to 2010 was reviewed. Descriptive statistics were used to describe the study sample, and bivariate analyses were performed separately for HIV and syphilis to identify factors associated with these infectious diseases. Variables that were significantly associated (p < 0.05) with HIV and syphilis in the bivariate analysis were considered for inclusion in the logistic regression models. Overall, 11.2% and 14.1% of the men were infected with HIV and syphilis, respectively, and 5.1% were coinfected with HIV and syphilis. In multivariate logistic regression models, ever injecting drugs (POR = 8.1; 95% CI 3.0, 21.8) and being a man who has sex with men (MSM) (POR = 5.3; 95% CI 2.3, 11.9) were positively associated with HIV infection. Being a man older than 45 years (POR = 4.0; 95% CI: 1.9, 8.9) and being an MSM (POR = 2.5; 95% CI: 1.3, 4.9) were both significantly associated with syphilis infection. These findings reinforce the need for greater education and prevention efforts for HIV and other STIs among men in PR, particularly those who are MSM. However, there is a need to make an a priori assessment of the level of health literacy in the members of this group so that a culturally sensitive intervention can be provided to the men who attend this STI clinic.
Colón-López, Vivian; Ortiz, Ana P.; Banerjee, Geetanjoli; Gertz, Alida M.; García, Hermes
2013-01-01
Objective This study aimed to assess the demographic, behavioral, and clinical factors associated with HIV and syphilis infection among a sample of men attending a sexually transmitted infection clinic during 2009 to 2010 in San Juan, Puerto Rico (PR). Methods A sample of 350 clinical records from men visiting the clinic for the first time during 2009 to 2010 was reviewed. Descriptive statistics were used to describe the study sample, and bivariate analyses were performed separately for HIV and syphilis to identify factors associated with these infectious diseases. Variables that were significantly associated (p<0.05) with HIV and syphilis in the bivariate analysis were considered for inclusion in the logistic regression models. Results Overall, 11.2% and 14.1% of the men were infected with HIV and syphilis, respectively, and 5.1% were coinfected with HIV and syphilis. In multivariate logistic regression models, ever injecting drugs (POR = 8.1; 95%Cl 3.0, 21.8) and being a man who has sex with men (MSM) (POR = 5.3; 95%CI 2.3, 11.9) were positively associated with HIV infection. Being a man older than 45 years (POR = 4.0; 95%CI: 1.9, 8.9) and being an MSM (POR = 2.5; 95%CI: 1.3, 4.9) were both significantly associated with syphilis infection. Conclusion These findings reinforce the need for greater education and prevention efforts for HIV and other STIs among men in PR, particularly those who are MSM. However, there is a need to make an a priori assessment of the level of health literacy in the members of this group so that a culturally sensitive intervention can be provided to the men who attend this STI clinic. PMID:23556260
Employment program for patients with severe mental illness in Malaysia: a 3-month outcome.
Wan Kasim, Syarifah Hafizah; Midin, Marhani; Abu Bakar, Abdul Kadir; Sidi, Hatta; Nik Jaafar, Nik Ruzyanei; Das, Srijit
2014-01-01
This study aimed to examine the rate and predictive factors of successful employment at 3 months upon enrolment into an employment program among patients with severe mental illness (SMI). A cross-sectional study using universal sampling technique was conducted on patients with SMI who completed a 3-month period of being employed at Hospital Permai, Malaysia. A total of 147 patients were approached and 126 were finally included in the statistical analyses. Successful employment was defined as the ability to work 40 or more hours per month. Factors significantly associated with successful employment from bivariate analyses were entered into a multiple logistic regression analysis to identify predictors of successful employment. The rate of successful employment at 3 months was 68.3% (n=81). Significant factors associated with successful employment from bivariate analyses were having past history of working, good family support, less number of psychiatric admissions, good compliance to medicine, good interest in work, living in hostel, being motivated to work, satisfied with the job or salary, getting a preferred job, being in competitive or supported employment and having higher than median scores of PANNS on the positive, negative and general psychopathology. Significant predictors of employment, from a logistic regression model were having good past history of working (p<0.021; OR 6.12; [95% CI 2.1-11.9]) and getting a preferred job (p<0.032; [OR 4.021; 95% CI 1.83-12.1]). Results showed a high employment rate among patients with SMI. Good past history of working and getting a preferred job were significant predictors of successful employment. Copyright © 2014 Elsevier Inc. All rights reserved.
Kaul, Rupert; Loutfy, Mona; Myers, Ted; Brunetta, Jason; Gesink, Dionne
2018-01-01
Background Non-disclosure criminal prosecutions among gay, bisexual and other men who have sex with men (MSM) are increasing, even though transmission risk is low when effective antiretroviral treatment (ART) is used. Reduced HIV testing may reduce the impact of HIV “test and treat” strategies. We aimed to quantify the potential impact of non-disclosure prosecutions on HIV testing and transmission among MSM. Methods MSM attending an HIV and primary care clinic in Toronto completed an audio computer-assisted self-interview questionnaire. HIV-negative participants were asked concern over non-disclosure prosecution altered their likelihood of HIV testing. Responses were characterized using cross-tabulations and bivariate logistic regressions. Flow charts modelled how changes in HIV testing behaviour impacted HIV transmission rates controlling for ART use, condom use and HIV status disclosure. Results 150 HIV-negative MSM were recruited September 2010 to June 2012. 7% (9/124) were less or much less likely to be tested for HIV due to concern over future prosecution. Bivariate regression showed no obvious socio/sexual demographic characteristics associated with decreased willingness of HIV testing to due concern about prosecution. Subsequent models estimated that this 7% reduction in testing could cause an 18.5% increase in community HIV transmission, 73% of which was driven by the failure of HIV-positive but undiagnosed MSM to access care and reduce HIV transmission risk by using ART. Conclusions Fear of prosecution over HIV non-disclosure was reported to reduce HIV testing willingness by a minority of HIV-negative MSM in Toronto; however, this reduction has the potential to significantly increase HIV transmission at the community level which has important public health implications. PMID:29489890
Children's mental health and family functioning in Rhode Island.
Kim, Hyun Hanna K; Viner-Brown, Samara I; Garcia, Jorge
2007-02-01
Our objectives were to (a) estimate the prevalence of children's mental health problems, (b) assess family functioning, and (c) investigate the relationship between children's mental health and family functioning in Rhode Island. From the 2003 National Survey of Children's Health, Rhode Island data for children 6 to 17 years of age were used for the analyses (N = 1326). Two aspects of family functioning measures, parental stress and parental involvement, were constructed and were examined by children's mental health problems, as well as other child and family characteristics (child's age, gender, race/ethnicity, special needs, parent's education, income, employment, family structure, number of children, and mother's general and mental health). Bivariate analyses and multivariate logistic regression were used to investigate the relationship. Among Rhode Island children, nearly 1 (19.0%) in 5 had mental health problems, 1 (15.6%) in 6 lived with a highly stressed parent, and one third (32.7%) had parents with low involvement. Bivariate analyses showed that high parental stress and low parental involvement were higher among parents of children with mental health problems than parents of children without those problems (33.2% vs 11.0% and 41.0% vs 30.3%, respectively). In multivariate logistic regression, parents of children with mental health problems had nearly 4 times the odds of high stress compared with parents of children without those problems. When children's mental health problems were severe, the odds of high parental stress were elevated. However, children's mental health was not associated with parental involvement. Children's mental health was strongly associated with parental stress, but it was not associated with parental involvement. The findings indicate that when examining the mental health issues of children, parental mental health and stress must be considered.
An operator calculus for surface and volume modeling
NASA Technical Reports Server (NTRS)
Gordon, W. J.
1984-01-01
The mathematical techniques which form the foundation for most of the surface and volume modeling techniques used in practice are briefly described. An outline of what may be termed an operator calculus for the approximation and interpolation of functions of more than one independent variable is presented. By considering the linear operators associated with bivariate and multivariate interpolation/approximation schemes, it is shown how they can be compounded by operator multiplication and Boolean addition to obtain a distributive lattice of approximation operators. It is then demonstrated via specific examples how this operator calculus leads to practical techniques for sculptured surface and volume modeling.
Biostatistics Series Module 6: Correlation and Linear Regression.
Hazra, Avijit; Gogtay, Nithya
2016-01-01
Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient ( r ). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r 2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation ( y = a + bx ), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous.
Biostatistics Series Module 6: Correlation and Linear Regression
Hazra, Avijit; Gogtay, Nithya
2016-01-01
Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient (r). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation (y = a + bx), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous. PMID:27904175
Rotolo, Federico; Paoletti, Xavier; Michiels, Stefan
2018-03-01
Surrogate endpoints are attractive for use in clinical trials instead of well-established endpoints because of practical convenience. To validate a surrogate endpoint, two important measures can be estimated in a meta-analytic context when individual patient data are available: the R indiv 2 or the Kendall's τ at the individual level, and the R trial 2 at the trial level. We aimed at providing an R implementation of classical and well-established as well as more recent statistical methods for surrogacy assessment with failure time endpoints. We also intended incorporating utilities for model checking and visualization and data generating methods described in the literature to date. In the case of failure time endpoints, the classical approach is based on two steps. First, a Kendall's τ is estimated as measure of individual level surrogacy using a copula model. Then, the R trial 2 is computed via a linear regression of the estimated treatment effects; at this second step, the estimation uncertainty can be accounted for via measurement-error model or via weights. In addition to the classical approach, we recently developed an approach based on bivariate auxiliary Poisson models with individual random effects to measure the Kendall's τ and treatment-by-trial interactions to measure the R trial 2 . The most common data simulation models described in the literature are based on: copula models, mixed proportional hazard models, and mixture of half-normal and exponential random variables. The R package surrosurv implements the classical two-step method with Clayton, Plackett, and Hougaard copulas. It also allows to optionally adjusting the second-step linear regression for measurement-error. The mixed Poisson approach is implemented with different reduced models in addition to the full model. We present the package functions for estimating the surrogacy models, for checking their convergence, for performing leave-one-trial-out cross-validation, and for plotting the results. We illustrate their use in practice on individual patient data from a meta-analysis of 4069 patients with advanced gastric cancer from 20 trials of chemotherapy. The surrosurv package provides an R implementation of classical and recent statistical methods for surrogacy assessment of failure time endpoints. Flexible simulation functions are available to generate data according to the methods described in the literature. Copyright © 2017 Elsevier B.V. All rights reserved.
ERIC Educational Resources Information Center
Quinino, Roberto C.; Reis, Edna A.; Bessegato, Lupercio F.
2013-01-01
This article proposes the use of the coefficient of determination as a statistic for hypothesis testing in multiple linear regression based on distributions acquired by beta sampling. (Contains 3 figures.)
Rasmussen, Patrick P.; Gray, John R.; Glysson, G. Douglas; Ziegler, Andrew C.
2009-01-01
In-stream continuous turbidity and streamflow data, calibrated with measured suspended-sediment concentration data, can be used to compute a time series of suspended-sediment concentration and load at a stream site. Development of a simple linear (ordinary least squares) regression model for computing suspended-sediment concentrations from instantaneous turbidity data is the first step in the computation process. If the model standard percentage error (MSPE) of the simple linear regression model meets a minimum criterion, this model should be used to compute a time series of suspended-sediment concentrations. Otherwise, a multiple linear regression model using paired instantaneous turbidity and streamflow data is developed and compared to the simple regression model. If the inclusion of the streamflow variable proves to be statistically significant and the uncertainty associated with the multiple regression model results in an improvement over that for the simple linear model, the turbidity-streamflow multiple linear regression model should be used to compute a suspended-sediment concentration time series. The computed concentration time series is subsequently used with its paired streamflow time series to compute suspended-sediment loads by standard U.S. Geological Survey techniques. Once an acceptable regression model is developed, it can be used to compute suspended-sediment concentration beyond the period of record used in model development with proper ongoing collection and analysis of calibration samples. Regression models to compute suspended-sediment concentrations are generally site specific and should never be considered static, but they represent a set period in a continually dynamic system in which additional data will help verify any change in sediment load, type, and source.
Arab, Ali; Holan, Scott H.; Wikle, Christopher K.; Wildhaber, Mark L.
2012-01-01
Ecological studies involving counts of abundance, presence–absence or occupancy rates often produce data having a substantial proportion of zeros. Furthermore, these types of processes are typically multivariate and only adequately described by complex nonlinear relationships involving externally measured covariates. Ignoring these aspects of the data and implementing standard approaches can lead to models that fail to provide adequate scientific understanding of the underlying ecological processes, possibly resulting in a loss of inferential power. One method of dealing with data having excess zeros is to consider the class of univariate zero-inflated generalized linear models. However, this class of models fails to address the multivariate and nonlinear aspects associated with the data usually encountered in practice. Therefore, we propose a semiparametric bivariate zero-inflated Poisson model that takes into account both of these data attributes. The general modeling framework is hierarchical Bayes and is suitable for a broad range of applications. We demonstrate the effectiveness of our model through a motivating example on modeling catch per unit area for multiple species using data from the Missouri River Benthic Fishes Study, implemented by the United States Geological Survey.
NASA Astrophysics Data System (ADS)
Kutzbach, L.; Schneider, J.; Sachs, T.; Giebels, M.; Nykänen, H.; Shurpali, N. J.; Martikainen, P. J.; Alm, J.; Wilmking, M.
2007-11-01
Closed (non-steady state) chambers are widely used for quantifying carbon dioxide (CO2) fluxes between soils or low-stature canopies and the atmosphere. It is well recognised that covering a soil or vegetation by a closed chamber inherently disturbs the natural CO2 fluxes by altering the concentration gradients between the soil, the vegetation and the overlying air. Thus, the driving factors of CO2 fluxes are not constant during the closed chamber experiment, and no linear increase or decrease of CO2 concentration over time within the chamber headspace can be expected. Nevertheless, linear regression has been applied for calculating CO2 fluxes in many recent, partly influential, studies. This approach has been justified by keeping the closure time short and assuming the concentration change over time to be in the linear range. Here, we test if the application of linear regression is really appropriate for estimating CO2 fluxes using closed chambers over short closure times and if the application of nonlinear regression is necessary. We developed a nonlinear exponential regression model from diffusion and photosynthesis theory. This exponential model was tested with four different datasets of CO2 flux measurements (total number: 1764) conducted at three peatlands sites in Finland and a tundra site in Siberia. Thorough analyses of residuals demonstrated that linear regression was frequently not appropriate for the determination of CO2 fluxes by closed-chamber methods, even if closure times were kept short. The developed exponential model was well suited for nonlinear regression of the concentration over time c(t) evolution in the chamber headspace and estimation of the initial CO2 fluxes at closure time for the majority of experiments. However, a rather large percentage of the exponential regression functions showed curvatures not consistent with the theoretical model which is considered to be caused by violations of the underlying model assumptions. Especially the effects of turbulence and pressure disturbances by the chamber deployment are suspected to have caused unexplainable curvatures. CO2 flux estimates by linear regression can be as low as 40% of the flux estimates of exponential regression for closure times of only two minutes. The degree of underestimation increased with increasing CO2 flux strength and was dependent on soil and vegetation conditions which can disturb not only the quantitative but also the qualitative evaluation of CO2 flux dynamics. The underestimation effect by linear regression was observed to be different for CO2 uptake and release situations which can lead to stronger bias in the daily, seasonal and annual CO2 balances than in the individual fluxes. To avoid serious bias of CO2 flux estimates based on closed chamber experiments, we suggest further tests using published datasets and recommend the use of nonlinear regression models for future closed chamber studies.
Developing a bivariate spatial association measure: An integration of Pearson's r and Moran's I
NASA Astrophysics Data System (ADS)
Lee, Sang-Il
This research is concerned with developing a bivariate spatial association measure or spatial correlation coefficient, which is intended to capture spatial association among observations in terms of their point-to-point relationships across two spatial patterns. The need for parameterization of the bivariate spatial dependence is precipitated by the realization that aspatial bivariate association measures, such as Pearson's correlation coefficient, do not recognize spatial distributional aspects of data sets. This study devises an L statistic by integrating Pearson's r as an aspatial bivariate association measure and Moran's I as a univariate spatial association measure. The concept of a spatial smoothing scalar (SSS) plays a pivotal role in this task.
Gregori, Dario; Rosato, Rosalba; Zecchin, Massimo; Di Lenarda, Andrea
2005-01-01
This paper discusses the use of bivariate survival curves estimators within the competing risk framework. Competing risks models are used for the analysis of medical data with more than one cause of death. The case of dilated cardiomiopathy is explored. Bivariate survival curves plot the conjoint mortality processes. The different graphic representation of bivariate survival analysis is the major contribute of this methodology to the competing risks analysis.
NASA Astrophysics Data System (ADS)
Mahaboob, B.; Venkateswarlu, B.; Sankar, J. Ravi; Balasiddamuni, P.
2017-11-01
This paper uses matrix calculus techniques to obtain Nonlinear Least Squares Estimator (NLSE), Maximum Likelihood Estimator (MLE) and Linear Pseudo model for nonlinear regression model. David Pollard and Peter Radchenko [1] explained analytic techniques to compute the NLSE. However the present research paper introduces an innovative method to compute the NLSE using principles in multivariate calculus. This study is concerned with very new optimization techniques used to compute MLE and NLSE. Anh [2] derived NLSE and MLE of a heteroscedatistic regression model. Lemcoff [3] discussed a procedure to get linear pseudo model for nonlinear regression model. In this research article a new technique is developed to get the linear pseudo model for nonlinear regression model using multivariate calculus. The linear pseudo model of Edmond Malinvaud [4] has been explained in a very different way in this paper. David Pollard et.al used empirical process techniques to study the asymptotic of the LSE (Least-squares estimation) for the fitting of nonlinear regression function in 2006. In Jae Myung [13] provided a go conceptual for Maximum likelihood estimation in his work “Tutorial on maximum likelihood estimation
A method for fitting regression splines with varying polynomial order in the linear mixed model.
Edwards, Lloyd J; Stewart, Paul W; MacDougall, James E; Helms, Ronald W
2006-02-15
The linear mixed model has become a widely used tool for longitudinal analysis of continuous variables. The use of regression splines in these models offers the analyst additional flexibility in the formulation of descriptive analyses, exploratory analyses and hypothesis-driven confirmatory analyses. We propose a method for fitting piecewise polynomial regression splines with varying polynomial order in the fixed effects and/or random effects of the linear mixed model. The polynomial segments are explicitly constrained by side conditions for continuity and some smoothness at the points where they join. By using a reparameterization of this explicitly constrained linear mixed model, an implicitly constrained linear mixed model is constructed that simplifies implementation of fixed-knot regression splines. The proposed approach is relatively simple, handles splines in one variable or multiple variables, and can be easily programmed using existing commercial software such as SAS or S-plus. The method is illustrated using two examples: an analysis of longitudinal viral load data from a study of subjects with acute HIV-1 infection and an analysis of 24-hour ambulatory blood pressure profiles.
Evaluating Evidence for Conceptually Related Constructs Using Bivariate Correlations
ERIC Educational Resources Information Center
Swank, Jacqueline M.; Mullen, Patrick R.
2017-01-01
The article serves as a guide for researchers in developing evidence of validity using bivariate correlations, specifically construct validity. The authors outline the steps for calculating and interpreting bivariate correlations. Additionally, they provide an illustrative example and discuss the implications.
GIS Tools to Estimate Average Annual Daily Traffic
DOT National Transportation Integrated Search
2012-06-01
This project presents five tools that were created for a geographical information system to estimate Annual Average Daily : Traffic using linear regression. Three of the tools can be used to prepare spatial data for linear regression. One tool can be...
Jose F. Negron; Willis C. Schaupp; Kenneth E. Gibson; John Anhold; Dawn Hansen; Ralph Thier; Phil Mocettini
1999-01-01
Data collected from Douglas-fir stands infected by the Douglas-fir beetle in Wyoming, Montana, Idaho, and Utah, were used to develop models to estimate amount of mortality in terms of basal area killed. Models were built using stepwise linear regression and regression tree approaches. Linear regression models using initial Douglas-fir basal area were built for all...
Ling, Ru; Liu, Jiawang
2011-12-01
To construct prediction model for health workforce and hospital beds in county hospitals of Hunan by multiple linear regression. We surveyed 16 counties in Hunan with stratified random sampling according to uniform questionnaires,and multiple linear regression analysis with 20 quotas selected by literature view was done. Independent variables in the multiple linear regression model on medical personnels in county hospitals included the counties' urban residents' income, crude death rate, medical beds, business occupancy, professional equipment value, the number of devices valued above 10 000 yuan, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, and utilization rate of hospital beds. Independent variables in the multiple linear regression model on county hospital beds included the the population of aged 65 and above in the counties, disposable income of urban residents, medical personnel of medical institutions in county area, business occupancy, the total value of professional equipment, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, utilization rate of hospital beds, and length of hospitalization. The prediction model shows good explanatory and fitting, and may be used for short- and mid-term forecasting.
Watanabe, Hiroyuki; Miyazaki, Hiroyasu
2006-01-01
Over- and/or under-correction of QT intervals for changes in heart rate may lead to misleading conclusions and/or masking the potential of a drug to prolong the QT interval. This study examines a nonparametric regression model (Loess Smoother) to adjust the QT interval for differences in heart rate, with an improved fitness over a wide range of heart rates. 240 sets of (QT, RR) observations collected from each of 8 conscious and non-treated beagle dogs were used as the materials for investigation. The fitness of the nonparametric regression model to the QT-RR relationship was compared with four models (individual linear regression, common linear regression, and Bazett's and Fridericia's correlation models) with reference to Akaike's Information Criterion (AIC). Residuals were visually assessed. The bias-corrected AIC of the nonparametric regression model was the best of the models examined in this study. Although the parametric models did not fit, the nonparametric regression model improved the fitting at both fast and slow heart rates. The nonparametric regression model is the more flexible method compared with the parametric method. The mathematical fit for linear regression models was unsatisfactory at both fast and slow heart rates, while the nonparametric regression model showed significant improvement at all heart rates in beagle dogs.
Linear regression analysis: part 14 of a series on evaluation of scientific publications.
Schneider, Astrid; Hommel, Gerhard; Blettner, Maria
2010-11-01
Regression analysis is an important statistical method for the analysis of medical data. It enables the identification and characterization of relationships among multiple factors. It also enables the identification of prognostically relevant risk factors and the calculation of risk scores for individual prognostication. This article is based on selected textbooks of statistics, a selective review of the literature, and our own experience. After a brief introduction of the uni- and multivariable regression models, illustrative examples are given to explain what the important considerations are before a regression analysis is performed, and how the results should be interpreted. The reader should then be able to judge whether the method has been used correctly and interpret the results appropriately. The performance and interpretation of linear regression analysis are subject to a variety of pitfalls, which are discussed here in detail. The reader is made aware of common errors of interpretation through practical examples. Both the opportunities for applying linear regression analysis and its limitations are presented.
Grajeda, Laura M; Ivanescu, Andrada; Saito, Mayuko; Crainiceanu, Ciprian; Jaganath, Devan; Gilman, Robert H; Crabtree, Jean E; Kelleher, Dermott; Cabrera, Lilia; Cama, Vitaliano; Checkley, William
2016-01-01
Childhood growth is a cornerstone of pediatric research. Statistical models need to consider individual trajectories to adequately describe growth outcomes. Specifically, well-defined longitudinal models are essential to characterize both population and subject-specific growth. Linear mixed-effect models with cubic regression splines can account for the nonlinearity of growth curves and provide reasonable estimators of population and subject-specific growth, velocity and acceleration. We provide a stepwise approach that builds from simple to complex models, and account for the intrinsic complexity of the data. We start with standard cubic splines regression models and build up to a model that includes subject-specific random intercepts and slopes and residual autocorrelation. We then compared cubic regression splines vis-à-vis linear piecewise splines, and with varying number of knots and positions. Statistical code is provided to ensure reproducibility and improve dissemination of methods. Models are applied to longitudinal height measurements in a cohort of 215 Peruvian children followed from birth until their fourth year of life. Unexplained variability, as measured by the variance of the regression model, was reduced from 7.34 when using ordinary least squares to 0.81 (p < 0.001) when using a linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p < 0.001) and slopes (p < 0.001) of the individual growth trajectories. We also identified important serial correlation within the structure of the data (ρ = 0.66; 95 % CI 0.64 to 0.68; p < 0.001), which we modeled with a first order continuous autoregressive error term as evidenced by the variogram of the residuals and by a lack of association among residuals. The final model provides a parametric linear regression equation for both estimation and prediction of population- and individual-level growth in height. We show that cubic regression splines are superior to linear regression splines for the case of a small number of knots in both estimation and prediction with the full linear mixed effect model (AIC 19,352 vs. 19,598, respectively). While the regression parameters are more complex to interpret in the former, we argue that inference for any problem depends more on the estimated curve or differences in curves rather than the coefficients. Moreover, use of cubic regression splines provides biological meaningful growth velocity and acceleration curves despite increased complexity in coefficient interpretation. Through this stepwise approach, we provide a set of tools to model longitudinal childhood data for non-statisticians using linear mixed-effect models.
Prediction of monthly rainfall in Victoria, Australia: Clusterwise linear regression approach
NASA Astrophysics Data System (ADS)
Bagirov, Adil M.; Mahmood, Arshad; Barton, Andrew
2017-05-01
This paper develops the Clusterwise Linear Regression (CLR) technique for prediction of monthly rainfall. The CLR is a combination of clustering and regression techniques. It is formulated as an optimization problem and an incremental algorithm is designed to solve it. The algorithm is applied to predict monthly rainfall in Victoria, Australia using rainfall data with five input meteorological variables over the period of 1889-2014 from eight geographically diverse weather stations. The prediction performance of the CLR method is evaluated by comparing observed and predicted rainfall values using four measures of forecast accuracy. The proposed method is also compared with the CLR using the maximum likelihood framework by the expectation-maximization algorithm, multiple linear regression, artificial neural networks and the support vector machines for regression models using computational results. The results demonstrate that the proposed algorithm outperforms other methods in most locations.
Regression Model Term Selection for the Analysis of Strain-Gage Balance Calibration Data
NASA Technical Reports Server (NTRS)
Ulbrich, Norbert Manfred; Volden, Thomas R.
2010-01-01
The paper discusses the selection of regression model terms for the analysis of wind tunnel strain-gage balance calibration data. Different function class combinations are presented that may be used to analyze calibration data using either a non-iterative or an iterative method. The role of the intercept term in a regression model of calibration data is reviewed. In addition, useful algorithms and metrics originating from linear algebra and statistics are recommended that will help an analyst (i) to identify and avoid both linear and near-linear dependencies between regression model terms and (ii) to make sure that the selected regression model of the calibration data uses only statistically significant terms. Three different tests are suggested that may be used to objectively assess the predictive capability of the final regression model of the calibration data. These tests use both the original data points and regression model independent confirmation points. Finally, data from a simplified manual calibration of the Ames MK40 balance is used to illustrate the application of some of the metrics and tests to a realistic calibration data set.
Some properties of a 5-parameter bivariate probability distribution
NASA Technical Reports Server (NTRS)
Tubbs, J. D.; Brewer, D. W.; Smith, O. E.
1983-01-01
A five-parameter bivariate gamma distribution having two shape parameters, two location parameters and a correlation parameter was developed. This more general bivariate gamma distribution reduces to the known four-parameter distribution. The five-parameter distribution gives a better fit to the gust data. The statistical properties of this general bivariate gamma distribution and a hypothesis test were investigated. Although these developments have come too late in the Shuttle program to be used directly as design criteria for ascent wind gust loads, the new wind gust model has helped to explain the wind profile conditions which cause large dynamic loads. Other potential applications of the newly developed five-parameter bivariate gamma distribution are in the areas of reliability theory, signal noise, and vibration mechanics.
Bivariate extreme value distributions
NASA Technical Reports Server (NTRS)
Elshamy, M.
1992-01-01
In certain engineering applications, such as those occurring in the analyses of ascent structural loads for the Space Transportation System (STS), some of the load variables have a lower bound of zero. Thus, the need for practical models of bivariate extreme value probability distribution functions with lower limits was identified. We discuss the Gumbel models and present practical forms of bivariate extreme probability distributions of Weibull and Frechet types with two parameters. Bivariate extreme value probability distribution functions can be expressed in terms of the marginal extremel distributions and a 'dependence' function subject to certain analytical conditions. Properties of such bivariate extreme distributions, sums and differences of paired extremals, as well as the corresponding forms of conditional distributions, are discussed. Practical estimation techniques are also given.
Predictors of anemia among pregnant women in Westmoreland, Jamaica
Charles, Alyson M.; Campbell-Stennett, Dianne; Yatich, Nelly; Jolly, Pauline E.
2010-01-01
Anemia in pregnancy is a worldwide problem, but it is most prevalent in the developing world. This research project was conducted to determine the predictors of anemia in pregnant women in Westmoreland, Jamaica. A cross-sectional study design was conducted and descriptive, bivariate, and multiple logistic regression analyses were used. Body mass index, Mid-upper arm circumference, and the number of antenatal care visits showed a statistically significant association with anemia. Based on the results, we believe that maintaining a healthy body weight, and frequently visiting an antenatal clinic, will help to lower the prevalence of anemia among pregnant women in Westmoreland. PMID:20526925
Access to Care and Satisfaction Among Health Center Patients With Chronic Conditions.
Shi, Leiyu; Lee, De-Chih; Haile, Geraldine Pierre; Liang, Hailun; Chung, Michelle; Sripipatana, Alek
This study examined access to care and satisfaction among health center patients with chronic conditions. Data for this study were obtained from the 2009 Health Center Patient Survey. Dependent variables of interest included 5 measures of access to and satisfaction with care, whereas the main independent variable was number of chronic conditions. Results of bivariate analysis and multiple logistic regressions showed that patients with chronic conditions had significantly higher odds of reporting access barriers than those without chronic conditions. Our results suggested that additional efforts and resources are necessary to address the needs of health center patients with chronic conditions.
Predictors of workplace violence among female sex workers in Tijuana, Mexico.
Katsulis, Yasmina; Durfee, Alesha; Lopez, Vera; Robillard, Alyssa
2015-05-01
For sex workers, differences in rates of exposure to workplace violence are likely influenced by a variety of risk factors, including where one works and under what circumstances. Economic stressors, such as housing insecurity, may also increase the likelihood of exposure. Bivariate analyses demonstrate statistically significant associations between workplace violence and selected predictor variables, including age, drug use, exchanging sex for goods, soliciting clients outdoors, and experiencing housing insecurity. Multivariate regression analysis shows that after controlling for each of these variables in one model, only soliciting clients outdoors and housing insecurity emerge as statistically significant predictors for workplace violence. © The Author(s) 2014.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rupšys, P.
A system of stochastic differential equations (SDE) with mixed-effects parameters and multivariate normal copula density function were used to develop tree height model for Scots pine trees in Lithuania. A two-step maximum likelihood parameter estimation method is used and computational guidelines are given. After fitting the conditional probability density functions to outside bark diameter at breast height, and total tree height, a bivariate normal copula distribution model was constructed. Predictions from the mixed-effects parameters SDE tree height model calculated during this research were compared to the regression tree height equations. The results are implemented in the symbolic computational language MAPLE.
Mroz, T A
1999-10-01
This paper contains a Monte Carlo evaluation of estimators used to control for endogeneity of dummy explanatory variables in continuous outcome regression models. When the true model has bivariate normal disturbances, estimators using discrete factor approximations compare favorably to efficient estimators in terms of precision and bias; these approximation estimators dominate all the other estimators examined when the disturbances are non-normal. The experiments also indicate that one should liberally add points of support to the discrete factor distribution. The paper concludes with an application of the discrete factor approximation to the estimation of the impact of marriage on wages.
Covariations of adolescent weight-control, health-risk and health-promoting behaviors.
Rafiroiu, Codruta; Sargent, Roger G; Parra-Medina, Deborah; Drane, Wanzer J; Valois, Robert F
2003-01-01
To assess the prevalence of dieting and investigate clusters of risk behaviors among adolescents. Data were secured from a random sample of adolescents (4,636) and analyzed using bivariate methods and logistic regression. From the survey sample, 19.2% adolescents were classified as extreme, 43.2% as moderate dieters, 37.2% as nondieters. Extreme dieters were more likely to use alcohol, cigarettes, and/or marijuana and to attempt suicide and less likely to practice vigorous exercise. Moderate dieters were less likely to use cigarettes, marijuana and more likely to engage in vigorous exercise, with differences across gender-race categories. Results have relevance for developing multicomponent programs for adolescents.
Scoring and staging systems using cox linear regression modeling and recursive partitioning.
Lee, J W; Um, S H; Lee, J B; Mun, J; Cho, H
2006-01-01
Scoring and staging systems are used to determine the order and class of data according to predictors. Systems used for medical data, such as the Child-Turcotte-Pugh scoring and staging systems for ordering and classifying patients with liver disease, are often derived strictly from physicians' experience and intuition. We construct objective and data-based scoring/staging systems using statistical methods. We consider Cox linear regression modeling and recursive partitioning techniques for censored survival data. In particular, to obtain a target number of stages we propose cross-validation and amalgamation algorithms. We also propose an algorithm for constructing scoring and staging systems by integrating local Cox linear regression models into recursive partitioning, so that we can retain the merits of both methods such as superior predictive accuracy, ease of use, and detection of interactions between predictors. The staging system construction algorithms are compared by cross-validation evaluation of real data. The data-based cross-validation comparison shows that Cox linear regression modeling is somewhat better than recursive partitioning when there are only continuous predictors, while recursive partitioning is better when there are significant categorical predictors. The proposed local Cox linear recursive partitioning has better predictive accuracy than Cox linear modeling and simple recursive partitioning. This study indicates that integrating local linear modeling into recursive partitioning can significantly improve prediction accuracy in constructing scoring and staging systems.
Scarneciu, Camelia C; Sangeorzan, Livia; Rus, Horatiu; Scarneciu, Vlad D; Varciu, Mihai S; Andreescu, Oana; Scarneciu, Ioan
2017-01-01
This study aimed at assessing the incidence of pulmonary hypertension (PH) at newly diagnosed hyperthyroid patients and at finding a simple model showing the complex functional relation between pulmonary hypertension in hyperthyroidism and the factors causing it. The 53 hyperthyroid patients (H-group) were evaluated mainly by using an echocardiographical method and compared with 35 euthyroid (E-group) and 25 healthy people (C-group). In order to identify the factors causing pulmonary hypertension the statistical method of comparing the values of arithmetical means is used. The functional relation between the two random variables (PAPs and each of the factors determining it within our research study) can be expressed by linear or non-linear function. By applying the linear regression method described by a first-degree equation the line of regression (linear model) has been determined; by applying the non-linear regression method described by a second degree equation, a parabola-type curve of regression (non-linear or polynomial model) has been determined. We made the comparison and the validation of these two models by calculating the determination coefficient (criterion 1), the comparison of residuals (criterion 2), application of AIC criterion (criterion 3) and use of F-test (criterion 4). From the H-group, 47% have pulmonary hypertension completely reversible when obtaining euthyroidism. The factors causing pulmonary hypertension were identified: previously known- level of free thyroxin, pulmonary vascular resistance, cardiac output; new factors identified in this study- pretreatment period, age, systolic blood pressure. According to the four criteria and to the clinical judgment, we consider that the polynomial model (graphically parabola- type) is better than the linear one. The better model showing the functional relation between the pulmonary hypertension in hyperthyroidism and the factors identified in this study is given by a polynomial equation of second degree where the parabola is its graphical representation.
As a fast and effective technique, the multiple linear regression (MLR) method has been widely used in modeling and prediction of beach bacteria concentrations. Among previous works on this subject, however, several issues were insufficiently or inconsistently addressed. Those is...
A simplified competition data analysis for radioligand specific activity determination.
Venturino, A; Rivera, E S; Bergoc, R M; Caro, R A
1990-01-01
Non-linear regression and two-step linear fit methods were developed to determine the actual specific activity of 125I-ovine prolactin by radioreceptor self-displacement analysis. The experimental results obtained by the different methods are superposable. The non-linear regression method is considered to be the most adequate procedure to calculate the specific activity, but if its software is not available, the other described methods are also suitable.
Height and Weight Estimation From Anthropometric Measurements Using Machine Learning Regressions
Fernandes, Bruno J. T.; Roque, Alexandre
2018-01-01
Height and weight are measurements explored to tracking nutritional diseases, energy expenditure, clinical conditions, drug dosages, and infusion rates. Many patients are not ambulant or may be unable to communicate, and a sequence of these factors may not allow accurate estimation or measurements; in those cases, it can be estimated approximately by anthropometric means. Different groups have proposed different linear or non-linear equations which coefficients are obtained by using single or multiple linear regressions. In this paper, we present a complete study of the application of different learning models to estimate height and weight from anthropometric measurements: support vector regression, Gaussian process, and artificial neural networks. The predicted values are significantly more accurate than that obtained with conventional linear regressions. In all the cases, the predictions are non-sensitive to ethnicity, and to gender, if more than two anthropometric parameters are analyzed. The learning model analysis creates new opportunities for anthropometric applications in industry, textile technology, security, and health care. PMID:29651366
NASA Astrophysics Data System (ADS)
Samhouri, M.; Al-Ghandoor, A.; Fouad, R. H.
2009-08-01
In this study two techniques, for modeling electricity consumption of the Jordanian industrial sector, are presented: (i) multivariate linear regression and (ii) neuro-fuzzy models. Electricity consumption is modeled as function of different variables such as number of establishments, number of employees, electricity tariff, prevailing fuel prices, production outputs, capacity utilizations, and structural effects. It was found that industrial production and capacity utilization are the most important variables that have significant effect on future electrical power demand. The results showed that both the multivariate linear regression and neuro-fuzzy models are generally comparable and can be used adequately to simulate industrial electricity consumption. However, comparison that is based on the square root average squared error of data suggests that the neuro-fuzzy model performs slightly better for future prediction of electricity consumption than the multivariate linear regression model. Such results are in full agreement with similar work, using different methods, for other countries.
Carvalho, Carlos; Gomes, Danielo G.; Agoulmine, Nazim; de Souza, José Neuman
2011-01-01
This paper proposes a method based on multivariate spatial and temporal correlation to improve prediction accuracy in data reduction for Wireless Sensor Networks (WSN). Prediction of data not sent to the sink node is a technique used to save energy in WSNs by reducing the amount of data traffic. However, it may not be very accurate. Simulations were made involving simple linear regression and multiple linear regression functions to assess the performance of the proposed method. The results show a higher correlation between gathered inputs when compared to time, which is an independent variable widely used for prediction and forecasting. Prediction accuracy is lower when simple linear regression is used, whereas multiple linear regression is the most accurate one. In addition to that, our proposal outperforms some current solutions by about 50% in humidity prediction and 21% in light prediction. To the best of our knowledge, we believe that we are probably the first to address prediction based on multivariate correlation for WSN data reduction. PMID:22346626
The measured effect magnitude of co-morbidities on burn injury mortality.
Knowlin, Laquanda; Stanford, Lindsay; Moore, Danier; Cairns, Bruce; Charles, Anthony
2016-11-01
The ability to better prognosticate burn injury outcome is challenging and historically, most center use the Baux or revised Baux score to help prognosticate burn outcome, however, the weighted contribution of comorbidity on burn mortality has traditionally not been accounted for nor adequately studied. We therefore sought to determine the effect of comorbidities, using the Charlson comorbidity index (CCI) on burn mortality. The purpose of this study was to determine the effect of comorbidities on burn injury mortality as determined by the LA50 (lethal TBSA burn at which 50% of the cohort will succumb from the burn injury) in a retrospective analysis of patients admitted to a regional burn center from 2002 to 2012. Independent variables analyzed included basic demographics, burn mechanism, presence of inhalation injury, TBSA (total body surface area), length of hospital stay, and pre-existing comorbidities. Bivariate analysis was performed and logistic regression modeling using significant variables was utilized to estimate odds of death. 7640 patients were included in this study. Overall survival rate was 96%. 40% of our burn cohort had at least one comorbidity. There was a linear increase in the likelihood of death with an increase in CCI. The logistic regression model for mortality outcomes identified four statistically significant variables: age, TBSA, inhalational injury and the presence of comorbidities (OR=1.59 for each 1 point increase in CCI; 95% CI 1.44-1.77). The unadjusted LA50 was 53% for the entire cohort. Partial adjustment multivariate regression controlling for burn mechanism and inhalation injury only, produced a slight reduction in LA50 for the 0-18 and 19-64 age categories to 76% and 48% TBSA, respectively, but a significant decrease occurred in the ≥65 years age group with a reduced LA50 to 20% TBSA (p<0.001). After full adjustment for all significant covariates, including comorbidities, the independent magnitude of effect of comorbidities on the LA50 was evident in the <65 cohort. The full adjustment showed a LA50 decreased to 61% and 43% TBSA, respectively in the 0-18 and >18-65 age groups respectively (p<0.001), however, in the >65 years age cohort there was no change in the LA50. Preexisting comorbidities have a significant effect on burn injury mortality in all age groups, particularly the younger burn population. The measured effect of comorbidities in the >65 yr age cohort was mitigated by the co-linearity between age and comorbidities. The inclusion of CCI is imperative so as to better prognosticate burn outcome and help guide expectations and resource utilization, particularly in the younger burn cohort. Copyright © 2016 Elsevier Ltd and ISBI. All rights reserved.
The Measured Effect Magnitude of Co-Morbidities on Burn injury Mortality
Knowlin, Laquanda; Stanford, Lindsay; Moore, Danier; Cairns, Bruce; Charles, Anthony
2016-01-01
Introduction The ability to better prognosticate burn injury outcome is challenging and historically, most center use the Baux or revised Baux score to help prognosticate burn outcome, however, the weighted contribution of comorbidity on burn mortality has traditionally not been accounted for nor adequately studied. We therefore sought to determine the effect of comorbidities, using the Charlson comorbidity index (CCI) on burn mortality. Methods The purpose of this study was to determine the effect of comorbidities on burn injury mortality as determined by the LA50 (lethal TBSA burn at which 50% of the cohort will succumb from the burn injury) in a retrospective analysis of patients admitted to a regional burn center from 2002–2012. Independent variables analyzed included basic demographics, burn mechanism, presence of inhalation injury, TBSA (total body surface area), length of hospital stay, and pre-existing comorbidities. Bivariate analysis was performed and logistic regression modeling using significant variables was utilized to estimate odds of death. Results 7640 patients were included in this study. Overall survival rate was 96%. 40% of our burn cohort had at least one comorbidity. There was a linear increase in the likelihood of death with an increase in CCI. The logistic regression model for mortality outcomes identified four statistically significant variables: age, TBSA, inhalational injury and the presence of comorbidities (OR = 1.59 for each 1 point increase in CCI; 95% CI 1.44–1.77). The unadjusted LA50 was 53% for the entire cohort. Partial adjustment multivariate regression controlling for burn mechanism and inhalation injury only, produced a slight reduction in LA50 for the 0–18 and 19–64 age categories to 76% and 48%, respectively, but a significant decrease occurred in the ≥ 65 years age group with a reduced LA50 to 20% (p<0.001). After full adjustment for all significant covariates, including comorbidities, the independent magnitude of effect of comorbidities on the LA50 was evident in the <65 cohort. The full adjustment showed a LA50 decreased by 15 and 5%, respectively in the 0–18 and >18–65 age groups respectively (p<0.001), however, in the >65 years age cohort there was no change in the LA50. Conclusion Preexisting comorbidities have a significant effect on burn injury mortality in all age groups, particularly the younger burn population. The measured effect of comorbidities in the >65yr age cohort was mitigated by the co-linearity between age and comorbidities. The inclusion of CCI is imperative so as to better prognosticate burn outcome and help guide expectations and resource utilization, particularly in the younger burn cohort.. PMID:27593340
Predictors of scoring at least 600 on COMLEX-USA Level 1: successful preparation strategies.
Vora, Aditya; Maltezos, Nathan; Alfonzo, Lauren; Hernandez, Nilda; Calix, Erica; Fernandez, M Isabel
2013-02-01
Comprehensive Osteopathic Medical Licensing Examination-USA (COMLEX-USA) Level 1 scores are an important criterion used by residency directors to make residency placement decisions. To explore the association between scoring at least 600 on COMLEX-USA Level 1 and grade point average (GPA), scores on the Medical College Admission Test (MCAT), and different test preparation strategies. Third-year osteopathic medical students at Nova Southeastern University were invited to complete a self-administered survey regarding their COMLEX-USA preparation strategies and to provide consent for the researchers to access their preclinical GPA and their MCAT and COMLEX-USA scores. Descriptive analyses were conducted to understand examination preparation procedures and resources used, and bivariate analyses were conducted to identify the statisically significant predictors of scoring 600 or higher. Two separate logistic regressions were also run. The first included all of the statisically significant factors that emerged from the bivariate analyses, and the second examined which candidate predictors remained statistically significant once the effects of GPA and MCAT scores were removed. One hundred twenty-two students completed the survey, and 113 (93%) provided informed consent to access their preclinical GPA and their MCAT and COMLEX-USA scores. In the first regression, scoring 600 or higher was associated with a higher GPA (P<.02), a higher MCAT score (P<.05), earlier preparation initiation (P<.05), and not ranking the Comprehensive Osteopathic Medical Self-Assessment Examination (COMSAE) as the most helpful practice examination (P<.04). In the second regression, scoring 600 or higher was associated with earlier initiation of examination preparation (P<.01) and not ranking COMBANK (question bank for COMLEX-USA) as the most helpful question bank (P<.03). Among the different examination preparation methods, the specific resources ranked as most helpful were First Aid for the USMLE (United States Medical Licensing Examination) (review book), the COMSAE (practice examination); COMBANK (question bank); and Kaplan USMLE (lecture videos). Preclinical GPA and MCAT scores continue to be important predictors of scoring at least 600 on COMLEX-USA Level 1. However, the findings underscore the importance of maintaining a high GPA during the first 2 years of medical school and initiating COMLEX-USA preparation early.
Using the Ridge Regression Procedures to Estimate the Multiple Linear Regression Coefficients
NASA Astrophysics Data System (ADS)
Gorgees, HazimMansoor; Mahdi, FatimahAssim
2018-05-01
This article concerns with comparing the performance of different types of ordinary ridge regression estimators that have been already proposed to estimate the regression parameters when the near exact linear relationships among the explanatory variables is presented. For this situations we employ the data obtained from tagi gas filling company during the period (2008-2010). The main result we reached is that the method based on the condition number performs better than other methods since it has smaller mean square error (MSE) than the other stated methods.
Weichenthal, Scott; Ryswyk, Keith Van; Goldstein, Alon; Bagg, Scott; Shekkarizfard, Maryam; Hatzopoulou, Marianne
2016-04-01
Existing evidence suggests that ambient ultrafine particles (UFPs) (<0.1µm) may contribute to acute cardiorespiratory morbidity. However, few studies have examined the long-term health effects of these pollutants owing in part to a need for exposure surfaces that can be applied in large population-based studies. To address this need, we developed a land use regression model for UFPs in Montreal, Canada using mobile monitoring data collected from 414 road segments during the summer and winter months between 2011 and 2012. Two different approaches were examined for model development including standard multivariable linear regression and a machine learning approach (kernel-based regularized least squares (KRLS)) that learns the functional form of covariate impacts on ambient UFP concentrations from the data. The final models included parameters for population density, ambient temperature and wind speed, land use parameters (park space and open space), length of local roads and rail, and estimated annual average NOx emissions from traffic. The final multivariable linear regression model explained 62% of the spatial variation in ambient UFP concentrations whereas the KRLS model explained 79% of the variance. The KRLS model performed slightly better than the linear regression model when evaluated using an external dataset (R(2)=0.58 vs. 0.55) or a cross-validation procedure (R(2)=0.67 vs. 0.60). In general, our findings suggest that the KRLS approach may offer modest improvements in predictive performance compared to standard multivariable linear regression models used to estimate spatial variations in ambient UFPs. However, differences in predictive performance were not statistically significant when evaluated using the cross-validation procedure. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.
Mohammad, Khandoker Akib; Fatima-Tuz-Zahura, Most; Bari, Wasimul
2017-01-28
The cause-specific under-five mortality of Bangladesh has been studied by fitting cumulative incidence function (CIF) based Fine and Gray competing risk regression model (1999). For the purpose of analysis, Bangladesh Demographic and Health Survey (BDHS), 2011 data set was used. Three types of mode of mortality for the under-five children are considered. These are disease, non-disease and other causes. Product-Limit survival probabilities for the under-five child mortality with log-rank test were used to select a set of covariates for the regression model. The covariates found to have significant association in bivariate analysis were only considered in the regression analysis. Potential determinants of under-five child mortality due to disease is size of child at birth, while gender of child, NGO (non-government organization) membership of mother, mother's education level, and size of child at birth are due to non-disease and age of mother at birth, NGO membership of mother, and mother's education level are for the mortality due to other causes. Female participation in the education programs needs to be increased because of the improvement of child health and government should arrange family and social awareness programs as well as health related programs for women so that they are aware of their child health.
Maletz, Reinhard; Ottl, Peter; Warkentin, Mareike
2018-01-01
Objective Over time dental composites age due to mechanical impacts such as chewing and chemical impacts such as saliva enzymes and food ingredients. For this research, the focus was placed on chemical degradation. The objective of this study was to simulate hydrolysis by using different food simulating liquids and to assess their impact on the mechanical parameter Vickers microhardness (MHV) and the physicochemical parameter contact angle (CA). Methods Specimen of three composites (d = 6 mm, h = 2 mm; n = 435) classified with respect to their filler content (wt%), namely low-filled, medium-filled and highly-filled, were stored for 0, 14, 30, 90 and 180 days in artificial saliva (pH 7), citric acid (pH 3; pH 5), lactic acid (pH 3; pH 5) and ethanol (40%vol; 60%vol) and assessed regarding to MHV and CA. Statistics: Kruskal-Wallis test, stepwise linear regression, bivariate Spearman Rank Correlation (p < 0.05). Results While stored in artificial saliva, acid and ethanol the CA decreased especially for the low- and medium-filled composites. It was shown that rising the filler content caused less surface changes in the CA. Storage in ethanol led to a significant decrease of MHV of all composites. Regression analysis showed that the effect of in vitro aging on MHV was mainly influenced by the composite material and therefore by filler content (R2 = 0.67; p < 0.05). In contrast, the CA is more influenced by incubation time and filler content (R2 = 0.2; p < 0.05) leading to a higher risk of plaque accumulation over time. Significance: In vitro aging showed significant changes on the mechanical and physicochemical properties of dental composites which may shorten their long-term functionality. In conclusion, it can be stated, that the type of composite material, especially rising filler content seems to improve the materials’ resistance against the processes of chemical degradation. PMID:29630621
Zeigler, Cecilia C; Wondimu, Biniyam; Marcus, Claude; Modéer, Thomas
2015-03-24
Obesity, a well-known risk factor for developing cardiovascular disease (CVD), is associated with chronic periodontitis in adults. This cross-sectional pilot study on obese adolescents was designed to investigate whether periodontal disease in terms of pathological periodontal pockets is associated with raised blood pressure and other risk markers for CVD. The study included 75 obese subjects between 12 to 18 years of age, mean 14.5. Subjects answered a questionnaire regarding health, oral hygiene habits and sociodemographic factors. A clinical examination included Visible Plaque Index (VPI %), Gingival inflammation (BOP %) and the occurrence of pathological pockets exceeding 4 mm (PD ≥ 4 mm). Blood serum were collected and analyzed. The systolic and diastolic blood pressures were registered. Adolescents with pathological periodontal pockets (PD ≥ 4 mm; n = 14) had significantly higher BOP >25% (P = 0.002), higher diastolic blood pressure (P = 0.008), higher levels of Interleukin (IL)-6 (P < 0.001), Leptin (P = 0.018), Macrophage Chemoattractant Protein-1 (MCP-1) (P = 0.049) and thyroid stimulating hormone (TSH) (P = 0.004) in blood serum compared with subjects without pathological periodontal pockets (PD ≥ 4 mm; n = 61). The bivariate linear regression analysis demonstrated that PD ≥ 4 mm (P = 0.008) and systolic blood pressure (P < 0.001) were significantly associated with the dependent variable "diastolic blood pressure". The association between PD ≥ 4 mm and diastolic blood pressure remained significant (P = 0.006) even after adjusting for potential confounders BMI-sds, age, gender, mother's country of birth, BOP >25%, IL-6, IL-8, Leptin, MCP-1, TSH and total cholesterol in the multiple regression analysis. In conclusion, this study indicates an association between pathological periodontal pockets and diastolic blood pressure in obese adolescents. The association was unaffected by other risk markers for cardiovascular events or periodontal disease. The results call for collaboration between pediatric dentists and medical physicians in preventing obesity development and its associated disorders.
Javier, Joyce R; Lahiff, Maureen; Ferrer, Rizaldy R; Huffman, Lynne C
2010-05-01
We compared measures of depressive symptoms and use of counseling in the past year for Filipino versus non-Hispanic white adolescents in California. This cross-sectional study used data from 4421 adolescents who completed the 2003 and 2005 California Health Interview Survey. Bivariate analyses, linear regression, and logistic regression were performed. Compared to non-Hispanic white adolescents, Filipino adolescents had higher mean 8-item version of Center for Epidemiologic Studies Depression Scale scores (5.43 vs 3.94) and were more likely to report a clinically significant level of depressive symptoms (defined as 8-item version of Center for Epidemiologic Studies Depression Scale score > or = 7) (29.0 vs 17.9%). Filipino adolescents are just as likely as their non-Hispanic white counterparts to report low use of counseling in the past year (17.6 vs 28.4%). Multivariate analyses indicate that depressive symptoms were positively associated with Filipino ethnicity, female gender, living in a single parent household, lower parental education, and poverty. The effect that ethnicity had on use of counseling in the past year varied by gender, income level, and parental education level. Filipino male adolescents with family incomes > or = 300% federal poverty level and parents with more than a college degree were significantly less likely than their non-Hispanic white counterparts to report use of counseling in the past year (odds ratio, 0.01; confidence interval, 0.0004-0.44). Filipino female adolescents with family incomes <300% federal poverty level and parental education less than a college degree were significantly more likely to report use of counseling than their non-Hispanic white counterparts (odds ratio, 3.99; confidence interval, 1.00-15.89). Further studies and interventions are needed to effectively screen for and treat depression among Filipino adolescents.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Holliday, Emma B.; Jagsi, Reshma; Thomas, Charles R.
Purpose: To analyze survey information regarding mentorship practices and cross-correlate the results with objective metrics of academic productivity among academic radiation oncologists at US Accreditation Council for Graduate Medical Education (ACGME)-accredited residency training programs. Methods and Materials: An institutional review board-approved survey for the Radiation Oncology Academic Development and Mentorship Assessment Project (ROADMAP) was sent to 1031 radiation oncologists employed at an ACGME-accredited residency training program and administered using an international secure web application designed exclusively to support data capture for research studies. Data collected included demographics, presence of mentorship, and the nature of specific mentoring activities. Productivity metrics, includingmore » number of publications, number of citations, h-index, and date of first publication, were collected for each survey respondent from a commercially available online database, and m-index was calculated. Results: A total of 158 academic radiation oncologists completed the survey, 96 of whom reported having an academic/scientific mentor. Faculty with a mentor had higher numbers of publications, citations, and h- and m-indices. Differences in gender and race/ethnicity were not associated with significant differences in mentorship rates, but those with a mentor were more likely to have a PhD degree and were more likely to have more time protected for research. Bivariate fit regression modeling showed a positive correlation between a mentor's h-index and their mentee's h-index (R{sup 2} = 0.16; P<.001). Linear regression also showed significant correlates of higher h-index, in addition to having a mentor (P=.001), included a longer career duration (P<.001) and fewer patients in treatment (P=.02). Conclusions: Mentorship is widely believed to be important to career development and academic productivity. These results emphasize the importance of identifying and striving to overcome potential barriers to effective mentorship.« less
Gloede, T D; Ernstmann, N; Baumann, W; Groß, S E; Ansmann, L; Nitzsche, A; Neumann, M; Wirtz, M; Schmitz, S; Schulz-Nieswandt, F; Pfaff, H
2015-11-01
While a lot is known about potential and actual turnover of non-medical hospital staff, only few data exist for the outpatient setting. In addition, little is known about actual instruments which leaders can use to influence staff turnover in physician practices. In the literature, the social capital of an organisation, which means the amount of trust, common values and reciprocal behaviour in the organisation, has been discussed as a possible field of action. In the present study, staff turnover as perceived by outpatient haematologists and oncologists is presented and analysed as to whether social capital is associated with that staff turnover. In conclusion, measures to increase the social capital of a practice are presented. The present study is based on data gathered in a questionnaire-based survey with members of the Professional Organisation of -Office-Based Haematologists and Oncologists (N=551). The social capital of the practice was captured from the haematologists and oncologists using an existing and validated scale. To analyse the impact of the practice's social capital on staff turnover, as perceived by the physicians, bivariate correlations and linear regression analyses were calculated. In total, 152 haematologists and oncologists participated in the study which represents a response rate of 28%. In the regression analyses, social capital appears as a significant and strong predictor of staff turnover (beta=-0.34; p<0.001). Building social capital within the practice may be an important contribution to reducing staff turnover although the underlying study design does not allow for drawing causal conclusions regarding this relationship. To create social capital in their practice, outpatient physicians may apply measures that facilitate social interaction among staff, foster trust and facilitate cooperation. Such measures may already be applied when hiring and training new staff, but also continuously when leading employees and when organising work tasks, e.g., by establishing regular team meetings. © Georg Thieme Verlag KG Stuttgart · New York.
Javier, Joyce R.; Lahiff, Maureen; Ferrer, Rizaldy R.; Huffman, Lynne C.
2014-01-01
Objective We compared measures of depressive symptoms and use of counseling in the past year for Filipino versus non-Hispanic white adolescents in California. Methods This cross-sectional study used data from 4421 adolescents who completed the 2003 and 2005 California Health Interview Survey. Bivariate analyses, linear regression, and logistic regression were performed. Results Compared to non-Hispanic white adolescents, Filipino adolescents had higher mean 8-item version of Center for Epidemiologic Studies Depression Scale scores (5.43 vs 3.94) and were more likely to report a clinically significant level of depressive symptoms (defined as 8-item version of Center for Epidemiologic Studies Depression Scale score >7) (29.0 vs 17.9%). Filipino adolescents are just as likely as their non-Hispanic white counterparts to report low use of counseling in the past year (17.6 vs 28.4%). Multivariate analyses indicate that depressive symptoms were positively associated with Filipino ethnicity, female gender, living in a single parent household, lower parental education, and poverty. The effect that ethnicity had on use of counseling in the past year varied by gender, income level, and parental education level. Filipino male adolescents with family incomes >300% federal poverty level and parents with more than a college degree were significantly less likely than their non-Hispanic white counterparts to report use of counseling in the past year (odds ratio, 0.01; confidence interval, 0.0004 – 0.44). Filipino female adolescents with family incomes <300% federal poverty level and parental education less than a college degree were significantly more likely to report use of counseling than their non-Hispanic white counterparts (odds ratio, 3.99; confidence interval, 1.00 –15.89). Conclusion Further studies and interventions are needed to effectively screen for and treat depression among Filipino adolescents. PMID:20431400
Valdés-Stauber, Juan; Lemaczyk, Rafael; Kilian, Reinhold
2018-06-01
ABSTRACTObjective:Our aim was to identify possible patterns of change or durability in sources of meaning for family caregivers of terminally ill patients after the onset of support at home by an outreach palliative nursing team during a three-month survey period. The Sources of Meaning and Meaning in Life Questionnaire (SoMe) was administered to 100 caregivers of terminally ill patients at four measurement timepoints: immediately before the onset of the palliative care (t0), and at 1 week, 1 month, and 3 months after t0. Time-dependent changes were assessed for the completed subsample (n = 24) by means of bivariate linear as well as quadratic regression models. Multivariate regressions with dimensions of meaning in life as dependent variables were performed for the whole sample by means of random-effects models: dependent variables changed over time (four timepoints), whereas regressors remained constant. No significant differences were found for psychosocial and clinical variables or for sources of meaning between the uncompleted and completed subsamples. Growth curve analyses revealed no statistically significant but tendentiously parabolic changes for any dimensions or for single sources of meaning. In multivariate models, a negative association was found between patient age, psychological burden of family caregivers, and changes in total SoMe score, as well as for the superordinate dimensions. According to our hypothesis, sources of meaning and meaning in life seem to remain robust in relatives caring for terminally ill family members during the three-month survey period. A parabolic development pattern of single sources of meaning indicates an adjustment process. An important limitation of our study is the small number of participants compared with larger multivariate models because of high dropout rates, primarily due to the death of three-quarters of the participants during the survey period.
Job satisfaction and retention of health-care providers in Afghanistan and Malawi.
Fogarty, Linda; Kim, Young Mi; Juon, Hee-Soon; Tappis, Hannah; Noh, Jin Won; Zainullah, Partamin; Rozario, Aleisha
2014-02-17
This study describes job satisfaction and intention to stay on the job among primary health-care providers in countries with distinctly different human resources crises, Afghanistan and Malawi. Using a cross-sectional design, we enrolled 87 health-care providers in 32 primary health-care facilities in Afghanistan and 360 providers in 10 regional hospitals in Malawi. The study questionnaire was used to assess job satisfaction, intention to stay on the job and five features of the workplace environment: resources, performance recognition, financial compensation, training opportunities and safety. Descriptive analyses, exploratory factor analyses for scale development, bivariate correlation analyses and bivariate and multiple linear regression analyses were conducted. The multivariate model for Afghanistan, with demographic, background and work environment variables, explained 23.9% of variance in job satisfaction (F(9,73) = 5.08; P < 0.01). However, none of the work environment variables were significantly related to job satisfaction. The multivariate model for intention to stay for Afghanistan explained 23.6% of variance (F(8,74) = 4.10; P < 0.01). Those with high scores for recognition were more likely to have higher intention to stay (β = 0.328, P < 0.05). However, being paid an appropriate salary was negatively related to intent to stay (β = -0.326, P < 0.01). For Malawi, the overall model explained only 9.8% of variance in job satisfaction (F(8,332) = 4.19; P < 0.01) and 9.1% of variance in intention to stay (F(10,330) = 3.57; P < 0.01). The construction of concepts of health-care worker satisfaction and intention to stay on the job are highly dependent on the local context. Although health-care workers in both Afghanistan and Malawi reported satisfaction with their jobs, the predictors of satisfaction, and the extent to which those predictors explained variations in job satisfaction and intention to stay on the job, differed substantially. These findings demonstrate the need for more detailed comparative human resources for health-care research, particularly regarding the relative importance of different determinants of job satisfaction and intention to stay in different contexts and the effectiveness of interventions designed to improve health-care worker performance and retention.
Job satisfaction and retention of health-care providers in Afghanistan and Malawi
2014-01-01
Background This study describes job satisfaction and intention to stay on the job among primary health-care providers in countries with distinctly different human resources crises, Afghanistan and Malawi. Methods Using a cross-sectional design, we enrolled 87 health-care providers in 32 primary health-care facilities in Afghanistan and 360 providers in 10 regional hospitals in Malawi. The study questionnaire was used to assess job satisfaction, intention to stay on the job and five features of the workplace environment: resources, performance recognition, financial compensation, training opportunities and safety. Descriptive analyses, exploratory factor analyses for scale development, bivariate correlation analyses and bivariate and multiple linear regression analyses were conducted. Results The multivariate model for Afghanistan, with demographic, background and work environment variables, explained 23.9% of variance in job satisfaction (F(9,73) = 5.08; P < 0.01). However, none of the work environment variables were significantly related to job satisfaction. The multivariate model for intention to stay for Afghanistan explained 23.6% of variance (F(8,74) = 4.10; P < 0.01). Those with high scores for recognition were more likely to have higher intention to stay (β = 0.328, P < 0.05). However, being paid an appropriate salary was negatively related to intent to stay (β = -0.326, P < 0.01). For Malawi, the overall model explained only 9.8% of variance in job satisfaction (F(8,332) = 4.19; P < 0.01) and 9.1% of variance in intention to stay (F(10,330) = 3.57; P < 0.01). Conclusions The construction of concepts of health-care worker satisfaction and intention to stay on the job are highly dependent on the local context. Although health-care workers in both Afghanistan and Malawi reported satisfaction with their jobs, the predictors of satisfaction, and the extent to which those predictors explained variations in job satisfaction and intention to stay on the job, differed substantially. These findings demonstrate the need for more detailed comparative human resources for health-care research, particularly regarding the relative importance of different determinants of job satisfaction and intention to stay in different contexts and the effectiveness of interventions designed to improve health-care worker performance and retention. PMID:24533615
Alzheimer's Disease Detection by Pseudo Zernike Moment and Linear Regression Classification.
Wang, Shui-Hua; Du, Sidan; Zhang, Yin; Phillips, Preetha; Wu, Le-Nan; Chen, Xian-Qing; Zhang, Yu-Dong
2017-01-01
This study presents an improved method based on "Gorji et al. Neuroscience. 2015" by introducing a relatively new classifier-linear regression classification. Our method selects one axial slice from 3D brain image, and employed pseudo Zernike moment with maximum order of 15 to extract 256 features from each image. Finally, linear regression classification was harnessed as the classifier. The proposed approach obtains an accuracy of 97.51%, a sensitivity of 96.71%, and a specificity of 97.73%. Our method performs better than Gorji's approach and five other state-of-the-art approaches. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
We compared the use of ternary and bivariate diagrams to distinguish the effects of atmospheric precipitation, rock weathering, and evaporation on inland surface and subsurface water chemistry. The three processes could not be statistically differentiated using bivariate models e...
An Examination of New Paradigms for Spline Approximations.
Witzgall, Christoph; Gilsinn, David E; McClain, Marjorie A
2006-01-01
Lavery splines are examined in the univariate and bivariate cases. In both instances relaxation based algorithms for approximate calculation of Lavery splines are proposed. Following previous work Gilsinn, et al. [7] addressing the bivariate case, a rotationally invariant functional is assumed. The version of bivariate splines proposed in this paper also aims at irregularly spaced data and uses Hseih-Clough-Tocher elements based on the triangulated irregular network (TIN) concept. In this paper, the univariate case, however, is investigated in greater detail so as to further the understanding of the bivariate case.
Costing Hospital Surgery Services: The Method Matters
Mercier, Gregoire; Naro, Gerald
2014-01-01
Background Accurate hospital costs are required for policy-makers, hospital managers and clinicians to improve efficiency and transparency. However, different methods are used to allocate direct costs, and their agreement is poorly understood. The aim of this study was to assess the agreement between bottom-up and top-down unit costs of a large sample of surgical operations in a French tertiary centre. Methods Two thousand one hundred and thirty consecutive procedures performed between January and October 2010 were analysed. Top-down costs were based on pre-determined weights, while bottom-up costs were calculated through an activity-based costing (ABC) model. The agreement was assessed using correlation coefficients and the Bland and Altman method. Variables associated with the difference between methods were identified with bivariate and multivariate linear regressions. Results The correlation coefficient amounted to 0.73 (95%CI: 0.72; 0.76). The overall agreement between methods was poor. In a multivariate analysis, the cost difference was independently associated with age (Beta = −2.4; p = 0.02), ASA score (Beta = 76.3; p<0.001), RCI (Beta = 5.5; p<0.001), staffing level (Beta = 437.0; p<0.001) and intervention duration (Beta = −10.5; p<0.001). Conclusions The ability of the current method to provide relevant information to managers, clinicians and payers is questionable. As in other European countries, a shift towards time-driven activity-based costing should be advocated. PMID:24817167
Al-Abdely, Hail M; Khidir Mohammed, Yassir; Rosenthal, Victor D; Orellano, Pablo W; ALazhary, Mohamed; Kaid, Eman; Al-Attas, Anan; Hawsawi, Ghadeer; Kelany, Ashraf; Hussein, Bedoor; Esam, Bayan; Altowerqi, Rami; Alkamaly, Modhi A; Tawfic, Nader A; Cruzpero, Elinita; Al Rashidi, Raya M; Thomas, Reny; Molano, Apsia M; Al Enazy, Hessa A; Al Adwani, Fatima M; Casuyon Pahilanga, Arlu M; Alatawi, Sharifa; Nakhla, Raslan; Al Adwani, Fatma M; Gasmin Aromin, Rosita; Balon Ubalde, Evangelina; Hanafy Diab, Hanan; Kader, Nahla A; Hassan Assiry, Ibtesam Y; Sawan, Fahad A; Ammari, Hassan E; Mashiakhy, Alhasan M; Santiago, Elaine B; Chua, Christian M S; Dalis, Imee M; Arishi, Haider M; Lozada, Ruthelma; Al-Zaydani Asiri, Ibrahim A M; Ahmed, Hala; Jarie, Al; Al-Qathani, Ali S M; Al-Alkami, Halima Y; AlDalaton, Mervat; Alih, Siti J B; Alaliany, Mohammed J; Helali, Najla J; Sindayen, Grace; Malificio, Annalyn A; Al Dossari, Haya B; Algethami, Abdulmajid G; Mohamed, Dia; Yanne, Leigh; Tan, Avigail; Babu, Sheema; Abduljabbar, Shatha M; Rushdi, Hala; Fernandez, Janice; Hussain, Waleed M; Rajavel, Renuga D; Bukhari, Syed Z; Turkistani, Abdullah A; Mushtaq, Jeyashri J; Albeladi, Eida; Aboushoushah, Sally; Qushmaq, Nahed; Shyrine, Leide; Philipose, Jomol; Raees, Mohamed; AbdulKhalik, Nawal S; Madco, Marjory; Abdulghany, Mohd; Manao, Athena; Acostan, Catherine; Safwat, Rania; Halwani, Muhammad; Abdul Aal, Nahla A H; Thomas, Anumol; Abdulatif, Shaymaa M; Ariola, Nelia C; Mutwalli, Aisha H; Ariola, Nelia; Bohlega, Eatedal; Simon, Saly; Damlig, Estelita; Elsherbini, Sherin G; Krishne, Ilama T; Abraham, Sheela; Ali Karrar, Mohammed A; Gosn, Nisreen A; Al Hindi, Abdulaziz A; Jaha, Rasha N; AlQahtani, Saeda M; Abdul Aziz, Ali O; Demaisip, Nadia L; Laungayan Cortez, Elizabeth; Cabato, Analen F; Gonzales Celiz, Jerlie M; Al Raey, Mohammed A; Al Darani, Saeed A; Aziz, Misbah R; Manea, Batool A; Samy, Eslam; Briones, Solita; Krishnan, Radhika; Raees, Saman S M; Tabassum, Kehkashan; Ghalilah, Khalid M; Alradady, Mohamed; Al Qatri, Abdulrahim; Chaouali, Mafaten; Elsisi, Magdy; Aldossary, Hajer A; Al-Suliman, Shehab; Al Talib, Amina A; Albaghly, Nadira; Haqlre Mia, Mohammad E; Al-Gethamy, Manal M; Alamri, Dhafer M; Al-Saadi, Adnan S; Ayugat, Evelyn P; Al Hazazi, Nawaf A; Al Hussain, Modi I; Caminade, Yvonne; Santos, Ann J; Abdulwahab, Mohamed H; Al-Garni, Bushra T A
2018-06-23
To analyze the impact of the International Nosocomial Infection Control Consortium (INICC) Multidimensional Approach (IMA) and use of INICC Surveillance Online System (ISOS) on ventilator-associated pneumonia (VAP) rates in Saudi Arabia from September 2013 to February 2017. A multicenter, prospective, before-after surveillance study on 14,961 patients in 37 intensive care units (ICUs) of 22 hospitals. During baseline, we performed outcome surveillance of VAP applying the definitions of the CDC/NHSN. During intervention, we implemented the IMA and the ISOS, which included: (1) a bundle of infection prevention practice interventions, (2) education, (3) outcome surveillance, (4) process surveillance, (5) feedback on VAP rates and consequences and (6) performance feedback of process surveillance. Bivariate and multivariate regression analyses were performed using generalized linear mixed models to estimate the effect of intervention. The baseline rate of 7.84 VAPs per 1000 mechanical-ventilator (MV)-days-with 20,927 MV-days and 164 VAPs-, was reduced to 4.74 VAPs per 1000 MV-days-with 118,929 MV-days and 771 VAPs-, accounting for a 39% rate reduction (IDR 0.61; 95% CI 0.5-0.7; P 0.001). Implementing the IMA was associated with significant reductions in VAP rates in ICUs of Saudi Arabia. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.
High levels of postmigration HIV acquisition within nine European countries.
Alvarez-Del Arco, Debora; Fakoya, Ibidun; Thomadakis, Christos; Pantazis, Nikos; Touloumi, Giota; Gennotte, Anne-Francoise; Zuure, Freke; Barros, Henrique; Staehelin, Cornelia; Göpel, Siri; Boesecke, Christoph; Prestileo, Tullio; Volny-Anne, Alain; Burns, Fiona; Del Amo, Julia
2017-09-10
We aimed to estimate the proportion of postmigration HIV acquisition among HIV-positive migrants in Europe. To reach HIV-positive migrants, we designed a cross-sectional study performed in HIV clinics. The study was conducted from July 2013 to July 2015 in 57 clinics (nine European countries), targeting individuals over 18 years diagnosed in the preceding 5 years and born abroad. Electronic questionnaires supplemented with clinical data were completed in any of 15 languages. Postmigration HIV acquisition was estimated through Bayesian approaches combining extensive information on migration and patients' characteristics. CD4 cell counts and HIV-RNA trajectories from seroconversion were estimated by bivariate linear mixed models fitted to natural history data. Postmigration acquisition risk factors were investigated with weighted logistic regression. Of 2009 participants, 46% were MSM and a third originated from sub-Saharan Africa and Latin America & Caribbean, respectively. Median time in host countries was 8 years. Postmigration HIV acquisition was 63% (95% confidence interval: 57-67%); 72% among MSM, 58 and 51% in heterosexual men and women, respectively. Postmigration HIV acquisition was 71% for Latin America and Caribbean migrants and 45% for people from sub-Saharan Africa. Factors associated with postmigration HIV acquisition among heterosexual women and MSM were age at migration, length of stay in host country and HIV diagnosis year and among heterosexual men, length of stay in host country and HIV diagnosis year. A substantial proportion of HIV-positive migrants living in Europe acquired HIV postmigration. This has important implications for European public health policies.
Hadden, Kristie B; Puglisi, Lisa; Prince, Latrina; Aminawung, Jenerius A; Shavit, Shira; Pflaum, David; Calderon, Joe; Wang, Emily A; Zaller, Nickolas
2018-06-25
Health literacy is increasingly understood to be a mediator of chronic disease self-management and health care utilization. However, there has been very little research examining health literacy among incarcerated persons. This study aimed to describe the health literacy and relevant patient characteristics in a recently incarcerated primary care patient population in 12 communities in 6 states and Puerto Rico. Baseline data were collected from 751 individuals through the national Transitions Clinic Network (TCN), a model which utilizes a community health worker (CHW) with a previous history of incarceration to engage previously incarcerated people with chronic medical diseases in medical care upon release. Participants in this study completed study measures during or shortly after their first medical visit in the TCN. Data included demographics, health-related survey responses, and a measure of health literacy, The Newest Vital Sign (NVS). Bivariate and linear regression models were fit to explore associations among health literacy and the time from release to first clinic appointment, number of emergency room visits before first clinic appointment and confidence in adhering to medication. Our study found that almost 60% of the sample had inadequate health literacy. Inadequate health literacy was associated with decreased confidence in taking medications following release and an increased likelihood of visiting the emergency department prior to primary care. Early engagement may improve health risks for this population of individuals that is at high risk of death, acute care utilization, and hospitalization following release.