Flexible Link Functions in Nonparametric Binary Regression with Gaussian Process Priors

PubMed Central

Li, Dan; Lin, Lizhen; Dey, Dipak K.

2015-01-01

Summary In many scientific fields, it is a common practice to collect a sequence of 0-1 binary responses from a subject across time, space, or a collection of covariates. Researchers are interested in finding out how the expected binary outcome is related to covariates, and aim at better prediction in the future 0-1 outcomes. Gaussian processes have been widely used to model nonlinear systems; in particular to model the latent structure in a binary regression model allowing nonlinear functional relationship between covariates and the expectation of binary outcomes. A critical issue in modeling binary response data is the appropriate choice of link functions. Commonly adopted link functions such as probit or logit links have fixed skewness and lack the flexibility to allow the data to determine the degree of the skewness. To address this limitation, we propose a flexible binary regression model which combines a generalized extreme value link function with a Gaussian process prior on the latent structure. Bayesian computation is employed in model estimation. Posterior consistency of the resulting posterior distribution is demonstrated. The flexibility and gains of the proposed model are illustrated through detailed simulation studies and two real data examples. Empirical results show that the proposed model outperforms a set of alternative models, which only have either a Gaussian process prior on the latent regression function or a Dirichlet prior on the link function. PMID:26686333

The influence of endometriosis-related symptoms on work life and work ability: a study of Danish endometriosis patients in employment.

PubMed

Hansen, Karina E; Kesmodel, Ulrik S; Baldursson, Einar B; Schultz, Rikke; Forman, Axel

2013-07-01

Little is known about the implications of endometriosis on women's work life. This study aimed at examining the relation between endometriosis-related symptoms and work ability in employed women with endometriosis. In a cohort study, 610 patients with diagnosed endometriosis and 751 reference women completed an electronic survey based on the Endometriosis Health Profile 30-questionnaire and the Work Ability Index (short form). Percentages were reported for all data. Binary and multivariate logistic regression analyses were used to assess risk factors for low work ability. The level of statistical significance was set at p<0.025 in all analyses. In binary analyses a diagnosis of endometriosis was associated with more sick days, work disturbances due to symptoms, lower work ability and a wide number of other implications on work life in employed women. Moreover, a higher pain level and degree of symptoms were associated with low work ability. Full regression analysis indicated that tiredness, frequent pain, a higher daily pain level, a higher number of sick days and feeling depressed at work were associated with low work ability. A long delay from symptom onset to diagnosis was associated with low work ability. These data indicate a severe impact of endometriosis on the work ability of employed women with endometriosis and add to the evidence that this disease represents a significant socio-economic burden. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Logic regression and its extensions.

PubMed

Schwender, Holger; Ruczinski, Ingo

2010-01-01

Logic regression is an adaptive classification and regression procedure, initially developed to reveal interacting single nucleotide polymorphisms (SNPs) in genetic association studies. In general, this approach can be used in any setting with binary predictors, when the interaction of these covariates is of primary interest. Logic regression searches for Boolean (logic) combinations of binary variables that best explain the variability in the outcome variable, and thus, reveals variables and interactions that are associated with the response and/or have predictive capabilities. The logic expressions are embedded in a generalized linear regression framework, and thus, logic regression can handle a variety of outcome types, such as binary responses in case-control studies, numeric responses, and time-to-event data. In this chapter, we provide an introduction to the logic regression methodology, list some applications in public health and medicine, and summarize some of the direct extensions and modifications of logic regression that have been proposed in the literature. Copyright © 2010 Elsevier Inc. All rights reserved.

Performance and separation occurrence of binary probit regression estimator using maximum likelihood method and Firths approach under different sample size

NASA Astrophysics Data System (ADS)

Lusiana, Evellin Dewi

2017-12-01

The parameters of binary probit regression model are commonly estimated by using Maximum Likelihood Estimation (MLE) method. However, MLE method has limitation if the binary data contains separation. Separation is the condition where there are one or several independent variables that exactly grouped the categories in binary response. It will result the estimators of MLE method become non-convergent, so that they cannot be used in modeling. One of the effort to resolve the separation is using Firths approach instead. This research has two aims. First, to identify the chance of separation occurrence in binary probit regression model between MLE method and Firths approach. Second, to compare the performance of binary probit regression model estimator that obtained by MLE method and Firths approach using RMSE criteria. Those are performed using simulation method and under different sample size. The results showed that the chance of separation occurrence in MLE method for small sample size is higher than Firths approach. On the other hand, for larger sample size, the probability decreased and relatively identic between MLE method and Firths approach. Meanwhile, Firths estimators have smaller RMSE than MLEs especially for smaller sample sizes. But for larger sample sizes, the RMSEs are not much different. It means that Firths estimators outperformed MLE estimator.

High statistical heterogeneity is more frequent in meta-analysis of continuous than binary outcomes.

PubMed

Alba, Ana C; Alexander, Paul E; Chang, Joanne; MacIsaac, John; DeFry, Samantha; Guyatt, Gordon H

2016-02-01

We compared the distribution of heterogeneity in meta-analyses of binary and continuous outcomes. We searched citations in MEDLINE and Cochrane databases for meta-analyses of randomized trials published in 2012 that reported a measure of heterogeneity of either binary or continuous outcomes. Two reviewers independently performed eligibility screening and data abstraction. We evaluated the distribution of I(2) in meta-analyses of binary and continuous outcomes and explored hypotheses explaining the difference in distributions. After full-text screening, we selected 671 meta-analyses evaluating 557 binary and 352 continuous outcomes. Heterogeneity as assessed by I(2) proved higher in continuous than in binary outcomes: the proportion of continuous and binary outcomes reporting an I(2) of 0% was 34% vs. 52%, respectively, and reporting an I(2) of 60-100% was 39% vs. 14%. In continuous but not binary outcomes, I(2) increased with larger number of studies included in a meta-analysis. Increased precision and sample size do not explain the larger I(2) found in meta-analyses of continuous outcomes with a larger number of studies. Meta-analyses evaluating continuous outcomes showed substantially higher I(2) than meta-analyses of binary outcomes. Results suggest differing standards for interpreting I(2) in continuous vs. binary outcomes may be appropriate. Copyright © 2016 Elsevier Inc. All rights reserved.

Sensitivity subgroup analysis based on single-center vs. multi-center trial status when interpreting meta-analyses pooled estimates: the logical way forward.

PubMed

Alexander, Paul E; Bonner, Ashley J; Agarwal, Arnav; Li, Shelly-Anne; Hariharan, Abishek; Izhar, Zain; Bhatnagar, Neera; Alba, Carolina; Akl, Elie A; Fei, Yutong; Guyatt, Gordon H; Beyene, Joseph

2016-06-01

Prior studies regarding whether single-center trial estimates are larger than multi-center are equivocal. We examined the extent to which single-center trials yield systematically larger effects than multi-center trials. We searched the 119 core clinical journals and the Cochrane Database of Systematic Reviews for meta-analyses (MAs) of randomized controlled trials (RCTs) published during 2012. In this meta-epidemiologic study, for binary variables, we computed the pooled ratio of ORs (RORs), and for continuous outcomes mean difference in standardized mean differences (SMDs), we conducted weighted random-effects meta-regression and random-effects MA modeling. Our primary analyses were restricted to MAs that included at least five RCTs and in which at least 25% of the studies used each of single trial center (SC) and more trial center (MC) designs. We identified 81 MAs for the odds ratio (OR) and 43 for the SMD outcome measures. Based on our analytic plan, our primary analysis (core) is based on 25 MAs/241 RCTs (binary outcome) and 18 MAs/173 RCTs (continuous outcome). Based on the core analysis, we found no difference in magnitude of effect between SC and MC for binary outcomes [RORs: 1.02; 95% confidence interval (CI): 0.83, 1.24; I(2) 20.2%]. Effect sizes were systematically larger for SC than MC for the continuous outcome measure (mean difference in SMDs: -0.13; 95% CI: -0.21, -0.05; I(2) 0%). Our results do not support prior findings of larger effects in SC than MC trials addressing binary outcomes but show a very similar small increase in effect in SC than MC trials addressing continuous outcomes. Authors of systematic reviews would be wise to include all trials irrespective of SC vs. MC design and address SC vs. MC status as a possible explanation of heterogeneity (and consider sensitivity analyses). Copyright © 2015 Elsevier Inc. All rights reserved.

Predicting Social Trust with Binary Logistic Regression

ERIC Educational Resources Information Center

Adwere-Boamah, Joseph; Hufstedler, Shirley

2015-01-01

This study used binary logistic regression to predict social trust with five demographic variables from a national sample of adult individuals who participated in The General Social Survey (GSS) in 2012. The five predictor variables were respondents' highest degree earned, race, sex, general happiness and the importance of personally assisting…

Association Between Socio-Demographic Background and Self-Esteem of University Students.

PubMed

Haq, Muhammad Ahsan Ul

2016-12-01

The purpose of this study was to scrutinize self-esteem of university students and explore association of self-esteem with academic achievement, gender and other factors. A sample of 346 students was selected from Punjab University, Lahore Pakistan. Rosenberg self-esteem scale with demographic variables was used for data collection. Besides descriptive statistics, binary logistic regression and t test were used for analysing the data. Significant gender difference was observed, self-esteem was significantly higher in males than females. Logistic regression indicates that age, medium of instruction, family income, student monthly expenditures, GPA and area of residence has direct effect on self-esteem; while number of siblings showed an inverse effect.

glmnetLRC f/k/a lrc package: Logistic Regression Classification

DOE Office of Scientific and Technical Information (OSTI.GOV)

2016-06-09

Methods for fitting and predicting logistic regression classifiers (LRC) with an arbitrary loss function using elastic net or best subsets. This package adds additional model fitting features to the existing glmnet and bestglm R packages. This package was created to perform the analyses described in Amidan BG, Orton DJ, LaMarche BL, et al. 2014. Signatures for Mass Spectrometry Data Quality. Journal of Proteome Research. 13(4), 2215-2222. It makes the model fitting available in the glmnet and bestglm packages more general by identifying optimal model parameters via cross validation with an customizable loss function. It also identifies the optimal threshold formore » binary classification.« less

Assessment of Weighted Quantile Sum Regression for Modeling Chemical Mixtures and Cancer Risk

PubMed Central

Czarnota, Jenna; Gennings, Chris; Wheeler, David C

2015-01-01

In evaluation of cancer risk related to environmental chemical exposures, the effect of many chemicals on disease is ultimately of interest. However, because of potentially strong correlations among chemicals that occur together, traditional regression methods suffer from collinearity effects, including regression coefficient sign reversal and variance inflation. In addition, penalized regression methods designed to remediate collinearity may have limitations in selecting the truly bad actors among many correlated components. The recently proposed method of weighted quantile sum (WQS) regression attempts to overcome these problems by estimating a body burden index, which identifies important chemicals in a mixture of correlated environmental chemicals. Our focus was on assessing through simulation studies the accuracy of WQS regression in detecting subsets of chemicals associated with health outcomes (binary and continuous) in site-specific analyses and in non-site-specific analyses. We also evaluated the performance of the penalized regression methods of lasso, adaptive lasso, and elastic net in correctly classifying chemicals as bad actors or unrelated to the outcome. We based the simulation study on data from the National Cancer Institute Surveillance Epidemiology and End Results Program (NCI-SEER) case–control study of non-Hodgkin lymphoma (NHL) to achieve realistic exposure situations. Our results showed that WQS regression had good sensitivity and specificity across a variety of conditions considered in this study. The shrinkage methods had a tendency to incorrectly identify a large number of components, especially in the case of strong association with the outcome. PMID:26005323

Assessment of weighted quantile sum regression for modeling chemical mixtures and cancer risk.

PubMed

Czarnota, Jenna; Gennings, Chris; Wheeler, David C

2015-01-01

In evaluation of cancer risk related to environmental chemical exposures, the effect of many chemicals on disease is ultimately of interest. However, because of potentially strong correlations among chemicals that occur together, traditional regression methods suffer from collinearity effects, including regression coefficient sign reversal and variance inflation. In addition, penalized regression methods designed to remediate collinearity may have limitations in selecting the truly bad actors among many correlated components. The recently proposed method of weighted quantile sum (WQS) regression attempts to overcome these problems by estimating a body burden index, which identifies important chemicals in a mixture of correlated environmental chemicals. Our focus was on assessing through simulation studies the accuracy of WQS regression in detecting subsets of chemicals associated with health outcomes (binary and continuous) in site-specific analyses and in non-site-specific analyses. We also evaluated the performance of the penalized regression methods of lasso, adaptive lasso, and elastic net in correctly classifying chemicals as bad actors or unrelated to the outcome. We based the simulation study on data from the National Cancer Institute Surveillance Epidemiology and End Results Program (NCI-SEER) case-control study of non-Hodgkin lymphoma (NHL) to achieve realistic exposure situations. Our results showed that WQS regression had good sensitivity and specificity across a variety of conditions considered in this study. The shrinkage methods had a tendency to incorrectly identify a large number of components, especially in the case of strong association with the outcome.

A novel hybrid method of beta-turn identification in protein using binary logistic regression and neural network

PubMed Central

Asghari, Mehdi Poursheikhali; Hayatshahi, Sayyed Hamed Sadat; Abdolmaleki, Parviz

2012-01-01

From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a β-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other β-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying β-turns in proteins. PMID:27418910

A novel hybrid method of beta-turn identification in protein using binary logistic regression and neural network.

PubMed

Asghari, Mehdi Poursheikhali; Hayatshahi, Sayyed Hamed Sadat; Abdolmaleki, Parviz

2012-01-01

From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a β-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other β-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying β-turns in proteins.

Prediction of cold and heat patterns using anthropometric measures based on machine learning.

PubMed

Lee, Bum Ju; Lee, Jae Chul; Nam, Jiho; Kim, Jong Yeol

2018-01-01

To examine the association of body shape with cold and heat patterns, to determine which anthropometric measure is the best indicator for discriminating between the two patterns, and to investigate whether using a combination of measures can improve the predictive power to diagnose these patterns. Based on a total of 4,859 subjects (3,000 women and 1,859 men), statistical analyses using binary logistic regression were performed to assess the significance of the difference and the predictive power of each anthropometric measure, and binary logistic regression and Naive Bayes with the variable selection technique were used to assess the improvement in the predictive power of the patterns using the combined measures. In women, the strongest indicators for determining the cold and heat patterns among anthropometric measures were body mass index (BMI) and rib circumference; in men, the best indicator was BMI. In experiments using a combination of measures, the values of the area under the receiver operating characteristic curve in women were 0.776 by Naive Bayes and 0.772 by logistic regression, and the values in men were 0.788 by Naive Bayes and 0.779 by logistic regression. Individuals with a higher BMI have a tendency toward a heat pattern in both women and men. The use of a combination of anthropometric measures can slightly improve the diagnostic accuracy. Our findings can provide fundamental information for the diagnosis of cold and heat patterns based on body shape for personalized medicine.

Headspace quantification of pure and aqueous solutions of binary mixtures of key volatile organic compounds in Swiss cheeses using selected ion flow tube mass spectrometry.

PubMed

Castada, Hardy Z; Wick, Cheryl; Harper, W James; Barringer, Sheryl

2015-01-15

Twelve volatile organic compounds (VOCs) have recently been identified as key compounds in Swiss cheese with split defects. It is important to know how these VOCs interact in binary mixtures and if their behavior changes with concentration in binary mixtures. Selected ion flow tube mass spectrometry (SIFT-MS) was used for the headspace analysis of VOCs commonly found in Swiss cheeses. Headspace (H/S) sampling and quantification checks using SIFT-MS and further linear regression analyses were carried out on twelve selected aqueous solutions of VOCs. Five binary mixtures of standard solutions of VOCs were also prepared and the H/S profile of each mixture was analyzed. A very good fit of linearity for the twelve VOCs (95% confidence level) confirms direct proportionality between the H/S and the aqueous concentration of the standard solutions. Henry's Law coefficients were calculated with a high degree of confidence. SIFT-MS analysis of five binary mixtures showed that the more polar compounds reduced the H/S concentration of the less polar compounds, while the addition of a less polar compound increased the H/S concentration of the more polar compound. In the binary experiment, it was shown that the behavior of a compound in the headspace can be significantly affected by the presence of another compound. Thus, the matrix effect plays a significant role in the behavior of molecules in a mixed solution. Copyright © 2014 John Wiley & Sons, Ltd.

Face Alignment via Regressing Local Binary Features.

PubMed

Ren, Shaoqing; Cao, Xudong; Wei, Yichen; Sun, Jian

2016-03-01

This paper presents a highly efficient and accurate regression approach for face alignment. Our approach has two novel components: 1) a set of local binary features and 2) a locality principle for learning those features. The locality principle guides us to learn a set of highly discriminative local binary features for each facial landmark independently. The obtained local binary features are used to jointly learn a linear regression for the final output. This approach achieves the state-of-the-art results when tested on the most challenging benchmarks to date. Furthermore, because extracting and regressing local binary features are computationally very cheap, our system is much faster than previous methods. It achieves over 3000 frames per second (FPS) on a desktop or 300 FPS on a mobile phone for locating a few dozens of landmarks. We also study a key issue that is important but has received little attention in the previous research, which is the face detector used to initialize alignment. We investigate several face detectors and perform quantitative evaluation on how they affect alignment accuracy. We find that an alignment friendly detector can further greatly boost the accuracy of our alignment method, reducing the error up to 16% relatively. To facilitate practical usage of face detection/alignment methods, we also propose a convenient metric to measure how good a detector is for alignment initialization.

Multidetector CT features of pulmonary focal ground-glass opacity: differences between benign and malignant

PubMed Central

Fan, L; Liu, S-Y; Li, Q-C; Yu, H; Xiao, X-S

2012-01-01

Objective To evaluate different features between benign and malignant pulmonary focal ground-glass opacity (fGGO) on multidetector CT (MDCT). Methods 82 pathologically or clinically confirmed fGGOs were retrospectively analysed with regard to demographic data, lesion size and location, attenuation value and MDCT features including shape, margin, interface, internal characteristics and adjacent structure. Differences between benign and malignant fGGOs were analysed using a χ2 test, Fisher's exact test or Mann–Whitney U-test. Morphological characteristics were analysed by binary logistic regression analysis to estimate the likelihood of malignancy. Results There were 21 benign and 61 malignant lesions. No statistical differences were found between benign and malignant fGGOs in terms of demographic data, size, location and attenuation value. The frequency of lobulation (p=0.000), spiculation (p=0.008), spine-like process (p=0.004), well-defined but coarse interface (p=0.000), bronchus cut-off (p=0.003), other air-containing space (p=0.000), pleural indentation (p=0.000) and vascular convergence (p=0.006) was significantly higher in malignant fGGOs than that in benign fGGOs. Binary logistic regression analysis showed that lobulation, interface and pleural indentation were important indicators for malignant diagnosis of fGGO, with the corresponding odds ratios of 8.122, 3.139 and 9.076, respectively. In addition, a well-defined but coarse interface was the most important indicator of malignancy among all interface types. With all three important indicators considered, the diagnostic sensitivity, specificity and accuracy were 93.4%, 66.7% and 86.6%, respectively. Conclusion An fGGO with lobulation, a well-defined but coarse interface and pleural indentation gives a greater than average likelihood of being malignant. PMID:22128130

No compelling positive association between ovarian hormones and wearing red clothing when using multinomial analyses.

PubMed

Blake, Khandis R; Dixson, Barnaby J W; O'Dean, Siobhan M; Denson, Thomas F

2017-04-01

Several studies report that wearing red clothing enhances women's attractiveness and signals sexual proceptivity to men. The associated hypothesis that women will choose to wear red clothing when fertility is highest, however, has received mixed support from empirical studies. One possible cause of these mixed findings may be methodological. The current study aimed to replicate recent findings suggesting a positive association between hormonal profiles associated with high fertility (high estradiol to progesterone ratios) and the likelihood of wearing red. We compared the effect of the estradiol to progesterone ratio on the probability of wearing: red versus non-red (binary logistic regression); red versus neutral, black, blue, green, orange, multi-color, and gray (multinomial logistic regression); and each of these same colors in separate binary models (e.g., green versus non-green). Red versus non-red analyses showed a positive trend between a high estradiol to progesterone ratio and wearing red, but the effect only arose for younger women and was not robust across samples. We found no compelling evidence for ovarian hormones increasing the probability of wearing red in the other analyses. However, we did find that the probability of wearing neutral was positively associated with the estradiol to progesterone ratio, though the effect did not reach conventional levels of statistical significance. Findings suggest that although ovarian hormones may affect younger women's preference for red clothing under some conditions, the effect is not robust when differentiating amongst other colors of clothing. In addition, the effect of ovarian hormones on clothing color preference may not be specific to the color red. Copyright © 2017 Elsevier Inc. All rights reserved.

Odds Ratio, Delta, ETS Classification, and Standardization Measures of DIF Magnitude for Binary Logistic Regression

ERIC Educational Resources Information Center

Monahan, Patrick O.; McHorney, Colleen A.; Stump, Timothy E.; Perkins, Anthony J.

2007-01-01

Previous methodological and applied studies that used binary logistic regression (LR) for detection of differential item functioning (DIF) in dichotomously scored items either did not report an effect size or did not employ several useful measures of DIF magnitude derived from the LR model. Equations are provided for these effect size indices.…

Measures of clustering and heterogeneity in multilevel Poisson regression analyses of rates/count data

PubMed Central

Austin, Peter C.; Stryhn, Henrik; Leckie, George; Merlo, Juan

2017-01-01

Multilevel data occur frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models. These models incorporate cluster‐specific random effects that allow one to partition the total variation in the outcome into between‐cluster variation and between‐individual variation. The magnitude of the effect of clustering provides a measure of the general contextual effect. When outcomes are binary or time‐to‐event in nature, the general contextual effect can be quantified by measures of heterogeneity like the median odds ratio or the median hazard ratio, respectively, which can be calculated from a multilevel regression model. Outcomes that are integer counts denoting the number of times that an event occurred are common in epidemiological and medical research. The median (incidence) rate ratio in multilevel Poisson regression for counts that corresponds to the median odds ratio or median hazard ratio for binary or time‐to‐event outcomes respectively is relatively unknown and is rarely used. The median rate ratio is the median relative change in the rate of the occurrence of the event when comparing identical subjects from 2 randomly selected different clusters that are ordered by rate. We also describe how the variance partition coefficient, which denotes the proportion of the variation in the outcome that is attributable to between‐cluster differences, can be computed with count outcomes. We illustrate the application and interpretation of these measures in a case study analyzing the rate of hospital readmission in patients discharged from hospital with a diagnosis of heart failure. PMID:29114926

Association of funding and conclusions in randomized drug trials: a reflection of treatment effect or adverse events?

PubMed

Als-Nielsen, Bodil; Chen, Wendong; Gluud, Christian; Kjaergard, Lise L

2003-08-20

Previous studies indicate that industry-sponsored trials tend to draw proindustry conclusions. To explore whether the association between funding and conclusions in randomized drug trials reflects treatment effects or adverse events. Observational study of 370 randomized drug trials included in meta-analyses from Cochrane reviews selected from the Cochrane Library, May 2001. From a random sample of 167 Cochrane reviews, 25 contained eligible meta-analyses (assessed a binary outcome; pooled at least 5 full-paper trials of which at least 1 reported adequate and 1 reported inadequate allocation concealment). The primary binary outcome from each meta-analysis was considered the primary outcome for all trials included in each meta-analysis. The association between funding and conclusions was analyzed by logistic regression with adjustment for treatment effect, adverse events, and additional confounding factors (methodological quality, control intervention, sample size, publication year, and place of publication). Conclusions in trials, classified into whether the experimental drug was recommended as the treatment of choice or not. The experimental drug was recommended as treatment of choice in 16% of trials funded by nonprofit organizations, 30% of trials not reporting funding, 35% of trials funded by both nonprofit and for-profit organizations, and 51% of trials funded by for-profit organizations (P<.001; chi2 test). Logistic regression analyses indicated that funding, treatment effect, and double blinding were the only significant predictors of conclusions. Adjusted analyses showed that trials funded by for-profit organizations were significantly more likely to recommend the experimental drug as treatment of choice (odds ratio, 5.3; 95% confidence interval, 2.0-14.4) compared with trials funded by nonprofit organizations. This association did not appear to reflect treatment effect or adverse events. Conclusions in trials funded by for-profit organizations may be more positive due to biased interpretation of trial results. Readers should carefully evaluate whether conclusions in randomized trials are supported by data.

Genome-wide regression and prediction with the BGLR statistical package.

PubMed

Pérez, Paulino; de los Campos, Gustavo

2014-10-01

Many modern genomic data analyses require implementing regressions where the number of parameters (p, e.g., the number of marker effects) exceeds sample size (n). Implementing these large-p-with-small-n regressions poses several statistical and computational challenges, some of which can be confronted using Bayesian methods. This approach allows integrating various parametric and nonparametric shrinkage and variable selection procedures in a unified and consistent manner. The BGLR R-package implements a large collection of Bayesian regression models, including parametric variable selection and shrinkage methods and semiparametric procedures (Bayesian reproducing kernel Hilbert spaces regressions, RKHS). The software was originally developed for genomic applications; however, the methods implemented are useful for many nongenomic applications as well. The response can be continuous (censored or not) or categorical (either binary or ordinal). The algorithm is based on a Gibbs sampler with scalar updates and the implementation takes advantage of efficient compiled C and Fortran routines. In this article we describe the methods implemented in BGLR, present examples of the use of the package, and discuss practical issues emerging in real-data analysis. Copyright © 2014 by the Genetics Society of America.

Partial Least Squares with Structured Output for Modelling the Metabolomics Data Obtained from Complex Experimental Designs: A Study into the Y-Block Coding.

PubMed

Xu, Yun; Muhamadali, Howbeer; Sayqal, Ali; Dixon, Neil; Goodacre, Royston

2016-10-28

Partial least squares (PLS) is one of the most commonly used supervised modelling approaches for analysing multivariate metabolomics data. PLS is typically employed as either a regression model (PLS-R) or a classification model (PLS-DA). However, in metabolomics studies it is common to investigate multiple, potentially interacting, factors simultaneously following a specific experimental design. Such data often cannot be considered as a "pure" regression or a classification problem. Nevertheless, these data have often still been treated as a regression or classification problem and this could lead to ambiguous results. In this study, we investigated the feasibility of designing a hybrid target matrix Y that better reflects the experimental design than simple regression or binary class membership coding commonly used in PLS modelling. The new design of Y coding was based on the same principle used by structural modelling in machine learning techniques. Two real metabolomics datasets were used as examples to illustrate how the new Y coding can improve the interpretability of the PLS model compared to classic regression/classification coding.

Collagen Triple Helix Repeat Containing-1 (CTHRC1) Expression in Oral Squamous Cell Carcinoma (OSCC): Prognostic Value and Clinico-Pathological Implications

PubMed Central

Lee, Chia Ee; Vincent-Chong, Vui King; Ramanathan, Anand; Kallarakkal, Thomas George; Karen-Ng, Lee Peng; Ghani, Wan Maria Nabillah; Rahman, Zainal Ariff Abdul; Ismail, Siti Mazlipah; Abraham, Mannil Thomas; Tay, Keng Kiong; Mustafa, Wan Mahadzir Wan; Cheong, Sok Ching; Zain, Rosnah Binti

2015-01-01

BACKGROUND: Collagen Triple Helix Repeat Containing 1 (CTHRC1) is a protein often found to be over-expressed in various types of human cancers. However, correlation between CTHRC1 expression level with clinico-pathological characteristics and prognosis in oral cancer remains unclear. Therefore, this study aimed to determine mRNA and protein expression of CTHRC1 in oral squamous cell carcinoma (OSCC) and to evaluate the clinical and prognostic impact of CTHRC1 in OSCC. METHODS: In this study, mRNA and protein expression of CTHRC1 in OSCCs were determined by quantitative PCR and immunohistochemistry, respectively. The association between CTHRC1 and clinico-pathological parameters were evaluated by univariate and multivariate binary logistic regression analyses. Correlation between CTHRC1 protein expressions with survival were analysed using Kaplan-Meier and Cox regression models. RESULTS: Current study demonstrated CTHRC1 was significantly overexpressed at the mRNA level in OSCC. Univariate analyses indicated a high-expression of CTHRC1 that was significantly associated with advanced stage pTNM staging, tumour size ≥ 4 cm and positive lymph node metastasis (LNM). However, only positive LNM remained significant after adjusting with other confounder factors in multivariate logistic regression analyses. Kaplan-Meier survival analyses and Cox model demonstrated that patients with high-expression of CTHRC1 protein were associated with poor prognosis and is an independent prognostic factor in OSCC. CONCLUSION: This study indicated that over-expression of CTHRC1 potentially as an independent predictor for positive LNM and poor prognosis in OSCC. PMID:26664254

A comparison of methods for the analysis of binomial clustered outcomes in behavioral research.

PubMed

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.

Missing Data in Alcohol Clinical Trials with Binary Outcomes

PubMed Central

Hallgren, Kevin A.; Witkiewitz, Katie; Kranzler, Henry R.; Falk, Daniel E.; Litten, Raye Z.; O’Malley, Stephanie S.; Anton, Raymond F.

2017-01-01

Background Missing data are common in alcohol clinical trials for both continuous and binary endpoints. Approaches to handle missing data have been explored for continuous outcomes, yet no studies have compared missing data approaches for binary outcomes (e.g., abstinence, no heavy drinking days). The present study compares approaches to modeling binary outcomes with missing data in the COMBINE study. Method We included participants in the COMBINE Study who had complete drinking data during treatment and who were assigned to active medication or placebo conditions (N=1146). Using simulation methods, missing data were introduced under common scenarios with varying sample sizes and amounts of missing data. Logistic regression was used to estimate the effect of naltrexone (vs. placebo) in predicting any drinking and any heavy drinking outcomes at the end of treatment using four analytic approaches: complete case analysis (CCA), last observation carried forward (LOCF), the worst-case scenario of missing equals any drinking or heavy drinking (WCS), and multiple imputation (MI). In separate analyses, these approaches were compared when drinking data were manually deleted for those participants who discontinued treatment but continued to provide drinking data. Results WCS produced the greatest amount of bias in treatment effect estimates. MI usually yielded less biased estimates than WCS and CCA in the simulated data, and performed considerably better than LOCF when estimating treatment effects among individuals who discontinued treatment. Conclusions Missing data can introduce bias in treatment effect estimates in alcohol clinical trials. Researchers should utilize modern missing data methods, including MI, and avoid WCS and CCA when analyzing binary alcohol clinical trial outcomes. PMID:27254113

Missing Data in Alcohol Clinical Trials with Binary Outcomes.

PubMed

Hallgren, Kevin A; Witkiewitz, Katie; Kranzler, Henry R; Falk, Daniel E; Litten, Raye Z; O'Malley, Stephanie S; Anton, Raymond F

2016-07-01

Missing data are common in alcohol clinical trials for both continuous and binary end points. Approaches to handle missing data have been explored for continuous outcomes, yet no studies have compared missing data approaches for binary outcomes (e.g., abstinence, no heavy drinking days). This study compares approaches to modeling binary outcomes with missing data in the COMBINE study. We included participants in the COMBINE study who had complete drinking data during treatment and who were assigned to active medication or placebo conditions (N = 1,146). Using simulation methods, missing data were introduced under common scenarios with varying sample sizes and amounts of missing data. Logistic regression was used to estimate the effect of naltrexone (vs. placebo) in predicting any drinking and any heavy drinking outcomes at the end of treatment using 4 analytic approaches: complete case analysis (CCA), last observation carried forward (LOCF), the worst case scenario (WCS) of missing equals any drinking or heavy drinking, and multiple imputation (MI). In separate analyses, these approaches were compared when drinking data were manually deleted for those participants who discontinued treatment but continued to provide drinking data. WCS produced the greatest amount of bias in treatment effect estimates. MI usually yielded less biased estimates than WCS and CCA in the simulated data and performed considerably better than LOCF when estimating treatment effects among individuals who discontinued treatment. Missing data can introduce bias in treatment effect estimates in alcohol clinical trials. Researchers should utilize modern missing data methods, including MI, and avoid WCS and CCA when analyzing binary alcohol clinical trial outcomes. Copyright © 2016 by the Research Society on Alcoholism.

Predicting the occurrence of wildfires with binary structured additive regression models.

PubMed

Ríos-Pena, Laura; Kneib, Thomas; Cadarso-Suárez, Carmen; Marey-Pérez, Manuel

2017-02-01

Wildfires are one of the main environmental problems facing societies today, and in the case of Galicia (north-west Spain), they are the main cause of forest destruction. This paper used binary structured additive regression (STAR) for modelling the occurrence of wildfires in Galicia. Binary STAR models are a recent contribution to the classical logistic regression and binary generalized additive models. Their main advantage lies in their flexibility for modelling non-linear effects, while simultaneously incorporating spatial and temporal variables directly, thereby making it possible to reveal possible relationships among the variables considered. The results showed that the occurrence of wildfires depends on many covariates which display variable behaviour across space and time, and which largely determine the likelihood of ignition of a fire. The joint possibility of working on spatial scales with a resolution of 1 × 1 km cells and mapping predictions in a colour range makes STAR models a useful tool for plotting and predicting wildfire occurrence. Lastly, it will facilitate the development of fire behaviour models, which can be invaluable when it comes to drawing up fire-prevention and firefighting plans. Copyright © 2016 Elsevier Ltd. All rights reserved.

Intermediate and advanced topics in multilevel logistic regression analysis

PubMed Central

Merlo, Juan

2017-01-01

Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher‐level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within‐cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population‐average effect of covariates measured at the subject and cluster level, in contrast to the within‐cluster or cluster‐specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster‐level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:28543517

Intermediate and advanced topics in multilevel logistic regression analysis.

PubMed

Austin, Peter C; Merlo, Juan

2017-09-10

Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher-level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within-cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population-average effect of covariates measured at the subject and cluster level, in contrast to the within-cluster or cluster-specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster-level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Income or living standard and health in Germany: different ways of measurement of relative poverty with regard to self-rated health.

PubMed

Pfoertner, Timo-Kolja; Andress, Hans-Juergen; Janssen, Christian

2011-08-01

Current study introduces the living standard concept as an alternative approach of measuring poverty and compares its explanatory power to an income-based poverty measure with regard to subjective health status of the German population. Analyses are based on the German Socio-Economic Panel (2001, 2003 and 2005) and refer to binary logistic regressions of poor subjective health status with regard to each poverty condition, their duration and their causal influence from a previous time point. To calculate the discriminate power of both poverty indicators, initially the indicators were considered separately in regression models and subsequently, both were included simultaneously. The analyses reveal a stronger poverty-health relationship for the living standard indicator. An inadequate living standard in 2005, longer spells of an inadequate living standard between 2001, 2003 and 2005 as well as an inadequate living standard at a previous time point is significantly strongly associated with subjective health than income poverty. Our results challenge conventional measurements of the relationship between poverty and health that probably has been underestimated by income measures so far.

No rationale for 1 variable per 10 events criterion for binary logistic regression analysis.

PubMed

van Smeden, Maarten; de Groot, Joris A H; Moons, Karel G M; Collins, Gary S; Altman, Douglas G; Eijkemans, Marinus J C; Reitsma, Johannes B

2016-11-24

Ten events per variable (EPV) is a widely advocated minimal criterion for sample size considerations in logistic regression analysis. Of three previous simulation studies that examined this minimal EPV criterion only one supports the use of a minimum of 10 EPV. In this paper, we examine the reasons for substantial differences between these extensive simulation studies. The current study uses Monte Carlo simulations to evaluate small sample bias, coverage of confidence intervals and mean square error of logit coefficients. Logistic regression models fitted by maximum likelihood and a modified estimation procedure, known as Firth's correction, are compared. The results show that besides EPV, the problems associated with low EPV depend on other factors such as the total sample size. It is also demonstrated that simulation results can be dominated by even a few simulated data sets for which the prediction of the outcome by the covariates is perfect ('separation'). We reveal that different approaches for identifying and handling separation leads to substantially different simulation results. We further show that Firth's correction can be used to improve the accuracy of regression coefficients and alleviate the problems associated with separation. The current evidence supporting EPV rules for binary logistic regression is weak. Given our findings, there is an urgent need for new research to provide guidance for supporting sample size considerations for binary logistic regression analysis.

Regression to the Mean and Changes in Risk Behavior following Study Enrollment in a Cohort of US Women at Risk for HIV

PubMed Central

Hughes, James P.; Haley, Danielle F.; Frew, Paula M.; Golin, Carol E.; Adimora, Adaora A; Kuo, Irene; Justman, Jessica; Soto-Torres, Lydia; Wang, Jing; Hodder, Sally

2015-01-01

Purpose Reductions in risk behaviors are common following enrollment in HIV prevention studies. We develop methods to quantify the proportion of change in risk behaviors that can be attributed to regression to the mean versus study participation and other factors. Methods A novel model that incorporates both regression to the mean and study participation effects is developed for binary measures. The model is used to estimate the proportion of change in the prevalence of “unprotected sex in the past 6 months” that can be attributed to study participation versus regression to the mean in a longitudinal cohort of women at risk for HIV infection who were recruited from ten US communities with high rates of HIV and poverty. HIV risk behaviors were evaluated using audio computer-assisted self-interviews at baseline and every 6 months for up to 12 months. Results The prevalence of “unprotected sex in the past 6 months” declined from 96% at baseline to 77% at 12 months. However, this change could be almost completely explained by regression to the mean. Conclusions Analyses that examine changes over time in cohorts selected for high or low risk behaviors should account for regression to the mean effects. PMID:25883065

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…

Optimization of binary thermodynamic and phase diagram data

NASA Astrophysics Data System (ADS)

Bale, Christopher W.; Pelton, A. D.

1983-03-01

An optimization technique based upon least squares regression is presented to permit the simultaneous analysis of diverse experimental binary thermodynamic and phase diagram data. Coefficients of polynomial expansions for the enthalpy and excess entropy of binary solutions are obtained which can subsequently be used to calculate the thermodynamic properties or the phase diagram. In an interactive computer-assisted analysis employing this technique, one can critically analyze a large number of diverse data in a binary system rapidly, in a manner which is fully self-consistent thermodynamically. Examples of applications to the Bi-Zn, Cd-Pb, PbCl2-KCl, LiCl-FeCl2, and Au-Ni binary systems are given.

Quantitative analysis of binary polymorphs mixtures of fusidic acid by diffuse reflectance FTIR spectroscopy, diffuse reflectance FT-NIR spectroscopy, Raman spectroscopy and multivariate calibration.

PubMed

Guo, Canyong; Luo, Xuefang; Zhou, Xiaohua; Shi, Beijia; Wang, Juanjuan; Zhao, Jinqi; Zhang, Xiaoxia

2017-06-05

Vibrational spectroscopic techniques such as infrared, near-infrared and Raman spectroscopy have become popular in detecting and quantifying polymorphism of pharmaceutics since they are fast and non-destructive. This study assessed the ability of three vibrational spectroscopy combined with multivariate analysis to quantify a low-content undesired polymorph within a binary polymorphic mixture. Partial least squares (PLS) regression and support vector machine (SVM) regression were employed to build quantitative models. Fusidic acid, a steroidal antibiotic, was used as the model compound. It was found that PLS regression performed slightly better than SVM regression in all the three spectroscopic techniques. Root mean square errors of prediction (RMSEP) were ranging from 0.48% to 1.17% for diffuse reflectance FTIR spectroscopy and 1.60-1.93% for diffuse reflectance FT-NIR spectroscopy and 1.62-2.31% for Raman spectroscopy. The results indicate that diffuse reflectance FTIR spectroscopy offers significant advantages in providing accurate measurement of polymorphic content in the fusidic acid binary mixtures, while Raman spectroscopy is the least accurate technique for quantitative analysis of polymorphs. Copyright © 2017 Elsevier B.V. All rights reserved.

Temperature dependence of nucleation rate in a binary solid solution

NASA Astrophysics Data System (ADS)

Wang, H. Y.; Philippe, T.; Duguay, S.; Blavette, D.

2012-12-01

The influence of regression (partial dissolution) effects on the temperature dependence of nucleation rate in a binary solid solution has been studied theoretically. The results of the analysis are compared with the predictions of the simplest Volmer-Weber theory. Regression effects are shown to have a strong influence on the shape of the curve of nucleation rate versus temperature. The temperature TM at which the maximum rate of nucleation occurs is found to be lowered, particularly for low interfacial energy (coherent precipitation) and high-mobility species (e.g. interstitial atoms).

Portugal and Angola: similarities and differences in Toxoplasma gondii seroprevalence and risk factors in pregnant women.

PubMed

Lobo, M L; Patrocinio, G; Sevivas, T; DE Sousa, B; Matos, O

2017-01-01

In this study we determined the presence of IgM/IgG antibodies to Toxoplasma gondii in sera of 155 and 300 pregnant women from Lisbon (Portugal) and Luanda (Angola), respectively, and evaluated the potential risk factors associated with this infection. DNA detection was performed by PCR assays targeting T. gondii regions (RE/B1). Overall, 21·9% (10·9% IgG, 10·9% IgG/IgM) of the Lisbon women and 27·3% (23·7%, IgG, 2% IgM, 1·7% IgG/IgM) of the Luanda women had antibodies to T. gondii. Single variable and binary logistic regression analyses were conducted. Based on the latter, contacts with cats (family/friends), and having more than two births were identified as risk factors for Toxoplasma infection in Lisbon women. In Luanda, the risk factors for T. gondii infection suggested by the single variable analysis (outdoor contact with cats and consumption of pasteurized milk/dairy products) were not confirmed by binary logistic regression. This study shows original data from Angola, and updated data from Portugal in the study of infection by T. gondii in pregnant women, indicating that the prevalence of anti-Toxoplasma antibodies is high enough to alert the government health authorities and implement appropriate measures to control this infection.

Prevalence and Extrinsic Risk Factors for Dental Erosion in Adolescents.

PubMed

Mafla, Ana C; Cerón-Bastidas, Ximena A; Munoz-Ceballos, Maria E; Vallejo-Bravo, Diana C; Fajardo-Santacruz, Maria C

This manuscript examined the prevalence and extrinsic risk factors for dental erosion (DE) in early and middle adolescents in Pasto, Colombia. Dental erosion was evaluated in a random sample of 384 individuals aged 10-15 years attending three primary and high schools in this cross-sectional study. Clinical dental assessment for DE was done using O'Sullivan index. Data on general sociodemographic variables and extrinsic risks factors were obtained. Descriptive and univariate binary logistic regression analyses were performed. Dental erosion was observed in 57.3% of individuals. The univariate binary logistic regression analysis showed that frequency of drinking natural fruit juices (OR 2.670, 95% CI 1.346 - 5.295, P=0.004) and their pH (OR 2.303, 95% CI 1.292 - 4.107, P=0.004) were more associated with the odd of DE in early adolescence. However, a high SES (OR 10.360, 95% CI 3.700 - 29.010, P<0.001) and frequency of snacks with artificial lemon taste (OR 3.659, 95% CI 1.506 - 8.891, P=0.003) were highly associated with the risk of DE in middle adolescence. The results suggest that DE is a prevalent condition in adolescents living in a city in southern Colombia. The transition from early to middle adolescence implies new bio-psychosocial changes, which increase the risk for DE.

Logistic Regression: Concept and Application

ERIC Educational Resources Information Center

Cokluk, Omay

2010-01-01

The main focus of logistic regression analysis is classification of individuals in different groups. The aim of the present study is to explain basic concepts and processes of binary logistic regression analysis intended to determine the combination of independent variables which best explain the membership in certain groups called dichotomous…

A Comparison of Methods for Nonparametric Estimation of Item Characteristic Curves for Binary Items

ERIC Educational Resources Information Center

Lee, Young-Sun

2007-01-01

This study compares the performance of three nonparametric item characteristic curve (ICC) estimation procedures: isotonic regression, smoothed isotonic regression, and kernel smoothing. Smoothed isotonic regression, employed along with an appropriate kernel function, provides better estimates and also satisfies the assumption of strict…

A computer tool for a minimax criterion in binary response and heteroscedastic simple linear regression models.

PubMed

Casero-Alonso, V; López-Fidalgo, J; Torsney, B

2017-01-01

Binary response models are used in many real applications. For these models the Fisher information matrix (FIM) is proportional to the FIM of a weighted simple linear regression model. The same is also true when the weight function has a finite integral. Thus, optimal designs for one binary model are also optimal for the corresponding weighted linear regression model. The main objective of this paper is to provide a tool for the construction of MV-optimal designs, minimizing the maximum of the variances of the estimates, for a general design space. MV-optimality is a potentially difficult criterion because of its nondifferentiability at equal variance designs. A methodology for obtaining MV-optimal designs where the design space is a compact interval [a, b] will be given for several standard weight functions. The methodology will allow us to build a user-friendly computer tool based on Mathematica to compute MV-optimal designs. Some illustrative examples will show a representation of MV-optimal designs in the Euclidean plane, taking a and b as the axes. The applet will be explained using two relevant models. In the first one the case of a weighted linear regression model is considered, where the weight function is directly chosen from a typical family. In the second example a binary response model is assumed, where the probability of the outcome is given by a typical probability distribution. Practitioners can use the provided applet to identify the solution and to know the exact support points and design weights. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Is parenting style a predictor of suicide attempts in a representative sample of adolescents?

PubMed

Donath, Carolin; Graessel, Elmar; Baier, Dirk; Bleich, Stefan; Hillemacher, Thomas

2014-04-26

Suicidal ideation and suicide attempts are serious but not rare conditions in adolescents. However, there are several research and practical suicide-prevention initiatives that discuss the possibility of preventing serious self-harm. Profound knowledge about risk and protective factors is therefore necessary. The aim of this study is a) to clarify the role of parenting behavior and parenting styles in adolescents' suicide attempts and b) to identify other statistically significant and clinically relevant risk and protective factors for suicide attempts in a representative sample of German adolescents. In the years 2007/2008, a representative written survey of N = 44,610 students in the 9th grade of different school types in Germany was conducted. In this survey, the lifetime prevalence of suicide attempts was investigated as well as potential predictors including parenting behavior. A three-step statistical analysis was carried out: I) As basic model, the association between parenting and suicide attempts was explored via binary logistic regression controlled for age and sex. II) The predictive values of 13 additional potential risk/protective factors were analyzed with single binary logistic regression analyses for each predictor alone. Non-significant predictors were excluded in Step III. III) In a multivariate binary logistic regression analysis, all significant predictor variables from Step II and the parenting styles were included after testing for multicollinearity. Three parental variables showed a relevant association with suicide attempts in adolescents - (all protective): mother's warmth and father's warmth in childhood and mother's control in adolescence (Step I). In the full model (Step III), Authoritative parenting (protective: OR: .79) and Rejecting-Neglecting parenting (risk: OR: 1.63) were identified as significant predictors (p < .001) for suicidal attempts. Seven further variables were interpreted to be statistically significant and clinically relevant: ADHD, female sex, smoking, Binge Drinking, absenteeism/truancy, migration background, and parental separation events. Parenting style does matter. While children of Authoritative parents profit, children of Rejecting-Neglecting parents are put at risk - as we were able to show for suicide attempts in adolescence. Some of the identified risk factors contribute new knowledge and potential areas of intervention for special groups such as migrants or children diagnosed with ADHD.

Analyzing Student Learning Outcomes: Usefulness of Logistic and Cox Regression Models. IR Applications, Volume 5

ERIC Educational Resources Information Center

Chen, Chau-Kuang

2005-01-01

Logistic and Cox regression methods are practical tools used to model the relationships between certain student learning outcomes and their relevant explanatory variables. The logistic regression model fits an S-shaped curve into a binary outcome with data points of zero and one. The Cox regression model allows investigators to study the duration…

Analysis of Binary Adherence Data in the Setting of Polypharmacy: A Comparison of Different Approaches

PubMed Central

Esserman, Denise A.; Moore, Charity G.; Roth, Mary T.

2009-01-01

Older community dwelling adults often take multiple medications for numerous chronic diseases. Non-adherence to these medications can have a large public health impact. Therefore, the measurement and modeling of medication adherence in the setting of polypharmacy is an important area of research. We apply a variety of different modeling techniques (standard linear regression; weighted linear regression; adjusted linear regression; naïve logistic regression; beta-binomial (BB) regression; generalized estimating equations (GEE)) to binary medication adherence data from a study in a North Carolina based population of older adults, where each medication an individual was taking was classified as adherent or non-adherent. In addition, through simulation we compare these different methods based on Type I error rates, bias, power, empirical 95% coverage, and goodness of fit. We find that estimation and inference using GEE is robust to a wide variety of scenarios and we recommend using this in the setting of polypharmacy when adherence is dichotomously measured for multiple medications per person. PMID:20414358

Frontal lobe function and behavioral changes in amyotrophic lateral sclerosis: a study from Southwest China.

PubMed

Wei, QianQian; Chen, XuePing; Zheng, ZhenZhen; Huang, Rui; Guo, XiaoYan; Cao, Bei; Zhao, Bi; Shang, Hui-Fang

2014-12-01

Despite growing interest, the frequency and characteristics of frontal lobe functional and behavioral deficits in Chinese people with amyotrophic lateral sclerosis (ALS), as well as their impact on the survival of ALS patients, remain unknown. The Chinese version of the frontal assessment battery (FAB) and frontal behavioral inventory (FBI) were used to evaluate 126 sporadic ALS patients and 50 healthy controls. The prevalence of frontal lobe dysfunction was 32.5%. The most notable impairment domain of the FAB was lexical fluency (30.7%). The binary logistic regression model revealed that an onset age older than 45 years (OR 5.976, P = 0.002) and a lower educational level (OR 0.858, P = 0.002) were potential determinants of an abnormal FAB. Based on the FBI score, 46.0% of patients showed varied degrees of frontal behavioral changes. The most common impaired neurobehavioral domains were irritability (25.4%), logopenia (20.6%) and apathy (19.0%). The binary logistic regression model revealed that the ALS Functional Rating Scale-Revised scale score (OR 0.127, P = 0.001) was a potential determinant of an abnormal FBI. Frontal functional impairment and the severity of frontal behavioral changes were not associated with the survival status or the progression of ALS by the cox proportional hazard model and multivariate regression analyses, respectively. Frontal lobe dysfunction and frontal behavioral changes are common in Chinese ALS patients. Frontal lobe dysfunction may be related to the onset age and educational level. The severity of frontal behavioral changes may be associated with the ALSFRS-R. However, the frontal functional impairment and the frontal behavioral changes do not worsen the progression or survival of ALS.

Regression to the mean and changes in risk behavior following study enrollment in a cohort of U.S. women at risk for HIV.

PubMed

Hughes, James P; Haley, Danielle F; Frew, Paula M; Golin, Carol E; Adimora, Adaora A; Kuo, Irene; Justman, Jessica; Soto-Torres, Lydia; Wang, Jing; Hodder, Sally

2015-06-01

Reductions in risk behaviors are common following enrollment in human immunodeficiency virus (HIV) prevention studies. We develop methods to quantify the proportion of change in risk behaviors that can be attributed to regression to the mean versus study participation and other factors. A novel model that incorporates both regression to the mean and study participation effects is developed for binary measures. The model is used to estimate the proportion of change in the prevalence of "unprotected sex in the past 6 months" that can be attributed to study participation versus regression to the mean in a longitudinal cohort of women at risk for HIV infection who were recruited from ten U.S. communities with high rates of HIV and poverty. HIV risk behaviors were evaluated using audio computer-assisted self-interviews at baseline and every 6 months for up to 12 months. The prevalence of "unprotected sex in the past 6 months" declined from 96% at baseline to 77% at 12 months. However, this change could be almost completely explained by regression to the mean. Analyses that examine changes over time in cohorts selected for high- or low- risk behaviors should account for regression to the mean effects. Copyright © 2015 Elsevier Inc. All rights reserved.

Velocity Curve Analysis of Spectroscopic Binary Stars AI Phe, GM Dra, HD 93917 and V502 Oph by Nonlinear Regression

NASA Astrophysics Data System (ADS)

Karami, K.; Mohebi, R.

2007-08-01

We introduce a new method to derive the orbital parameters of spectroscopic binary stars by nonlinear least squares of (o-c). Using the measured radial velocity data of the four double lined spectroscopic binary systems, AI Phe, GM Dra, HD 93917 and V502 Oph, we derived both the orbital and combined spectroscopic elements of these systems. Our numerical results are in good agreement with the those obtained using the method of Lehmann-Filhé.

Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model

PubMed Central

2013-01-01

Background Malnutrition is one of the principal causes of child mortality in developing countries including Bangladesh. According to our knowledge, most of the available studies, that addressed the issue of malnutrition among under-five children, considered the categorical (dichotomous/polychotomous) outcome variables and applied logistic regression (binary/multinomial) to find their predictors. In this study malnutrition variable (i.e. outcome) is defined as the number of under-five malnourished children in a family, which is a non-negative count variable. The purposes of the study are (i) to demonstrate the applicability of the generalized Poisson regression (GPR) model as an alternative of other statistical methods and (ii) to find some predictors of this outcome variable. Methods The data is extracted from the Bangladesh Demographic and Health Survey (BDHS) 2007. Briefly, this survey employs a nationally representative sample which is based on a two-stage stratified sample of households. A total of 4,460 under-five children is analysed using various statistical techniques namely Chi-square test and GPR model. Results The GPR model (as compared to the standard Poisson regression and negative Binomial regression) is found to be justified to study the above-mentioned outcome variable because of its under-dispersion (variance < mean) property. Our study also identify several significant predictors of the outcome variable namely mother’s education, father’s education, wealth index, sanitation status, source of drinking water, and total number of children ever born to a woman. Conclusions Consistencies of our findings in light of many other studies suggest that the GPR model is an ideal alternative of other statistical models to analyse the number of under-five malnourished children in a family. Strategies based on significant predictors may improve the nutritional status of children in Bangladesh. PMID:23297699

The impact of comorbid post-traumatic stress disorder in patients with major depressive disorder on clinical features, pharmacological treatment strategies, and treatment outcomes - Results from a cross-sectional European multicenter study.

PubMed

Dold, Markus; Bartova, Lucie; Kautzky, Alexander; Souery, Daniel; Mendlewicz, Julien; Serretti, Alessandro; Porcelli, Stefano; Zohar, Joseph; Montgomery, Stuart; Kasper, Siegfried

2017-07-01

This international, multicenter, cross-sectional study comprising 1346 adult in- and outpatients with major depressive disorder (MDD) investigated the association between MDD as primary diagnosis and comorbid post-traumatic stress disorder (PTSD). In a cross-sectional data collection process, the presence of comorbid PTSD was determined by the Mini International Neuropsychiatric Interview (MINI) and the patients' socio-demographic, clinical, psychopharmacological, and response information were obtained. Clinical features between MDD with and without concurrent PTSD were compared using descriptive statistics, analyses of covariance (ANCOVA), and binary logistic regression analyses. 1.49% of the MDD patients suffered from comorbid PTSD. Significantly more MDD + comorbid PTSD patients exhibited atypical features, comorbid anxiety disorders (any comorbid anxiety disorder, panic disorder, agoraphobia, and social phobia), comorbid bulimia nervosa, current suicide risk, and augmentation treatment with low-dose antipsychotic drugs. In the binary logistic regression analyses, the presence of atypical features (odds ratio (OR) = 4.49, 95%CI:1.01-20.12; p≤.05), any comorbid anxiety disorder (OR = 3.89, 95%CI:1.60-9.44; p = .003), comorbid panic disorder (OR = 6.45, 95%CI:2.52-16.51; p = .001), comorbid agoraphobia (OR = 6.51, 95%CI:2.54-16.68; p≤.001), comorbid social phobia (OR = 6.16, 95%CI:1.71-22.17; p≤.001), comorbid bulimia nervosa (OR = 10.39, 95%CI:1.21-88.64; p = .03), current suicide risk (OR = 3.58, 95%CI:1.30-9.91; p = .01), and augmentation with low-potency antipsychotics (OR = 6.66, 95%CI:2.50-17.77; p<.001) were associated with concurrent PTSD in predominant MDD. Major findings of this study were (1.) the much lower prevalence rate of comorbid PTSD in predominant MDD compared to the reverse prevalence rates of concurrent MDD in primary PTSD, (2.) the high association to comorbid anxiety disorders, and (3.) the increased suicide risk due to concurrent PTSD. Copyright © 2017 Elsevier B.V. and ECNP. All rights reserved.

Do classic blood biomarkers of JSLE identify active lupus nephritis? Evidence from the UK JSLE Cohort Study.

PubMed

Smith, E M D; Jorgensen, A L; Beresford, M W

2017-10-01

Background Lupus nephritis (LN) affects up to 80% of juvenile-onset systemic lupus erythematosus (JSLE) patients. The value of commonly available biomarkers, such as anti-dsDNA antibodies, complement (C3/C4), ESR and full blood count parameters in the identification of active LN remains uncertain. Methods Participants from the UK JSLE Cohort Study, aged <16 years at diagnosis, were categorized as having active or inactive LN according to the renal domain of the British Isles Lupus Assessment Group score. Classic biomarkers: anti-dsDNA, C3, C4, ESR, CRP, haemoglobin, total white cells, neutrophils, lymphocytes, platelets and immunoglobulins were assessed for their ability to identify active LN using binary logistic regression modeling, with stepAIC function applied to select a final model. Receiver-operating curve analysis was used to assess diagnostic accuracy. Results A total of 370 patients were recruited; 191 (52%) had active LN and 179 (48%) had inactive LN. Binary logistic regression modeling demonstrated a combination of ESR, C3, white cell count, neutrophils, lymphocytes and IgG to be best for the identification of active LN (area under the curve 0.724). Conclusions At best, combining common classic blood biomarkers of lupus activity using multivariate analysis provides a 'fair' ability to identify active LN. Urine biomarkers were not included in these analyses. These results add to the concern that classic blood biomarkers are limited in monitoring discrete JSLE manifestations such as LN.

Cluster randomised crossover trials with binary data and unbalanced cluster sizes: application to studies of near-universal interventions in intensive care.

PubMed

Forbes, Andrew B; Akram, Muhammad; Pilcher, David; Cooper, Jamie; Bellomo, Rinaldo

2015-02-01

Cluster randomised crossover trials have been utilised in recent years in the health and social sciences. Methods for analysis have been proposed; however, for binary outcomes, these have received little assessment of their appropriateness. In addition, methods for determination of sample size are currently limited to balanced cluster sizes both between clusters and between periods within clusters. This article aims to extend this work to unbalanced situations and to evaluate the properties of a variety of methods for analysis of binary data, with a particular focus on the setting of potential trials of near-universal interventions in intensive care to reduce in-hospital mortality. We derive a formula for sample size estimation for unbalanced cluster sizes, and apply it to the intensive care setting to demonstrate the utility of the cluster crossover design. We conduct a numerical simulation of the design in the intensive care setting and for more general configurations, and we assess the performance of three cluster summary estimators and an individual-data estimator based on binomial-identity-link regression. For settings similar to the intensive care scenario involving large cluster sizes and small intra-cluster correlations, the sample size formulae developed and analysis methods investigated are found to be appropriate, with the unweighted cluster summary method performing well relative to the more optimal but more complex inverse-variance weighted method. More generally, we find that the unweighted and cluster-size-weighted summary methods perform well, with the relative efficiency of each largely determined systematically from the study design parameters. Performance of individual-data regression is adequate with small cluster sizes but becomes inefficient for large, unbalanced cluster sizes. When outcome prevalences are 6% or less and the within-cluster-within-period correlation is 0.05 or larger, all methods display sub-nominal confidence interval coverage, with the less prevalent the outcome the worse the coverage. As with all simulation studies, conclusions are limited to the configurations studied. We confined attention to detecting intervention effects on an absolute risk scale using marginal models and did not explore properties of binary random effects models. Cluster crossover designs with binary outcomes can be analysed using simple cluster summary methods, and sample size in unbalanced cluster size settings can be determined using relatively straightforward formulae. However, caution needs to be applied in situations with low prevalence outcomes and moderate to high intra-cluster correlations. © The Author(s) 2014.

Reduction from cost-sensitive ordinal ranking to weighted binary classification.

PubMed

Lin, Hsuan-Tien; Li, Ling

2012-05-01

We present a reduction framework from ordinal ranking to binary classification. The framework consists of three steps: extracting extended examples from the original examples, learning a binary classifier on the extended examples with any binary classification algorithm, and constructing a ranker from the binary classifier. Based on the framework, we show that a weighted 0/1 loss of the binary classifier upper-bounds the mislabeling cost of the ranker, both error-wise and regret-wise. Our framework allows not only the design of good ordinal ranking algorithms based on well-tuned binary classification approaches, but also the derivation of new generalization bounds for ordinal ranking from known bounds for binary classification. In addition, our framework unifies many existing ordinal ranking algorithms, such as perceptron ranking and support vector ordinal regression. When compared empirically on benchmark data sets, some of our newly designed algorithms enjoy advantages in terms of both training speed and generalization performance over existing algorithms. In addition, the newly designed algorithms lead to better cost-sensitive ordinal ranking performance, as well as improved listwise ranking performance.

Predicting the Risk of Breakthrough Urinary Tract Infections: Primary Vesicoureteral Reflux.

PubMed

Hidas, Guy; Billimek, John; Nam, Alexander; Soltani, Tandis; Kelly, Maryellen S; Selby, Blake; Dorgalli, Crystal; Wehbi, Elias; McAleer, Irene; McLorie, Gordon; Greenfield, Sheldon; Kaplan, Sherrie H; Khoury, Antoine E

2015-11-01

We constructed a risk prediction instrument stratifying patients with primary vesicoureteral reflux into groups according to their 2-year probability of breakthrough urinary tract infection. Demographic and clinical information was retrospectively collected in children diagnosed with primary vesicoureteral reflux and followed for 2 years. Bivariate and binary logistic regression analyses were performed to identify factors associated with breakthrough urinary tract infection. The final regression model was used to compute an estimation of the 2-year probability of breakthrough urinary tract infection for each subject. Accuracy of the binary classifier for breakthrough urinary tract infection was evaluated using receiver operator curve analysis. Three distinct risk groups were identified. The model was then validated in a prospective cohort. A total of 252 bivariate analyses showed that high grade (IV or V) vesicoureteral reflux (OR 9.4, 95% CI 3.8-23.5, p <0.001), presentation after urinary tract infection (OR 5.3, 95% CI 1.1-24.7, p = 0.034) and female gender (OR 2.6, 95% CI 0.097-7.11, p <0.054) were important risk factors for breakthrough urinary tract infection. Subgroup analysis revealed bladder and bowel dysfunction was a significant risk factor more pronounced in low grade (I to III) vesicoureteral reflux (OR 2.8, p = 0.018). The estimation model was applied for prospective validation, which demonstrated predicted vs actual 2-year breakthrough urinary tract infection rates of 19% vs 21%. Stratifying the patients into 3 risk groups based on parameters in the risk model showed 2-year risk for breakthrough urinary tract infection was 8.6%, 26.0% and 62.5% in the low, intermediate and high risk groups, respectively. This proposed risk stratification and probability model allows prediction of 2-year risk of patient breakthrough urinary tract infection to better inform parents of possible outcomes and treatment strategies. Copyright © 2015 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

ANALYSES OF THE INTERACTIONS WITHIN BINARY MIXTURES OF CARCINOGENIC PAHS USING MORPHOLOGICAL CELL TRANSFORMATION OF C3H10T1/2CL8 CELLS

EPA Science Inventory

ANALYSES OF THE INTERACTIONS WITHIN BINARY MIXTURES OF CARCINOGENIC PAHS USING MORPHOLOGICAL CELL TRANSFORMATION OF C3HIOT1/2 CL8 CELLS.

Studies of defined mixtures of carcinogenic polycyclic aromatic hydrocarbons (PAH) have identified three major categories of interacti...

Diagnostic Algorithm to Reflect Regressive Changes of Human Papilloma Virus in Tissue Biopsies

PubMed Central

Lhee, Min Jin; Cha, Youn Jin; Bae, Jong Man; Kim, Young Tae

2014-01-01

Purpose Landmark indicators have not yet to be developed to detect the regression of cervical intraepithelial neoplasia (CIN). We propose that quantitative viral load and indicative histological criteria can be used to differentiate between atypical squamous cells of undetermined significance (ASCUS) and a CIN of grade 1. Materials and Methods We collected 115 tissue biopsies from women who tested positive for the human papilloma virus (HPV). Nine morphological parameters including nuclear size, perinuclear halo, hyperchromasia, typical koilocyte (TK), abortive koilocyte (AK), bi-/multi-nucleation, keratohyaline granules, inflammation, and dyskeratosis were examined for each case. Correlation analyses, cumulative logistic regression, and binary logistic regression were used to determine optimal cut-off values of HPV copy numbers. The parameters TK, perinuclear halo, multi-nucleation, and nuclear size were significantly correlated quantitatively to HPV copy number. Results An HPV loading number of 58.9 and AK number of 20 were optimal to discriminate between negative and subtle findings in biopsies. An HPV loading number of 271.49 and AK of 20 were optimal for discriminating between equivocal changes and obvious koilocytosis. Conclusion We propose that a squamous epithelial lesion with AK of >20 and quantitative HPV copy number between 58.9-271.49 represents a new spectrum of subtle pathological findings, characterized by AK in ASCUS. This can be described as a distinct entity and called "regressing koilocytosis". PMID:24532500

Methods for calculating confidence and credible intervals for the residual between-study variance in random effects meta-regression models

PubMed Central

2014-01-01

Background Meta-regression is becoming increasingly used to model study level covariate effects. However this type of statistical analysis presents many difficulties and challenges. Here two methods for calculating confidence intervals for the magnitude of the residual between-study variance in random effects meta-regression models are developed. A further suggestion for calculating credible intervals using informative prior distributions for the residual between-study variance is presented. Methods Two recently proposed and, under the assumptions of the random effects model, exact methods for constructing confidence intervals for the between-study variance in random effects meta-analyses are extended to the meta-regression setting. The use of Generalised Cochran heterogeneity statistics is extended to the meta-regression setting and a Newton-Raphson procedure is developed to implement the Q profile method for meta-analysis and meta-regression. WinBUGS is used to implement informative priors for the residual between-study variance in the context of Bayesian meta-regressions. Results Results are obtained for two contrasting examples, where the first example involves a binary covariate and the second involves a continuous covariate. Intervals for the residual between-study variance are wide for both examples. Conclusions Statistical methods, and R computer software, are available to compute exact confidence intervals for the residual between-study variance under the random effects model for meta-regression. These frequentist methods are almost as easily implemented as their established counterparts for meta-analysis. Bayesian meta-regressions are also easily performed by analysts who are comfortable using WinBUGS. Estimates of the residual between-study variance in random effects meta-regressions should be routinely reported and accompanied by some measure of their uncertainty. Confidence and/or credible intervals are well-suited to this purpose. PMID:25196829

Effect of Placenta Previa on Preeclampsia

PubMed Central

Ying, Hao; Lu, Yi; Dong, Yi-Nuo; Wang, De-Fen

2016-01-01

Background The correlation between gestational hypertension-preeclampsia (GH-PE) and placenta previa (PP) is controversial. Specifically, it is unknown whether placenta previa has any effect on the various types of preeclampsia (PE), and the role PP with concurrent placenta accreta (PA) play in the occurrence of GH-PE are not well understood. Objective The aim of this study was to identify the effects of PP on GH, mild and severe preeclampsia (MPE and SPE), and early- and late-onset preeclampsia (EPE and LPE). Another aim of the study was to determine if concurrent PA impacts the relationship between PP and GH-PE. Methods A retrospective single-center study of 1,058 patients having singleton pregnancies with PP was performed, and 2,116 pregnant women were randomly included as controls. These cases were collected from a tertiary hospital and met the inclusion criteria for the study. Clinical information, including PP and the gestational age at the onset of GH-PE were collected. Binary and multiple logistic regression analyses were conducted after the confounding variables were controlled to assess the effects of PP on different types of GH-PE. Results There were 155 patients with GH-PE in the two groups. The incidences of GH-PE in the PP group and the control group were 2.5% (26/1058) and 6.1% (129/2116), respectively (P = 0.000). Binary and multiple regression analyses were conducted after controlling for confounding variables. Compared to the control group, in the PP group, the risk of GH-PE was reduced significantly by 78% (AOR: 0.216; 95% CI: 0.135–0.345); the risks of GH and PE were reduced by 55% (AOR: 0.451; 95% CI: 0.233–0.873) and 86% (AOR: 0.141; 95% CI: 0.073–0.271), respectively; the risks of MPE and SPE were reduced by 73% (AOR: 0.269; 95% CI: 0.087–0828) and 88% (AOR: 0.123; 95% CI: 0.055–0.279), respectively; and the risks of EPE and LPE were reduced by 95% (AOR: 0.047; 95% CI: 0.012–0.190) and 67% (AOR: 0.330; 95% CI: 0.153–0.715), respectively. The incidence of concurrent PA in women with PP was 5.86%; PP with PA did not significantly further reduce the incidence of GH-PE compared with PP without PA (1.64% vs. 2.51%, P>0.05). Binary logistic regression analyses were conducted after controlling for confounding variables, compared with the non-PP + GH-PE group, and the AOR of FGR in the non-PP + non-GH-PE group was 0.206 (0.124–0.342). Compared with the PP + GH-PE group, the AOR of FGR in the PP + non-GH-PE group was 0.430 (0.123–1.500). Conclusion PP is not only associated with a significant reduction in the incidence of GH-PE, but also is associated with a reduction in incidence of various types of PE. Concurrent PA and PP do not show association with a reduction in incidence of GH-PE. PMID:26731265

The crux of the method: assumptions in ordinary least squares and logistic regression.

PubMed

Long, Rebecca G

2008-10-01

Logistic regression has increasingly become the tool of choice when analyzing data with a binary dependent variable. While resources relating to the technique are widely available, clear discussions of why logistic regression should be used in place of ordinary least squares regression are difficult to find. The current paper compares and contrasts the assumptions of ordinary least squares with those of logistic regression and explains why logistic regression's looser assumptions make it adept at handling violations of the more important assumptions in ordinary least squares.

Eccentric binaries - still interesting targets

NASA Astrophysics Data System (ADS)

Zasche, P.

2018-04-01

Eccentric binaries still provides us with valuable results and new observations of these systems are welcome. Especially these ones never analysed before should be observed for their light curves and minima.

Predicting the geographic distribution of a species from presence-only data subject to detection errors

USGS Publications Warehouse

Dorazio, Robert M.

2012-01-01

Several models have been developed to predict the geographic distribution of a species by combining measurements of covariates of occurrence at locations where the species is known to be present with measurements of the same covariates at other locations where species occurrence status (presence or absence) is unknown. In the absence of species detection errors, spatial point-process models and binary-regression models for case-augmented surveys provide consistent estimators of a species’ geographic distribution without prior knowledge of species prevalence. In addition, these regression models can be modified to produce estimators of species abundance that are asymptotically equivalent to those of the spatial point-process models. However, if species presence locations are subject to detection errors, neither class of models provides a consistent estimator of covariate effects unless the covariates of species abundance are distinct and independently distributed from the covariates of species detection probability. These analytical results are illustrated using simulation studies of data sets that contain a wide range of presence-only sample sizes. Analyses of presence-only data of three avian species observed in a survey of landbirds in western Montana and northern Idaho are compared with site-occupancy analyses of detections and nondetections of these species.

Is parenting style a predictor of suicide attempts in a representative sample of adolescents?

PubMed Central

2014-01-01

Background Suicidal ideation and suicide attempts are serious but not rare conditions in adolescents. However, there are several research and practical suicide-prevention initiatives that discuss the possibility of preventing serious self-harm. Profound knowledge about risk and protective factors is therefore necessary. The aim of this study is a) to clarify the role of parenting behavior and parenting styles in adolescents’ suicide attempts and b) to identify other statistically significant and clinically relevant risk and protective factors for suicide attempts in a representative sample of German adolescents. Methods In the years 2007/2008, a representative written survey of N = 44,610 students in the 9th grade of different school types in Germany was conducted. In this survey, the lifetime prevalence of suicide attempts was investigated as well as potential predictors including parenting behavior. A three-step statistical analysis was carried out: I) As basic model, the association between parenting and suicide attempts was explored via binary logistic regression controlled for age and sex. II) The predictive values of 13 additional potential risk/protective factors were analyzed with single binary logistic regression analyses for each predictor alone. Non-significant predictors were excluded in Step III. III) In a multivariate binary logistic regression analysis, all significant predictor variables from Step II and the parenting styles were included after testing for multicollinearity. Results Three parental variables showed a relevant association with suicide attempts in adolescents – (all protective): mother’s warmth and father’s warmth in childhood and mother’s control in adolescence (Step I). In the full model (Step III), Authoritative parenting (protective: OR: .79) and Rejecting-Neglecting parenting (risk: OR: 1.63) were identified as significant predictors (p < .001) for suicidal attempts. Seven further variables were interpreted to be statistically significant and clinically relevant: ADHD, female sex, smoking, Binge Drinking, absenteeism/truancy, migration background, and parental separation events. Conclusions Parenting style does matter. While children of Authoritative parents profit, children of Rejecting-Neglecting parents are put at risk – as we were able to show for suicide attempts in adolescence. Some of the identified risk factors contribute new knowledge and potential areas of intervention for special groups such as migrants or children diagnosed with ADHD. PMID:24766881

Extramural vascular invasion and response to neoadjuvant chemoradiotherapy in rectal cancer: Influence of the CpG island methylator phenotype

PubMed Central

Williamson, Jeremy Stuart; Jones, Huw Geraint; Williams, Namor; Griffiths, Anthony Paul; Jenkins, Gareth; Beynon, John; Harris, Dean Anthony

2017-01-01

AIM To identify whether CpG island methylator phenotype (CIMP) is predictive of response to neoadjuvant chemoradiotherapy (NACRT) and outcomes in rectal cancer. METHODS Patients undergoing NACRT and surgical resection for rectal cancer in a tertiary referral centre between 2002-2011 were identified. Pre-treatment tumour biopsies were analysed for CIMP status (high, intermediate or low) using methylation specific PCR. KRAS and BRAF status were also determined using pyrosequencing analysis. Clinical information was extracted from case records and cancer services databases. Response to radiotherapy was measured by tumour regression scores determined upon histological examination of the resected specimen. The relationship between these molecular features, response to NACRT and oncological outcomes were analysed. RESULTS There were 160 patients analysed with a median follow-up time of 46.4 mo. Twenty-one (13%) patients demonstrated high levels of CIMP methylation (CIMP-H) and this was significantly associated with increased risk of extramural vascular invasion (EMVI) compared with CIMP-L [8/21 (38%) vs 15/99 (15%), P = 0.028]. CIMP status was not related to tumour regression after radiotherapy or survival, however EMVI was significantly associated with adverse survival (P < 0.001). Intermediate CIMP status was significantly associated with KRAS mutation (P = 0.01). There were 14 (9%) patients with a pathological complete response (pCR) compared to 116 (73%) patients having no or minimal regression after neoadjuvant chemoradiotherapy. Those patients with pCR had median survival of 106 mo compared to 65.8 mo with minimal regression, although this was not statistically significant (P = 0.26). Binary logistic regression analysis of the relationship between EMVI and other prognostic features revealed, EMVI positivity was associated with poor overall survival, advanced “T” stage and CIMP-H but not nodal status, age, sex, KRAS mutation status and presence of local or systemic recurrence. CONCLUSION We report a novel association of pre-treatment characterisation of CIMP-H with EMVI status which has prognostic implications and is not readily detectable on pre-treatment histological examination. PMID:28567185

Extramural vascular invasion and response to neoadjuvant chemoradiotherapy in rectal cancer: Influence of the CpG island methylator phenotype.

PubMed

Williamson, Jeremy Stuart; Jones, Huw Geraint; Williams, Namor; Griffiths, Anthony Paul; Jenkins, Gareth; Beynon, John; Harris, Dean Anthony

2017-05-15

To identify whether CpG island methylator phenotype (CIMP) is predictive of response to neoadjuvant chemoradiotherapy (NACRT) and outcomes in rectal cancer. Patients undergoing NACRT and surgical resection for rectal cancer in a tertiary referral centre between 2002-2011 were identified. Pre-treatment tumour biopsies were analysed for CIMP status (high, intermediate or low) using methylation specific PCR. KRAS and BRAF status were also determined using pyrosequencing analysis. Clinical information was extracted from case records and cancer services databases. Response to radiotherapy was measured by tumour regression scores determined upon histological examination of the resected specimen. The relationship between these molecular features, response to NACRT and oncological outcomes were analysed. There were 160 patients analysed with a median follow-up time of 46.4 mo. Twenty-one (13%) patients demonstrated high levels of CIMP methylation (CIMP-H) and this was significantly associated with increased risk of extramural vascular invasion (EMVI) compared with CIMP-L [8/21 (38%) vs 15/99 (15%), P = 0.028]. CIMP status was not related to tumour regression after radiotherapy or survival, however EMVI was significantly associated with adverse survival ( P < 0.001). Intermediate CIMP status was significantly associated with KRAS mutation ( P = 0.01). There were 14 (9%) patients with a pathological complete response (pCR) compared to 116 (73%) patients having no or minimal regression after neoadjuvant chemoradiotherapy. Those patients with pCR had median survival of 106 mo compared to 65.8 mo with minimal regression, although this was not statistically significant ( P = 0.26). Binary logistic regression analysis of the relationship between EMVI and other prognostic features revealed, EMVI positivity was associated with poor overall survival, advanced "T" stage and CIMP-H but not nodal status, age, sex, KRAS mutation status and presence of local or systemic recurrence. We report a novel association of pre-treatment characterisation of CIMP-H with EMVI status which has prognostic implications and is not readily detectable on pre-treatment histological examination.

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…

Walk Score(TM), Perceived Neighborhood Walkability, and walking in the US.

PubMed

Tuckel, Peter; Milczarski, William

2015-03-01

To investigate both the Walk Score(TM) and a self-reported measure of neighborhood walkability ("Perceived Neighborhood Walkability") as estimators of transport and recreational walking among Americans. The study is based upon a survey of a nationally-representative sample of 1224 American adults. The survey gauged walking for both transport and recreation and included a self-reported measure of neighborhood walkability and each respondent's Walk Score(TM). Binary logistic and linear regression analyses were performed on the data. The Walk Score(TM) is associated with walking for transport, but not recreational walking nor total walking. Perceived Neighborhood Walkability is associated with transport, recreational and total walking. Perceived Neighborhood Walkability captures the experiential nature of walking more than the Walk Score(TM).

Spatial properties of snow cover in the Upper Merced River Basin: implications for a distributed snow measurement network

NASA Astrophysics Data System (ADS)

Bouffon, T.; Rice, R.; Bales, R.

2006-12-01

The spatial distributions of snow water equivalent (SWE) and snow depth within a 1, 4, and 16 km2 grid element around two automated snow pillows in a forested and open- forested region of the Upper Merced River Basin (2,800 km2) of Yosemite National Park were characterized using field observations and analyzed using binary regression trees. Snow surveys occurred at the forested site during the accumulation and ablation seasons, while at the open-forest site a survey was performed only during the accumulation season. An average of 130 snow depth and 7 snow density measurements were made on each survey, within the 4 km2 grid. Snow depth was distributed using binary regression trees and geostatistical methods using the physiographic parameters (e.g. elevation, slope, vegetation, aspect). Results in the forest region indicate that the snow pillow overestimated average SWE within the 1, 4, and 16 km2 areas by 34 percent during ablation, but during accumulation the snow pillow provides a good estimate of the modeled mean SWE grid value, however it is suspected that the snow pillow was underestimating SWE. However, at the open forest site, during accumulation, the snow pillow was 28 percent greater than the mean modeled grid element. In addition, the binary regression trees indicate that the independent variables of vegetation, slope, and aspect are the most influential parameters of snow depth distribution. The binary regression tree and multivariate linear regression models explain about 60 percent of the initial variance for snow depth and 80 percent for density, respectively. This short-term study provides motivation and direction for the installation of a distributed snow measurement network to fill the information gap in basin-wide SWE and snow depth measurements. Guided by these results, a distributed snow measurement network was installed in the Fall 2006 at Gin Flat in the Upper Merced River Basin with the specific objective of measuring accumulation and ablation across topographic variables with the aim of providing guidance for future larger scale observation network designs.

HYPOTHESIS TESTING FOR HIGH-DIMENSIONAL SPARSE BINARY REGRESSION

PubMed Central

Mukherjee, Rajarshi; Pillai, Natesh S.; Lin, Xihong

2015-01-01

In this paper, we study the detection boundary for minimax hypothesis testing in the context of high-dimensional, sparse binary regression models. Motivated by genetic sequencing association studies for rare variant effects, we investigate the complexity of the hypothesis testing problem when the design matrix is sparse. We observe a new phenomenon in the behavior of detection boundary which does not occur in the case of Gaussian linear regression. We derive the detection boundary as a function of two components: a design matrix sparsity index and signal strength, each of which is a function of the sparsity of the alternative. For any alternative, if the design matrix sparsity index is too high, any test is asymptotically powerless irrespective of the magnitude of signal strength. For binary design matrices with the sparsity index that is not too high, our results are parallel to those in the Gaussian case. In this context, we derive detection boundaries for both dense and sparse regimes. For the dense regime, we show that the generalized likelihood ratio is rate optimal; for the sparse regime, we propose an extended Higher Criticism Test and show it is rate optimal and sharp. We illustrate the finite sample properties of the theoretical results using simulation studies. PMID:26246645

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhuang Quntao; Gao Xun; Yu Qingjuan, E-mail: yuqj@pku.edu.cn

In this paper, we study possible signatures of binary planets or exomoons on the Rossiter-McLaughlin (R-M) effect. Our analyses show that the R-M effect for a binary planet or an exomoon during its complete transit phase can be divided into two parts. The first is the conventional one similar to the R-M effect from the transit of a single planet, of which the mass and the projected area are the combinations of the binary components; the second is caused by the orbital rotation of the binary components, which may add a sine- or linear-mode deviation to the stellar radial velocitymore » curve. We find that the latter effect can be up to several ten m s{sup -1}. Our numerical simulations as well as analyses illustrate that the distribution and dispersion of the latter effects obtained from multiple transit events can be used to constrain the dynamical configuration of the binary planet, such as how the inner orbit of the binary planet is inclined to its orbit rotating around the central star. We find that the signatures caused by the orbital rotation of the binary components are more likely to be revealed if the two components of a binary planet have different masses and mass densities, especially if the heavy one has a high mass density and the light one has a low density. Similar signatures on the R-M effect may also be revealed in a hierarchical triple star system containing a dark compact binary and a tertiary star.« less

Empirical evidence about inconsistency among studies in a pair‐wise meta‐analysis

PubMed Central

Turner, Rebecca M.; Higgins, Julian P. T.

2015-01-01

This paper investigates how inconsistency (as measured by the I2 statistic) among studies in a meta‐analysis may differ, according to the type of outcome data and effect measure. We used hierarchical models to analyse data from 3873 binary, 5132 continuous and 880 mixed outcome meta‐analyses within the Cochrane Database of Systematic Reviews. Predictive distributions for inconsistency expected in future meta‐analyses were obtained, which can inform priors for between‐study variance. Inconsistency estimates were highest on average for binary outcome meta‐analyses of risk differences and continuous outcome meta‐analyses. For a planned binary outcome meta‐analysis in a general research setting, the predictive distribution for inconsistency among log odds ratios had median 22% and 95% CI: 12% to 39%. For a continuous outcome meta‐analysis, the predictive distribution for inconsistency among standardized mean differences had median 40% and 95% CI: 15% to 73%. Levels of inconsistency were similar for binary data measured by log odds ratios and log relative risks. Fitted distributions for inconsistency expected in continuous outcome meta‐analyses using mean differences were almost identical to those using standardized mean differences. The empirical evidence on inconsistency gives guidance on which outcome measures are most likely to be consistent in particular circumstances and facilitates Bayesian meta‐analysis with an informative prior for heterogeneity. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. PMID:26679486

Serum osteocalcin is significantly related to indices of obesity and lipid profile in Malaysian men.

PubMed

Chin, Kok-Yong; Ima-Nirwana, Soelaiman; Mohamed, Isa Naina; Ahmad, Fairus; Ramli, Elvy Suhana Mohd; Aminuddin, Amilia; Ngah, Wan Zurinah Wan

2014-01-01

Recent studies revealed a possible reciprocal relationship between the skeletal system and obesity and lipid metabolism, mediated by osteocalcin, an osteoblast-specific protein. This study aimed to validate the relationship between serum osteocalcin and indices of obesity and lipid parameters in a group of Malaysian men. A total of 373 men from the Malaysian Aging Male Study were included in the analysis. Data on subjects' demography, body mass index (BMI), body fat (BF) mass, waist circumference (WC), serum osteocalcin and fasting lipid levels were collected. Bioelectrical impendence (BIA) method was used to estimate BF. Multiple linear and binary logistic regression analyses were performed to analyze the association between serum osteocalcin and the aforementioned variables, with adjustment for age, ethnicity and BMI. Multiple regression results indicated that weight, BMI, BF mass, BF %, WC were significantly and negatively associated with serum osteocalcin (p < 0.001). There was a significant positive association between serum osteocalcin and high density lipoprotein (HDL) cholesterol (p = 0.032). Binary logistic results indicated that subjects with low serum osteocalcin level were more likely to be associated with high BMI (obese and overweight), high BF%, high WC and low HDL cholesterol (p < 0.05). Subjects with high osteocalcin level also demonstrated high total cholesterol level (p < 0.05) but this association was probably driven by high HDL level. These variables were not associated with serum C-terminal of telopeptide crosslinks in the subjects (p > 0.05). Serum osteocalcin is associated with indices of obesity and HDL level in men. These relationships should be validated by a longitudinal study, with comprehensive hormone profile testing.

Logits and Tigers and Bears, Oh My! A Brief Look at the Simple Math of Logistic Regression and How It Can Improve Dissemination of Results

ERIC Educational Resources Information Center

Osborne, Jason W.

2012-01-01

Logistic regression is slowly gaining acceptance in the social sciences, and fills an important niche in the researcher's toolkit: being able to predict important outcomes that are not continuous in nature. While OLS regression is a valuable tool, it cannot routinely be used to predict outcomes that are binary or categorical in nature. These…

America's Democracy Colleges: The Civic Engagement of Community College Students

ERIC Educational Resources Information Center

Angeli Newell, Mallory

2014-01-01

This study explored the civic engagement of current two- and four-year students to explore whether differences exist between the groups and what may explain the differences. Using binary logistic regression and Ordinary Least Squares regression it was found that community-based engagement was lower for two- than four-year students, though…

Multiple Logistic Regression Analysis of Cigarette Use among High School Students

ERIC Educational Resources Information Center

Adwere-Boamah, Joseph

2011-01-01

A binary logistic regression analysis was performed to predict high school students' cigarette smoking behavior from selected predictors from 2009 CDC Youth Risk Behavior Surveillance Survey. The specific target student behavior of interest was frequent cigarette use. Five predictor variables included in the model were: a) race, b) frequency of…

Nutritional status of under-five children in Bangladesh: a multilevel analysis.

PubMed

Alom, Jahangir; Quddus, Md Abdul; Islam, Mohammad Amirul

2012-09-01

The nutritional status of under-five children is a sensitive sign of a country's health status as well as economic condition. This study investigated the differential impact of some demographic, socioeconomic, environmental and health-related factors on the nutritional status among under-five children in Bangladesh using Bangladesh Demographic and Health Survey 2007 data. Two-level random intercept binary logistic regression models were used to identify the determinants of under-five malnutrition. The analyses revealed that 16% of the children were severely stunted and 25% were moderately stunted. Among the children under five years of age 3% were severely wasted and 14% were moderately wasted. Furthermore, 11% of the children were severely underweight and 28% were moderately underweight. The main contributing factors for under-five malnutrition were found to be child's age, mother's education, father's education, father's occupation, family wealth index, currently breast-feeding, place of delivery and division. Significant community-level variations were found in the analyses.

Screening utility of the social anxiety screening scale in Spanish speaking adolescents.

PubMed

Piqueras, José Antonio; Olivares, José; Hidalgo, María Dolores

2012-07-01

The aim of this study was to analyse the screening utility of the Social Anxiety Screening Scale (SASS/EDAS) in a sample of 227 adolescents with social anxiety disorder and 156 Without it (14-17 years). Results showed that the EDAS subscales (Avoidance, Distress and Interference) scores were reliable in terms of internal consistency (alpha > .80). All the subscales discriminated between adolescents with and without the disorder. They also showed a positive and significant correlation with other empirically validated measures of social anxiety. The three subscales indicated relevant sensitivity (69.16-84.14%), specificity (63.46-66.03%) and areas under the curve (.74-.81%). Binary logistic regression analyses indicated the adequate predictive utility of EDAS subscales, with the Distress subscale as the best diagnostic predictor. The data provide empirical evidence of the usefulness of EDAS as a screener for adolescent social anxiety disorder in terms of reliability, convergent and discriminant validity, diagnostic accuracy and clinical usefulness.

Parameter Estimation for Compact Binaries with Ground-Based Gravitational-Wave Observations Using the LALInference

NASA Technical Reports Server (NTRS)

Veitch, J.; Raymond, V.; Farr, B.; Farr, W.; Graff, P.; Vitale, S.; Aylott, B.; Blackburn, K.; Christensen, N.; Coughlin, M.

2015-01-01

The Advanced LIGO and Advanced Virgo gravitational wave (GW) detectors will begin operation in the coming years, with compact binary coalescence events a likely source for the first detections. The gravitational waveforms emitted directly encode information about the sources, including the masses and spins of the compact objects. Recovering the physical parameters of the sources from the GW observations is a key analysis task. This work describes the LALInference software library for Bayesian parameter estimation of compact binary signals, which builds on several previous methods to provide a well-tested toolkit which has already been used for several studies. We show that our implementation is able to correctly recover the parameters of compact binary signals from simulated data from the advanced GW detectors. We demonstrate this with a detailed comparison on three compact binary systems: a binary neutron star (BNS), a neutron star - black hole binary (NSBH) and a binary black hole (BBH), where we show a cross-comparison of results obtained using three independent sampling algorithms. These systems were analysed with non-spinning, aligned spin and generic spin configurations respectively, showing that consistent results can be obtained even with the full 15-dimensional parameter space of the generic spin configurations. We also demonstrate statistically that the Bayesian credible intervals we recover correspond to frequentist confidence intervals under correct prior assumptions by analysing a set of 100 signals drawn from the prior. We discuss the computational cost of these algorithms, and describe the general and problem-specific sampling techniques we have used to improve the efficiency of sampling the compact binary coalescence (CBC) parameter space.

Empirical evidence about inconsistency among studies in a pair-wise meta-analysis.

PubMed

Rhodes, Kirsty M; Turner, Rebecca M; Higgins, Julian P T

2016-12-01

This paper investigates how inconsistency (as measured by the I 2 statistic) among studies in a meta-analysis may differ, according to the type of outcome data and effect measure. We used hierarchical models to analyse data from 3873 binary, 5132 continuous and 880 mixed outcome meta-analyses within the Cochrane Database of Systematic Reviews. Predictive distributions for inconsistency expected in future meta-analyses were obtained, which can inform priors for between-study variance. Inconsistency estimates were highest on average for binary outcome meta-analyses of risk differences and continuous outcome meta-analyses. For a planned binary outcome meta-analysis in a general research setting, the predictive distribution for inconsistency among log odds ratios had median 22% and 95% CI: 12% to 39%. For a continuous outcome meta-analysis, the predictive distribution for inconsistency among standardized mean differences had median 40% and 95% CI: 15% to 73%. Levels of inconsistency were similar for binary data measured by log odds ratios and log relative risks. Fitted distributions for inconsistency expected in continuous outcome meta-analyses using mean differences were almost identical to those using standardized mean differences. The empirical evidence on inconsistency gives guidance on which outcome measures are most likely to be consistent in particular circumstances and facilitates Bayesian meta-analysis with an informative prior for heterogeneity. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.

WIYN OPEN CLUSTER STUDY. XXXVI. SPECTROSCOPIC BINARY ORBITS IN NGC 188

DOE Office of Scientific and Technical Information (OSTI.GOV)

Geller, Aaron M.; Mathieu, Robert D.; Harris, Hugh C.

2009-04-15

We present 98 spectroscopic binary orbits resulting from our ongoing radial velocity survey of the old (7 Gyr) open cluster NGC 188. All but 13 are high-probability cluster members based on both radial velocity and proper motion membership analyses. Fifteen of these member binaries are double lined. Our stellar sample spans a magnitude range of 10.8 {<=}V{<=} 16.5 (1.14-0.92 M {sub sun}) and extends spatially to 17 pc ({approx}13 core radii). All of our binary orbits have periods ranging from a few days to on the order of 10{sup 3} days, and thus are hard binaries that dynamically power themore » cluster. For each binary, we present the orbital solutions and place constraints on the component masses. Additionally, we discuss a few binaries of note from our sample, identifying a likely blue straggler-blue straggler binary system (7782), a double-lined binary with a secondary star which is underluminous for its mass (5080), two potential eclipsing binaries (4705 and 5762), and two binaries which are likely members of a quadruple system (5015a and 5015b)« less

Candidate Binary Microlensing Events from the MACHO Project

NASA Astrophysics Data System (ADS)

Becker, A. C.; Alcock, C.; Allsman, R. A.; Alves, D. R.; Axelrod, T. S.; Bennett, D. P.; Cook, K. H.; Drake, A. J.; Freeman, K. C.; Griest, K.; King, L. J.; Lehner, M. J.; Marshall, S. L.; Minniti, D.; Peterson, B. A.; Popowski, P.; Pratt, M. R.; Quinn, P. J.; Rodgers, A. W.; Stubbs, C. W.; Sutherland, W.; Tomaney, A.; Vandehei, T.; Welch, D. L.; Baines, D.; Brakel, A.; Crook, B.; Howard, J.; Leach, T.; McDowell, D.; McKeown, S.; Mitchell, J.; Moreland, J.; Pozza, E.; Purcell, P.; Ring, S.; Salmon, A.; Ward, K.; Wyper, G.; Heller, A.; Kaspi, S.; Kovo, O.; Maoz, D.; Retter, A.; Rhie, S. H.; Stetson, P.; Walker, A.; MACHO Collaboration

1998-12-01

We present the lightcurves of 22 gravitational microlensing events from the first six years of the MACHO Project gravitational microlensing survey which are likely examples of lensing by binary systems. These events were selected from a total sample of ~ 300 events which were either detected by the MACHO Alert System or discovered through retrospective analyses of the MACHO database. Many of these events appear to have undergone a caustic or cusp crossing, and 2 of the events are well fit with lensing by binary systems with large mass ratios, indicating secondary companions of approximately planetary mass. The event rate is roughly consistent with predictions based upon our knowledge of the properties of binary stars. The utility of binary lensing in helping to solve the Galactic dark matter problem is demonstrated with analyses of 3 binary microlensing events seen towards the Magellanic Clouds. Source star resolution during caustic crossings in 2 of these events allows us to estimate the location of the lensing systems, assuming each source is a single star and not a short period binary. * MACHO LMC-9 appears to be a binary lensing event with a caustic crossing partially resolved in 2 observations. The resulting lens proper motion appears too small for a single source and LMC disk lens. However, it is considerably less likely to be a single source star and Galactic halo lens. We estimate the a priori probability of a short period binary source with a detectable binary character to be ~ 10 %. If the source is also a binary, then we currently have no constraints on the lens location. * The most recent of these events, MACHO 98-SMC-1, was detected in real-time. Follow-up observations by the MACHO/GMAN, PLANET, MPS, EROS and OGLE microlensing collaborations lead to the robust conclusion that the lens likely resides in the SMC.

Modelling of binary logistic regression for obesity among secondary students in a rural area of Kedah

NASA Astrophysics Data System (ADS)

Kamaruddin, Ainur Amira; Ali, Zalila; Noor, Norlida Mohd.; Baharum, Adam; Ahmad, Wan Muhamad Amir W.

2014-07-01

Logistic regression analysis examines the influence of various factors on a dichotomous outcome by estimating the probability of the event's occurrence. Logistic regression, also called a logit model, is a statistical procedure used to model dichotomous outcomes. In the logit model the log odds of the dichotomous outcome is modeled as a linear combination of the predictor variables. The log odds ratio in logistic regression provides a description of the probabilistic relationship of the variables and the outcome. In conducting logistic regression, selection procedures are used in selecting important predictor variables, diagnostics are used to check that assumptions are valid which include independence of errors, linearity in the logit for continuous variables, absence of multicollinearity, and lack of strongly influential outliers and a test statistic is calculated to determine the aptness of the model. This study used the binary logistic regression model to investigate overweight and obesity among rural secondary school students on the basis of their demographics profile, medical history, diet and lifestyle. The results indicate that overweight and obesity of students are influenced by obesity in family and the interaction between a student's ethnicity and routine meals intake. The odds of a student being overweight and obese are higher for a student having a family history of obesity and for a non-Malay student who frequently takes routine meals as compared to a Malay student.

Association of salivary levels of the bone remodelling regulators sRANKL and OPG with periodontal clinical status.

PubMed

Tobón-Arroyave, Sergio I; Isaza-Guzmán, Diana M; Restrepo-Cadavid, Eliana M; Zapata-Molina, Sandra M; Martínez-Pabón, María C

2012-12-01

To determine the variations in salivary concentrations of sRANKL, osteoprotegerin (OPG) and its ratio, regarding the periodontal status. Ninety-seven chronic periodontitis (CP) subjects and 43 healthy controls were selected. Periodontal status was assessed based on full-mouth clinical periodontal measurements. sRANKL and OPG salivary levels were analysed by ELISA. The association between these analytes and its ratio with CP was analysed individually and adjusted for confounding using a binary logistic regression model. sRANKL and sRANKL/OPG ratio were increased, whereas OPG was decreased in CP compared with healthy controls subjects. Although univariate analysis revealed a positive association of sRANKL salivary levels ≥6 pg/ml, OPG salivary levels ≤131 pg/ml and sRANKL/OPG ratio ≥0.062 with CP, after logistic regression analysis only the latter parameter was strongly and independently associated with disease status. Confounding and interaction effects of ageing and smoking habit on sRANKL and OPG levels could be noted. Although salivary concentrations of sRANKL, OPG and its ratio may act as indicators of the amount/extent of periodontal breakdown, the mutual confounding and synergistic biological interactive effects related to ageing and smoking habit of the susceptible host may also promote the tissue destruction in CP. © 2012 John Wiley & Sons A/S.

[Factors determining patient satisfaction with the pre-anaesthesia consultation].

PubMed

Echevarria, M; Ramos, P; Caba, F; López, J; Almeida, C; Cortes Gonzalez, C

2015-01-01

To analyse patient satisfaction with care provided in the pre-anaesthetic consultation and its determining factors. An anonymous questionnaire was randomly distributed to patients attending a pre-anaesthesia clinic, which included 4 questions with 5 possible answers on a (very dissatisfied, dissatisfied, fairly satisfied, satisfied and very satisfied) categorical graduated scale related to punctuality, understanding of the information received, respectful treatment, and overall satisfaction. The fifth question was about the knowledge or the name of the anaesthesiologist who attended them. A binary logistic regression model was used, which identified the predictors of satisfaction, calculated the odds ratios, and their respective 95% confidence intervals. A total of 4006 questionnaires were analysed, in which 99.2% (3966) of users rated as satisfied/very satisfied the question about the respectful treatment, 98.4% (3937) of the information received and understanding, 77.4% (3096) punctuality in attending, and 97, 6% (3909) overall satisfaction. Almost three-quarters (71%, 2844) did not know the name of the anaesthesiologist. Regression analysis associated the more satisfied with their treatment (OR 17.44; P<.0005) and the information received (OR 14.94, P<.0005), while punctuality (OR 5 40; P<.0005) was the factor that contributed less to the result. In our population satisfaction in pre-anaesthesia consultation is due mainly to the communication skills of the anaesthesiologist. Copyright © 2014 SECA. Published by Elsevier Espana. All rights reserved.

Family Medicine or Primary Care Residency Selection: Effects of Family Medicine Interest Groups, MD/MPH Dual Degrees, and Rural Medical Education.

PubMed

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.

A study of the kinetics and isotherms for Cr(VI) adsorption in a binary mixture of Cr(VI)-Ni(II) using hierarchical porous carbon obtained from pig bone.

PubMed

Li, Chengxian; Huang, Zhe; Huang, Bicheng; Liu, Changfeng; Li, Chengming; Huang, Yaqin

2014-01-01

Cr(VI) adsorption in a binary mixture Cr(VI)-Ni(II) using the hierarchical porous carbon prepared from pig bone (HPC) was investigated. The various factors affecting adsorption of Cr(VI) ions from aqueous solutions such as initial concentration, pH, temperature and contact time were analyzed. The results showed excellent efficiency of Cr(VI) adsorption by HPC. The kinetics and isotherms for Cr(VI) adsorption from a binary mixture Cr(VI)-Ni(II) by HPC were studied. The adsorption equilibrium described by the Langmuir isotherm model is better than that described by the Freundlich isotherm model for the binary mixture in this study. The maximum adsorption capacity was reliably found to be as high as 192.68 mg/g in the binary mixture at pH 2. On fitting the experimental data to both pseudo-first- and second-order equations, the regression analysis of the second-order equation gave a better R² value.

Binary Decision Trees for Preoperative Periapical Cyst Screening Using Cone-beam Computed Tomography.

PubMed

Pitcher, Brandon; Alaqla, Ali; Noujeim, Marcel; Wealleans, James A; Kotsakis, Georgios; Chrepa, Vanessa

2017-03-01

Cone-beam computed tomographic (CBCT) analysis allows for 3-dimensional assessment of periradicular lesions and may facilitate preoperative periapical cyst screening. The purpose of this study was to develop and assess the predictive validity of a cyst screening method based on CBCT volumetric analysis alone or combined with designated radiologic criteria. Three independent examiners evaluated 118 presurgical CBCT scans from cases that underwent apicoectomies and had an accompanying gold standard histopathological diagnosis of either a cyst or granuloma. Lesion volume, density, and specific radiologic characteristics were assessed using specialized software. Logistic regression models with histopathological diagnosis as the dependent variable were constructed for cyst prediction, and receiver operating characteristic curves were used to assess the predictive validity of the models. A conditional inference binary decision tree based on a recursive partitioning algorithm was constructed to facilitate preoperative screening. Interobserver agreement was excellent for volume and density, but it varied from poor to good for the radiologic criteria. Volume and root displacement were strong predictors for cyst screening in all analyses. The binary decision tree classifier determined that if the volume of the lesion was >247 mm 3 , there was 80% probability of a cyst. If volume was <247 mm 3 and root displacement was present, cyst probability was 60% (78% accuracy). The good accuracy and high specificity of the decision tree classifier renders it a useful preoperative cyst screening tool that can aid in clinical decision making but not a substitute for definitive histopathological diagnosis after biopsy. Confirmatory studies are required to validate the present findings. Published by Elsevier Inc.

Risk factors for acute surgical site infections after lumbar surgery: a retrospective study.

PubMed

Lai, Qi; Song, Quanwei; Guo, Runsheng; Bi, Haidi; Liu, Xuqiang; Yu, Xiaolong; Zhu, Jianghao; Dai, Min; Zhang, Bin

2017-07-19

Currently, many scholars are concerned about the treatment of postoperative infection; however, few have completed multivariate analyses to determine factors that contribute to the risk of infection. Therefore, we conducted a multivariate analysis of a retrospectively collected database to analyze the risk factors for acute surgical site infection following lumbar surgery, including fracture fixation, lumbar fusion, and minimally invasive lumbar surgery. We retrospectively reviewed data from patients who underwent lumbar surgery between 2014 and 2016, including lumbar fusion, internal fracture fixation, and minimally invasive surgery in our hospital's spinal surgery unit. Patient demographics, procedures, and wound infection rates were analyzed using descriptive statistics, and risk factors were analyzed using logistic regression analyses. Twenty-six patients (2.81%) experienced acute surgical site infection following lumbar surgery in our study. The patients' mean body mass index, smoking history, operative time, blood loss, draining time, and drainage volume in the acute surgical site infection group were significantly different from those in the non-acute surgical site infection group (p < 0.05). Additionally, diabetes mellitus, chronic obstructive pulmonary disease, osteoporosis, preoperative antibiotics, type of disease, and operative type in the acute surgical site infection group were significantly different than those in the non-acute surgical site infection group (p < 0.05). Using binary logistic regression analyses, body mass index, smoking, diabetes mellitus, osteoporosis, preoperative antibiotics, fracture, operative type, operative time, blood loss, and drainage time were independent predictors of acute surgical site infection following lumbar surgery. In order to reduce the risk of infection following lumbar surgery, patients should be evaluated for the risk factors noted above.

Socio-Economic, Demographic and Lifestyle Determinants of Overweight and Obesity among Adults of Northeast India.

PubMed

Rengma, Melody Seb; Sen, Jaydip; Mondal, Nitish

2015-07-01

Overweight and obesity are the accumulation of high body adiposity, which can have detrimental health effects and contribute to the development of numerous preventable non-communicable diseases. This study aims to evaluate the effect of socio-economic, demographic and lifestyle factors on the prevalence of overweight and obesity among adults belonging to the Rengma-Naga population of North-east India. This cross-sectional study was conducted among 826 Rengma-Naga individuals (males: 422; females: 404) aged 20-49 years from the Karbi Anglong District of Assam, using a two-stage stratified random sampling. The socio-economic, demographic and lifestyle variables were recorded using structured schedules. Height and weight were recorded and the Body Mass Index (BMI) was calculated using standard procedures and equation. The WHO (2000) cut-off points were utilized to assess the prevalence of overweight (BMI ≥23.00-24.99 kg/m(2)) and obesity (BMI ≥25.00 kg/m(2)). The data were analysed using ANOVA, chi-square analysis and binary logistic regression analysis using SPSS (version 17.0). The prevalence of overweight and obesity were 32.57% (males: 39.34%; females: 25.50%) and 10.77% (males: 9.95%; females: 11.63%), respectively. The binary logistic regression analysis showed that age groups (e.g., 40-49 years), education (≥9(th) standard), part-time occupation and monthly income (≥Rs.10000) were significantly associated with overweight and obesity (p<0.05). Age, education occupation and income appear to have higher associations with overweight and obesity among adults. Suitable healthcare strategies and intervention programmes are needed for combating such prevalence in population.

Determinants of preventive oral health behaviour among senior dental students in Nigeria

PubMed Central

2013-01-01

Background To study the association between oral health behaviour of senior dental students in Nigeria and their gender, age, knowledge of preventive care, and attitudes towards preventive dentistry. Methods Questionnaires were administered to 179 senior dental students in the six dental schools in Nigeria. The questionnaire obtained information on age, gender, oral self-care, knowledge of preventive dental care and attitudes towards preventive dentistry. Attending a dental clinic for check-up by a dentist or a classmate within the last year was defined as preventive care use. Students who performed oral self-care and attended dental clinic for check-ups were noted to have complied with recommended oral self-care. Chi-square test and binary logistic regression models were used for statistical analyses. Results More male respondents agreed that the use of fluoride toothpaste was more important than the tooth brushing technique for caries prevention (P < 0.001). While the use of dental floss was very low (7.3%), more females were more likely to report using dental floss (p=0.03). Older students were also more likely to comply with recommended oral self-care (p<0.001). In binary regression models, respondents who were younger (p=0.04) and those with higher knowledge of preventive dental care (p=0.008) were more likely to consume sugary snacks less than once a day. Conclusion Gender differences in the awareness of the superiority of using fluoridated toothpaste over brushing in caries prevention; and in the use of dental floss were observed. While older students were more likely to comply with recommended oral self-care measures, younger students with good knowledge of preventive dental care were more likely to consume sugary snacks less than once a day. PMID:23777298

Determinants of preventive oral health behaviour among senior dental students in Nigeria.

PubMed

Folayan, Morenike O; Khami, Mohammad R; Folaranmi, Nkiru; Popoola, Bamidele O; Sofola, Oyinkan O; Ligali, Taofeek O; Esan, Ayodeji O; Orenuga, Omolola O

2013-06-18

To study the association between oral health behaviour of senior dental students in Nigeria and their gender, age, knowledge of preventive care, and attitudes towards preventive dentistry. Questionnaires were administered to 179 senior dental students in the six dental schools in Nigeria. The questionnaire obtained information on age, gender, oral self-care, knowledge of preventive dental care and attitudes towards preventive dentistry. Attending a dental clinic for check-up by a dentist or a classmate within the last year was defined as preventive care use. Students who performed oral self-care and attended dental clinic for check-ups were noted to have complied with recommended oral self-care. Chi-square test and binary logistic regression models were used for statistical analyses. More male respondents agreed that the use of fluoride toothpaste was more important than the tooth brushing technique for caries prevention (P < 0.001). While the use of dental floss was very low (7.3%), more females were more likely to report using dental floss (p=0.03). Older students were also more likely to comply with recommended oral self-care (p<0.001). In binary regression models, respondents who were younger (p=0.04) and those with higher knowledge of preventive dental care (p=0.008) were more likely to consume sugary snacks less than once a day. Gender differences in the awareness of the superiority of using fluoridated toothpaste over brushing in caries prevention; and in the use of dental floss were observed. While older students were more likely to comply with recommended oral self-care measures, younger students with good knowledge of preventive dental care were more likely to consume sugary snacks less than once a day.

Association of Ghrelin Gene Polymorphisms and Serum Ghrelin Levels with the Risk of Hepatitis B Virus-Related Liver Diseases in a Chinese Population.

PubMed

Zhang, Xiaolian; Zhai, Limin; Rong, Chengzhi; Qin, Xue; Li, Shan

2015-01-01

The functions of ghrelin (GHRL) include anti-inflammatory effects, reduction of the fibrogenic response, protection of liver tissue, and regulation of cell proliferation. Genetic variations in the GHRL gene may play an important role in the development of chronic hepatitis B (CHB), liver cirrhosis (LC) and hepatocellular carcinoma (HCC). Therefore, we investigated whether GHRL gene polymorphisms and its serum levels are associated with hepatitis B virus (HBV)-related diseases risk in a Chinese population. 176 patients with CHB, 106 patients with HBV-related LC, 151 patients with HBV-related HCC, and 167 healthy controls were recruited in the study. Genotyping of GHRL rs26311, rs27647, rs696217, and rs34911341 polymorphisms were determined with the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and DNA sequencing. The serum GHRL concentrations were determined using enzyme-linked immunosorbent assay (ELISA). Binary logistic regression analyses adjusting for gender and age revealed that a significant increased risk of LC was found in the GHRL rs26311 GC genotype and combined GC+CC genotypes when compared with the GG genotype (GC vs. GG: OR = 1.671, 95% CI = 1.013-2.757, P = 0.044; GC+CC vs. GG: OR = 1.674, 95% CI = 1.040-2.696, P = 0.034). In subgroup analysis by gender, binary logistic regression analyses adjusting for age showed that the GHRL rs26311 C allele and combined GC+CC genotypes were associated with a significantly increased risk to LC in males (C vs. G OR = 1.416, 95% CI = 1.017-1.972, P = 0.040; GC+CC vs. GG: OR = 1.729, 95% CI = 1.019-2.933, P = 0.042). In addition, we found significant decreased serum GHRL levels in LC patients compared with the healthy controls. However, there was no significant association of the GHRL rs26311 polymorphism with serum GHRL levels in LC patients. These observations suggest that the GHRL rs26311 polymorphism is associated with an increased risk to HBV-related LC, especially in men. We also found an inverse association of serum GHRL levels with LC.

Associations Between Night Work and Anxiety, Depression, Insomnia, Sleepiness and Fatigue in a Sample of Norwegian Nurses

PubMed Central

Øyane, Nicolas M. F.; Pallesen, Ståle; Moen, Bente Elisabeth; Åkerstedt, Torbjörn; Bjorvatn, Bjørn

2013-01-01

Background Night work has been reported to be associated with various mental disorders and complaints. We investigated relationships between night work and anxiety, depression, insomnia, sleepiness and fatigue among Norwegian nurses. Methods The study design was cross-sectional, based on validated self-assessment questionnaires. A total of 5400 nurses were invited to participate in a health survey through the Norwegian Nurses' Organization, whereof 2059 agreed to participate (response rate 38.1%). Nurses completed a questionnaire containing items on demographic variables (gender, age, years of experience as a nurse, marital status and children living at home), work schedule, anxiety/depression (Hospital Anxiety and Depression Scale), insomnia (Bergen Insomnia Scale), sleepiness (Epworth Sleepiness Scale) and fatigue (Fatigue Questionnaire). They were also asked to report number of night shifts in the last 12 months (NNL). First, the parameters were compared between nurses i) never working nights, ii) currently working nights, and iii) previously working nights, using binary logistic regression analyses. Subsequently, a cumulative approach was used investigating associations between NNL with the continuous scores on the same dependent variables in hierarchical multiple regression analyses. Results Nurses with current night work were more often categorized with insomnia (OR = 1.48, 95% CI = 1.10–1.99) and chronic fatigue (OR = 1.78, 95% CI = 1.02–3.11) than nurses with no night work experience. Previous night work experience was also associated with insomnia (OR = 1.45, 95% CI = 1.04–2.02). NNL was not associated with any parameters in the regression analyses. Conclusion Nurses with current or previous night work reported more insomnia than nurses without any night work experience, and current night work was also associated with chronic fatigue. Anxiety, depression and sleepiness were not associated with night work, and no cumulative effect of night shifts during the last 12 months was found on any parameters. PMID:23950914

The intermediate endpoint effect in logistic and probit regression

PubMed Central

MacKinnon, DP; Lockwood, CM; Brown, CH; Wang, W; Hoffman, JM

2010-01-01

Background An intermediate endpoint is hypothesized to be in the middle of the causal sequence relating an independent variable to a dependent variable. The intermediate variable is also called a surrogate or mediating variable and the corresponding effect is called the mediated, surrogate endpoint, or intermediate endpoint effect. Clinical studies are often designed to change an intermediate or surrogate endpoint and through this intermediate change influence the ultimate endpoint. In many intermediate endpoint clinical studies the dependent variable is binary, and logistic or probit regression is used. Purpose The purpose of this study is to describe a limitation of a widely used approach to assessing intermediate endpoint effects and to propose an alternative method, based on products of coefficients, that yields more accurate results. Methods The intermediate endpoint model for a binary outcome is described for a true binary outcome and for a dichotomization of a latent continuous outcome. Plots of true values and a simulation study are used to evaluate the different methods. Results Distorted estimates of the intermediate endpoint effect and incorrect conclusions can result from the application of widely used methods to assess the intermediate endpoint effect. The same problem occurs for the proportion of an effect explained by an intermediate endpoint, which has been suggested as a useful measure for identifying intermediate endpoints. A solution to this problem is given based on the relationship between latent variable modeling and logistic or probit regression. Limitations More complicated intermediate variable models are not addressed in the study, although the methods described in the article can be extended to these more complicated models. Conclusions Researchers are encouraged to use an intermediate endpoint method based on the product of regression coefficients. A common method based on difference in coefficient methods can lead to distorted conclusions regarding the intermediate effect. PMID:17942466

Modelling Status Food Security Households Disease Sufferers Pulmonary Tuberculosis Uses the Method Regression Logistics Binary

NASA Astrophysics Data System (ADS)

Wulandari, S. P.; Salamah, M.; Rositawati, A. F. D.

2018-04-01

Food security is the condition where the food fulfilment is managed well for the country till the individual. Indonesia is one of the country which has the commitment to create the food security becomes main priority. However, the food necessity becomes common thing means that it doesn’t care about nutrient standard and the health condition of family member, so in the fulfilment of food necessity also has to consider the disease suffered by the family member, one of them is pulmonary tuberculosa. From that reasons, this research is conducted to know the factors which influence on household food security status which suffered from pulmonary tuberculosis in the coastal area of Surabaya by using binary logistic regression method. The analysis result by using binary logistic regression shows that the variables wife latest education, house density and spacious house ventilation significantly affect on household food security status which suffered from pulmonary tuberculosis in the coastal area of Surabaya, where the wife education level is University/equivalent, the house density is eligible or 8 m2/person and spacious house ventilation 10% of the floor area has the opportunity to become food secure households amounted to 0.911089. While the chance of becoming food insecure households amounted to 0.088911. The model household food security status which suffered from pulmonary tuberculosis in the coastal area of Surabaya has been conformable, and the overall percentages of those classifications are at 71.8%.

NEUROBEHAVIORAL EVALUATIONS OF BINARY AND TERTIARY MIXTURES OF CHEMICALS: LESSIONS LEARNING.

EPA Science Inventory

The classical approach to the statistical analysis of binary chemical mixtures is to construct full dose-response curves for one compound in the presence of a range of doses of the second compound (isobolographic analyses). For interaction studies using more than two chemicals, ...

Long-term magnetic activity in close binary systems. I. Patterns of color variations

NASA Astrophysics Data System (ADS)

Messina, S.

2008-03-01

Aims:This is the first of a series of papers in which we present the results of a long-term photometric monitoring project carried out at Catania Astrophysical Observatory aimed at studying magnetic activity in late-type components of close binary systems, its dependence on global stellar parameters, and its evolution on different time scales from days to years. In this first paper, we present the complete observation dataset and new results of an investigation into the origin of brightness and color variations observed in the well-known magnetically active close binary stars: AR Psc, VY Ari, UX Ari, V711 Tau, EI Eri, V1149 Ori, DH Leo, HU Vir, RS CVn, V775 Her, AR Lac, SZ Psc, II Peg and BY Dra Methods: About 38 000 high-precision photoelectric nightly observations in the U, B and V filters are analysed. Correlation and regression analyses of the V magnitude vs. U-B and B-V color variations are carried out and a comparison with model variations for a grid of active region temperature and filling factor values is also performed. Results: We find the existence of two different patterns of color variation. Eight stars in our sample: BY Dra, VY Ari, V775 Her, II Peg, V1149 Ori, HU Vir, EI Eri and DH Leo become redder when they become fainter, as is expected from the presence of active regions consisting of cool spots. The other six stars show the opposite behaviour, i.e. they become bluer when they become fainter. For V711 Tau this behaviour could be explained by the increased relative U- and B-flux contribution by the earlier-type component of the binary system when the cooler component becomes fainter. On the other hand, for AR Psc, UX Ari, RS CVn, SZ Psc and AR Lac the existence of hot photospheric faculae must be invoked. We also found that in single-lined and double-lined binary stars in which the fainter component is inactive or much less active the V magnitude is correlated to B-V and U-B color variations in more than 60% of observation seasons. The correlation is found in less than 40% of observation seasons when the fainter component has a non-negligible level of activity and/or hot faculae are present but they are either spatially or temporally uncorrelated to spots. I dedicate this paper to the memory of the P.I. of this project, Prof. Marcello Rodonò, who suddenly passed away on October 23, 2005. To him my sincere estimation and deepest gratitude. Based on observations collected at INAF-Catania Astrophysical Observatory, Italy.

Completing the Remedial Sequence and College-Level Credit-Bearing Math: Comparing Binary, Cumulative, and Continuation Ratio Logistic Regression Models

ERIC Educational Resources Information Center

Davidson, J. Cody

2016-01-01

Mathematics is the most common subject area of remedial need and the majority of remedial math students never pass a college-level credit-bearing math class. The majorities of studies that investigate this phenomenon are conducted at community colleges and use some type of regression model; however, none have used a continuation ratio model. The…

Vitamin D is associated with testosterone and hypogonadism in Chinese men: Results from a cross-sectional SPECT-China study.

PubMed

Wang, Ningjian; Han, Bing; Li, Qin; Chen, Yi; Chen, Yingchao; Xia, Fangzhen; Lin, Dongping; Jensen, Michael D; Lu, Yingli

2015-07-16

To date, no study has explored the association between androgen levels and 25-hydroxyvitamin D (25(OH)D) levels in Chinese men. We aimed to investigate the relationship between 25(OH)D levels and total and free testosterone (T), sex hormone binding globulin (SHBG), estradiol, and hypogonadism in Chinese men. Our data, which were based on the population, were collected from 16 sites in East China. There were 2,854 men enrolled in the study, with a mean (SD) age of 53.0 (13.5) years. Hypogonadism was defined as total T <11.3 nmol/L or free T <22.56 pmol/L. The 25(OH)D, follicle-stimulating hormone, luteinizing hormone, total T, estradiol and SHBG were measured using chemiluminescence and free T by enzyme-linked immune-sorbent assay. The associations between 25(OH)D and reproductive hormones and hypogonadism were analyzed using linear regression and binary logistic regression analyses, respectively. A total of 713 (25.0 %) men had hypogonadism with significantly lower 25(OH)D levels but greater BMI and HOMA-IR. Using linear regression, after fully adjusting for age, residence area, economic status, smoking, BMI, HOMA-IR, diabetes and systolic pressure, 25(OH)D was associated with total T and estradiol (P < 0.05). In the logistic regression analyses, increased quartiles of 25(OH)D were associated with significantly decreased odds ratios of hypogonadism (P for trend <0.01). This association, which was considerably attenuated by BMI and HOMA-IR, persisted in the fully adjusted model (P for trend <0.01) in which for the lowest compared with the highest quartile of 25(OH)D, the odds ratio of hypogonadism was 1.50 (95 % CI, 1.14, 1.97). A lower vitamin D level was associated with a higher prevalence of hypogonadism in Chinese men. This association might, in part, be explained by adiposity and insulin resistance and warrants additional investigation.

Association between narcotic use and anabolic-androgenic steroid use among American adolescents.

PubMed

Denham, Bryan E

2009-01-01

Drawing on the data gathered in the 2006 Monitoring the Future study of American youth, the present research examines associations between use of narcotics and use of anabolic-androgenic steroids (AASs) among high-school seniors (n = 2,489). With independent measures and controls including sex, race, media exposure, socializing with friends, participation in recreational and school-sponsored sports, perceptions of drug use among professional athletes, and perceptions of steroid use among close friends, binary logistic regression analyses revealed significant associations between AAS use and the use of alcohol, crack cocaine, Vicodin, gamma-hydroxybutyrate (GHB), Ketamine, and Rohypnol. While use of both AASs and the narcotic drugs generally did not eclipse 5% of the sample, the numbers extend to many thousands in larger populations. Implications for health practitioners and recommendations for future research are offered. The study's limitations are noted.

Multicategory reclassification statistics for assessing improvements in diagnostic accuracy

PubMed Central

Li, Jialiang; Jiang, Binyan; Fine, Jason P.

2013-01-01

In this paper, we extend the definitions of the net reclassification improvement (NRI) and the integrated discrimination improvement (IDI) in the context of multicategory classification. Both measures were proposed in Pencina and others (2008. Evaluating the added predictive ability of a new marker: from area under the receiver operating characteristic (ROC) curve to reclassification and beyond. Statistics in Medicine 27, 157–172) as numeric characterizations of accuracy improvement for binary diagnostic tests and were shown to have certain advantage over analyses based on ROC curves or other regression approaches. Estimation and inference procedures for the multiclass NRI and IDI are provided in this paper along with necessary asymptotic distributional results. Simulations are conducted to study the finite-sample properties of the proposed estimators. Two medical examples are considered to illustrate our methodology. PMID:23197381

Functional limitations as potential mediators of the effects of self-reported vision status on fall risk of older adults.

PubMed

Steinman, Bernard A; Allen, Susan M; Chen, Jie; Pynoos, Jon

2015-02-01

To test whether limitations in mobility and large-muscle functioning mediate self-reported vision status to increase fall risk among respondents age 65 and above. This study used two waves from the Health and Retirement Study. We conducted binary logistic and negative binomial regression analyses to test indirect paths leading from self-reported vision status to falls, via indices of mobility and large-muscle functioning. Limited evidence was found for a mediating effect among women; however, large-muscle groups were implicated as partially mediating risk factors for falls among men with fair self-reported vision status. Implications of these findings are discussed including the need for prioritizing improved muscle strength of older men and women with poor vision as a preventive measure against falls. © The Author(s) 2014.

Independent Life Skills among psychosocial care network users of Rio Grande do Sul, Brazil.

PubMed

Rodrigues, Cândida Garcia Sinott Silveira; Jardim, Vanda Maria da Rosa; Kantorski, Luciane Prado; Coimbra, Valeria Cristina Christello; Treichel, Carlos Alberto Dos Santos; Francchini, Beatriz; Bretanha, Andreia Ferreira; Neutzling, Aline Dos Santos

2016-08-01

This is a cross-sectional study that aims to identify the prevalence of lower independent living skills and their associations in 390 users of psychiatric community-based services in the state Rio Grande do Sul, Brazil. For tracing the outcome it was used the "scale Independent Living Skills Survey", adopting a cut-off value lower than 2. The crude and adjusted analyses were conducted on binary logistic regressions and they considered a hierarchical model developed through a systematic literature review. In adjusted analysis the level of the same variables were adjusted to each other and to previous levels. The statistical significance remained as a < 0.05 p-value. The prevalence of smaller independent living skills was 33% and their associations were: younger age; no partner; lower education; resident at SRT; diagnosis of schizophrenia and younger diagnosis.

Locally Weighted Score Estimation for Quantile Classification in Binary Regression Models

PubMed Central

Rice, John D.; Taylor, Jeremy M. G.

2016-01-01

One common use of binary response regression methods is classification based on an arbitrary probability threshold dictated by the particular application. Since this is given to us a priori, it is sensible to incorporate the threshold into our estimation procedure. Specifically, for the linear logistic model, we solve a set of locally weighted score equations, using a kernel-like weight function centered at the threshold. The bandwidth for the weight function is selected by cross validation of a novel hybrid loss function that combines classification error and a continuous measure of divergence between observed and fitted values; other possible cross-validation functions based on more common binary classification metrics are also examined. This work has much in common with robust estimation, but diers from previous approaches in this area in its focus on prediction, specifically classification into high- and low-risk groups. Simulation results are given showing the reduction in error rates that can be obtained with this method when compared with maximum likelihood estimation, especially under certain forms of model misspecification. Analysis of a melanoma data set is presented to illustrate the use of the method in practice. PMID:28018492

Multivariate Models for Normal and Binary Responses in Intervention Studies

ERIC Educational Resources Information Center

Pituch, Keenan A.; Whittaker, Tiffany A.; Chang, Wanchen

2016-01-01

Use of multivariate analysis (e.g., multivariate analysis of variance) is common when normally distributed outcomes are collected in intervention research. However, when mixed responses--a set of normal and binary outcomes--are collected, standard multivariate analyses are no longer suitable. While mixed responses are often obtained in…

pKa values of hyodeoxycholic and cholic acids in the binary mixed micelles sodium-hyodeoxycholate-Tween 40 and sodium-cholate-Tween 40: Thermodynamic stability of the micelle and the cooperative hydrogen bond formation with the steroid skeleton.

PubMed

Poša, Mihalj; Pilipović, Ana; Bećarević, Mirjana; Farkaš, Zita

2017-01-01

Due to a relatively small size of bile acid salts, their mixed micelles with nonionic surfactants are analysed. Of the special interests are real binary mixed micelles that are thermodynamically more stable than ideal mixed micelles. Thermodynamic stability is expressed with an excess Gibbs energy (G E ) or over an interaction parameter (β ij ). In this paper sodium salts of cholic (C) and hyodeoxycholic acid (HD) in their mixed micelles with Tween 40 (T40) are analysed by potentiometric titration and their pKa values are determined. Examined bile acids in mixed micelles with T40 have higher pKa values than free bile acids. The increase of ΔpKa acid constant of micellary bound C and HD is in a correlation with absolute values of an interaction parameter. According to an interaction parameter and an excess Gibbs energy, mixed micelle HD-T40 are thermodynamically more stable than mixed micelles C-T40. ΔpKa values are higher for mixed micelles with Tween 40 whose second building unit is HD, related to the building unit C. In both micellar systems, ΔpKa increases with the rise of a molar fraction of Tween 40 in binary mixtures of surfactants with sodium salts of bile acids. This suggests that, ΔpKa can be a measure of a thermodynamic stabilization of analysed binary mixed micelles as well as an interaction parameter. ΔpKa values are confirmed by determination of a distribution coefficient of HD and C in systems: water phase with Tween 40 in a micellar concentration and 1-octanol, with a change of a pH value of a water phase. Conformational analyses suggests that synergistic interactions between building units of analysed binary micelles originates from formation of hydrogen bonds between steroid OH groups and polyoxyethylene groups of the T40. Relative similarity and spatial orientation of C 3 and C 6 OH group allows cooperative formation of hydrogen bonds between T40 and HD - excess entropy in formation of mixed micelle. If a water solution of analysed binary mixtures of surfactants contains urea in concentration of 4M significant decreases of an interaction parameter value happens which confirms the importance of hydrogen bonds in synergistic interactions (urea compete in hydrogen bonds). Copyright © 2016 Elsevier Inc. All rights reserved.

Introduction to the use of regression models in epidemiology.

PubMed

Bender, Ralf

2009-01-01

Regression modeling is one of the most important statistical techniques used in analytical epidemiology. By means of regression models the effect of one or several explanatory variables (e.g., exposures, subject characteristics, risk factors) on a response variable such as mortality or cancer can be investigated. From multiple regression models, adjusted effect estimates can be obtained that take the effect of potential confounders into account. Regression methods can be applied in all epidemiologic study designs so that they represent a universal tool for data analysis in epidemiology. Different kinds of regression models have been developed in dependence on the measurement scale of the response variable and the study design. The most important methods are linear regression for continuous outcomes, logistic regression for binary outcomes, Cox regression for time-to-event data, and Poisson regression for frequencies and rates. This chapter provides a nontechnical introduction to these regression models with illustrating examples from cancer research.

Linear regression analysis and its application to multivariate chromatographic calibration for the quantitative analysis of two-component mixtures.

PubMed

Dinç, Erdal; Ozdemir, Abdil

2005-01-01

Multivariate chromatographic calibration technique was developed for the quantitative analysis of binary mixtures enalapril maleate (EA) and hydrochlorothiazide (HCT) in tablets in the presence of losartan potassium (LST). The mathematical algorithm of multivariate chromatographic calibration technique is based on the use of the linear regression equations constructed using relationship between concentration and peak area at the five-wavelength set. The algorithm of this mathematical calibration model having a simple mathematical content was briefly described. This approach is a powerful mathematical tool for an optimum chromatographic multivariate calibration and elimination of fluctuations coming from instrumental and experimental conditions. This multivariate chromatographic calibration contains reduction of multivariate linear regression functions to univariate data set. The validation of model was carried out by analyzing various synthetic binary mixtures and using the standard addition technique. Developed calibration technique was applied to the analysis of the real pharmaceutical tablets containing EA and HCT. The obtained results were compared with those obtained by classical HPLC method. It was observed that the proposed multivariate chromatographic calibration gives better results than classical HPLC.

Binary Star Fractions from the LAMOST DR4

NASA Astrophysics Data System (ADS)

Tian, Zhi-Jia; Liu, Xiao-Wei; Yuan, Hai-Bo; Chen, Bing-Qiu; Xiang, Mao-Sheng; Huang, Yang; Wang, Chun; Zhang, Hua-Wei; Guo, Jin-Cheng; Ren, Juan-Juan; Huo, Zhi-Ying; Yang, Yong; Zhang, Meng; Bi, Shao-Lan; Yang, Wu-Ming; Liu, Kang; Zhang, Xian-Fei; Li, Tan-Da; Wu, Ya-Qian; Zhang, Jing-Hua

2018-05-01

Stellar systems composed of single, double, triple or higher-order systems are rightfully regarded as the fundamental building blocks of the Milky Way. Binary stars play an important role in formation and evolution of the Galaxy. Through comparing the radial velocity variations from multi-epoch observations, we analyze the binary fraction of dwarf stars observed with LAMOST. Effects of different model assumptions, such as orbital period distributions on the estimate of binary fractions, are investigated. The results based on log-normal distribution of orbital periods reproduce the previous complete analyses better than the power-law distribution. We find that the binary fraction increases with T eff and decreases with [Fe/H]. We first investigate the relation between α-elements and binary fraction in such a large sample as provided by LAMOST. The old stars with high [α/Fe] dominate with a higher binary fraction than young stars with low [α/Fe]. At the same mass, earlier forming stars possess a higher binary fraction than newly forming ones, which may be related with evolution of the Galaxy.

Binary Logistic Regression Analysis for Detecting Differential Item Functioning: Effectiveness of R[superscript 2] and Delta Log Odds Ratio Effect Size Measures

ERIC Educational Resources Information Center

Hidalgo, Mª Dolores; Gómez-Benito, Juana; Zumbo, Bruno D.

2014-01-01

The authors analyze the effectiveness of the R[superscript 2] and delta log odds ratio effect size measures when using logistic regression analysis to detect differential item functioning (DIF) in dichotomous items. A simulation study was carried out, and the Type I error rate and power estimates under conditions in which only statistical testing…

An initial-abstraction, constant-loss model for unit hydrograph modeling for applicable watersheds in Texas

USGS Publications Warehouse

Asquith, William H.; Roussel, Meghan C.

2007-01-01

Estimation of representative hydrographs from design storms, which are known as design hydrographs, provides for cost-effective, riskmitigated design of drainage structures such as bridges, culverts, roadways, and other infrastructure. During 2001?07, the U.S. Geological Survey (USGS), in cooperation with the Texas Department of Transportation, investigated runoff hydrographs, design storms, unit hydrographs,and watershed-loss models to enhance design hydrograph estimation in Texas. Design hydrographs ideally should mimic the general volume, peak, and shape of observed runoff hydrographs. Design hydrographs commonly are estimated in part by unit hydrographs. A unit hydrograph is defined as the runoff hydrograph that results from a unit pulse of excess rainfall uniformly distributed over the watershed at a constant rate for a specific duration. A time-distributed, watershed-loss model is required for modeling by unit hydrographs. This report develops a specific time-distributed, watershed-loss model known as an initial-abstraction, constant-loss model. For this watershed-loss model, a watershed is conceptualized to have the capacity to store or abstract an absolute depth of rainfall at and near the beginning of a storm. Depths of total rainfall less than this initial abstraction do not produce runoff. The watershed also is conceptualized to have the capacity to remove rainfall at a constant rate (loss) after the initial abstraction is satisfied. Additional rainfall inputs after the initial abstraction is satisfied contribute to runoff if the rainfall rate (intensity) is larger than the constant loss. The initial abstraction, constant-loss model thus is a two-parameter model. The initial-abstraction, constant-loss model is investigated through detailed computational and statistical analysis of observed rainfall and runoff data for 92 USGS streamflow-gaging stations (watersheds) in Texas with contributing drainage areas from 0.26 to 166 square miles. The analysis is limited to a previously described, watershed-specific, gamma distribution model of the unit hydrograph. In particular, the initial-abstraction, constant-loss model is tuned to the gamma distribution model of the unit hydrograph. A complex computational analysis of observed rainfall and runoff for the 92 watersheds was done to determine, by storm, optimal values of initial abstraction and constant loss. Optimal parameter values for a given storm were defined as those values that produced a modeled runoff hydrograph with volume equal to the observed runoff hydrograph and also minimized the residual sum of squares of the two hydrographs. Subsequently, the means of the optimal parameters were computed on a watershed-specific basis. These means for each watershed are considered the most representative, are tabulated, and are used in further statistical analyses. Statistical analyses of watershed-specific, initial abstraction and constant loss include documentation of the distribution of each parameter using the generalized lambda distribution. The analyses show that watershed development has substantial influence on initial abstraction and limited influence on constant loss. The means and medians of the 92 watershed-specific parameters are tabulated with respect to watershed development; although they have considerable uncertainty, these parameters can be used for parameter prediction for ungaged watersheds. The statistical analyses of watershed-specific, initial abstraction and constant loss also include development of predictive procedures for estimation of each parameter for ungaged watersheds. Both regression equations and regression trees for estimation of initial abstraction and constant loss are provided. The watershed characteristics included in the regression analyses are (1) main-channel length, (2) a binary factor representing watershed development, (3) a binary factor representing watersheds with an abundance of rocky and thin-soiled terrain, and (4) curve numb

A cross–sectional study on the prevalence and associated risk factors for workplace violence against Chinese nurses

PubMed Central

Shi, Lei; Zhang, Danyang; Zhou, Chenyu; Yang, Libin; Sun, Tao; Hao, Tianjun; Peng, Xiangwen; Gao, Lei; Liu, Wenhui; Mu, Yi; Han, Yuzhen; Fan, Lihua

2017-01-01

Objectives The purpose of the present study was to explore the characteristics of workplace violence that Chinese nurses at tertiary and county–level hospitals encountered in the 12 months from December 2014 to January 2016, to identify and analyse risk factors for workplace violence, and to establish the basis for future preventive strategies. Design A cross–sectional study. Setting A total of 44 tertiary hospitals and 90 county–level hospitals in 16 provinces (municipalities or autonomous regions) in China. Methods We used stratified random sampling to collect data from December 2014 to January 2016. We distributed 21 360 questionnaires, and 15 970 participants provided valid data (effective response rate=74.77%). We conducted binary logistic regression analyses on the risk factors for workplace violence among the nurses in our sample and analysed the reasons for aggression. Results The prevalence of workplace violence was 65.8%; of this, 64.9% was verbal violence, and physical violence and sexual harassment accounted for 11.8% and 3.9%, respectively. Frequent workplace violence occurred primarily in emergency and paediatric departments. Respondents reported that patients’ relatives were the main perpetrators in tertiary and county–level hospitals. Logistic regression analysis showed that respondents’ age, department, years of experience and direct contact with patients were common risk factors at different levels of hospitals. Conclusions Workplace violence is frequent in China’s tertiary and county–level hospitals; its occurrence is especially frequent in the emergency and paediatric departments. It is necessary to cope with workplace violence by developing effective control strategies at individual, hospital and national levels. PMID:28647719

A cross-sectional study on the prevalence and associated risk factors for workplace violence against Chinese nurses.

PubMed

Shi, Lei; Zhang, Danyang; Zhou, Chenyu; Yang, Libin; Sun, Tao; Hao, Tianjun; Peng, Xiangwen; Gao, Lei; Liu, Wenhui; Mu, Yi; Han, Yuzhen; Fan, Lihua

2017-06-24

The purpose of the present study was to explore the characteristics of workplace violence that Chinese nurses at tertiary and county-level hospitals encountered in the 12 months from December 2014 to January 2016, to identify and analyse risk factors for workplace violence, and to establish the basis for future preventive strategies. A cross-sectional study. A total of 44 tertiary hospitals and 90 county-level hospitals in 16 provinces (municipalities or autonomous regions) in China. We used stratified random sampling to collect data from December 2014 to January 2016. We distributed 21 360 questionnaires, and 15 970 participants provided valid data (effective response rate=74.77%). We conducted binary logistic regression analyses on the risk factors for workplace violence among the nurses in our sample and analysed the reasons for aggression. The prevalence of workplace violence was 65.8%; of this, 64.9% was verbal violence, and physical violence and sexual harassment accounted for 11.8% and 3.9%, respectively. Frequent workplace violence occurred primarily in emergency and paediatric departments. Respondents reported that patients' relatives were the main perpetrators in tertiary and county-level hospitals. Logistic regression analysis showed that respondents' age, department, years of experience and direct contact with patients were common risk factors at different levels of hospitals. Workplace violence is frequent in China's tertiary and county-level hospitals; its occurrence is especially frequent in the emergency and paediatric departments. It is necessary to cope with workplace violence by developing effective control strategies at individual, hospital and national levels. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Domestic Violence, Unwanted Pregnancy and Pregnancy Termination among Urban Women of Bangladesh

PubMed Central

2013-01-01

Objective This paper explores the relationship between domestic violence against women inflicted by husbands, unwanted pregnancy and pregnancy termination of Bangladeshi urban women. Materials and methods The study used the nationally representative 2007 Bangladesh Demographic and Health Survey (BDHS) data. The BDHS covered a representative sample of 10,996 ever married women from rural and urban areas. The BDHS used a separate module to collect information from women regarding domestic violence. The survey gathered information of domestic violence from 1,013 urban women which are the basis of the study. Simple cross tabulation, bivariate and multivariate statistical analyses were performed to analyzing data. Results Overall, the lifetime prevalence of domestic violence was 47.5%. Of the most recent pregnancies, 15.6% were unwanted and 16.0% of the women terminated pregnancy in their marital life. The multivariate binary logistic regression analyses yielded quantitatively important and reliable estimate of unwanted pregnancy and pregnancy termination. The regression analyses yielded significantly (p < 0.05) increased risk of unwanted pregnancy only for physical violence (OR = 2.35, 95% CI = 1.28-4.32) and for both physical and sexual violence (OR = 2.27, 95% CI = 1.02-5.28), and higher risk of pregnancy termination for only physical violence (OR = 1.41, 95% CI = 0.95-2.10) and for both physical and sexual violence (OR = 1.81, 95% CI = 1.07-3.04) than women who were never abused. Current age, higher parity and early marriage are also important determinants of unwanted pregnancy and pregnancy termination. Conclusion Violence against women inflicted by husbands is commonplace in Bangladesh. Any strategy to reduce the burden of unwanted pregnancy and induced abortion should include prevention of violence against women and strengthening women's sexual and reproductive health. PMID:24971097

Gender aspects of the relationship between migraine and cardiovascular risk factors: A cross-sectional evaluation in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil).

PubMed

Goulart, Alessandra C; Santos, Itamar S; Lotufo, Paulo A; Benseñor, Isabela M

2015-10-01

The relationship between cardiovascular risk factors (CVRF) and migraine is controversial and might be different in both genders. These associations were evaluated in Brazilian middle-aged men and women from the Longitudinal Study of Adult Health (ELSA-Brasil). The cross-sectional relationship between our main outcome, which was migraine headache (definite, probable and overall), and CVRF was evaluated in the total sample and according to gender. We calculated frequencies and odds ratios (95% CI) for this relationship using binary and multinomial logistic regression analyses in crude, age-adjusted and multivariable models adjusted by potential confounders. Of 14,953 individuals who completed the data about headache and CVRF, the frequency of one-year migraine was of 29.5% (22.5% in women and 7.0% in men). In the multivariable-adjusted regression analyses, an inverse association between hypertension (OR, 0.53; 95% CI, 0.36-0.79), metabolic syndrome (OR, 0.65; 95% CI, 0.43-0.99) and definite migraine were confirmed for men, but not for women. In the opposite direction, a positive association between migraine headaches (definite, probable and overall) and dyslipidemia (overall migraine OR, 1.25; 95% CI, 1.13-1.38) was observed only for women, but not for men. A gender influence on the relationship between migraine and CVRF was verified in the ELSA-Brasil. © International Headache Society 2015.

Configuration-specific kinetic theory applied to an ideal binary gas mixture.

PubMed

Wiseman, Floyd L

2006-10-05

This paper is the second in a two-part series dealing with the configuration-specific analyses for molecular collision events of hard, spherical molecules at thermal equilibrium. The first paper analyzed a single-component system, and the reader is referred to it for the fundamental concepts. In this paper, the expressions for the configuration-specific collision frequencies and the average line-of-centers collision angles and speeds are derived for an ideal binary gas mixture. The analyses show that the average line-of-centers quantities are all dependent upon the ratio of the masses of the two components, but not upon molecular size. Of course, the configuration-specific collision frequencies do depend on molecular size. The expression for the overall binary collision frequency is a simple sum of the configuration-specific collision frequencies and is identical to the conventional expression.

Binary logistic regression modelling: Measuring the probability of relapse cases among drug addict

NASA Astrophysics Data System (ADS)

Ismail, Mohd Tahir; Alias, Siti Nor Shadila

2014-07-01

For many years Malaysia faced the drug addiction issues. The most serious case is relapse phenomenon among treated drug addict (drug addict who have under gone the rehabilitation programme at Narcotic Addiction Rehabilitation Centre, PUSPEN). Thus, the main objective of this study is to find the most significant factor that contributes to relapse to happen. The binary logistic regression analysis was employed to model the relationship between independent variables (predictors) and dependent variable. The dependent variable is the status of the drug addict either relapse, (Yes coded as 1) or not, (No coded as 0). Meanwhile the predictors involved are age, age at first taking drug, family history, education level, family crisis, community support and self motivation. The total of the sample is 200 which the data are provided by AADK (National Antidrug Agency). The finding of the study revealed that age and self motivation are statistically significant towards the relapse cases..

Low triiodothyronine: A new facet of inflammation in acute ischemic stroke.

PubMed

Ma, Lili; Zhu, Dongliang; Jiang, Ying; Liu, Yingying; Ma, Xiaomeng; Liu, Mei; Chen, Xiaohong

2016-07-01

Patients with acute ischemic stroke (AIS) frequently experience low free triiodothyronine (fT3) concentrations. Inflammation is recognized as a key contributor to the pathophysiology of stroke. Previous studies, however, did not simultaneously evaluate fT3 and inflammation biomarkers in AIS patients. Markers of inflammation, including serum concentrations of C-reactive protein (CRP) and albumin, and fT3 were assessed retrospectively in 117 patients. Stroke severity was measured on the National Institutes of Health Stroke Scale (NIHSS). Regression analyses were performed to adjust for confounders. Serum fT3 concentrations were significantly lower in moderate AIS patients than those in mild AIS patients (P<0.001). fT3 concentration also positively correlated with serum albumin concentration (r=0.358, P<0.001) and negatively correlated with log10CRP concentration (r=-0.341, P<0.001), NIHSS score (r=-0.384, P<0.001). Multiple regression analysis showed that CRP, albumin concentrations and NIHSS score were independently correlated with fT3 concentration. Binary logistic regression analysis showed that fT3 concentration was an independent factor correlated with NIHSS score, the area under the receiver operating characteristic curve was 0.712 (95% CI, 0.618-0.805). Low fT3 concentrations may be involved in the pathogenic pathway linking inflammation to stroke severity in AIS patients. Copyright © 2016 Elsevier B.V. All rights reserved.

Work related complaints of neck, shoulder and arm among computer office workers: a cross-sectional evaluation of prevalence and risk factors in a developing country.

PubMed

Ranasinghe, Priyanga; Perera, Yashasvi S; Lamabadusuriya, Dilusha A; Kulatunga, Supun; Jayawardana, Naveen; Rajapakse, Senaka; Katulanda, Prasad

2011-08-04

Complaints of arms, neck and shoulders (CANS) is common among computer office workers. We evaluated an aetiological model with physical/psychosocial risk-factors. We invited 2,500 computer office workers for the study. Data on prevalence and risk-factors of CANS were collected by validated Maastricht-Upper-extremity-Questionnaire. Workstations were evaluated by Occupational Safety and Health Administration (OSHA) Visual-Display-Terminal workstation-checklist. Participants' knowledge and awareness was evaluated by a set of expert-validated questions. A binary logistic regression analysis investigated relationships/correlations between risk-factors and symptoms. Sample size was 2,210. Mean age 30.8 ± 8.1 years, 50.8% were males. The 1-year prevalence of CANS was 56.9%, commonest region of complaint was forearm/hand (42.6%), followed by neck (36.7%) and shoulder/arm (32.0%). In those with CANS, 22.7% had taken treatment from a health care professional, only in 1.1% seeking medical advice an occupation-related injury had been suspected/diagnosed. In addition 9.3% reported CANS-related absenteeism from work, while 15.4% reported CANS causing disruption of normal activities. A majority of evaluated workstations in all participants (88.4%,) and in those with CANS (91.9%) had OSHA non-compliant workstations. In the binary logistic regression analyses female gender, daily computer usage, incorrect body posture, bad work-habits, work overload, poor social support and poor ergonomic knowledge were associated with CANS and its' severity In a multiple logistic regression analysis controlling for age, gender and duration of occupation, incorrect body posture, bad work-habits and daily computer usage were significant independent predictors of CANS. The prevalence of work-related CANS among computer office workers in Sri Lanka, a developing, South Asian country is high and comparable to prevalence in developed countries. Work-related physical factors, psychosocial factors and lack of awareness were all important associations of CANS and effective preventive strategies need to address all three areas.

Constraints on the Dynamical Environments of Supermassive Black-Hole Binaries Using Pulsar-Timing Arrays.

PubMed

Taylor, Stephen R; Simon, Joseph; Sampson, Laura

2017-05-05

We introduce a technique for gravitational-wave analysis, where Gaussian process regression is used to emulate the strain spectrum of a stochastic background by training on population-synthesis simulations. This leads to direct Bayesian inference on astrophysical parameters. For pulsar timing arrays specifically, we interpolate over the parameter space of supermassive black-hole binary environments, including three-body stellar scattering, and evolving orbital eccentricity. We illustrate our approach on mock data, and assess the prospects for inference with data similar to the NANOGrav 9-yr data release.

School bullying and traumatic dental injuries in East London adolescents.

PubMed

Agel, M; Marcenes, W; Stansfeld, S A; Bernabé, E

2014-12-01

To explore the association between school bullying and traumatic dental injuries (TDI) among 15-16-year-old school children from East London. Data from phase III of the Research with East London Adolescents Community Health Survey (RELACHS), a school-based prospective study of a representative sample of adolescents, were analysed. Adolescents provided information on demographic characteristics, socioeconomic measures and frequency of bullying in school through self-administered questionnaires and were clinically examined for overjet, lip coverage and TDI. The association between school bullying and TDI was assessed using binary logistic regression models. The prevalence of TDI was 17%, while lifetime and current prevalence of bullying was 32% and 11%, respectively. The prevalence of TDI increased with a growing frequency of bullying; from 16% among adolescents who had never been bullied at school, to 21% among those who were bullied in the past but not this school term, to 22% for those who were bullied this school term. However, this association was not statistically significant either in crude or adjusted regression models. There was no evidence of an association between frequency of school bullying and TDI in this sample of 15-16-year-old adolescents in East London.

Examining the Link Between Public Transit Use and Active Commuting

PubMed Central

Bopp, Melissa; Gayah, Vikash V.; Campbell, Matthew E.

2015-01-01

Background: An established relationship exists between public transportation (PT) use and physical activity. However, there is limited literature that examines the link between PT use and active commuting (AC) behavior. This study examines this link to determine if PT users commute more by active modes. Methods: A volunteer, convenience sample of adults (n = 748) completed an online survey about AC/PT patterns, demographic, psychosocial, community and environmental factors. t-test compared differences between PT riders and non-PT riders. Binary logistic regression analyses examined the effect of multiple factors on AC and a full logistic regression model was conducted to examine AC. Results: Non-PT riders (n = 596) reported less AC than PT riders. There were several significant relationships with AC for demographic, interpersonal, worksite, community and environmental factors when considering PT use. The logistic multivariate analysis for included age, number of children and perceived distance to work as negative predictors and PT use, feelings of bad weather and lack of on-street bike lanes as a barrier to AC, perceived behavioral control and spouse AC were positive predictors. Conclusions: This study revealed the complex relationship between AC and PT use. Further research should investigate how AC and public transit use are related. PMID:25898405

Utilization of maternal health care services among indigenous women in Bangladesh: A study on the Mru tribe.

PubMed

Islam, Rakibul M

2017-01-01

Despite startling developments in maternal health care services, use of these services has been disproportionately distributed among different minority groups in Bangladesh. This study aimed to explore the factors associated with the use of these services among the Mru indigenous women in Bangladesh. A total of 374 currently married Mru women were interviewed using convenience sampling from three administrative sub-districts of the Bandarban district from June to August of 2009. Associations were assessed using Chi-square tests, and a binary logistic regression model was employed to explore factors associated with the use of maternal health care services. Among the women surveyed, 30% had ever visited maternal health care services in the Mru community, a very low proportion compared with mainstream society. Multivariable logistic regression analyses revealed that place of residence, religion, school attendance, place of service provided, distance to the service center, and exposure to mass media were factors significantly associated with the use of maternal health care services among Mru women. Considering indigenous socio-cultural beliefs and practices, comprehensive community-based outreach health programs are recommended in the community with a special emphasis on awareness through maternal health education and training packages for the Mru adolescents.

Examining the link between public transit use and active commuting.

PubMed

Bopp, Melissa; Gayah, Vikash V; Campbell, Matthew E

2015-04-17

An established relationship exists between public transportation (PT) use and physical activity. However, there is limited literature that examines the link between PT use and active commuting (AC) behavior. This study examines this link to determine if PT users commute more by active modes. A volunteer, convenience sample of adults (n = 748) completed an online survey about AC/PT patterns, demographic, psychosocial, community and environmental factors. t-test compared differences between PT riders and non-PT riders. Binary logistic regression analyses examined the effect of multiple factors on AC and a full logistic regression model was conducted to examine AC. Non-PT riders (n = 596) reported less AC than PT riders. There were several significant relationships with AC for demographic, interpersonal, worksite, community and environmental factors when considering PT use. The logistic multivariate analysis for included age, number of children and perceived distance to work as negative predictors and PT use, feelings of bad weather and lack of on-street bike lanes as a barrier to AC, perceived behavioral control and spouse AC were positive predictors. This study revealed the complex relationship between AC and PT use. Further research should investigate how AC and public transit use are related.

Cognitive function and competitive employment in schizophrenia: relative contribution of insight and psychopathology.

PubMed

Giugiario, Michela; Crivelli, Barbara; Mingrone, Cinzia; Montemagni, Cristiana; Scalese, Mara; Sigaudo, Monica; Rocca, Giuseppe; Rocca, Paola

2012-04-01

This study investigated the relationships among insight, psychopathology, cognitive function, and competitive employment in order to determine whether insight and/or psychopathology carried the influence of cognitive function to competitive employment. We recruited 253 outpatients with stable schizophrenia and we further divided our sample into two groups of patients (unemployed and competitive employment subjects). Clinical and neuropsychological assessments were performed. All clinical variables significantly different between the two groups of subjects were subsequently analyzed using a binary logistic regression to assess their independent contribution to competitive employment in the two patients' groups. On the basis of the regression results two mediation analyses were performed. Verbal memory, general psychopathology, and awareness of mental illness were significantly associated with competitive employment in our sample. Both awareness of mental illness and general psychopathology had a role in mediating the verbal memory-competitive employment relationship. Taken together, these findings confirmed the importance of cognitive function in obtaining competitive employment. Our results also highlighted the independent role of general psychopathology and awareness of illness on occupational functioning in schizophrenia. Thus, a greater attention must be given to the systematic investigation of insight and general psychopathology in light of an amelioration of vocational functioning in stable schizophrenia.

Modelling long-term fire occurrence factors in Spain by accounting for local variations with geographically weighted regression

NASA Astrophysics Data System (ADS)

Martínez-Fernández, J.; Chuvieco, E.; Koutsias, N.

2013-02-01

Humans are responsible for most forest fires in Europe, but anthropogenic factors behind these events are still poorly understood. We tried to identify the driving factors of human-caused fire occurrence in Spain by applying two different statistical approaches. Firstly, assuming stationary processes for the whole country, we created models based on multiple linear regression and binary logistic regression to find factors associated with fire density and fire presence, respectively. Secondly, we used geographically weighted regression (GWR) to better understand and explore the local and regional variations of those factors behind human-caused fire occurrence. The number of human-caused fires occurring within a 25-yr period (1983-2007) was computed for each of the 7638 Spanish mainland municipalities, creating a binary variable (fire/no fire) to develop logistic models, and a continuous variable (fire density) to build standard linear regression models. A total of 383 657 fires were registered in the study dataset. The binary logistic model, which estimates the probability of having/not having a fire, successfully classified 76.4% of the total observations, while the ordinary least squares (OLS) regression model explained 53% of the variation of the fire density patterns (adjusted R2 = 0.53). Both approaches confirmed, in addition to forest and climatic variables, the importance of variables related with agrarian activities, land abandonment, rural population exodus and developmental processes as underlying factors of fire occurrence. For the GWR approach, the explanatory power of the GW linear model for fire density using an adaptive bandwidth increased from 53% to 67%, while for the GW logistic model the correctly classified observations improved only slightly, from 76.4% to 78.4%, but significantly according to the corrected Akaike Information Criterion (AICc), from 3451.19 to 3321.19. The results from GWR indicated a significant spatial variation in the local parameter estimates for all the variables and an important reduction of the autocorrelation in the residuals of the GW linear model. Despite the fitting improvement of local models, GW regression, more than an alternative to "global" or traditional regression modelling, seems to be a valuable complement to explore the non-stationary relationships between the response variable and the explanatory variables. The synergy of global and local modelling provides insights into fire management and policy and helps further our understanding of the fire problem over large areas while at the same time recognizing its local character.

A menu-driven software package of Bayesian nonparametric (and parametric) mixed models for regression analysis and density estimation.

PubMed

Karabatsos, George

2017-02-01

Most of applied statistics involves regression analysis of data. In practice, it is important to specify a regression model that has minimal assumptions which are not violated by data, to ensure that statistical inferences from the model are informative and not misleading. This paper presents a stand-alone and menu-driven software package, Bayesian Regression: Nonparametric and Parametric Models, constructed from MATLAB Compiler. Currently, this package gives the user a choice from 83 Bayesian models for data analysis. They include 47 Bayesian nonparametric (BNP) infinite-mixture regression models; 5 BNP infinite-mixture models for density estimation; and 31 normal random effects models (HLMs), including normal linear models. Each of the 78 regression models handles either a continuous, binary, or ordinal dependent variable, and can handle multi-level (grouped) data. All 83 Bayesian models can handle the analysis of weighted observations (e.g., for meta-analysis), and the analysis of left-censored, right-censored, and/or interval-censored data. Each BNP infinite-mixture model has a mixture distribution assigned one of various BNP prior distributions, including priors defined by either the Dirichlet process, Pitman-Yor process (including the normalized stable process), beta (two-parameter) process, normalized inverse-Gaussian process, geometric weights prior, dependent Dirichlet process, or the dependent infinite-probits prior. The software user can mouse-click to select a Bayesian model and perform data analysis via Markov chain Monte Carlo (MCMC) sampling. After the sampling completes, the software automatically opens text output that reports MCMC-based estimates of the model's posterior distribution and model predictive fit to the data. Additional text and/or graphical output can be generated by mouse-clicking other menu options. This includes output of MCMC convergence analyses, and estimates of the model's posterior predictive distribution, for selected functionals and values of covariates. The software is illustrated through the BNP regression analysis of real data.

Evidence for a planetary mass third body orbiting the binary star KIC 5095269

NASA Astrophysics Data System (ADS)

Getley, A. K.; Carter, B.; King, R.; O'Toole, S.

2017-07-01

In this paper, we report the evidence for a planetary mass body orbiting the close binary star KIC 5095269. This detection arose from a search for eclipse timing variations amongst the more than 2000 eclipsing binaries observed by Kepler. Light curve and periodic eclipse time variations have been analysed using systemic and a custom Binary Eclipse Timings code based on the Transit Analysis Package which indicates a 7.70 ± 0.08MJup object orbiting every 237.7 ± 0.1 d around a 1.2 M⊙ primary and a 0.51 M⊙ secondary in an 18.6 d orbit. A dynamical integration over 107 yr suggests a stable orbital configuration. Radial velocity observations are recommended to confirm the properties of the binary star components and the planetary mass of the companion.

Health Implications of Adults' Eating at and Living near Fast Food or Quick Service Restaurants.

PubMed

Jiao, J; Moudon, A V; Kim, S Y; Hurvitz, P M; Drewnowski, A

2015-07-20

This paper examined whether the reported health impacts of frequent eating at a fast food or quick service restaurant on health were related to having such a restaurant near home. Logistic regressions estimated associations between frequent fast food or quick service restaurant use and health status, being overweight or obese, having a cardiovascular disease or diabetes, as binary health outcomes. In all, 2001 participants in the 2008-2009 Seattle Obesity Study survey were included in the analyses. Results showed eating ⩾2 times a week at a fast food or quick service restaurant was associated with perceived poor health status, overweight and obese. However, living close to such restaurants was not related to negative health outcomes. Frequent eating at a fast food or quick service restaurant was associated with perceived poor health status and higher body mass index, but living close to such facilities was not.

Migration Background Influences Consumption Patterns Based on Dietary Recommendations of Food Bank Users in Germany.

PubMed

Stroebele-Benschop, Nanette; Depa, Julia; Gyngell, Fiona; Müller, Annalena; Eleraky, Laila; Hilzendegen, Carolin

2018-03-29

People with low income tend to eat less balanced than people with higher income. This seems to be particularly the case for people with migration background. This cross-sectional study examined the relation of consumption patterns of 597 food bank users with different migration background in Germany. Questionnaires were distributed assessing sociodemographic information and consumption patterns. Analyses were conducted using binary logistic regressions. Models were controlled for age, gender, type of household and education. The group of German food bank users consumed fewer fruits and vegetables and less fish compared to all other groups with migration background (former USSR, Balkan region, Middle East). A significant predictor for fruit and vegetable consumption was migration status. Participants from the former USSR consumed less often SSBs compared to the other groups. Dietary recommendations for low income populations should take into consideration other aspects besides income such as migration status.

Cognitive and Social Functioning Correlates of Employment Among People with Severe Mental Illness.

PubMed

Saavedra, Javier; López, Marcelino; González, Sergio; Arias, Samuel; Crawford, Paul

2016-10-01

We assess how social and cognitive functioning is associated to gaining employment for 213 people diagnosed with severe mental illness taking part in employment programs in Andalusia (Spain). We used the Repeatable Battery for the Assessment of Neuropsychological Status and the Social Functioning Scale and conducted two binary logistical regression analyses. Response variables were: having a job or not, in ordinary companies (OCs) and social enterprises, and working in an OC or not. There were two variables with significant adjusted odds ratios for having a job: "attention" and "Educational level". There were five variables with significant odds ratios for having a job in an OC: "Sex", "Educational level", "Attention", "Communication", and "Independence-competence". The study looks at the possible benefits of combining employment with support and social enterprises in employment programs for these people and underlines how both social and cognitive functioning are central to developing employment models.

Correlates and consequences of parent-teen incongruence in reports of teens' sexual experience.

PubMed

Mollborn, Stefanie; Everett, Bethany

2010-07-01

Using the National Longitudinal Study of Adolescent Health, factors associated with incongruence between parents' and adolescents' reports of teens' sexual experience were investigated, and the consequences of inaccurate parental knowledge for adolescents' subsequent sexual behaviors were explored. Most parents of virgins accurately reported teens' lack of experience, but most parents of teens who had had sex provided inaccurate reports. Binary logistic regression analyses showed that many adolescent-, parent-, and family-level factors predicted the accuracy of parents' reports. Parents' accurate knowledge of their teens' sexual experience was not found to be consistently beneficial for teens' subsequent sexual outcomes. Rather, parents' expectations about teens' sexual experience created a self-fulfilling prophecy, with teens' subsequent sexual outcomes conforming to parents' expectations. These findings suggest that research on parent-teen communication about sex needs to consider the expectations being expressed, as well as the information being exchanged.

Correlates and Consequences of Parent–Teen Incongruence in Reports of Teens’ Sexual Experience

PubMed Central

Mollborn, Stefanie; Everett, Bethany

2011-01-01

Using the National Longitudinal Study of Adolescent Health, factors associated with incongruence between parents’ and adolescents’ reports of teens’ sexual experience were investigated, and the consequences of inaccurate parental knowledge for adolescents’ subsequent sexual behaviors were explored. Most parents of virgins accurately reported teens’ lack of experience, but most parents of teens who had had sex provided inaccurate reports. Binary logistic regression analyses showed that many adolescent-, parent-, and family-level factors predicted the accuracy of parents’ reports. Parents’ accurate knowledge of their teens’ sexual experience was not found to be consistently beneficial for teens’ subsequent sexual outcomes. Rather, parents’ expectations about teens’ sexual experience created a self-fulfilling prophecy, with teens’ subsequent sexual outcomes conforming to parents’ expectations. These findings suggest that research on parent–teen communication about sex needs to consider the expectations being expressed, as well as the information being exchanged. PMID:19431037

RBSURFpred: Modeling protein accessible surface area in real and binary space using regularized and optimized regression.

PubMed

Tarafder, Sumit; Toukir Ahmed, Md; Iqbal, Sumaiya; Tamjidul Hoque, Md; Sohel Rahman, M

2018-03-14

Accessible surface area (ASA) of a protein residue is an effective feature for protein structure prediction, binding region identification, fold recognition problems etc. Improving the prediction of ASA by the application of effective feature variables is a challenging but explorable task to consider, specially in the field of machine learning. Among the existing predictors of ASA, REGAd 3 p is a highly accurate ASA predictor which is based on regularized exact regression with polynomial kernel of degree 3. In this work, we present a new predictor RBSURFpred, which extends REGAd 3 p on several dimensions by incorporating 58 physicochemical, evolutionary and structural properties into 9-tuple peptides via Chou's general PseAAC, which allowed us to obtain higher accuracies in predicting both real-valued and binary ASA. We have compared RBSURFpred for both real and binary space predictions with state-of-the-art predictors, such as REGAd 3 p and SPIDER2. We also have carried out a rigorous analysis of the performance of RBSURFpred in terms of different amino acids and their properties, and also with biologically relevant case-studies. The performance of RBSURFpred establishes itself as a useful tool for the community. Copyright © 2018 Elsevier Ltd. All rights reserved.

Sequence analysis to assess labour market participation following vocational rehabilitation: an observational study among patients sick-listed with low back pain from a randomised clinical trial in Denmark

PubMed Central

Lindholdt, Louise; Labriola, Merete; Nielsen, Claus Vinther; Horsbøl, Trine Allerslev; Lund, Thomas

2017-01-01

Introduction The return-to-work (RTW) process after long-term sickness absence is often complex and long and implies multiple shifts between different labour market states for the absentee. Standard methods for examining RTW research typically rely on the analysis of one outcome measure at a time, which will not capture the many possible states and transitions the absentee can go through. The purpose of this study was to explore the potential added value of sequence analysis in supplement to standard regression analysis of a multidisciplinary RTW intervention among patients with low back pain (LBP). Methods The study population consisted of 160 patients randomly allocated to either a hospital-based brief or a multidisciplinary intervention. Data on labour market participation following intervention were obtained from a national register and analysed in two ways: as a binary outcome expressed as active or passive relief at a 1-year follow-up and as four different categories for labour market participation. Logistic regression and sequence analysis were performed. Results The logistic regression analysis showed no difference in labour market participation for patients in the two groups after 1 year. Applying sequence analysis showed differences in subsequent labour market participation after 2 years after baseline in favour of the brief intervention group versus the multidisciplinary intervention group. Conclusion The study indicated that sequence analysis could provide added analytical value as a supplement to traditional regression analysis in prospective studies of RTW among patients with LBP. PMID:28729315

Baseline adjustments for binary data in repeated cross-sectional cluster randomized trials.

PubMed

Nixon, R M; Thompson, S G

2003-09-15

Analysis of covariance models, which adjust for a baseline covariate, are often used to compare treatment groups in a controlled trial in which individuals are randomized. Such analysis adjusts for any baseline imbalance and usually increases the precision of the treatment effect estimate. We assess the value of such adjustments in the context of a cluster randomized trial with repeated cross-sectional design and a binary outcome. In such a design, a new sample of individuals is taken from the clusters at each measurement occasion, so that baseline adjustment has to be at the cluster level. Logistic regression models are used to analyse the data, with cluster level random effects to allow for different outcome probabilities in each cluster. We compare the estimated treatment effect and its precision in models that incorporate a covariate measuring the cluster level probabilities at baseline and those that do not. In two data sets, taken from a cluster randomized trial in the treatment of menorrhagia, the value of baseline adjustment is only evident when the number of subjects per cluster is large. We assess the generalizability of these findings by undertaking a simulation study, and find that increased precision of the treatment effect requires both large cluster sizes and substantial heterogeneity between clusters at baseline, but baseline imbalance arising by chance in a randomized study can always be effectively adjusted for. Copyright 2003 John Wiley & Sons, Ltd.

Binary dislocation junction formation and strength in hexagonal close-packed crystals

DOE PAGES

Wu, Chi -Chin; Aubry, Sylvie; Arsenlis, Athanasios; ...

2015-12-17

This work examines binary dislocation interactions, junction formation and junction strengths in hexagonal close-packed ( hcp ) crystals. Through a line-tension model and dislocation dynamics (DD) simulations, the interaction and dissociation of different sets of binary junctions are investigated involving one dislocation on the (011¯0) prismatic plane and a second dislocation on one of the following planes: (0001) basal, (11¯00) prismatic, (11¯01) primary pyramidal, or (2¯112) secondary pyramidal. Varying pairs of Burgers vectors are chosen from among the common types the basal type < a > 1/3 < 112¯0 >, prismatic type < c > <0001>, and pyramidal type 1/3 < 112¯3¯ >. For binary interaction due to dislocation intersection, both the analytical results and DD-simulations indicate a relationship between symmetry of interaction maps and the relative magnitude of the Burgers vectors that constitute the junction. Using analytical formulae, a simple regressive model is also developed to represent the junction yield surface. The equation is treated as a degenerated super elliptical equation to quantify the aspect ratio and tilting angle. Lastly, the results provide analytical insights on binary dislocation interactions that may occur in general hcp metals.« less

Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes.

PubMed

Cook, James P; Mahajan, Anubha; Morris, Andrew P

2017-02-01

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population stratification and relatedness through inclusion of random effects for a genetic relationship matrix. However, the utility of linear (mixed) models in the context of meta-analysis of GWAS of binary phenotypes has not been previously explored. In this investigation, we present simulations to compare the performance of linear and logistic regression models under alternative weighting schemes in a fixed-effects meta-analysis framework, considering designs that incorporate variable case-control imbalance, confounding factors and population stratification. Our results demonstrate that linear models can be used for meta-analysis of GWAS of binary phenotypes, without loss of power, even in the presence of extreme case-control imbalance, provided that one of the following schemes is used: (i) effective sample size weighting of Z-scores or (ii) inverse-variance weighting of allelic effect sizes after conversion onto the log-odds scale. Our conclusions thus provide essential recommendations for the development of robust protocols for meta-analysis of binary phenotypes with linear models.

The journey of Typhon-Echidna as a binary system through the planetary region

NASA Astrophysics Data System (ADS)

Araujo, R. A. N.; Galiazzo, M. A.; Winter, O. C.; Sfair, R.

2018-06-01

Among the current population of the 81 known trans-Neptunian binaries (TNBs), only two are in orbits that cross the orbit of Neptune. These are (42355) Typhon-Echidna and (65489) Ceto-Phorcys. In this work, we focused our analyses on the temporal evolution of the Typhon-Echidna binary system through the outer and inner planetary systems. Using numerical integrations of the N-body gravitational problem, we explored the orbital evolutions of 500 clones of Typhon, recording the close encounters of those clones with planets. We then analysed the effects of those encounters on the binary system. It was found that only {≈ }22 per cent of the encounters with the giant planets were strong enough to disrupt the binary. This binary system has an ≈ 3.6 per cent probability of reaching the terrestrial planetary region over a time-scale of approximately 5.4 Myr. Close encounters of Typhon-Echidna with Earth and Venus were also registered, but the probabilities of such events occurring are low ({≈}0.4 per cent). The orbital evolution of the system in the past was also investigated. It was found that in the last 100 Myr, Typhon might have spent most of its time as a TNB crossing the orbit of Neptune. Therefore, our study of the Typhon-Echidna orbital evolution illustrates the possibility of large cometary bodies (radii of 76 km for Typhon and 42 km for Echidna) coming from a remote region of the outer Solar system and that might enter the terrestrial planetary region preserving its binarity throughout the journey.

Clostridium difficile binary toxin CDT

PubMed Central

Gerding, Dale N; Johnson, Stuart; Rupnik, Maja; Aktories, Klaus

2014-01-01

Binary toxin (CDT) is frequently observed in Clostridium difficile strains associated with increased severity of C. difficile infection (CDI). CDT belongs to the family of binary ADP-ribosylating toxins consisting of two separate toxin components: CDTa, the enzymatic ADP-ribosyltransferase which modifies actin, and CDTb which binds to host cells and translocates CDTa into the cytosol. CDTb is activated by serine proteases and binds to lipolysis stimulated lipoprotein receptor. ADP-ribosylation induces depolymerization of the actin cytoskeleton. Toxin-induced actin depolymerization also produces microtubule-based membrane protrusions which form a network on epithelial cells and increase bacterial adherence. Multiple clinical studies indicate an association between binary toxin genes in C. difficile and increased 30-d CDI mortality independent of PCR ribotype. Further studies including measures of binary toxin in stool, analyses of CDI mortality caused by CDT-producing strains, and examination of the relationship of CDT expression to TcdA and TcdB toxin variants and PCR ribotypes are needed. PMID:24253566

Association of Ghrelin Gene Polymorphisms and Serum Ghrelin Levels with the Risk of Hepatitis B Virus-Related Liver Diseases in a Chinese Population

PubMed Central

Rong, Chengzhi; Qin, Xue; Li, Shan

2015-01-01

Background The functions of ghrelin (GHRL) include anti-inflammatory effects, reduction of the fibrogenic response, protection of liver tissue, and regulation of cell proliferation. Genetic variations in the GHRL gene may play an important role in the development of chronic hepatitis B (CHB), liver cirrhosis (LC) and hepatocellular carcinoma (HCC). Therefore, we investigated whether GHRL gene polymorphisms and its serum levels are associated with hepatitis B virus (HBV)-related diseases risk in a Chinese population. Methods 176 patients with CHB, 106 patients with HBV-related LC, 151 patients with HBV-related HCC, and 167 healthy controls were recruited in the study. Genotyping of GHRL rs26311, rs27647, rs696217, and rs34911341 polymorphisms were determined with the polymerase chain reaction–restriction fragment length polymorphism (PCR–RFLP) and DNA sequencing. The serum GHRL concentrations were determined using enzyme-linked immunosorbent assay (ELISA). Results Binary logistic regression analyses adjusting for gender and age revealed that a significant increased risk of LC was found in the GHRL rs26311 GC genotype and combined GC+CC genotypes when compared with the GG genotype (GC vs. GG: OR = 1.671, 95% CI = 1.013–2.757, P = 0.044; GC+CC vs. GG: OR = 1.674, 95% CI = 1.040–2.696, P = 0.034). In subgroup analysis by gender, binary logistic regression analyses adjusting for age showed that the GHRL rs26311 C allele and combined GC+CC genotypes were associated with a significantly increased risk to LC in males (C vs. G OR = 1.416, 95% CI = 1.017–1.972, P = 0.040; GC+CC vs. GG: OR = 1.729, 95% CI = 1.019–2.933, P = 0.042). In addition, we found significant decreased serum GHRL levels in LC patients compared with the healthy controls. However, there was no significant association of the GHRL rs26311 polymorphism with serum GHRL levels in LC patients. Conclusions These observations suggest that the GHRL rs26311 polymorphism is associated with an increased risk to HBV-related LC, especially in men. We also found an inverse association of serum GHRL levels with LC. PMID:26599409

Research Capacity and Dissemination among Academics in Tanzania: Examining Knowledge Production and the Perceived Binary of 'Local' and 'International' Journals

ERIC Educational Resources Information Center

Thomas, Matthew A. M.

2018-01-01

This article explores two distinct strategies suggested by academics in Tanzania for publishing and disseminating their research amidst immense higher education expansion. It draws on Arjun Appadurai's notions of 'strong' and 'weak' internationalisation to analyse the perceived binary between 'international' and 'local' academic journals and their…

Binary and ternary ionic compounds in the outer crust of accreted neutron stars

NASA Astrophysics Data System (ADS)

Chamel, N.

2017-12-01

The outer crust of an accreted neutron star is thought to contain a large distribution of different nuclear species resulting from the burying of ashes of X-ray bursts and superbursts. By analysing the stability of multicomponent Coulomb crystals against phase separation, it is found that various binary and ternary ionic compounds could be formed.

Attitude towards the incorporation of the selective collection of biowaste in a municipal solid waste management system. A case study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernad-Beltrán, D.; Simó, A.; Bovea, M.D., E-mail: bovea@uji.es

Highlights: • Attitude towards incorporating biowaste selective collection is analysed. • Willingness to participate and to pay in biowaste selective collection is obtained. • Socioeconomic aspects affecting WtParticipate and WtPay are identified. - Abstract: European waste legislation has been encouraging for years the incorporation of selective collection systems for the biowaste fraction. European countries are therefore incorporating it into their current municipal solid waste management (MSWM) systems. However, this incorporation involves changes in the current waste management habits of households. In this paper, the attitude of the public towards the incorporation of selective collection of biowaste into an existing MSWMmore » system in a Spanish municipality is analysed. A semi-structured telephone interview was used to obtain information regarding aspects such as: level of participation in current waste collection systems, willingness to participate in selective collection of biowaste, reasons and barriers that affect participation, willingness to pay for the incorporation of the selective collection of biowaste and the socioeconomic characteristics of citizens who are willing to participate and pay for selective collection of biowaste. The results showed that approximately 81% of the respondents were willing to participate in selective collection of biowaste. This percentage would increase until 89% if the Town Council provided specific waste bins and bags, since the main barrier to participate in the new selective collection system is the need to use specific waste bin and bags for the separation of biowaste. A logit response model was applied to estimate the average willingness to pay, obtaining an estimated mean of 7.5% on top of the current waste management annual tax. The relationship of willingness to participate and willingness to pay for the implementation of this new selective collection with the socioeconomic variables (age, gender, size of the household, work, education and income) was analysed. Chi-square independence tests and binary logistic regression was used for willingness to participate, not being obtained any significant relationship. Chi-square independence tests, ordinal logistic regression and ordinary linear regression was applied for willingness to pay, obtaining statistically significant relationship for most of the socioeconomic variables.« less

Retargeted Least Squares Regression Algorithm.

PubMed

Zhang, Xu-Yao; Wang, Lingfeng; Xiang, Shiming; Liu, Cheng-Lin

2015-09-01

This brief presents a framework of retargeted least squares regression (ReLSR) for multicategory classification. The core idea is to directly learn the regression targets from data other than using the traditional zero-one matrix as regression targets. The learned target matrix can guarantee a large margin constraint for the requirement of correct classification for each data point. Compared with the traditional least squares regression (LSR) and a recently proposed discriminative LSR models, ReLSR is much more accurate in measuring the classification error of the regression model. Furthermore, ReLSR is a single and compact model, hence there is no need to train two-class (binary) machines that are independent of each other. The convex optimization problem of ReLSR is solved elegantly and efficiently with an alternating procedure including regression and retargeting as substeps. The experimental evaluation over a range of databases identifies the validity of our method.

Comparing methods for estimation of heterogeneous treatment effects using observational data from health care databases.

PubMed

Wendling, T; Jung, K; Callahan, A; Schuler, A; Shah, N H; Gallego, B

2018-06-03

There is growing interest in using routinely collected data from health care databases to study the safety and effectiveness of therapies in "real-world" conditions, as it can provide complementary evidence to that of randomized controlled trials. Causal inference from health care databases is challenging because the data are typically noisy, high dimensional, and most importantly, observational. It requires methods that can estimate heterogeneous treatment effects while controlling for confounding in high dimensions. Bayesian additive regression trees, causal forests, causal boosting, and causal multivariate adaptive regression splines are off-the-shelf methods that have shown good performance for estimation of heterogeneous treatment effects in observational studies of continuous outcomes. However, it is not clear how these methods would perform in health care database studies where outcomes are often binary and rare and data structures are complex. In this study, we evaluate these methods in simulation studies that recapitulate key characteristics of comparative effectiveness studies. We focus on the conditional average effect of a binary treatment on a binary outcome using the conditional risk difference as an estimand. To emulate health care database studies, we propose a simulation design where real covariate and treatment assignment data are used and only outcomes are simulated based on nonparametric models of the real outcomes. We apply this design to 4 published observational studies that used records from 2 major health care databases in the United States. Our results suggest that Bayesian additive regression trees and causal boosting consistently provide low bias in conditional risk difference estimates in the context of health care database studies. Copyright © 2018 John Wiley & Sons, Ltd.

Risk of Recurrence in Operated Parasagittal Meningiomas: A Logistic Binary Regression Model.

PubMed

Escribano Mesa, José Alberto; Alonso Morillejo, Enrique; Parrón Carreño, Tesifón; Huete Allut, Antonio; Narro Donate, José María; Méndez Román, Paddy; Contreras Jiménez, Ascensión; Pedrero García, Francisco; Masegosa González, José

2018-02-01

Parasagittal meningiomas arise from the arachnoid cells of the angle formed between the superior sagittal sinus (SSS) and the brain convexity. In this retrospective study, we focused on factors that predict early recurrence and recurrence times. We reviewed 125 patients with parasagittal meningiomas operated from 1985 to 2014. We studied the following variables: age, sex, location, laterality, histology, surgeons, invasion of the SSS, Simpson removal grade, follow-up time, angiography, embolization, radiotherapy, recurrence and recurrence time, reoperation, neurologic deficit, degree of dependency, and patient status at the end of follow-up. Patients ranged in age from 26 to 81 years (mean 57.86 years; median 60 years). There were 44 men (35.2%) and 81 women (64.8%). There were 57 patients with neurologic deficits (45.2%). The most common presenting symptom was motor deficit. World Health Organization grade I tumors were identified in 104 patients (84.6%), and the majority were the meningothelial type. Recurrence was detected in 34 cases. Time of recurrence was 9 to 336 months (mean: 84.4 months; median: 79.5 months). Male sex was identified as an independent risk for recurrence with relative risk 2.7 (95% confidence interval 1.21-6.15), P = 0.014. Kaplan-Meier curves for recurrence had statistically significant differences depending on sex, age, histologic type, and World Health Organization histologic grade. A binary logistic regression was made with the Hosmer-Lemeshow test with P > 0.05; sex, tumor size, and histologic type were used in this model. Male sex is an independent risk factor for recurrence that, associated with other factors such tumor size and histologic type, explains 74.5% of all cases in a binary regression model. Copyright © 2017 Elsevier Inc. All rights reserved.

A unifying theory for genetic epidemiological analysis of binary disease data

PubMed Central

2014-01-01

Background Genetic selection for host resistance offers a desirable complement to chemical treatment to control infectious disease in livestock. Quantitative genetics disease data frequently originate from field studies and are often binary. However, current methods to analyse binary disease data fail to take infection dynamics into account. Moreover, genetic analyses tend to focus on host susceptibility, ignoring potential variation in infectiousness, i.e. the ability of a host to transmit the infection. This stands in contrast to epidemiological studies, which reveal that variation in infectiousness plays an important role in the progression and severity of epidemics. In this study, we aim at filling this gap by deriving an expression for the probability of becoming infected that incorporates infection dynamics and is an explicit function of both host susceptibility and infectiousness. We then validate this expression according to epidemiological theory and by simulating epidemiological scenarios, and explore implications of integrating this expression into genetic analyses. Results Our simulations show that the derived expression is valid for a range of stochastic genetic-epidemiological scenarios. In the particular case of variation in susceptibility only, the expression can be incorporated into conventional quantitative genetic analyses using a complementary log-log link function (rather than probit or logit). Similarly, if there is moderate variation in both susceptibility and infectiousness, it is possible to use a logarithmic link function, combined with an indirect genetic effects model. However, in the presence of highly infectious individuals, i.e. super-spreaders, the use of any model that is linear in susceptibility and infectiousness causes biased estimates. Thus, in order to identify super-spreaders, novel analytical methods using our derived expression are required. Conclusions We have derived a genetic-epidemiological function for quantitative genetic analyses of binary infectious disease data, which, unlike current approaches, takes infection dynamics into account and allows for variation in host susceptibility and infectiousness. PMID:24552188

A unifying theory for genetic epidemiological analysis of binary disease data.

PubMed

Lipschutz-Powell, Debby; Woolliams, John A; Doeschl-Wilson, Andrea B

2014-02-19

Genetic selection for host resistance offers a desirable complement to chemical treatment to control infectious disease in livestock. Quantitative genetics disease data frequently originate from field studies and are often binary. However, current methods to analyse binary disease data fail to take infection dynamics into account. Moreover, genetic analyses tend to focus on host susceptibility, ignoring potential variation in infectiousness, i.e. the ability of a host to transmit the infection. This stands in contrast to epidemiological studies, which reveal that variation in infectiousness plays an important role in the progression and severity of epidemics. In this study, we aim at filling this gap by deriving an expression for the probability of becoming infected that incorporates infection dynamics and is an explicit function of both host susceptibility and infectiousness. We then validate this expression according to epidemiological theory and by simulating epidemiological scenarios, and explore implications of integrating this expression into genetic analyses. Our simulations show that the derived expression is valid for a range of stochastic genetic-epidemiological scenarios. In the particular case of variation in susceptibility only, the expression can be incorporated into conventional quantitative genetic analyses using a complementary log-log link function (rather than probit or logit). Similarly, if there is moderate variation in both susceptibility and infectiousness, it is possible to use a logarithmic link function, combined with an indirect genetic effects model. However, in the presence of highly infectious individuals, i.e. super-spreaders, the use of any model that is linear in susceptibility and infectiousness causes biased estimates. Thus, in order to identify super-spreaders, novel analytical methods using our derived expression are required. We have derived a genetic-epidemiological function for quantitative genetic analyses of binary infectious disease data, which, unlike current approaches, takes infection dynamics into account and allows for variation in host susceptibility and infectiousness.

Experimental Study on Oil Displacement Mechanism

NASA Astrophysics Data System (ADS)

Pi, Yanfu; Shao, Hongzhi; Pi, Yanming; Liu, Li

2018-02-01

In this work, the objective is enhancing oil recovery in offshore heavy oil after polymer flooding. The heterogeneous physical model is especially designed for oil fields with heavy oil. The comparative study of the two displacement experiments was carried out, and the experimental data was compared and analysed. The comparison between scheme one and scheme two was analysed from the production curve. The patterns of cores are analysed and compared with each other. It was found that the oil in the high permeability layer and medium permeability layer had been widely removed in the stage of binary combination flooding. There was a high degree of use in the low permeability layer. The recovery ratio is 66.29%. After polymer flooding, the addition of binary combination flooding in the heavy oil reservoir can greatly enhance oil recovery.

THE EFFECT OF UNRESOLVED BINARIES ON GLOBULAR CLUSTER PROPER-MOTION DISPERSION PROFILES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bianchini, P.; Norris, M. A.; Ven, G. van de

2016-03-20

High-precision kinematic studies of globular clusters (GCs) require an accurate knowledge of all possible sources of contamination. Among other sources, binary stars can introduce systematic biases in the kinematics. Using a set of Monte Carlo cluster simulations with different concentrations and binary fractions, we investigate the effect of unresolved binaries on proper-motion dispersion profiles, treating the simulations like Hubble Space Telescope proper-motion samples. Since GCs evolve toward a state of partial energy equipartition, more-massive stars lose energy and decrease their velocity dispersion. As a consequence, on average, binaries have a lower velocity dispersion, since they are more-massive kinematic tracers. Wemore » show that, in the case of clusters with high binary fractions (initial binary fractions of 50%) and high concentrations (i.e., closer to energy equipartition), unresolved binaries introduce a color-dependent bias in the velocity dispersion of main-sequence stars of the order of 0.1–0.3 km s{sup −1} (corresponding to 1%−6% of the velocity dispersion), with the reddest stars having a lower velocity dispersion, due to the higher fraction of contaminating binaries. This bias depends on the ability to distinguish binaries from single stars, on the details of the color–magnitude diagram and the photometric errors. We apply our analysis to the HSTPROMO data set of NGC 7078 (M15) and show that no effect ascribable to binaries is observed, consistent with the low binary fraction of the cluster. Our work indicates that binaries do not significantly bias proper-motion velocity-dispersion profiles, but should be taken into account in the error budget of kinematic analyses.« less

[Overload in the informal caregivers of patients with multiple comorbidities in an urban area].

PubMed

Álvarez-Tello, Margarita; Casado-Mejía, Rosa; Ortega-Calvo, Manuel; Ruiz-Arias, Esperanza

2012-01-01

The aim of the study was, to determine the profile of the family caregiver of patients with multiple pathologies, identify factors associated with overload, and construct predictive models using items from the Caregiver Strain Index (CSI). A cross-sectional study of caregivers of patients with multiple comorbidities who attended an urban health centre. Data were collected from health records and questionnaires (Barthel index, Pfeiffer index, and CSI). Statistical analysis was performed using measures of central tendency and dispersion, and by building multivariate models with binary logistic regression with the CSI items as predictors (program R version 2.14.0). The sample included 67 caregivers, with a mean age of 64.69 years (standard deviation=12.71, median 62 years), of whom 74.6% were women, 35.8% were wives, and 32.8% were daughters. The level of dependence of the patients cared for was total/severe in 77.6%, and moderate in 12% (Barthel), and 47.8% had some level of cognitive impairment (Pfeiffer). A CSI equal or greater than 7 was seen in 47.8% of caregivers, identifying life problems in more than 40% of them such as, restriction of social life, physical exertion, discomfort with change, bad behaviour, personal and family emotional changes, and sleep disturbances. Item 4 of the CSI, analysing the social restriction, was the one that showed a greater significance in the predictive multivariate model. Item 12 (economic burden) was the most significant with age in patients with cognitive impairment. Women tend to take the role of caregiver at an earlier age than men in the urban environment studied, and items from CSI showed that items 4 (social restrictions) and 12 (economic burden) have more significance in the predictive models constructed with Binary Logistic Regression. Copyright © 2012 Elsevier España, S.L. All rights reserved.

Association of the leptin-to-adiponectin ratio with metabolic syndrome in a sub-Saharan African population.

PubMed

Ayina, Clarisse Noël A; Endomba, Francky Teddy A; Mandengue, Samuel Honoré; Noubiap, Jean Jacques N; Ngoa, Laurent Serge Etoundi; Boudou, Philippe; Gautier, Jean-François; Mbanya, Jean Claude; Sobngwi, Eugene

2017-01-01

Worldwide there is an increased prevalence of metabolic syndrome mainly due to life-style modifications, and Africans are not saved of this situation. Many markers have been studied to predict the risk of this syndrome but the most used are leptin and adiponectin. Data on these metabolic markers are scare in Africa and this study aimed to assess the association between the leptin-to-adiponectin ratio (LAR) with metabolic syndrome in a Cameroonian population. This was a cross-sectional study that included 476 adults among a general population of Cameroon. Data collected concerned the body mass index, waist circumference, systolic blood pressure, diastolic blood pressure, fasting blood glucose, plasma lipids, adiponectin, leptin, insulin and homeostasis model for assessment of insulin resistance (HOMA-IR). To assess correlations we used Spearman's analyses and association of the studied variables with metabolic syndrome were done using binary logistic regression analysis. The leptin to adiponectin ratio was significantly and positively correlated with the body mass index (r = 0.669, p < 0.0001), waist circumference (r = 0.595, p < 0.0001), triglycerides (r = 0.190, p = 0.001), insulin levels (r = 0.333, p < 0.0001) and HOMA-IR (r = 0.306, p < 0.0001). Binary logistic regression analysis revealed that leptin, adiponectin and LAR were significantly associated with metabolic syndrome with respective unadjusted OR of 1.429, 0.468 and 1.502. After adjustment, for age and sex, the associations remained significative; LAR was also found to be significantly associated with metabolic syndrome (OR = 1.573, p value =0.000) as well as lower levels of adiponectin (OR = 0.359, p value =0.000) and higher levels of leptin (OR = 1.469, p value =0.001). This study revealed that LAR is significantly associated with metabolic syndrome in sub-Saharan African population, independently to age and sex.

Optimizing methods for linking cinematic features to fMRI data.

PubMed

Kauttonen, Janne; Hlushchuk, Yevhen; Tikka, Pia

2015-04-15

One of the challenges of naturalistic neurosciences using movie-viewing experiments is how to interpret observed brain activations in relation to the multiplicity of time-locked stimulus features. As previous studies have shown less inter-subject synchronization across viewers of random video footage than story-driven films, new methods need to be developed for analysis of less story-driven contents. To optimize the linkage between our fMRI data collected during viewing of a deliberately non-narrative silent film 'At Land' by Maya Deren (1944) and its annotated content, we combined the method of elastic-net regularization with the model-driven linear regression and the well-established data-driven independent component analysis (ICA) and inter-subject correlation (ISC) methods. In the linear regression analysis, both IC and region-of-interest (ROI) time-series were fitted with time-series of a total of 36 binary-valued and one real-valued tactile annotation of film features. The elastic-net regularization and cross-validation were applied in the ordinary least-squares linear regression in order to avoid over-fitting due to the multicollinearity of regressors, the results were compared against both the partial least-squares (PLS) regression and the un-regularized full-model regression. Non-parametric permutation testing scheme was applied to evaluate the statistical significance of regression. We found statistically significant correlation between the annotation model and 9 ICs out of 40 ICs. Regression analysis was also repeated for a large set of cubic ROIs covering the grey matter. Both IC- and ROI-based regression analyses revealed activations in parietal and occipital regions, with additional smaller clusters in the frontal lobe. Furthermore, we found elastic-net based regression more sensitive than PLS and un-regularized regression since it detected a larger number of significant ICs and ROIs. Along with the ISC ranking methods, our regression analysis proved a feasible method for ordering the ICs based on their functional relevance to the annotated cinematic features. The novelty of our method is - in comparison to the hypothesis-driven manual pre-selection and observation of some individual regressors biased by choice - in applying data-driven approach to all content features simultaneously. We found especially the combination of regularized regression and ICA useful when analyzing fMRI data obtained using non-narrative movie stimulus with a large set of complex and correlated features. Copyright © 2015. Published by Elsevier Inc.

Lamb survival analysis from birth to weaning in Iranian Kermani sheep.

PubMed

Barazandeh, Arsalan; Moghbeli, Sadrollah Molaei; Vatankhah, Mahmood; Hossein-Zadeh, Navid Ghavi

2012-04-01

Survival records from 1,763 Kermani lambs born between 1996 and 2004 from 294 ewes and 81 rams were used to determine genetic and non-genetic factors affecting lamb survival. Traits included were lamb survival across five periods from birth to 7, 14, 56, 70, and 90 days of age. Traits were analyzed under Weibull proportional hazard sire models. Several binary analyses were also conducted using animal models. Statistical models included the fixed class effects of sex of lamb, month and year of birth, a covariate effect of birth weight, and random genetic effects of both sire (in survival analyses) and animal (in binary analyses). The average survival to 90 days of age was 94.8%. Hazard rates ranged from 1.00 (birth to 90 days of age) to 1.73 (birth to 7 days of age) between the two sexes indicating that male lambs were at higher risk of mortality than females (P < 0.01). This study also revealed a curvilinear relationship between lamb survival and lamb birth weight, suggesting that viability and birth weight could be considered simultaneously in the selection programs to obtain optimal birth weight in Kermani lambs. Estimates of heritabilities from survival analyses were medium and ranged from 0.23 to 0.29. In addition, heritability estimates obtained from binary analyses were low and varied from 0.04 to 0.09. The results of this study suggest that progress in survival traits could be possible through managerial strategies and genetic selection.

Can Emotional and Behavioral Dysregulation in Youth Be Decoded from Functional Neuroimaging?

PubMed

Portugal, Liana C L; Rosa, Maria João; Rao, Anil; Bebko, Genna; Bertocci, Michele A; Hinze, Amanda K; Bonar, Lisa; Almeida, Jorge R C; Perlman, Susan B; Versace, Amelia; Schirda, Claudiu; Travis, Michael; Gill, Mary Kay; Demeter, Christine; Diwadkar, Vaibhav A; Ciuffetelli, Gary; Rodriguez, Eric; Forbes, Erika E; Sunshine, Jeffrey L; Holland, Scott K; Kowatch, Robert A; Birmaher, Boris; Axelson, David; Horwitz, Sarah M; Arnold, Eugene L; Fristad, Mary A; Youngstrom, Eric A; Findling, Robert L; Pereira, Mirtes; Oliveira, Leticia; Phillips, Mary L; Mourao-Miranda, Janaina

2016-01-01

High comorbidity among pediatric disorders characterized by behavioral and emotional dysregulation poses problems for diagnosis and treatment, and suggests that these disorders may be better conceptualized as dimensions of abnormal behaviors. Furthermore, identifying neuroimaging biomarkers related to dimensional measures of behavior may provide targets to guide individualized treatment. We aimed to use functional neuroimaging and pattern regression techniques to determine whether patterns of brain activity could accurately decode individual-level severity on a dimensional scale measuring behavioural and emotional dysregulation at two different time points. A sample of fifty-seven youth (mean age: 14.5 years; 32 males) was selected from a multi-site study of youth with parent-reported behavioral and emotional dysregulation. Participants performed a block-design reward paradigm during functional Magnetic Resonance Imaging (fMRI). Pattern regression analyses consisted of Relevance Vector Regression (RVR) and two cross-validation strategies implemented in the Pattern Recognition for Neuroimaging toolbox (PRoNTo). Medication was treated as a binary confounding variable. Decoded and actual clinical scores were compared using Pearson's correlation coefficient (r) and mean squared error (MSE) to evaluate the models. Permutation test was applied to estimate significance levels. Relevance Vector Regression identified patterns of neural activity associated with symptoms of behavioral and emotional dysregulation at the initial study screen and close to the fMRI scanning session. The correlation and the mean squared error between actual and decoded symptoms were significant at the initial study screen and close to the fMRI scanning session. However, after controlling for potential medication effects, results remained significant only for decoding symptoms at the initial study screen. Neural regions with the highest contribution to the pattern regression model included cerebellum, sensory-motor and fronto-limbic areas. The combination of pattern regression models and neuroimaging can help to determine the severity of behavioral and emotional dysregulation in youth at different time points.

Prevalence of and Factors Associated with Negative Microscopic Diagnosis of Cutaneous Leishmaniasis in Rural Peru.

PubMed

Lamm, Ryan; Alves, Clark; Perrotta, Grace; Murphy, Meagan; Messina, Catherine; Sanchez, Juan F; Perez, Erika; Rosales, Luis Angel; Lescano, Andres G; Smith, Edward; Valdivia, Hugo; Fuhrer, Jack; Ballard, Sarah-Blythe

2018-06-04

Cutaneous leishmaniasis is endemic to South America where diagnosis is most commonly conducted via microscopy. Patients with suspected leishmaniasis were referred for enrollment by the Ministry of Health (MoH) in Lima, Iquitos, Puerto Maldonado, and several rural areas of Peru. A 43-question survey requesting age, gender, occupation, characterization of the lesion(s), history of leishmaniasis, and insect-deterrent behaviors was administered. Polymerase chain reaction (PCR) was conducted on lesion materials at the Naval Medical Research Unit No. 6 in Lima, and the results were compared with those obtained by the MoH using microscopy. Factors associated with negative microscopy and positive PCR results were identified using χ 2 test, t -test, and multivariate logistic regression analyses. Negative microscopy with positive PCR occurred in 31% (123/403) of the 403 cases. After adjusting for confounders, binary multivariate logistic regression analyses revealed that negative microscopy with positive PCR was associated with patients who were male (adjusted OR = 1.93 [1.06-3.53], P = 0.032), had previous leishmaniasis (adjusted OR = 2.93 [1.65-5.22], P < 0.0001), had larger lesions (adjusted OR = 1.02 [1.003-1.03], P = 0.016), and/or had a longer duration between lesion appearance and PCR testing (adjusted OR = 1.12 [1.02-1.22], P = 0.017). Future research should focus on further exploration of these underlying variables, discovery of other factors that may be associated with negative microscopy diagnosis, and the development and implementation of improved testing in endemic regions.

Gender inequalities in the health of immigrants and workplace discrimination in Czechia.

PubMed

Dzúrová, Dagmar; Drbohlav, Dušan

2014-01-01

This study analyses the relationship between immigrants' self-reported/rated health (SRH) and their perceived working conditions in Czechia materialized via discrimination, based on the example of Ukrainian immigrants analyzed by gender dimension. The role of age, education, and marital status is also analyzed. A sample of native-born Czechs serves as a reference frame. A cross-sectional design was applied. Using data from two surveys of Ukrainian immigrants in Czechia and a countrywide health interview survey for Czechs, we analyse inequalities in SRH and workplace discrimination loads. Four binary logistic regression models were computed separately for women and men from Ukraine and Czechia to identify the determinants of fair/poor SRH. We found that only Ukrainian immigrant females were heavily exposed to all four measured types of workplace discrimination, thereby modifying and worsening the quality of their SRH. Determinants which are behind respondents' SRH differ between Ukrainian immigrants vis-à-vis Czechs with one exception. The "oldest age group" (41-62) contributes to poorer assessment of SRH among Ukrainian females, Czech females, and Czech males too. The lowest educational level (primary education) correlates with poor SRH within the sample of Czech males.

Ethnic differences in diabetes prevalence and ICT use.

PubMed

Umeh, Kanayo; Mackay, Michael; Le-Brun, Stephanie Davis

Uptake of information and communication technology (ICT) by individuals with diabetes can assist nursing care delivery, and improve patient outcomes. However, it is unclear how such uptake relates to ethnic differences in diabetes risk. To assess the moderating effects of ICT uptake on South Asian excess diabetes prevalence over a specific elapsed timeframe, accounting for selected environmental, socio-economic, and behavioural risk factors. Archived data from a UK Office for National Statistics household survey 2006-2011 (120 621 partly non-orthogonal participant records) were analysed using hierarchical binary logistic regression analyses. ICT uptake qualified ethnic differences in diabetes prevalence. Non-smoking diabetes cases living in terraced housing with a home computer were more likely to be South Asian than Caucasian. By contrast, such cases were more likely to be Caucasian if a computer was unavailable (OR: 0.61; CI: 0.43-0.86; P=0.005). Furthermore, diabetes cases from low-income, mobile-dependent homes were probably South Asian (OR: 0.05; CI: 0.00-0.50; P=0.012). Home computing was linked to better tobacco control among South Asians with diabetes living in terraced properties. Mobile phone dependence was pronounced in those that received income support. Implications for nursing care are considered.

What Influences Where They Give Birth? Determinants of Place of Delivery among Women in Rural Ghana.

PubMed

Dickson, Kwamena Sekyi; Adde, Kenneth Setorwu; Amu, Hubert

2016-01-01

Background . There is a paucity of empirical literature in Ghana on rural areas and their utilisation of health facilities. The study examined the effects of the sociodemographics of rural women on place of delivery in the country. Methods . The paper made use of data from the 2014 Ghana Demographic and Health Survey. Women from rural areas who had given birth within five years prior to the survey were included in the analysis. Descriptive analyses and binary logistic regression were used to analyse the data. Results . Wealth, maternal education, ecological zone, getting money for treatment, ethnicity, partner's education, parity, and distance to a health facility were found as the determinants of place of delivery among women in rural Ghana. Women in the richest wealth quintile were three times (OR = 3.04, 95% CI = 0.35-26.4) more likely to deliver at a health facility than the poorest women. Conclusions . It behoves the relevant stakeholders including the Ghana Health Service and the Ministry of Health to pay attention to the wealth status, maternal education, ecological zone, ethnicity, partner's education, parity, and distance in their planning regarding delivery care in rural Ghana.

Gender Inequalities in the Health of Immigrants and Workplace Discrimination in Czechia

PubMed Central

Dzúrová, Dagmar; Drbohlav, Dušan

2014-01-01

This study analyses the relationship between immigrants' self-reported/rated health (SRH) and their perceived working conditions in Czechia materialized via discrimination, based on the example of Ukrainian immigrants analyzed by gender dimension. The role of age, education, and marital status is also analyzed. A sample of native-born Czechs serves as a reference frame. A cross-sectional design was applied. Using data from two surveys of Ukrainian immigrants in Czechia and a countrywide health interview survey for Czechs, we analyse inequalities in SRH and workplace discrimination loads. Four binary logistic regression models were computed separately for women and men from Ukraine and Czechia to identify the determinants of fair/poor SRH. We found that only Ukrainian immigrant females were heavily exposed to all four measured types of workplace discrimination, thereby modifying and worsening the quality of their SRH. Determinants which are behind respondents' SRH differ between Ukrainian immigrants vis-à-vis Czechs with one exception. The “oldest age group” (41–62) contributes to poorer assessment of SRH among Ukrainian females, Czech females, and Czech males too. The lowest educational level (primary education) correlates with poor SRH within the sample of Czech males. PMID:25105125

Are math readiness and personality predictive of first-year retention in engineering?

PubMed

Moses, Laurie; Hall, Cathy; Wuensch, Karl; De Urquidi, Karen; Kauffmann, Paul; Swart, William; Duncan, Steve; Dixon, Gene

2011-01-01

On the basis of J. G. Borkowski, L. K. Chan, and N. Muthukrishna's model of academic success (2000), the present authors hypothesized that freshman retention in an engineering program would be related to not only basic aptitude but also affective factors. Participants were 129 college freshmen with engineering as their stated major. Aptitude was measured by SAT verbal and math scores, high school grade-point average (GPA), and an assessment of calculus readiness. Affective factors were assessed by the NEO-Five Factor Inventory (FFI; P. I. Costa & R. R. McCrae, 2007), and the Nowicki-Duke Locus of Control (LOC) scale (S. Nowicki & M. Duke, 1974). A binary logistic regression analysis found that calculus readiness and high school GPA were predictive of retention. Scores on the Neuroticism and Openness subscales from the NEO-FFI and LOC were correlated with retention status, but Openness was the only affective factor with a significant unique effect in the binary logistic regression. Results of the study lend modest support to Borkowski's model.

[Willingness of Patients with Obesity to Use New Media in Rehabilitation Aftercare].

PubMed

Dorow, M; Löbner, M; Stein, J; Kind, P; Markert, J; Keller, J; Weidauer, E; Riedel-Heller, S G

2017-06-01

Digital media offer new possibilities in rehabilitation aftercare. This study investigates the rehabilitants' willingness to use new media (sms, internet, social networks) in rehabilitation aftercare and factors that are associated with the willingness to use media-based aftercare. 92 rehabilitants (patients with obesity) filled in a questionnaire on the willingness to use new media in rehabilitation aftercare. In order to identify influencing factors, binary logistic regression models were calculated. 3 quarters of the rehabilitants (76.1%) reported that they would be willing to use new media in rehabilitation aftercare. The binary logistic regression model yielded two factors that were associated with the willingness to use media-based aftercare: the possession of a smartphone and the willingness to receive telephone counseling for aftercare. The majority of the rehabilitants was willing to use new media in rehabilitation aftercare. The reasons for refusal of media-based aftercare need to be examined more closely. © Georg Thieme Verlag KG Stuttgart · New York.

Statistical power to detect violation of the proportional hazards assumption when using the Cox regression model.

PubMed

Austin, Peter C

2018-01-01

The use of the Cox proportional hazards regression model is widespread. A key assumption of the model is that of proportional hazards. Analysts frequently test the validity of this assumption using statistical significance testing. However, the statistical power of such assessments is frequently unknown. We used Monte Carlo simulations to estimate the statistical power of two different methods for detecting violations of this assumption. When the covariate was binary, we found that a model-based method had greater power than a method based on cumulative sums of martingale residuals. Furthermore, the parametric nature of the distribution of event times had an impact on power when the covariate was binary. Statistical power to detect a strong violation of the proportional hazards assumption was low to moderate even when the number of observed events was high. In many data sets, power to detect a violation of this assumption is likely to be low to modest.

Statistical power to detect violation of the proportional hazards assumption when using the Cox regression model

PubMed Central

Austin, Peter C.

2017-01-01

The use of the Cox proportional hazards regression model is widespread. A key assumption of the model is that of proportional hazards. Analysts frequently test the validity of this assumption using statistical significance testing. However, the statistical power of such assessments is frequently unknown. We used Monte Carlo simulations to estimate the statistical power of two different methods for detecting violations of this assumption. When the covariate was binary, we found that a model-based method had greater power than a method based on cumulative sums of martingale residuals. Furthermore, the parametric nature of the distribution of event times had an impact on power when the covariate was binary. Statistical power to detect a strong violation of the proportional hazards assumption was low to moderate even when the number of observed events was high. In many data sets, power to detect a violation of this assumption is likely to be low to modest. PMID:29321694

Satellite radiance data assimilation for binary tropical cyclone cases over the western North Pacific

NASA Astrophysics Data System (ADS)

Choi, Yonghan; Cha, Dong-Hyun; Lee, Myong-In; Kim, Joowan; Jin, Chun-Sil; Park, Sang-Hun; Joh, Min-Su

2017-06-01

A total of three binary tropical cyclone (TC) cases over the Western North Pacific are selected to investigate the effects of satellite radiance data assimilation on analyses and forecasts of binary TCs. Two parallel cycling experiments with a 6 h interval are performed for each binary TC case, and the difference between the two experiments is whether satellite radiance observations are assimilated. Satellite radiance observations are assimilated using the Weather Research and Forecasting Data Assimilation (WRFDA)'s three-dimensional variational (3D-Var) system, which includes the observation operator, quality control procedures, and bias correction algorithm for radiance observations. On average, radiance assimilation results in slight improvements of environmental fields and track forecasts of binary TC cases, but the detailed effects vary with the case. When there is no direct interaction between binary TCs, radiance assimilation leads to better depictions of environmental fields, and finally it results in improved track forecasts. However, positive effects of radiance assimilation on track forecasts can be reduced when there exists a direct interaction between binary TCs and intensities/structures of binary TCs are not represented well. An initialization method (e.g., dynamic initialization) combined with radiance assimilation and/or more advanced DA techniques (e.g., hybrid method) can be considered to overcome these limitations.

Spectroscopic and Chemometric Analysis of Binary and Ternary Edible Oil Mixtures: Qualitative and Quantitative Study.

PubMed

Jović, Ozren; Smolić, Tomislav; Primožič, Ines; Hrenar, Tomica

2016-04-19

The aim of this study was to investigate the feasibility of FTIR-ATR spectroscopy coupled with the multivariate numerical methodology for qualitative and quantitative analysis of binary and ternary edible oil mixtures. Four pure oils (extra virgin olive oil, high oleic sunflower oil, rapeseed oil, and sunflower oil), as well as their 54 binary and 108 ternary mixtures, were analyzed using FTIR-ATR spectroscopy in combination with principal component and discriminant analysis, partial least-squares, and principal component regression. It was found that the composition of all 166 samples can be excellently represented using only the first three principal components describing 98.29% of total variance in the selected spectral range (3035-2989, 1170-1140, 1120-1100, 1093-1047, and 930-890 cm(-1)). Factor scores in 3D space spanned by these three principal components form a tetrahedral-like arrangement: pure oils being at the vertices, binary mixtures at the edges, and ternary mixtures on the faces of a tetrahedron. To confirm the validity of results, we applied several cross-validation methods. Quantitative analysis was performed by minimization of root-mean-square error of cross-validation values regarding the spectral range, derivative order, and choice of method (partial least-squares or principal component regression), which resulted in excellent predictions for test sets (R(2) > 0.99 in all cases). Additionally, experimentally more demanding gas chromatography analysis of fatty acid content was carried out for all specimens, confirming the results obtained by FTIR-ATR coupled with principal component analysis. However, FTIR-ATR provided a considerably better model for prediction of mixture composition than gas chromatography, especially for high oleic sunflower oil.

VizieR Online Data Catalog: ASAS, NSVS, and LINEAR detached eclipsing binaries (Lee, 2015)

NASA Astrophysics Data System (ADS)

Lee, C.-H.

2016-04-01

We follow the approach of Devor et al. (2008AJ....135..850D, Cat. J/AJ/135/850) to analyse the LC from ASAS (Pojmanski et al., Cat. II/264, NSVS (Wozniak et al., 2004AJ....127.2436W, and LINEAR (Palaversa et al., Cat. J/AJ/146/101) and extract the physical properties of the eclipsing binaries. (3 data files).

Vocational Education and the Binary Higher Education System in the Netherlands: Higher Education Symbiosis or Vocational Education Dichotomy?

ERIC Educational Resources Information Center

van Houten, Maarten Matheus

2018-01-01

The Netherlands has a binary higher education system in which academic education and higher professional education at EQF levels 5-8 co-exist. There is also secondary vocational education at EQF levels 1 up to 4. In this paper, I analyse policy documents resulting from the Bologna Process and argue that under neo-liberal conditions, higher…

Comparison of robustness to outliers between robust poisson models and log-binomial models when estimating relative risks for common binary outcomes: a simulation study.

PubMed

Chen, Wansu; Shi, Jiaxiao; Qian, Lei; Azen, Stanley P

2014-06-26

To estimate relative risks or risk ratios for common binary outcomes, the most popular model-based methods are the robust (also known as modified) Poisson and the log-binomial regression. Of the two methods, it is believed that the log-binomial regression yields more efficient estimators because it is maximum likelihood based, while the robust Poisson model may be less affected by outliers. Evidence to support the robustness of robust Poisson models in comparison with log-binomial models is very limited. In this study a simulation was conducted to evaluate the performance of the two methods in several scenarios where outliers existed. The findings indicate that for data coming from a population where the relationship between the outcome and the covariate was in a simple form (e.g. log-linear), the two models yielded comparable biases and mean square errors. However, if the true relationship contained a higher order term, the robust Poisson models consistently outperformed the log-binomial models even when the level of contamination is low. The robust Poisson models are more robust (or less sensitive) to outliers compared to the log-binomial models when estimating relative risks or risk ratios for common binary outcomes. Users should be aware of the limitations when choosing appropriate models to estimate relative risks or risk ratios.

Spectral energy distributions and colours of hot subluminous stars

NASA Astrophysics Data System (ADS)

Heber, Ulrich; Irrgang, Andreas; Schaffenroth, Johannes

2018-02-01

Photometric surveys at optical, ultraviolet, and infrared wavelengths provide ever-growing datasets as major surveys proceed. Colour-colour diagrams are useful tools to identify classes of star and provide large samples. However, combining all photometric measurements of a star into a spectral energy distribution will allow quantitative analyses to be carried out. We demonstrate how to construct and exploit spectral energy distributions and colours for sublumious B (sdB) stars. The aim is to identify cool companions to hot subdwarfs and to determine atmospheric parameters of apparently single sdB stars as well as composite spectrum sdB binaries.We analyse two sdB stars with high-quality photometric data which serve as our benchmarks, the apparently single sdB HD205805 and the sdB + K5 binary PG 0749+658, briefly present preliminary results for the sample of 142 sdB binaries with known orbits, and discuss future prospects from ongoing all-sky optical space- (Gaia) and ground-based (e.g. SkyMapper) as well as NIR surveys.

Agreeableness and pregnancy: Relations with coping and psychiatric symptoms, a longitudinal study on Spanish pregnant women.

PubMed

Peñacoba, Cecilia; Rodríguez, Laura; Carmona, Javier; Marín, Dolores

2018-02-01

Agreeableness is associated with good mental health during pregnancy. Although different studies have indicated that agreeableness is related to adaptive coping, this relation has scarcely been studied in pregnant women. The aim of this study was to analyze the possible differences between high and low agreeableness in relation to coping strategies and psychiatric symptoms in pregnant women. We conducted a longitudinal prospective study between October 2009 and January 2013. Pregnant women (n = 285) were assessed in the first trimester of pregnancy, and 122 of them were assessed during the third. Data were collected using the Coping Strategies Questionnaire, the Symptom Check List 90-R, and the agreeableness subscale of the NEO-FFI. Using the SPSS 21 statistics package, binary logistic regression, two-way mixed analysis of variance, and multiple regression analyses and a Sobel test were conducted. Higher levels of agreeableness were associated with positive reappraisal and problem-solving, and lower levels of agreeableness were associated with overt emotional expression and negative self-focused coping. Women with low agreeableness had poorer mental health, especially in the first trimester. These findings should be taken into account to improve women's experiences during pregnancy. Nevertheless, given the scarcity of data, additional studies are needed.

The relationship between lifestyle factors and clinical symptoms of bipolar disorder patients in a Chinese population.

PubMed

Huang, Jia; Yuan, Cheng Mei; Xu, Xian Rong; Wang, Yong; Hong, Wu; Wang, Zuo Wei; Su, You Song; Hu, Ying Yan; Cao, Lan; Wang, Yu; Chen, Jun; Fang, Yi Ru

2018-05-06

There is evidence that bipolar disorder (BD) patients with an unhealthy lifestyle have a worse course of illness. This study was designed to examine the extent to which lifestyle could influence the severity of clinical symptoms associated with BD. A total of 113 BD patients were recruited in this study. The lifestyle information including data on dietary patterns, physical activity, and sleep quality were collected using a self-rated questionnaire. The results showed that the consumption of whole grain, seafood, and dairy products were significantly negatively correlated with the 17-item Hamilton Rating Scale for Depression (HAMD-17) total score. The consumption of sugar, soft drinks, and alcohol as well as being a current smoker were positively correlated with the severity of clinical symptoms. Multiple linear regression and binary logistic regression analyses demonstrated an independent negative correlation between both whole grain and dairy product consumption with the HAMD-17 score. The results from the current study suggested that lifestyle factors, especially dietary patterns, might be associated with clinical symptoms of BD. The association between the consumption of specific foods and severity of depressive symptoms may offer some useful information and further understanding of the role of lifestyle factors in the development of BD. Copyright © 2018. Published by Elsevier B.V.

Predictors of Smoking among Saudi Dental Students in Jeddah.

PubMed

Mansour, Ameerah Y

2017-05-01

The objective of this study was to assess tobacco use, secondhand smoke exposure, knowledge of health risks, and smoking predictors among dental students attending King Abdulaziz University, Jeddah, Saudi Arabia. A cross-sectional study was conducted and 420 dental students were invited to participate. Binary logistic regression analyses assessed the predictors of smoking. A total of 336 dental students completed the questionnaires with 25% reporting current or previous tobacco use and 96% reporting secondhand smoke exposure. Nearly half of all smokers initiated smoking during the dental program. The logistic regression results revealed that being a male (OR = 7.1, p < .0001; 95%CI = 3.7-13.4) and having a smoker in the family (OR = 2.6, p = .005; 95%CI = 1.3-5.0) increased the likelihood of smoking. In contrast, knowledge of health risks decreased the likelihood of smoking (OR = 0.90, p = .014; 95%CI = 0.82-0.98). Despite possessing knowledge about the health risks of smoking, high numbers of dental students continue to smoke and were exposed to secondhand smoke. Sex and family influence were the main pro-smoking risk factors, whereas increased knowledge of health risks was a protective factor. Tobacco control programs to reduce and/or prevent tobacco use among future dentists are needed.

Obesity Increases Prevalence of Colonic Adenomas at Screening Colonoscopy: A Canadian Community-Based Study

PubMed Central

Chen, Grant I.; Devlin, Tim; Gibbs, Alison; Murray, Iain C.; Tran, Stanley; Weigensberg, Corey

2017-01-01

Background and Aims Obesity is a risk factor for colorectal neoplasia. We examined the influence of obesity and metabolic syndrome (MetS) on prevalence of neoplasia at screening colonoscopy. Methods We evaluated 2020 subjects undergoing first screening colonoscopy. Body mass index (BMI) was calculated at enrolment. Hyperlipidemia (HL), hypertension (HT), and diabetes mellitus (DM) were identified. Details of colonoscopy, polypectomy, and histology were recorded. Odds for adenomas (A) and advanced adenomas (ADV) in overweight (BMI 25.1–30) and obese (BMI > 30) subjects were assessed by multinomial regression, adjusted for covariates. Analyses included relationships between HL, HT, DM, age, tobacco usage, and neoplasia. Discriminatory power of HT, HL, DM, and BMI for neoplasia was assessed by binary logistic regression. Odds were calculated for neoplasia in each colonic segment related to BMI. Results A and ADV were commoner in overweight and obese males, obese females, older subjects, and smokers. HL, HT, and DM were associated with increased odds for neoplasia, significantly for A with hypertension. BMI alone predicted neoplasia as well as HT, HL, DM, or combinations thereof. All segments of the colon were affected. Multiple polyps were particularly prevalent in the obese. Conclusions Obesity and MetS are risk factors for colonic neoplasia in a Canadian population. PMID:28781966

Single-Trial Regression Elucidates the Role of Prefrontal Theta Oscillations in Response Conflict

PubMed Central

Cohen, Michael X; Cavanagh, James F.

2011-01-01

In most cognitive neuroscience experiments there are many behavioral and experimental dynamics, and many indices of brain activity, that vary from trial to trial. For example, in studies of response conflict, conflict is usually treated as a binary variable (i.e., response conflict exists or does not in any given trial), whereas some evidence and intuition suggests that conflict may vary in intensity from trial to trial. Here we demonstrate that single-trial multiple regression of time–frequency electrophysiological activity reveals neural mechanisms of cognitive control that are not apparent in cross-trial averages. We also introduce a novel extension to oscillation phase coherence and synchronization analyses, based on “weighted” phase modulation, that has advantages over standard coherence measures in terms of linking electrophysiological dynamics to trial-varying behavior and experimental variables. After replicating previous response conflict findings using trial-averaged data, we extend these findings using single-trial analytic methods to provide novel evidence for the role of medial frontal–lateral prefrontal theta-band synchronization in conflict-induced response time dynamics, including a role for lateral prefrontal theta-band activity in biasing response times according to perceptual conflict. Given that these methods shed new light on the prefrontal mechanisms of response conflict, they are also likely to be useful for investigating other neurocognitive processes. PMID:21713190

Has there been a change in the knowledge of GP registrars between 2011 and 2016 as measured by performance on common items in the Applied Knowledge Test?

PubMed

Neden, Catherine A; Parkin, Claire; Blow, Carol; Siriwardena, Aloysius Niroshan

2018-05-08

The aim of this study was to assess whether the absolute standard of candidates sitting the MRCGP Applied Knowledge Test (AKT) between 2011 and 2016 had changed. It is a descriptive study comparing the performance on marker questions of a reference group of UK graduates taking the AKT for the first time between 2011 and 2016. Using aggregated examination data, the performance of individual 'marker' questions was compared using Pearson's chi-squared tests and trend-line analysis. Binary logistic regression was used to analyse changes in performance over the study period. Changes in performance of individual marker questions using Pearson's chi-squared test showed statistically significant differences in 32 of the 49 questions included in the study. Trend line analysis showed a positive trend in 29 questions and a negative trend in the remaining 23. The magnitude of change was small. Logistic regression did not demonstrate any evidence for a change in the performance of the question set over the study period. However, candidates were more likely to get items on administration wrong compared with clinical medicine or research. There was no evidence of a change in performance of the question set as a whole.

Predictors for hospitalization and outpatient visits in patients with inflammatory bowel disease: results from the Swiss Inflammatory Bowel Disease Cohort Study.

PubMed

Sulz, Michael C; Siebert, Uwe; Arvandi, Marjan; Gothe, Raffaella M; Wurm, Johannes; von Känel, Roland; Vavricka, Stephan R; Meyenberger, Christa; Sagmeister, Markus

2013-07-01

Patients with inflammatory bowel disease (IBD) have a high resource consumption, with considerable costs for the healthcare system. In a system with sparse resources, treatment is influenced not only by clinical judgement but also by resource consumption. We aimed to determine the resource consumption of IBD patients and to identify its significant predictors. Data from the prospective Swiss Inflammatory Bowel Disease Cohort Study were analysed for the resource consumption endpoints hospitalization and outpatient consultations at enrolment [1187 patients; 41.1% ulcerative colitis (UC), 58.9% Crohn's disease (CD)] and at 1-year follow-up (794 patients). Predictors of interest were chosen through an expert panel and a review of the relevant literature. Logistic regressions were used for binary endpoints, and negative binomial regressions and zero-inflated Poisson regressions were used for count data. For CD, fistula, use of biologics and disease activity were significant predictors for hospitalization days (all P-values <0.001); age, sex, steroid therapy and biologics were significant predictors for the number of outpatient visits (P=0.0368, 0.023, 0.0002, 0.0003, respectively). For UC, biologics, C-reactive protein, smoke quitters, age and sex were significantly predictive for hospitalization days (P=0.0167, 0.0003, 0.0003, 0.0076 and 0.0175 respectively); disease activity and immunosuppressive therapy predicted the number of outpatient visits (P=0.0009 and 0.0017, respectively). The results of multivariate regressions are shown in detail. Several highly significant clinical predictors for resource consumption in IBD were identified that might be considered in medical decision-making. In terms of resource consumption and its predictors, CD and UC show a different behaviour.

Sequence analysis to assess labour market participation following vocational rehabilitation: an observational study among patients sick-listed with low back pain from a randomised clinical trial in Denmark.

PubMed

Lindholdt, Louise; Labriola, Merete; Nielsen, Claus Vinther; Horsbøl, Trine Allerslev; Lund, Thomas

2017-07-20

The return-to-work (RTW) process after long-term sickness absence is often complex and long and implies multiple shifts between different labour market states for the absentee. Standard methods for examining RTW research typically rely on the analysis of one outcome measure at a time, which will not capture the many possible states and transitions the absentee can go through. The purpose of this study was to explore the potential added value of sequence analysis in supplement to standard regression analysis of a multidisciplinary RTW intervention among patients with low back pain (LBP). The study population consisted of 160 patients randomly allocated to either a hospital-based brief or a multidisciplinary intervention. Data on labour market participation following intervention were obtained from a national register and analysed in two ways: as a binary outcome expressed as active or passive relief at a 1-year follow-up and as four different categories for labour market participation. Logistic regression and sequence analysis were performed. The logistic regression analysis showed no difference in labour market participation for patients in the two groups after 1 year. Applying sequence analysis showed differences in subsequent labour market participation after 2 years after baseline in favour of the brief intervention group versus the multidisciplinary intervention group. The study indicated that sequence analysis could provide added analytical value as a supplement to traditional regression analysis in prospective studies of RTW among patients with LBP. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Application of two-dimensional binary fingerprinting methods for the design of selective Tankyrase I inhibitors.

PubMed

Muddukrishna, B S; Pai, Vasudev; Lobo, Richard; Pai, Aravinda

2017-11-22

In the present study, five important binary fingerprinting techniques were used to model novel flavones for the selective inhibition of Tankyrase I. From the fingerprints used: the fingerprint atom pairs resulted in a statistically significant 2D QSAR model using a kernel-based partial least square regression method. This model indicates that the presence of electron-donating groups positively contributes to activity, whereas the presence of electron withdrawing groups negatively contributes to activity. This model could be used to develop more potent as well as selective analogues for the inhibition of Tankyrase I. Schematic representation of 2D QSAR work flow.

Modification of the Sandwich Estimator in Generalized Estimating Equations with Correlated Binary Outcomes in Rare Event and Small Sample Settings

PubMed Central

Rogers, Paul; Stoner, Julie

2016-01-01

Regression models for correlated binary outcomes are commonly fit using a Generalized Estimating Equations (GEE) methodology. GEE uses the Liang and Zeger sandwich estimator to produce unbiased standard error estimators for regression coefficients in large sample settings even when the covariance structure is misspecified. The sandwich estimator performs optimally in balanced designs when the number of participants is large, and there are few repeated measurements. The sandwich estimator is not without drawbacks; its asymptotic properties do not hold in small sample settings. In these situations, the sandwich estimator is biased downwards, underestimating the variances. In this project, a modified form for the sandwich estimator is proposed to correct this deficiency. The performance of this new sandwich estimator is compared to the traditional Liang and Zeger estimator as well as alternative forms proposed by Morel, Pan and Mancl and DeRouen. The performance of each estimator was assessed with 95% coverage probabilities for the regression coefficient estimators using simulated data under various combinations of sample sizes and outcome prevalence values with an Independence (IND), Autoregressive (AR) and Compound Symmetry (CS) correlation structure. This research is motivated by investigations involving rare-event outcomes in aviation data. PMID:26998504

Logistic Regression and Path Analysis Method to Analyze Factors influencing Students’ Achievement

NASA Astrophysics Data System (ADS)

Noeryanti, N.; Suryowati, K.; Setyawan, Y.; Aulia, R. R.

2018-04-01

Students' academic achievement cannot be separated from the influence of two factors namely internal and external factors. The first factors of the student (internal factors) consist of intelligence (X1), health (X2), interest (X3), and motivation of students (X4). The external factors consist of family environment (X5), school environment (X6), and society environment (X7). The objects of this research are eighth grade students of the school year 2016/2017 at SMPN 1 Jiwan Madiun sampled by using simple random sampling. Primary data are obtained by distributing questionnaires. The method used in this study is binary logistic regression analysis that aims to identify internal and external factors that affect student’s achievement and how the trends of them. Path Analysis was used to determine the factors that influence directly, indirectly or totally on student’s achievement. Based on the results of binary logistic regression, variables that affect student’s achievement are interest and motivation. And based on the results obtained by path analysis, factors that have a direct impact on student’s achievement are students’ interest (59%) and students’ motivation (27%). While the factors that have indirect influences on students’ achievement, are family environment (97%) and school environment (37).

An Attempt at Quantifying Factors that Affect Efficiency in the Management of Solid Waste Produced by Commercial Businesses in the City of Tshwane, South Africa

PubMed Central

Worku, Yohannes; Muchie, Mammo

2012-01-01

Objective. The objective was to investigate factors that affect the efficient management of solid waste produced by commercial businesses operating in the city of Pretoria, South Africa. Methods. Data was gathered from 1,034 businesses. Efficiency in solid waste management was assessed by using a structural time-based model designed for evaluating efficiency as a function of the length of time required to manage waste. Data analysis was performed using statistical procedures such as frequency tables, Pearson's chi-square tests of association, and binary logistic regression analysis. Odds ratios estimated from logistic regression analysis were used for identifying key factors that affect efficiency in the proper disposal of waste. Results. The study showed that 857 of the 1,034 businesses selected for the study (83%) were found to be efficient enough with regards to the proper collection and disposal of solid waste. Based on odds ratios estimated from binary logistic regression analysis, efficiency in the proper management of solid waste was significantly influenced by 4 predictor variables. These 4 influential predictor variables are lack of adherence to waste management regulations, wrong perception, failure to provide customers with enough trash cans, and operation of businesses by employed managers, in a decreasing order of importance. PMID:23209483

National data study showed that adolescents living in poorer households and with one parent were more likely to be bullied.

PubMed

Låftman, S B; Fransson, E; Modin, B; Östberg, V

2017-12-01

The aim of this study was to assess whether sociodemographic household characteristics were associated with which Swedish adolescents were more likely to be bullied. The data were derived from the Swedish Living Conditions Survey and its child supplements from the survey years 2008-2011. The analyses included information on 3951 adolescents aged 10-18 years. Exposure to bullying was reported by adolescents, and information on sociodemographic household characteristics was reported by parents and obtained from official registers. Binary logistic regression was used to analyse the data. Adolescents were more likely to be bullied if they lived in households with no cash margin, defined as the ability to pay an unexpected bill of 8000 Swedish Kronor or about 800 Euros, and if they lived with just one custodial parent. In the unadjusted analyses, elevated risks were identified if adolescents lived in working class households and had unemployed and foreign-born parents. However, these associations were at least partly accounted for by other sociodemographic household characteristics, in particular the lack of a cash margin. This study showed that Swedish adolescents living in households with more limited financial resources had an increased risk of being bullied, supporting results from previous international research. ©2017 The Authors. Acta Paediatrica published by John Wiley & Sons Ltd on behalf of Foundation Acta Paediatrica.

Association of Brain-Derived Neurotrophic Factor and Vitamin D with Depression and Obesity: A Population-Based Study.

PubMed

Goltz, Annemarie; Janowitz, Deborah; Hannemann, Anke; Nauck, Matthias; Hoffmann, Johanna; Seyfart, Tom; Völzke, Henry; Terock, Jan; Grabe, Hans Jörgen

2018-06-19

Depression and obesity are widespread and closely linked. Brain-derived neurotrophic factor (BDNF) and vitamin D are both assumed to be associated with depression and obesity. Little is known about the interplay between vitamin D and BDNF. We explored the putative associations and interactions between serum BDNF and vitamin D levels with depressive symptoms and abdominal obesity in a large population-based cohort. Data were obtained from the population-based Study of Health in Pomerania (SHIP)-Trend (n = 3,926). The associations of serum BDNF and vitamin D levels with depressive symptoms (measured using the Patient Health Questionnaire) were assessed with binary and multinomial logistic regression models. The associations of serum BDNF and vitamin D levels with obesity (measured by the waist-to-hip ratio [WHR]) were assessed with binary logistic and linear regression models with restricted cubic splines. Logistic regression models revealed inverse associations of vitamin D with depression (OR = 0.966; 95% CI 0.951-0.981) and obesity (OR = 0.976; 95% CI 0.967-0.985). No linear association of serum BDNF with depression or obesity was found. However, linear regression models revealed a U-shaped association of BDNF with WHR (p < 0.001). Vitamin D was inversely associated with depression and obesity. BDNF was associated with abdominal obesity, but not with depression. At the population level, our results support the relevant roles of vitamin D and BDNF in mental and physical health-related outcomes. © 2018 S. Karger AG, Basel.

Dynamics of Volunteering in Older Europeans

ERIC Educational Resources Information Center

Hank, Karsten; Erlinghagen, Marcel

2010-01-01

Purpose: To investigate the dynamics of volunteering in the population aged 50 years or older across 11 Continental European countries. Design and Methods: Using longitudinal data from the first 2 waves of the Survey of Health, Ageing and Retirement in Europe, we run multivariate regressions on a set of binary-dependent variables indicating…

Who Benefits from Tuition Discounts at Public Universities?

ERIC Educational Resources Information Center

Hillman, Nicholas W.

2010-01-01

This article uses data from the 2004 National Postsecondary Student Aid Study to provide insight about the range of tuition discounting practices at public institutions. Specifically, it examines the characteristics of students who receive tuition discounts from public four-year colleges and universities. A binary logistic regression is applied to…

An Examination of Master's Student Retention & Completion

ERIC Educational Resources Information Center

Barry, Melissa; Mathies, Charles

2011-01-01

This study was conducted at a research-extensive public university in the southeastern United States. It examined the retention and completion of master's degree students across numerous disciplines. Results were derived from a series of descriptive statistics, T-tests, and a series of binary logistic regression models. The findings from binary…

Graduate Unemployment in South Africa: Social Inequality Reproduced

ERIC Educational Resources Information Center

Baldry, Kim

2016-01-01

In this study, I examine the influence of demographic and educational characteristics of South African graduates on their employment/unemployment status. A sample of 1175 respondents who graduated between 2006 and 2012 completed an online survey. Using binary logistic regression, the strongest determinants of unemployment were the graduates' race,…

Commitment of Licensed Social Workers to Aging Practice

ERIC Educational Resources Information Center

Simons, Kelsey; Bonifas, Robin; Gammonley, Denise

2011-01-01

This study sought to identify client, professional, and employment characteristics that enhance licensed social workers' commitment to aging practice. A series of binary logistic regressions were performed using data from 181 licensed, full-time social workers who reported aging as their primary specialty area as part of the 2004 NASW's national…

Evaluating uses of data mining techniques in propensity score estimation: a simulation study.

PubMed

Setoguchi, Soko; Schneeweiss, Sebastian; Brookhart, M Alan; Glynn, Robert J; Cook, E Francis

2008-06-01

In propensity score modeling, it is a standard practice to optimize the prediction of exposure status based on the covariate information. In a simulation study, we examined in what situations analyses based on various types of exposure propensity score (EPS) models using data mining techniques such as recursive partitioning (RP) and neural networks (NN) produce unbiased and/or efficient results. We simulated data for a hypothetical cohort study (n = 2000) with a binary exposure/outcome and 10 binary/continuous covariates with seven scenarios differing by non-linear and/or non-additive associations between exposure and covariates. EPS models used logistic regression (LR) (all possible main effects), RP1 (without pruning), RP2 (with pruning), and NN. We calculated c-statistics (C), standard errors (SE), and bias of exposure-effect estimates from outcome models for the PS-matched dataset. Data mining techniques yielded higher C than LR (mean: NN, 0.86; RPI, 0.79; RP2, 0.72; and LR, 0.76). SE tended to be greater in models with higher C. Overall bias was small for each strategy, although NN estimates tended to be the least biased. C was not correlated with the magnitude of bias (correlation coefficient [COR] = -0.3, p = 0.1) but increased SE (COR = 0.7, p < 0.001). Effect estimates from EPS models by simple LR were generally robust. NN models generally provided the least numerically biased estimates. C was not associated with the magnitude of bias but was with the increased SE.

Correction factors for on-line microprobe analysis of multielement alloy systems

NASA Technical Reports Server (NTRS)

Unnam, J.; Tenney, D. R.; Brewer, W. D.

1977-01-01

An on-line correction technique was developed for the conversion of electron probe X-ray intensities into concentrations of emitting elements. This technique consisted of off-line calculation and representation of binary interaction data which were read into an on-line minicomputer to calculate variable correction coefficients. These coefficients were used to correct the X-ray data without significantly increasing computer core requirements. The binary interaction data were obtained by running Colby's MAGIC 4 program in the reverse mode. The data for each binary interaction were represented by polynomial coefficients obtained by least-squares fitting a third-order polynomial. Polynomial coefficients were generated for most of the common binary interactions at different accelerating potentials and are included. Results are presented for the analyses of several alloy standards to demonstrate the applicability of this correction procedure.

Neutron-star–black-hole binaries produced by binary-driven hypernovae

DOE PAGES

Fryer, Chris L.; Oliveira, F. G.; Rueda, Jorge A.; ...

2015-12-04

Here, binary-driven hypernovae (BdHNe) within the induced gravitational collapse paradigm have been introduced to explain energetic (E iso ≳10 52 erg), long gamma-ray bursts (GRBs) associated with type Ic supernovae (SNe). The progenitor is a tight binary composed of a carbon-oxygen (CO) core and a neutron-star (NS) companion, a subclass of the newly proposed “ultrastripped” binaries. The CO-NS short-period orbit causes the NS to accrete appreciable matter from the SN ejecta when the CO core collapses, ultimately causing it to collapse to a black hole (BH) and producing a GRB. These tight binaries evolve through the SN explosion very differentlymore » than compact binaries studied in population synthesis calculations. First, the hypercritical accretion onto the NS companion alters both the mass and the momentum of the binary. Second, because the explosion time scale is on par with the orbital period, the mass ejection cannot be assumed to be instantaneous. This dramatically affects the post-SN fate of the binary. Finally, the bow shock created as the accreting NS plows through the SN ejecta transfers angular momentum, braking the orbit. These systems remain bound even if a large fraction of the binary mass is lost in the explosion (well above the canonical 50% limit), and even large kicks are unlikely to unbind the system. Indeed, BdHNe produce a new family of NS-BH binaries unaccounted for in current population synthesis analyses and, although they may be rare, the fact that nearly 100% remain bound implies that they may play an important role in the compact merger rate, important for gravitational waves that, in turn, can produce a new class of ultrashort GRBs.« less

Neutron-Star-Black-Hole Binaries Produced by Binary-Driven Hypernovae.

PubMed

Fryer, Chris L; Oliveira, F G; Rueda, J A; Ruffini, R

2015-12-04

Binary-driven hypernovae (BdHNe) within the induced gravitational collapse paradigm have been introduced to explain energetic (E_{iso}≳10^{52}  erg), long gamma-ray bursts (GRBs) associated with type Ic supernovae (SNe). The progenitor is a tight binary composed of a carbon-oxygen (CO) core and a neutron-star (NS) companion, a subclass of the newly proposed "ultrastripped" binaries. The CO-NS short-period orbit causes the NS to accrete appreciable matter from the SN ejecta when the CO core collapses, ultimately causing it to collapse to a black hole (BH) and producing a GRB. These tight binaries evolve through the SN explosion very differently than compact binaries studied in population synthesis calculations. First, the hypercritical accretion onto the NS companion alters both the mass and the momentum of the binary. Second, because the explosion time scale is on par with the orbital period, the mass ejection cannot be assumed to be instantaneous. This dramatically affects the post-SN fate of the binary. Finally, the bow shock created as the accreting NS plows through the SN ejecta transfers angular momentum, braking the orbit. These systems remain bound even if a large fraction of the binary mass is lost in the explosion (well above the canonical 50% limit), and even large kicks are unlikely to unbind the system. Indeed, BdHNe produce a new family of NS-BH binaries unaccounted for in current population synthesis analyses and, although they may be rare, the fact that nearly 100% remain bound implies that they may play an important role in the compact merger rate, important for gravitational waves that, in turn, can produce a new class of ultrashort GRBs.

Neutron-Star-Black-Hole Binaries Produced by Binary-Driven Hypernovae

NASA Astrophysics Data System (ADS)

Fryer, Chris L.; Oliveira, F. G.; Rueda, J. A.; Ruffini, R.

2015-12-01

Binary-driven hypernovae (BdHNe) within the induced gravitational collapse paradigm have been introduced to explain energetic (Eiso≳1052 erg ), long gamma-ray bursts (GRBs) associated with type Ic supernovae (SNe). The progenitor is a tight binary composed of a carbon-oxygen (CO) core and a neutron-star (NS) companion, a subclass of the newly proposed "ultrastripped" binaries. The CO-NS short-period orbit causes the NS to accrete appreciable matter from the SN ejecta when the CO core collapses, ultimately causing it to collapse to a black hole (BH) and producing a GRB. These tight binaries evolve through the SN explosion very differently than compact binaries studied in population synthesis calculations. First, the hypercritical accretion onto the NS companion alters both the mass and the momentum of the binary. Second, because the explosion time scale is on par with the orbital period, the mass ejection cannot be assumed to be instantaneous. This dramatically affects the post-SN fate of the binary. Finally, the bow shock created as the accreting NS plows through the SN ejecta transfers angular momentum, braking the orbit. These systems remain bound even if a large fraction of the binary mass is lost in the explosion (well above the canonical 50% limit), and even large kicks are unlikely to unbind the system. Indeed, BdHNe produce a new family of NS-BH binaries unaccounted for in current population synthesis analyses and, although they may be rare, the fact that nearly 100% remain bound implies that they may play an important role in the compact merger rate, important for gravitational waves that, in turn, can produce a new class of ultrashort GRBs.

Light Curve and Orbital Period Analysis of VX Lac

NASA Astrophysics Data System (ADS)

Yılmaz, M.; Nelson, R. H.; Şenavcı, H. V.; İzci, D.; Özavcı, İ.; Gümüş, D.

2017-04-01

In this study, we performed simultaneously light curve and radial velocity, and also period analyses of the eclipsing binary system VX Lac. Four color (BVRI) light curves of the system were analysed using the W-D code. The results imply that VX Lac is a classic Algol-type binary with a mass ratio of q=0.27, of which the less massive secondary component fills its Roche lobe. The orbital period behaviour of the system was analysed by assuming the light time effect (LITE) from a third body. The O-C analysis yielded a mass transfer rate of dM/dt=1.86×10-8M⊙yr-1 and the minimal mass of the third body to be M3=0.31M⊙. The residuals from mass transfer and the third body were also analysed because another cyclic variation is seen in O-C diagram. This periodic variation was examined under the hypotheses of stellar magnetic activity and fourth body.

Logistic random effects regression models: a comparison of statistical packages for binary and ordinal outcomes.

PubMed

Li, Baoyue; Lingsma, Hester F; Steyerberg, Ewout W; Lesaffre, Emmanuel

2011-05-23

Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. We used individual patient data from 8509 patients in 231 centers with moderate and severe Traumatic Brain Injury (TBI) enrolled in eight Randomized Controlled Trials (RCTs) and three observational studies. We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS) as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. We then compared the implementations of frequentist and Bayesian methods to estimate the fixed and random effects. Frequentist approaches included R (lme4), Stata (GLLAMM), SAS (GLIMMIX and NLMIXED), MLwiN ([R]IGLS) and MIXOR, Bayesian approaches included WinBUGS, MLwiN (MCMC), R package MCMCglmm and SAS experimental procedure MCMC.Three data sets (the full data set and two sub-datasets) were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. For the ordinal outcome in the full data set also a proportional odds model with a random center effect was fitted. The packages gave similar parameter estimates for both the fixed and random effects and for the binary (and ordinal) models for the main study and when based on a relatively large number of level-1 (patient level) data compared to the number of level-2 (hospital level) data. However, when based on relatively sparse data set, i.e. when the numbers of level-1 and level-2 data units were about the same, the frequentist and Bayesian approaches showed somewhat different results. The software implementations differ considerably in flexibility, computation time, and usability. There are also differences in the availability of additional tools for model evaluation, such as diagnostic plots. The experimental SAS (version 9.2) procedure MCMC appeared to be inefficient. On relatively large data sets, the different software implementations of logistic random effects regression models produced similar results. Thus, for a large data set there seems to be no explicit preference (of course if there is no preference from a philosophical point of view) for either a frequentist or Bayesian approach (if based on vague priors). The choice for a particular implementation may largely depend on the desired flexibility, and the usability of the package. For small data sets the random effects variances are difficult to estimate. In the frequentist approaches the MLE of this variance was often estimated zero with a standard error that is either zero or could not be determined, while for Bayesian methods the estimates could depend on the chosen "non-informative" prior of the variance parameter. The starting value for the variance parameter may be also critical for the convergence of the Markov chain.

Use of generalized ordered logistic regression for the analysis of multidrug resistance data.

PubMed

Agga, Getahun E; Scott, H Morgan

2015-10-01

Statistical analysis of antimicrobial resistance data largely focuses on individual antimicrobial's binary outcome (susceptible or resistant). However, bacteria are becoming increasingly multidrug resistant (MDR). Statistical analysis of MDR data is mostly descriptive often with tabular or graphical presentations. Here we report the applicability of generalized ordinal logistic regression model for the analysis of MDR data. A total of 1,152 Escherichia coli, isolated from the feces of weaned pigs experimentally supplemented with chlortetracycline (CTC) and copper, were tested for susceptibilities against 15 antimicrobials and were binary classified into resistant or susceptible. The 15 antimicrobial agents tested were grouped into eight different antimicrobial classes. We defined MDR as the number of antimicrobial classes to which E. coli isolates were resistant ranging from 0 to 8. Proportionality of the odds assumption of the ordinal logistic regression model was violated only for the effect of treatment period (pre-treatment, during-treatment and post-treatment); but not for the effect of CTC or copper supplementation. Subsequently, a partially constrained generalized ordinal logistic model was built that allows for the effect of treatment period to vary while constraining the effects of treatment (CTC and copper supplementation) to be constant across the levels of MDR classes. Copper (Proportional Odds Ratio [Prop OR]=1.03; 95% CI=0.73-1.47) and CTC (Prop OR=1.1; 95% CI=0.78-1.56) supplementation were not significantly associated with the level of MDR adjusted for the effect of treatment period. MDR generally declined over the trial period. In conclusion, generalized ordered logistic regression can be used for the analysis of ordinal data such as MDR data when the proportionality assumptions for ordered logistic regression are violated. Published by Elsevier B.V.

Health behaviours associated with indoor tanning based on the 2012/13 Manitoba Youth Health Survey

PubMed Central

Harland, E.; Griffith, J.; Lu, H.; Erickson, T.; Magsino, K.

2016-01-01

Abstract Introduction: Although indoor tanning causes cancer, it remains relatively common among adolescents. Little is known about indoor tanning prevalence and habits in Canada, and even less about associated behaviours. This study explores the prevalence of adolescent indoor tanning in Manitoba and its association with other demographic characteristics and health behaviours. Methods: We conducted secondary analyses of the 2012/13 Manitoba Youth Health Survey data collected from Grade 7 to 12 students (n = 64 174) and examined associations between indoor tanning (whether participants had ever used artificial tanning equipment) and 25 variables. Variables with statistically significant associations to indoor tanning were tested for collinearity and grouped based on strong associations. For each group of highly associated variables, the variable with the greatest effect upon indoor tanning was placed into the final logistic regression model. Separate analyses were conducted for males and females to better understand sex-based differences, and analyses were adjusted for age. Results: Overall, 4% of male and 9% of female students reported indoor tanning, and prevalence increased with age. Relationships between indoor tanning and other variables were similar for male and female students. Binary logistic regression models indicated that several variables significantly predicted indoor tanning, including having part-time work, being physically active, engaging in various risk behaviours such as driving after drinking for males and unplanned sex after alcohol/drugs for females, experiencing someone say something bad about one’s body shape/size/appearance, identifying as trans or with another gender, consuming creatine/other supplements and, for females only, never/rarely using sun protection. Conclusion: Indoor tanning among adolescents was associated with age, part-time work, physical activity and many consumption behaviours and lifestyle risk factors. Though legislation prohibiting adolescent indoor tanning is critical, health promotion to discourage indoor tanning may be most beneficial if it also addresses these associated factors. PMID:27556919

Health behaviours associated with indoor tanning based on the 2012/13 Manitoba Youth Health Survey.

PubMed

Harland, E; Griffith, J; Lu, H; Erickson, T; Magsino, K

2016-08-01

Although indoor tanning causes cancer, it remains relatively common among adolescents. Little is known about indoor tanning prevalence and habits in Canada, and even less about associated behaviours. This study explores the prevalence of adolescent indoor tanning in Manitoba and its association with other demographic characteristics and health behaviours. We conducted secondary analyses of the 2012/13 Manitoba Youth Health Survey data collected from Grade 7 to 12 students (n = 64 174) and examined associations between indoor tanning (whether participants had ever used artificial tanning equipment) and 25 variables. Variables with statistically significant associations to indoor tanning were tested for collinearity and grouped based on strong associations. For each group of highly associated variables, the variable with the greatest effect upon indoor tanning was placed into the final logistic regression model. Separate analyses were conducted for males and females to better understand sex-based differences, and analyses were adjusted for age. Overall, 4% of male and 9% of female students reported indoor tanning, and prevalence increased with age. Relationships between indoor tanning and other variables were similar for male and female students. Binary logistic regression models indicated that several variables significantly predicted indoor tanning, including having part-time work, being physically active, engaging in various risk behaviours such as driving after drinking for males and unplanned sex after alcohol/drugs for females, experiencing someone say something bad about one's body shape/size/appearance, identifying as trans or with another gender, consuming creatine/other supplements and, for females only, never/rarely using sun protection. Indoor tanning among adolescents was associated with age, part-time work, physical activity and many consumption behaviours and lifestyle risk factors. Though legislation prohibiting adolescent indoor tanning is critical, health promotion to discourage indoor tanning may be most beneficial if it also addresses these associated factors.

Early presence of anti-angiogenesis-related adverse events as a potential biomarker of antitumor efficacy in metastatic gastric cancer patients treated with apatinib: a cohort study.

PubMed

Liu, Xinyang; Qin, Shukui; Wang, Zhichao; Xu, Jianming; Xiong, Jianping; Bai, Yuxian; Wang, Zhehai; Yang, Yan; Sun, Guoping; Wang, Liwei; Zheng, Leizhen; Xu, Nong; Cheng, Ying; Guo, Weijian; Yu, Hao; Liu, Tianshu; Lagiou, Pagona; Li, Jin

2017-09-05

Reliable biomarkers of apatinib response in gastric cancer (GC) are lacking. We investigated the association between early presence of common adverse events (AEs) and clinical outcomes in metastatic GC patients. We conducted a retrospective cohort study using data on 269 apatinib-treated GC patients in two clinical trials. AEs were assessed at baseline until 28 days after the last dose of apatinib. Clinical outcomes were compared between patients with and without hypertension (HTN), proteinuria, or hand and foot syndrome (HFS) in the first 4 weeks. Time-to-event variables were assessed using Kaplan-Meier methods and Cox proportional hazard regression models. Binary endpoints were assessed using logistic regression models. Landmark analyses were performed as sensitivity analyses. Predictive model was analyzed, and risk scores were calculated to predict overall survival. Presence of AEs in the first 4 weeks was associated with prolonged median overall survival (169 vs. 103 days, log-rank p = 0.0039; adjusted hazard ratio (HR) 0.64, 95% confidence interval [CI] 0.64-0.84, p = 0.001), prolonged median progression-free survival (86.5 vs. 62 days, log-rank p = 0.0309; adjusted HR 0.69, 95% CI 0.53-0.91, p = 0.007), and increased disease control rate (54.67 vs. 32.77%; adjusted odds ratio 2.67, p < 0.001). Results remained significant in landmark analyses. The onset of any single AE or any combinations of the AEs were all statistically significantly associated with prolonged OS, except for the presence of proteinuria. An AE-based prediction model and subsequently derived scoring system showed high calibration and discrimination in predicting overall survival. Presence of HTN, proteinuria, or HFS during the first cycle of apatinib treatment was a viable biomarker of antitumor efficacy in metastatic GC patients.

Low comorbid obsessive-compulsive disorder in patients with major depressive disorder - Findings from a European multicenter study.

PubMed

Dold, Markus; Bartova, Lucie; Souery, Daniel; Mendlewicz, Julien; Porcelli, Stefano; Serretti, Alessandro; Zohar, Joseph; Montgomery, Stuart; Kasper, Siegfried

2018-02-01

This cross-sectional European multicenter study examined the association between major depressive disorder (MDD) and comorbid obsessive-compulsive disorder (OCD). Socio-demographic, clinical, and treatment features of 1346 adult MDD patients were compared between MDD subjects with and without concurrent OCD using descriptive statistics, analyses of covariance (ANCOVA), and binary logistic regression analyses. We determined a point prevalence of comorbid OCD in MDD of 1.65%. In comparison to the MDD control group without concurrent OCD, a higher proportion of patients in the MDD + comorbid OCD group displayed concurrent panic disorder (31.81% vs 7.77%, p<.001), suicide risk (52.80% vs 44.81%, p=.04), polypsychopharmacy (95.45% vs 60.21%, p=.001), and augmentation treatment with antipsychotics (50.00% vs 25.46%, p=.01) and benzodiazepines (68.18% vs 33.31%, p=.001). Moreover, they were treated with higher mean doses of their antidepressant drugs (in fluoxetine equivalents: 48.99mg/day ± 18.81 vs 39.68mg/day ± 20.75, p=.04). In the logistic regression analyses, comorbid panic disorder (odds ratio (OR)=4.17, p=.01), suicide risk (OR=2.56, p=.04), simultaneous treatment with more psychiatric drugs (OR=1.51, p=<.05), polypsychopharmacy (OR=14.29, p=.01), higher antidepressant dosing (OR=1.01, p=<.05), and augmentation with antipsychotics (OR=2.94, p=.01) and benzodiazepines (OR=4.35, p=.002) were significantly associated with comorbid OCD. In summary, our findings suggest that concurrent OCD in MDD (1) has a low prevalence rate compared to the reverse prevalence rates of comorbid MDD in OCD, (2) provokes higher suicide risk, and (3) is associated with a characteristic prescription pattern reflected by a high amount of polypsychopharmaceutical treatment strategies comprising particularly augmentation with antipsychotics and benzodiazepines. Copyright © 2017 Elsevier B.V. All rights reserved.

Emotion-related personality traits and peer social standing: unique and interactive effects in cyberbullying behaviors.

PubMed

Ciucci, Enrica; Baroncelli, Andrea

2014-09-01

This study investigated the unique and interactive effects of emotion-related personality traits (i.e., callousness and uncaring traits) and peer social standing (i.e., social preference and perceived popularity) on cyberbullying behaviors in preadolescents. A total of 529 preadolescents (247 boys, 46.69%) were recruited from an Italian middle school (Mage=12 years and 7 months; SD=1 year and 2 months). The participants primarily consisted of Italian children (91.12%). A series of binary logistic regression analyses parted by gender were conducted to examine the main and interactive effects of self-reported emotion-related variables and peer-reported social standing in the prediction of self-reported cyberbullying behaviors, while controlling for cyber victimization and grade effects. In girls, an uncaring disposition was directly associated with cyberbullying behaviors, whereas in boys this association only emerged for those with low perceived popularity. Our results indicated that, in developing anti(cyber)bullying programs, school researchers and practitioners should jointly consider individual and contextual factors.

Predictors of online and offline sexual activities and behaviors among adolescents.

PubMed

Sevčíková, Anna; Vazsonyi, Alexander T; Sirůček, Jan; Konečný, Stěpán

2013-08-01

Despite the fact that many adolescents spend much time on the Internet, it is unknown who engages in sexually related online activities (SROA) and how these affect adolescent sexual development. The present longitudinal study on 323 adolescents (51.1% girls) aimed to explore how peer attachment processes predicted both SROA and offline sexual behaviors at the age of 17, while also considering puberty and prior offline sexual experiences in order to elucidate potential similarities or differences. Findings based on hierarchical, binary logistic regression analyses revealed that SROA were predicted by alienation attachment to peers (OR=3.36, p<0.05), puberty (OR=1.03, p<0.05), and prior SROA (OR=0.56, p<0.001), while only previous offline sexual experiences at the age of 15 increased the likelihood of offline sexual behaviors at the age of 17 (OR=6.04, p<0.001). Study findings indicate that the Internet provides an additional context for acquiring sexual experiences during adolescence.

Association of BPD and IVH with early neutrophil and white counts in VLBW neonates with gestational age <32 weeks

PubMed Central

Palta, Mari; Sadek-Badawi, Mona; Carlton, David P

2008-01-01

Objectives To investigate associations between early low neutrophil count from routine blood samples, white blood count (WBC), pregnancy complications and neonatal outcomes for very low birth weight infants (VLBW ≤1500g) with gestational age <32 weeks. Patients and Methods Information was abstracted on all infants admitted to level III NICUs in Wisconsin 2003-2004. 1002 (78%) had differential and corrected total white counts within 2 ½ hours of birth. Data analyses included frequency tables, binary logistic, ordinal logistc and ordinary regression. Results Low neutrophil count (<1000/μL) was strongly associated with low WBC, pregnancy complications and antenatal steroids. Low neutrophil count predicted bronchopulmonary dysplasia severity level (BPD) (OR: 1.7, 95% CI: 1.1-2.7) and intraventricular hemorrhage (IVH) grade (OR: 2.2, 95% CI: 1.3-3.8). Conclusions Early neutrophil counts may have multiple causes interfering with their routine use as an inflammatory marker. Nonetheless, low neutrophil count has consistent independent associations with outcomes. PMID:18563166

Safer sex negotiation and its association with condom use among clients of female sex workers in Bangladesh.

PubMed

Kamal, S M Mostafa; Hassan, Che Hashim; Salikon, Roslan Hj

2015-03-01

This study examines safer sex negotiation and its association with condom use among clients of female sex workers (FSWs) in Bangladesh. Data were collected from 484 FSWs living in Dhaka city following a convenient sampling procedure. Overall, 47% of the clients were suggested to use condom during last sexual intercourse and 21% did so. Both bivariate and multivariable binary logistic regression analyses yielded significantly increased risk of negotiation for safer sex with clients among FSWs with higher education. The power bargaining significantly (P < .001) increased the risk of condom use by 2.15 times (95% confidence interval = 1.28-3.59). The odds of condom use were significantly higher among the FSWs with higher education, unmarried, hotel-based, and among those with higher level of HIV/AIDS-related knowledge. The Bangladeshi FSWs have little control over their profession. HIV prevention programs should aim to encourage FSWs through information, education, and communication program to insist on condom use among clients. © 2013 APJPH.

Quantitative Analysis of Driving Factors of Grassland Degradation: A Case Study in Xilin River Basin, Inner Mongolia

PubMed Central

Xie, Yichun; Sha, Zongyao

2012-01-01

Current literature suggests that grassland degradation occurs in areas with poor soil conditions or noticeable environmental changes and is often a result of overgrazing or human disturbances. However, these views are questioned in our analyses. Based on the analysis of satellite vegetation maps from 1984, 1998, and 2004 for the Xilin River Basin, Inner Mongolia, China, and binary logistic regression (BLR) analysis, we observe the following: (1) grassland degradation is positively correlated with the growth density of climax communities; (2) our findings do not support a common notion that a decrease of biological productivity is a direct indicator of grassland degradation; (3) a causal relationship between grazing intensity and grassland degradation was not found; (4) degradation severity increased steadily towards roads but showed different trends near human settlements. This study found complex relationships between vegetation degradation and various microhabitat conditions, for example, elevation, slope, aspect, and proximity to water. PMID:22619613

Prevalence of Smoking and Associated Factors: Evidence From the CHILILAB Demographic Surveillance System in Vietnam.

PubMed

Thi Thanh Huong, Le; Khanh Long, Tran; Xuan Son, Phung; Thi Tuyet-Hanh, Tran

2017-07-01

This study analyzed secondary data from Chi Linh Health and Demographic Surveillance System (CHILILAB) database to identify smoking prevalence and associated demographic factors. Data were extracted from the database of the CHILILAB 2016, which included information on individual smoking behaviors, as well as individual and household demographic data. Descriptive and binary logistic regression analyses were performed with significance level of 0.05. The smoking prevalences were 34.7%, 0.9%, and 16.1% for men, women, and both genders, respectively. A total of 78.2% of current smokers smoked daily inside their houses. Lower smoking status was associated with younger age, being student, rich, and/or single. Future efforts should not only spend on further reduction of smoking rate in Chi Linh Town but should also pay special attention on reducing the prevalence of in-home smoking. This will help to decrease the risk of nonsmokers being exposed to secondhand smoke in their home environment.

Population Pharmacokinetics, Pharmacodynamics, and Exploratory Exposure–Response Analyses of Apixaban in Subjects Treated for Venous Thromboembolism

PubMed Central

Sweeney, K; Frost, C; Boyd, RA

2017-01-01

Apixaban is approved for treatment of venous thromboembolism (VTE) and prevention of recurrence. Population pharmacokinetics, pharmacokinetics–pharmacodynamics (anti‐FXa activity), and exposure–response (binary bleeding and thromboembolic endpoints) of apixaban in VTE treatment subjects were characterized using data from phase I–III studies. Apixaban pharmacokinetics were adequately characterized by a two‐compartment model with first‐order absorption and elimination. Age, sex, and Asian race had less than 25% impact on exposure, while subjects with severe renal impairment were predicted to have 56% higher exposure than the reference subject (60‐year‐old non‐Asian male weighing 85 kg with creatinine clearance of 100 mL/min). The relationship between apixaban concentration and anti‐FXa activity was described by a linear model with a slope estimate of 0.0159 IU/ng. The number of subjects with either a bleeding or thromboembolic event was small, and no statistically significant relationship between apixaban exposure and clinical endpoints could be discerned with a logistic regression analysis. PMID:28547774

Health Implications of Adults' Eating at and Living near Fast Food or Quick Service Restaurants

PubMed Central

Jiao, J; Moudon, A V; Kim, S Y; Hurvitz, P M; Drewnowski, A

2015-01-01

Background: This paper examined whether the reported health impacts of frequent eating at a fast food or quick service restaurant on health were related to having such a restaurant near home. Methods: Logistic regressions estimated associations between frequent fast food or quick service restaurant use and health status, being overweight or obese, having a cardiovascular disease or diabetes, as binary health outcomes. In all, 2001 participants in the 2008–2009 Seattle Obesity Study survey were included in the analyses. Results: Results showed eating ⩾2 times a week at a fast food or quick service restaurant was associated with perceived poor health status, overweight and obese. However, living close to such restaurants was not related to negative health outcomes. Conclusions: Frequent eating at a fast food or quick service restaurant was associated with perceived poor health status and higher body mass index, but living close to such facilities was not. PMID:26192449

Gender differences in physical disability among older adults in underprivileged communities in Lebanon.

PubMed

Zeki Al Hazzouri, Adina; Mehio Sibai, Abla; Chaaya, Monique; Mahfoud, Ziyad; Yount, Kathryn M

2011-03-01

To examine the role of health conditions, socioeconomic, and socioenvironmental factors in explaining gender differences in physical disability among older adults. We compared 412 women and 328 men residing in underprivileged communities in Lebanon on their activities of daily living (ADL), instrumental activities of daily living (IADL), and physical tasks (PT). Binary logistic regression analyses adjusting for possible explanatory covariates were conducted sequentially. Women showed higher prevalence rates of ADL, IADL, and PT compared to men. Gender disparities in ADL disability were explained by chronic-disease risk factors and health conditions (OR = 1.46; 95% CI = 0.94-2.25). The odds of disability in IADL and PT remained significantly higher for women compared to men after accounting for all available covariates. These results suggest underlying differences in functional status between women and men, yet, may have been influenced by the sensitivity of the measures to the social context and gendered environment surrounding daily activities.

Bayesian multivariate hierarchical transformation models for ROC analysis.

PubMed

O'Malley, A James; Zou, Kelly H

2006-02-15

A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box-Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial.

Bayesian multivariate hierarchical transformation models for ROC analysis

PubMed Central

O'Malley, A. James; Zou, Kelly H.

2006-01-01

SUMMARY A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box–Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial. PMID:16217836

Religious Social Support and Hypertension Among Older North American Seventh-Day Adventists.

PubMed

Charlemagne-Badal, Sherma J; Lee, Jerry W

2016-04-01

Seventh-day Adventists have been noted for their unique lifestyle, religious practices and longevity. However, we know little about how religion is directly related to health in this group. Specifically, we know nothing about how religious social support is related to hypertension. Using data from the Biopsychosocial Religion and Health Study, we carried out a cross-sectional study of 9581 and a prospective study of 5720 North American Seventh-day Adventists examining new 534 cases of hypertension occurring up to 4 years later. We used binary logistic regression analyses to examine study hypotheses. Of the religious social support variables, in both the cross-sectional and prospective study only anticipated support significantly predicted hypertension, but the relationship was mediated by BMI. There were no significant race or gender differences. The favorable relationships between anticipated support and hypertension appear to be mediated by BMI and are an indication of how this dimension of religion combined with lifestyle promotes good health, specifically, reduced risk of hypertension.

Correlates of Worry About Health Care Costs Among Older Adults.

PubMed

Choi, Namkee G; DiNitto, Diana M

2018-06-01

Although older adults in the United States incur more health care expenses than younger adults, little research has been done on their worry about health care costs. Using data from the 2013 National Health Interview Survey ( n = 7,253 for those 65+ years), we examined factors associated with older adults' health care cost worries, defined as at least a moderate level of worry, about ability to pay for normal health care and/or for health care due to a serious illness or accident. Bivariate analyses were used to compare worriers and nonworriers. Binary logistic regression analysis was used to examine the association of income, health status, health care service use, and insurance type with worry status. Older age and having Medicaid and Veterans Affairs (VA)/military health benefits were associated with lower odds of worry, while low income, chronic pain, functional limitations, psychological distress, and emergency department visits were associated with higher odds. Practice and policy implications for the findings are discussed.

Epidemiological, clinical and laboratory profile of scrub typhus cases detected by serology and RT-PCR in Kumaon, Uttarakhand: a hospital-based study.

PubMed

Rawat, Vinita; Singh, Rajesh Kumar; Kumar, Ashok; Saxena, Sandip R; Varshney, Umesh; Kumar, Mukesh

2018-04-01

We analysed the epidemiology, clinical and laboratory data of the 168 scrub typhus cases confirmed by a combination of any one of the following: real time polymerase chain reaction (RT-PCR) and/or immunofluorescence assay (IFA) (IgM and/or IgG). The peak season for scrub typhus was from July to October. By multivariate binary logistic regression analysis, the risk of scrub typhus was about four times in those working in occupation related to forest work. Major clinical manifestations were fever (100%), myalgia (65%), cough (51%) and vomiting (46%); major complications were meningitis/meningoencephatilitis (12.5%) and multi-organ failure (MOF) and pneumonia (5.3% each). Laboratory investigations revealed raised aminotranferase levels and thrombocytopenia in most confirmed cases. We conclude that scrub typhus is an important cause of febrile illness in the Kumaon hills of Uttarakhand where this disease had not previously been considered to exist.

Postsurgical complications in patients with renal tumours with venous thrombosis treated with surgery.

PubMed

Caño-Velasco, J; Herranz-Amo, F; Barbas-Bernardos, G; Mayor-de Castro, J; Aragón-Chamizo, J; Arnal-Chacón, G; Lledó García, E; Hernández-Fernández, C

2018-04-06

Surgery on renal tumours with venous thrombosis suffers a high rate of complications and non-negligible perioperative mortality. Our objective was to analyse the postoperative complications, their relationship with the level of the thrombus and its potential predisposing factors. A retrospective analysis was conducted of 101 patients with renal tumours with venous thrombosis operated on between 1988 and 2017. Two patients were excluded because of intraoperative pulmonary thromboembolism and exitus (2%). The postsurgical complications were classified according to Clavien-Dindo. To compare the qualitative variables, we employed the chi-squared test. We performed a multivariate analysis using binary logistic regression to identify the independent predictors. Some type of postsurgical complication occurred in 34 (34.3%) patients, 11 (11.1%) of which were severe (Clavien III-V). There were significant differences in the total complications (P=.003) and severe complications (Clavien≥III; P=.03) depending on the level of the tumour thrombus. Copyright © 2018 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

An examination of the MASC Social Anxiety Scale in a non-referred sample of adolescents.

PubMed

Anderson, Emily R; Jordan, Judith A; Smith, Ashley J; Inderbitzen-Nolan, Heidi M

2009-12-01

Social phobia is prevalent during adolescence and is associated with negative outcomes. Two self-report instruments are empirically validated to specifically assess social phobia symptomatology in youth: the Social Phobia and Anxiety Inventory for Children and the Social Anxiety Scale for Adolescents. The Multidimensional Anxiety Scale for Children is a broad-band measure of anxiety containing a scale assessing the social phobia construct. The present study investigated the MASC Social Anxiety Scale in relation to other well-established measures of social phobia and depression in a non-referred sample of adolescents. Results support the convergent validity of the MASC Social Anxiety Scale and provide some support for its discriminant validity, suggesting its utility in the initial assessment of social phobia. Receiver Operating Characteristics (ROCs) calculated the sensitivity and specificity of the MASC Social Anxiety Scale. Binary logistic regression analyses determined the predictive utility of the MASC Social Anxiety Scale. Implications for assessment are discussed.

Impact of Perceived Risk and Friend Influence on Alcohol and Marijuana Use Among Students.

PubMed

Merianos, Ashley L; Rosen, Brittany L; Montgomery, LaTrice; Barry, Adam E; Smith, Matthew Lee

2017-12-01

We performed a secondary analysis of Adolescent Health Risk Behavior Survey data ( N = 937), examining associations between lifetime alcohol and marijuana use with intrapersonal (i.e., risk perceptions) and interpersonal (e.g., peer approval and behavior) factors. Multinomial and binary logistic regression analyses contend students reporting lifetime alcohol use-compared to students who had never used alcohol or marijuana-perceived lower alcohol risk ( p < .001), higher friend drinking approval ( p < .001), and greater friend drinking ( p = .003). Using both alcohol and marijuana in one's life was associated with being in public schools ( p = .010), higher grade levels ( p = .001), lower perceived alcohol ( p = .011) and marijuana use risk ( p = .003), higher friend approval of alcohol ( p < .001) and marijuana use ( p < .001), and believed more friends used alcohol ( p < .001). Compared to lifetime alcohol only, perceived friend academic performance decreased the risk of lifetime alcohol and marijuana use ( p = .043). Findings are beneficial to school nurses with students experiencing effects associated with substance use.

A comparison of multiple imputation methods for incomplete longitudinal binary data.

PubMed

Yamaguchi, Yusuke; Misumi, Toshihiro; Maruo, Kazushi

2018-01-01

Longitudinal binary data are commonly encountered in clinical trials. Multiple imputation is an approach for getting a valid estimation of treatment effects under an assumption of missing at random mechanism. Although there are a variety of multiple imputation methods for the longitudinal binary data, a limited number of researches have reported on relative performances of the methods. Moreover, when focusing on the treatment effect throughout a period that has often been used in clinical evaluations of specific disease areas, no definite investigations comparing the methods have been available. We conducted an extensive simulation study to examine comparative performances of six multiple imputation methods available in the SAS MI procedure for longitudinal binary data, where two endpoints of responder rates at a specified time point and throughout a period were assessed. The simulation study suggested that results from naive approaches of a single imputation with non-responders and a complete case analysis could be very sensitive against missing data. The multiple imputation methods using a monotone method and a full conditional specification with a logistic regression imputation model were recommended for obtaining unbiased and robust estimations of the treatment effect. The methods were illustrated with data from a mental health research.

Self-declared stock ownership and association with positive trial outcome in randomized controlled trials with binary outcomes published in general medical journals: a cross-sectional study.

PubMed

Falk Delgado, Alberto; Falk Delgado, Anna

2017-07-26

Describe the prevalence and types of conflicts of interest (COI) in published randomized controlled trials (RCTs) in general medical journals with a binary primary outcome and assess the association between conflicts of interest and favorable outcome. Parallel-group RCTs with a binary primary outcome published in three general medical journals during 2013-2015 were identified. COI type, funding source, and outcome were extracted. Binomial logistic regression model was performed to assess association between COI and funding source with outcome. A total of 509 consecutive parallel-group RCTs were included in the study. COI was reported in 74% in mixed funded RCTs and in 99% in for-profit funded RCTs. Stock ownership was reported in none of the non-profit RCTs, in 7% of mixed funded RCTs, and in 50% of for-profit funded RCTs. Mixed-funded RCTs had employees from the funding company in 11% and for-profit RCTs in 76%. Multivariable logistic regression revealed that stock ownership in the funding company among any of the authors was associated with a favorable outcome (odds ratio = 3.53; 95% confidence interval = 1.59-7.86; p < 0.01). COI in for-profit funded RCTs is extensive, because the factors related to COI are not fully independent, a multivariable analysis should be cautiously interpreted. However, after multivariable adjustment only stock ownership from the funding company among authors is associated with a favorable outcome.

Did Groundwater Processes Shape the Saharan Landscape during the Previous Wet Periods? a Remote Sensing and Geostatistical Approach

NASA Astrophysics Data System (ADS)

Farag, A. Z. A.; Sultan, M.; Elkadiri, R.; Abdelhalim, A.

2014-12-01

An integrated approach using remote sensing, landscape analysis and statistical methods was conducted to assess the role of groundwater sapping in shaping the Saharan landscape. A GIS-based logistic regression model was constructed to automatically delineate the spatial distribution of the sapping features over areas occupied by the Nubian Sandstone Aquifer System (NSAS): (1) an inventory was compiled of known locations of sapping features identified either in the field or from satellite datasets (e.g. Orbview-3 and Google Earth Digital Globe imagery); (2) spatial analyses were conducted in a GIS environment and seven geomorphological and geological predisposing factors (i.e. slope, stream density, cross-sectional and profile curvature, minimum and maximum curvature, and lithology) were identified; (3) a binary logistic regression model was constructed, optimized and validated to describe the relationship between the sapping locations and the set of controlling factors and (4) the generated model (prediction accuracy: 90.1%) was used to produce a regional sapping map over the NSAS. Model outputs indicate: (1) groundwater discharge and structural control played an important role in excavating the Saharan natural depressions as evidenced by the wide distribution of sapping features (areal extent: 1180 km2) along the fault-controlled escarpments of the Libyan Plateau; (2) proximity of mapped sapping features to reported paleolake and tufa deposits suggesting a causal effect. Our preliminary observations (from satellite imagery) and statistical analyses together with previous studies in the North Western Sahara Aquifer System (North Africa), Sinai Peninsula, Negev Desert, and The Plateau of Najd (Saudi Arabia) indicate extensive occurrence of sapping features along the escarpments bordering the northern margins of the Saharan-Arabian Desert; these areas share similar hydrologic settings with the NSAS domains and they too witnessed wet climatic periods in the Mid-Late Quaternary.

[Risk factors for lower extremity amputation in patients with diabetic foot].

PubMed

Xu, B; Yang, C Z; Wu, S B; Zhang, D; Wang, L N; Xiao, L; Chen, Y; Wang, C R; Tong, A; Zhou, X F; Li, X H; Guan, X H

2017-01-01

Objective: To explore the risk factors for lower extremity amputation in patients with diabetic foot. Methods: The clinical data of 1 771 patients with diabetic foot at the Air Force General Hospital of PLA from November 2001 to April 2015 were retrospectively analyzed. The patients were divided into the non-amputation and amputation groups. Within the amputation group, subjects were further divided into the minor and major amputation subgroups. Binary logistic regression analyses were used to assess the association between risk factors and lower extremity amputation. Results: Among 1 771 patients with diabetic foot, 323 of them (18.24%) were in the amputation group (major amputation: 41; minor amputation: 282) and 1 448 (81.76%) in the non-amputation group. Compared with non-amputation patients, those in the amputation group had a longer hospital stay and higher estimated glomerular filtration rate(eGFR)levels. Fasting plasma glucose (FPG), glycosylated hemoglobin (HbA1c), C-reaction protein (CRP), ESR, ferritin, fibrinogen and WBC levels of the amputation group were higher, while hemoglobin albumin, transferrin, TC, TG, HDL-C and LDL-C were lower than those of the non-amputation group (all P <0.05). The proportion of hypertension(52.48% vs 59.98%), peripheral vascular disease (PAD)(68.11% vs 25.04%), and coronary heart disease(21.33% vs 28.71%)were different between the amputation and non-amputation groups (all P <0.05). Multivariable logistic regression analyses showed that Wagner's grade, PAD and CRP were the independent risk factors associated with lower extremity amputation in hospitalized patients with diabetic foot. Conclusion: Wagner's grade, ischemia of lower limbs and infection are closely associated with amputation of diabetic foot patients.

Clinical characteristics and treatment outcomes of patients with major depressive disorder and comorbid anxiety disorders - results from a European multicenter study.

PubMed

Dold, Markus; Bartova, Lucie; Souery, Daniel; Mendlewicz, Julien; Serretti, Alessandro; Porcelli, Stefano; Zohar, Joseph; Montgomery, Stuart; Kasper, Siegfried

2017-08-01

This naturalistic European multicenter study aimed to elucidate the association between major depressive disorder (MDD) and comorbid anxiety disorders. Demographic and clinical information of 1346 MDD patients were compared between those with and without concurrent anxiety disorders. The association between explanatory variables and the presence of comorbid anxiety disorders was examined using binary logistic regression analyses. 286 (21.2%) of the participants exhibited comorbid anxiety disorders, 10.8% generalized anxiety disorder (GAD), 8.3% panic disorder, 8.1% agoraphobia, and 3.3% social phobia. MDD patients with comorbid anxiety disorders were characterized by younger age (social phobia), outpatient status (agoraphobia), suicide risk (any anxiety disorder, panic disorder, agoraphobia, social phobia), higher depressive symptom severity (GAD), polypsychopharmacy (panic disorder, agoraphobia), and a higher proportion receiving augmentation treatment with benzodiazepines (any anxiety disorder, GAD, panic disorder, agoraphobia, social phobia) and pregabalin (any anxiety disorder, GAD, panic disorder). The results in terms of treatment response were conflicting (better response for panic disorder and poorer for GAD). The logistic regression analyses revealed younger age (any anxiety disorder, social phobia), outpatient status (agoraphobia), suicide risk (agoraphobia), severe depressive symptoms (any anxiety disorder, GAD, social phobia), poorer treatment response (GAD), and increased administration of benzodiazepines (any anxiety disorder, agoraphobia, social phobia) and pregabalin (any anxiety disorder, GAD, panic disorder) to be associated with comorbid anxiety disorders. Our findings suggest that the various anxiety disorders subtypes display divergent clinical characteristics and are associated with different variables. Especially comorbid GAD appears to be characterized by high symptom severity and poor treatment response. Copyright © 2017 Elsevier Ltd. All rights reserved.

Improving patient survival with the colorectal cancer multi-disciplinary team.

PubMed

MacDermid, E; Hooton, G; MacDonald, M; McKay, G; Grose, D; Mohammed, N; Porteous, C

2009-03-01

There is little information on the impact of the colorectal multi-disciplinary team (MDT) in the United Kingdom. Our single operator presented his patients before and after the inception of an MDT meeting in June 2002. The aim of this study was to assess the effect of this on his patients' survival, and trends in the use of adjuvant chemotherapy. Data were collected on all patients (n = 310) undergoing colectomy for colorectal cancer by one surgeon. Excluding patients with Dukes A stage, the pre-MDT cohort from January 1997 to May 2002 was 176 and the post-MDT cohort from June 2002 to December 2005 was 134. Three-year survival rates were calculated using Kaplan-Meier life table analysis. Prognostic factors were analysed using Cox-proportional hazard regression, and chemotherapy data analysed using the chi-squared test. Independent prognostic indicators of chemotherapy prescription were examined using binary logistic testing. MDT status was shown to be an independent predictor of survival on hazard regression analysis (P = 0.044). A significantly greater number of patients were prescribed adjuvant chemotherapy in the post-MDT cohort (P = 0.0002). MDT status was shown to be a significant prognostic indicator of chemotherapy prescription (P < 0.0001). Three-year survival for Dukes C patients was 58% in the pre-MDT group, and 66% in the post-MDT group (P = 0.023). There was a significant increase in patients undergoing adjuvant postoperative chemotherapy after the inception of the MDT. This was associated with a significant survival benefit in patients with Dukes C disease. The data suggest that the MDT process has resulted in an increase in the prescription of adjuvant chemotherapy, with 3-year survival being greater after its inception.

HAPRAP: a haplotype-based iterative method for statistical fine mapping using GWAS summary statistics.

PubMed

Zheng, Jie; Rodriguez, Santiago; Laurin, Charles; Baird, Denis; Trela-Larsen, Lea; Erzurumluoglu, Mesut A; Zheng, Yi; White, Jon; Giambartolomei, Claudia; Zabaneh, Delilah; Morris, Richard; Kumari, Meena; Casas, Juan P; Hingorani, Aroon D; Evans, David M; Gaunt, Tom R; Day, Ian N M

2017-01-01

Fine mapping is a widely used approach for identifying the causal variant(s) at disease-associated loci. Standard methods (e.g. multiple regression) require individual level genotypes. Recent fine mapping methods using summary-level data require the pairwise correlation coefficients ([Formula: see text]) of the variants. However, haplotypes rather than pairwise [Formula: see text], are the true biological representation of linkage disequilibrium (LD) among multiple loci. In this article, we present an empirical iterative method, HAPlotype Regional Association analysis Program (HAPRAP), that enables fine mapping using summary statistics and haplotype information from an individual-level reference panel. Simulations with individual-level genotypes show that the results of HAPRAP and multiple regression are highly consistent. In simulation with summary-level data, we demonstrate that HAPRAP is less sensitive to poor LD estimates. In a parametric simulation using Genetic Investigation of ANthropometric Traits height data, HAPRAP performs well with a small training sample size (N < 2000) while other methods become suboptimal. Moreover, HAPRAP's performance is not affected substantially by single nucleotide polymorphisms (SNPs) with low minor allele frequencies. We applied the method to existing quantitative trait and binary outcome meta-analyses (human height, QTc interval and gallbladder disease); all previous reported association signals were replicated and two additional variants were independently associated with human height. Due to the growing availability of summary level data, the value of HAPRAP is likely to increase markedly for future analyses (e.g. functional prediction and identification of instruments for Mendelian randomization). The HAPRAP package and documentation are available at http://apps.biocompute.org.uk/haprap/ CONTACT: : jie.zheng@bristol.ac.uk or tom.gaunt@bristol.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Hemostasis and Lipoprotein Indices Signify Exacerbated Lung Injury in TB With Diabetes Comorbidity.

PubMed

Dong, Zhengwei; Shi, Jingyun; Dorhoi, Anca; Zhang, Jie; Soodeen-Lalloo, Adiilah K; Tan, WenLing; Yin, Hongyun; Sha, Wei; Li, Weitong; Zheng, Ruijuan; Liu, Zhonghua; Yang, Hua; Qin, Lianhua; Wang, Jie; Huang, Xiaochen; Wu, Chunyan; Kaufmann, Stefan H E; Feng, Yonghong

2018-05-01

Exacerbated immunopathology is a frequent consequence of TB that is complicated by diabetes mellitus (DM); however, the underlying mechanisms are still poorly defined. In the two groups of age- and sex-matched patients with TB and DM (DM-TB) and with TB and without DM, we microscopically evaluated the areas of caseous necrosis and graded the extent of perinecrotic fibrosis in lung biopsies from the sputum smear-negative (SN) patients. We scored acid-fast bacilli in sputum smear-positive (SP) patients and compiled CT scan data from both the SN and SP patients. We compared inflammatory biomarkers and routine hematologic and biochemical parameters. Binary logistic regression analyses were applied to define the indices associated with the extent of lung injury. Enlarged caseous necrotic areas with exacerbated fibrotic encapsulations were found in SN patients with DM-TB, consistent with the higher ratio of thick-walled cavities and more bacilli in the sputum from SP patients with DM-TB. Larger necrotic foci were detected in men compared with women within the SN TB groups. Significantly higher fibrinogen and lower high-density lipoprotein cholesterol (HDL-C) were observed in SN patients with DM-TB. Regression analyses revealed that diabetes, activation of the coagulation pathway (shown by increased platelet distribution width, decreased mean platelet volume, and shortened prothrombin time), and dyslipidemia (shown by decreased low-density lipoprotein cholesterol, HDL-C, and apolipoprotein A) are risk factors for severe lung lesions in both SN and SP patients with TB. Hemostasis and dyslipidemia are associated with granuloma necrosis and fibroplasia leading to exacerbated lung damage in TB, especially in patients with DM-TB. Copyright © 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Clustering for Binary Data Sets by Using Genetic Algorithm-Incremental K-means

NASA Astrophysics Data System (ADS)

Saharan, S.; Baragona, R.; Nor, M. E.; Salleh, R. M.; Asrah, N. M.

2018-04-01

This research was initially driven by the lack of clustering algorithms that specifically focus in binary data. To overcome this gap in knowledge, a promising technique for analysing this type of data became the main subject in this research, namely Genetic Algorithms (GA). For the purpose of this research, GA was combined with the Incremental K-means (IKM) algorithm to cluster the binary data streams. In GAIKM, the objective function was based on a few sufficient statistics that may be easily and quickly calculated on binary numbers. The implementation of IKM will give an advantage in terms of fast convergence. The results show that GAIKM is an efficient and effective new clustering algorithm compared to the clustering algorithms and to the IKM itself. In conclusion, the GAIKM outperformed other clustering algorithms such as GCUK, IKM, Scalable K-means (SKM) and K-means clustering and paves the way for future research involving missing data and outliers.

2004 Carolyn Sherif Award Address: Heart Disease and Gender Inequity

ERIC Educational Resources Information Center

Travis, Cheryl Brown

2005-01-01

Individual patient records from the National Hospital Discharge Survey for 1988 and 1998 comprising approximately 10 million cases were the basis for a binary logistic regression model to predict coronary artery bypass graft. Patterns in 1988 and in 1998 indicated a dramatic and pernicious gender discrepancy in medical decisions involving bypass…

Factors Affecting Code Status in a University Hospital Intensive Care Unit

ERIC Educational Resources Information Center

Van Scoy, Lauren Jodi; Sherman, Michael

2013-01-01

The authors collected data on diagnosis, hospital course, and end-of-life preparedness in patients who died in the intensive care unit (ICU) with "full code" status (defined as receiving cardiopulmonary resuscitation), compared with those who didn't. Differences were analyzed using binary and stepwise logistic regression. They found no…

Comparison between students and residents on determinants of willingness to separate waste and waste separation behaviour in Zhengzhou, China.

PubMed

Dai, Xiaoping; Han, Yuping; Zhang, Xiaohong; Hu, Wei; Huang, Liangji; Duan, Wenpei; Li, Siyi; Liu, Xiaolu; Wang, Qian

2017-09-01

A better understanding of willingness to separate waste and waste separation behaviour can aid the design and improvement of waste management policies. Based on the intercept questionnaire survey data of undergraduate students and residents in Zhengzhou City of China, this article compared factors affecting the willingness and behaviour of students and residents to participate in waste separation using two binary logistic regression models. Improvement opportunities for waste separation were also discussed. Binary logistic regression results indicate that knowledge of and attitude to waste separation and acceptance of waste education significantly affect the willingness of undergraduate students to separate waste, and demographic factors, such as gender, age, education level, and income, significantly affect the willingness of residents to do so. Presence of waste-specific bins and attitude to waste separation are drivers of waste separation behaviour for both students and residents. Improved education about waste separation and facilities are effective to stimulate waste separation, and charging on unsorted waste may be an effective way to improve it in Zhengzhou.

White dwarf-main sequence binaries from LAMOST: the DR5 catalogue

NASA Astrophysics Data System (ADS)

Ren, J.-J.; Rebassa-Mansergas, A.; Parsons, S. G.; Liu, X.-W.; Luo, A.-L.; Kong, X.; Zhang, H.-T.

2018-07-01

We present the data release (DR) 5 catalogue of white dwarf-main sequence (WDMS) binaries from the Large sky Area Multi-Object fibre Spectroscopic Telescope (LAMOST). The catalogue contains 876 WDMS binaries, of which 757 are additions to our previous LAMOST DR1 sample and 357 are systems that have not been published before. We also describe a LAMOST-dedicated survey that aims at obtaining spectra of photometrically selected WDMS binaries from the Sloan Digital Sky Survey (SDSS) that are expected to contain cool white dwarfs and/or early-type M dwarf companions. This is a population under-represented in previous SDSS WDMS binary catalogues. We determine the stellar parameters (white dwarf effective temperatures, surface gravities and masses, and M dwarf spectral types) of the LAMOST DR5 WDMS binaries and make use of the parameter distributions to analyse the properties of the sample. We find that, despite our efforts, systems containing cool white dwarfs remain under-represented. Moreover, we make use of LAMOST DR5 and SDSS DR14 (when available) spectra to measure the Na I λλ 8183.27, 8194.81 absorption doublet and/or Hα emission radial velocities of our systems. This allows identifying 128 binaries displaying significant radial velocity variations, 76 of which are new. Finally, we cross-match our catalogue with the Catalina Surveys and identify 57 systems displaying light-curve variations. These include 16 eclipsing systems, two of which are new, and nine binaries that are new eclipsing candidates. We calculate periodograms from the photometric data and measure (estimate) the orbital periods of 30 (15) WDMS binaries.

White dwarf-main sequence binaries from LAMOST: the DR5 catalogue

NASA Astrophysics Data System (ADS)

Ren, J.-J.; Rebassa-Mansergas, A.; Parsons, S. G.; Liu, X.-W.; Luo, A.-L.; Kong, X.; Zhang, H.-T.

2018-03-01

We present the data release (DR) 5 catalogue of white dwarf-main sequence (WDMS) binaries from the Large Area Multi-Object fiber Spectroscopic Telescope (LAMOST). The catalogue contains 876 WDMS binaries, of which 757 are additions to our previous LAMOST DR1 sample and 357 are systems that have not been published before. We also describe a LAMOST-dedicated survey that aims at obtaining spectra of photometrically-selected WDMS binaries from the Sloan Digital Sky Survey (SDSS) that are expected to contain cool white dwarfs and/or early type M dwarf companions. This is a population under-represented in previous SDSS WDMS binary catalogues. We determine the stellar parameters (white dwarf effective temperatures, surface gravities and masses, and M dwarf spectral types) of the LAMOST DR5 WDMS binaries and make use of the parameter distributions to analyse the properties of the sample. We find that, despite our efforts, systems containing cool white dwarfs remain under-represented. Moreover, we make use of LAMOST DR5 and SDSS DR14 (when available) spectra to measure the Na I λλ 8183.27, 8194.81 absorption doublet and/or Hα emission radial velocities of our systems. This allows identifying 128 binaries displaying significant radial velocity variations, 76 of which are new. Finally, we cross-match our catalogue with the Catalina Surveys and identify 57 systems displaying light curve variations. These include 16 eclipsing systems, two of which are new, and nine binaries that are new eclipsing candidates. We calculate periodograms from the photometric data and measure (estimate) the orbital periods of 30 (15) WDMS binaries.

Race/Ethnicity and Success in Academic Medicine: Findings From a Longitudinal Multi-Institutional Study.

PubMed

Kaplan, Samantha E; Raj, Anita; Carr, Phyllis L; Terrin, Norma; Breeze, Janis L; Freund, Karen M

2017-10-24

To understand differences in productivity, advancement, retention, satisfaction, and compensation comparing underrepresented medical (URM) faculty with other faculty at multiple institutions. A 17-year follow-up was conducted of the National Faculty Survey, a random sample from 24 U.S. medical schools, oversampled for URM faculty. The authors examined academic productivity, advancement, retention, satisfaction, and compensation, comparing white, URM, and non-URM faculty. Retention, productivity, and advancement data were obtained from public sources for nonrespondents. Covariates included gender, specialty, time distribution, and years in academia. Negative binomial regression was used for count data, logistic regression for binary outcomes, and linear regression for continuous outcomes. In productivity analyses, advancement, and retention, 1,270 participants were included; 604 participants responded to the compensation and satisfaction survey. Response rates were lower for African American (26%) and Hispanic faculty (39%) than white faculty (52%, P < .0001). URM faculty had lower rates of peer-reviewed publications (relative number 0.64; 95% CI: 0.51, 0.79), promotion to professor (OR = 0.53; CI: 0.30, 0.93), and retention in academic medicine (OR = 0.49; CI: 0.32, 0.75). No differences were identified in federal grant acquisition, senior leadership roles, career satisfaction, or compensation between URM and white faculty. URM and white faculty had similar career satisfaction, grant support, leadership, and compensation; URM faculty had fewer publications and were less likely to be promoted and retained in academic careers. Successful retention of URM faculty requires comprehensive institutional commitment to changing the academic climate and deliberative programming to support productivity and advancement.

Extension of the Peters–Belson method to estimate health disparities among multiple groups using logistic regression with survey data

PubMed Central

Li, Y.; Graubard, B. I.; Huang, P.; Gastwirth, J. L.

2015-01-01

Determining the extent of a disparity, if any, between groups of people, for example, race or gender, is of interest in many fields, including public health for medical treatment and prevention of disease. An observed difference in the mean outcome between an advantaged group (AG) and disadvantaged group (DG) can be due to differences in the distribution of relevant covariates. The Peters–Belson (PB) method fits a regression model with covariates to the AG to predict, for each DG member, their outcome measure as if they had been from the AG. The difference between the mean predicted and the mean observed outcomes of DG members is the (unexplained) disparity of interest. We focus on applying the PB method to estimate the disparity based on binary/multinomial/proportional odds logistic regression models using data collected from complex surveys with more than one DG. Estimators of the unexplained disparity, an analytic variance–covariance estimator that is based on the Taylor linearization variance–covariance estimation method, as well as a Wald test for testing a joint null hypothesis of zero for unexplained disparities between two or more minority groups and a majority group, are provided. Simulation studies with data selected from simple random sampling and cluster sampling, as well as the analyses of disparity in body mass index in the National Health and Nutrition Examination Survey 1999–2004, are conducted. Empirical results indicate that the Taylor linearization variance–covariance estimation is accurate and that the proposed Wald test maintains the nominal level. PMID:25382235

A general method for handling missing binary outcome data in randomized controlled trials

PubMed Central

Jackson, Dan; White, Ian R; Mason, Dan; Sutton, Stephen

2014-01-01

Aims The analysis of randomized controlled trials with incomplete binary outcome data is challenging. We develop a general method for exploring the impact of missing data in such trials, with a focus on abstinence outcomes. Design We propose a sensitivity analysis where standard analyses, which could include ‘missing = smoking’ and ‘last observation carried forward’, are embedded in a wider class of models. Setting We apply our general method to data from two smoking cessation trials. Participants A total of 489 and 1758 participants from two smoking cessation trials. Measurements The abstinence outcomes were obtained using telephone interviews. Findings The estimated intervention effects from both trials depend on the sensitivity parameters used. The findings differ considerably in magnitude and statistical significance under quite extreme assumptions about the missing data, but are reasonably consistent under more moderate assumptions. Conclusions A new method for undertaking sensitivity analyses when handling missing data in trials with binary outcomes allows a wide range of assumptions about the missing data to be assessed. In two smoking cessation trials the results were insensitive to all but extreme assumptions. PMID:25171441

Binary Microlensing Events from the MACHO Project

NASA Astrophysics Data System (ADS)

Alcock, C.; Allsman, R. A.; Alves, D.; Axelrod, T. S.; Baines, D.; Becker, A. C.; Bennett, D. P.; Bourke, A.; Brakel, A.; Cook, K. H.; Crook, B.; Crouch, A.; Dan, J.; Drake, A. J.; Fragile, P. C.; Freeman, K. C.; Gal-Yam, A.; Geha, M.; Gray, J.; Griest, K.; Gurtierrez, A.; Heller, A.; Howard, J.; Johnson, B. R.; Kaspi, S.; Keane, M.; Kovo, O.; Leach, C.; Leach, T.; Leibowitz, E. M.; Lehner, M. J.; Lipkin, Y.; Maoz, D.; Marshall, S. L.; McDowell, D.; McKeown, S.; Mendelson, H.; Messenger, B.; Minniti, D.; Nelson, C.; Peterson, B. A.; Popowski, P.; Pozza, E.; Purcell, P.; Pratt, M. R.; Quinn, J.; Quinn, P. J.; Rhie, S. H.; Rodgers, A. W.; Salmon, A.; Shemmer, O.; Stetson, P.; Stubbs, C. W.; Sutherland, W.; Thomson, S.; Tomaney, A.; Vandehei, T.; Walker, A.; Ward, K.; Wyper, G.

2000-09-01

We present the light curves of 21 gravitational microlensing events from the first six years of the MACHO Project gravitational microlensing survey that are likely examples of lensing by binary systems. These events were manually selected from a total sample of ~350 candidate microlensing events that were either detected by the MACHO Alert System or discovered through retrospective analyses of the MACHO database. At least 14 of these 21 events exhibit strong (caustic) features, and four of the events are well fit with lensing by large mass ratio (brown dwarf or planetary) systems, although these fits are not necessarily unique. The total binary event rate is roughly consistent with predictions based upon our knowledge of the properties of binary stars, but a precise comparison cannot be made without a determination of our binary lens event detection efficiency. Toward the Galactic bulge, we find a ratio of caustic crossing to noncaustic crossing binary lensing events of 12:4, excluding one event for which we present two fits. This suggests significant incompleteness in our ability to detect and characterize noncaustic crossing binary lensing. The distribution of mass ratios, N(q), for these binary lenses appears relatively flat. We are also able to reliably measure source-face crossing times in four of the bulge caustic crossing events, and recover from them a distribution of lens proper motions, masses, and distances consistent with a population of Galactic bulge lenses at a distance of 7+/-1 kpc. This analysis yields two systems with companions of ~0.05 Msolar.

Determination of riverbank erosion probability using Locally Weighted Logistic Regression

NASA Astrophysics Data System (ADS)

Ioannidou, Elena; Flori, Aikaterini; Varouchakis, Emmanouil A.; Giannakis, Georgios; Vozinaki, Anthi Eirini K.; Karatzas, George P.; Nikolaidis, Nikolaos

2015-04-01

Riverbank erosion is a natural geomorphologic process that affects the fluvial environment. The most important issue concerning riverbank erosion is the identification of the vulnerable locations. An alternative to the usual hydrodynamic models to predict vulnerable locations is to quantify the probability of erosion occurrence. This can be achieved by identifying the underlying relations between riverbank erosion and the geomorphological or hydrological variables that prevent or stimulate erosion. Thus, riverbank erosion can be determined by a regression model using independent variables that are considered to affect the erosion process. The impact of such variables may vary spatially, therefore, a non-stationary regression model is preferred instead of a stationary equivalent. Locally Weighted Regression (LWR) is proposed as a suitable choice. This method can be extended to predict the binary presence or absence of erosion based on a series of independent local variables by using the logistic regression model. It is referred to as Locally Weighted Logistic Regression (LWLR). Logistic regression is a type of regression analysis used for predicting the outcome of a categorical dependent variable (e.g. binary response) based on one or more predictor variables. The method can be combined with LWR to assign weights to local independent variables of the dependent one. LWR allows model parameters to vary over space in order to reflect spatial heterogeneity. The probabilities of the possible outcomes are modelled as a function of the independent variables using a logistic function. Logistic regression measures the relationship between a categorical dependent variable and, usually, one or several continuous independent variables by converting the dependent variable to probability scores. Then, a logistic regression is formed, which predicts success or failure of a given binary variable (e.g. erosion presence or absence) for any value of the independent variables. The erosion occurrence probability can be calculated in conjunction with the model deviance regarding the independent variables tested. The most straightforward measure for goodness of fit is the G statistic. It is a simple and effective way to study and evaluate the Logistic Regression model efficiency and the reliability of each independent variable. The developed statistical model is applied to the Koiliaris River Basin on the island of Crete, Greece. Two datasets of river bank slope, river cross-section width and indications of erosion were available for the analysis (12 and 8 locations). Two different types of spatial dependence functions, exponential and tricubic, were examined to determine the local spatial dependence of the independent variables at the measurement locations. The results show a significant improvement when the tricubic function is applied as the erosion probability is accurately predicted at all eight validation locations. Results for the model deviance show that cross-section width is more important than bank slope in the estimation of erosion probability along the Koiliaris riverbanks. The proposed statistical model is a useful tool that quantifies the erosion probability along the riverbanks and can be used to assist managing erosion and flooding events. Acknowledgements This work is part of an on-going THALES project (CYBERSENSORS - High Frequency Monitoring System for Integrated Water Resources Management of Rivers). The project has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: THALES. Investing in knowledge society through the European Social Fund.

Deletion Diagnostics for Alternating Logistic Regressions

PubMed Central

Preisser, John S.; By, Kunthel; Perin, Jamie; Qaqish, Bahjat F.

2013-01-01

Deletion diagnostics are introduced for the regression analysis of clustered binary outcomes estimated with alternating logistic regressions, an implementation of generalized estimating equations (GEE) that estimates regression coefficients in a marginal mean model and in a model for the intracluster association given by the log odds ratio. The diagnostics are developed within an estimating equations framework that recasts the estimating functions for association parameters based upon conditional residuals into equivalent functions based upon marginal residuals. Extensions of earlier work on GEE diagnostics follow directly, including computational formulae for one-step deletion diagnostics that measure the influence of a cluster of observations on the estimated regression parameters and on the overall marginal mean or association model fit. The diagnostic formulae are evaluated with simulations studies and with an application concerning an assessment of factors associated with health maintenance visits in primary care medical practices. The application and the simulations demonstrate that the proposed cluster-deletion diagnostics for alternating logistic regressions are good approximations of their exact fully iterated counterparts. PMID:22777960

Fundamental parameters of massive stars in multiple systems: The cases of HD 17505A and HD 206267A

NASA Astrophysics Data System (ADS)

Raucq, F.; Rauw, G.; Mahy, L.; Simón-Díaz, S.

2018-06-01

Context. Many massive stars are part of binary or higher multiplicity systems. The present work focusses on two higher multiplicity systems: HD 17505A and HD 206267A. Aims: Determining the fundamental parameters of the components of the inner binary of these systems is mandatory to quantify the impact of binary or triple interactions on their evolution. Methods: We analysed high-resolution optical spectra to determine new orbital solutions of the inner binary systems. After subtracting the spectrum of the tertiary component, a spectral disentangling code was applied to reconstruct the individual spectra of the primary and secondary. We then analysed these spectra with the non-LTE model atmosphere code CMFGEN to establish the stellar parameters and the CNO abundances of these stars. Results: The inner binaries of these systems have eccentric orbits with e 0.13 despite their relatively short orbital periods of 8.6 and 3.7 days for HD 17505Aa and HD 206267Aa, respectively. Slight modifications of the CNO abundances are found in both components of each system. The components of HD 17505Aa are both well inside their Roche lobe, whilst the primary of HD 206267Aa nearly fills its Roche lobe around periastron passage. Whilst the rotation of the primary of HD 206267Aa is in pseudo-synchronization with the orbital motion, the secondary displays a rotation rate that is higher. Conclusions: The CNO abundances and properties of HD 17505Aa can be explained by single star evolutionary models accounting for the effects of rotation, suggesting that this system has not yet experienced binary interaction. The properties of HD 206267Aa suggest that some intermittent binary interaction might have taken place during periastron passages, but is apparently not operating anymore. Based on observations collected with the TIGRE telescope (La Luz, Mexico), the 1.93 m telescope at Observatoire de Haute Provence (France), the Nordic Optical Telescope at the Observatorio del Roque de los Muchachos (La Palma, Spain), and the Canada-France-Hawaii telescope (Mauna Kea, Hawaii).

Detection of melamine in milk powders using near-infrared hyperspectral imaging combined with regression coefficient of partial least square regression model.

PubMed

Lim, Jongguk; Kim, Giyoung; Mo, Changyeun; Kim, Moon S; Chao, Kuanglin; Qin, Jianwei; Fu, Xiaping; Baek, Insuck; Cho, Byoung-Kwan

2016-05-01

Illegal use of nitrogen-rich melamine (C3H6N6) to boost perceived protein content of food products such as milk, infant formula, frozen yogurt, pet food, biscuits, and coffee drinks has caused serious food safety problems. Conventional methods to detect melamine in foods, such as Enzyme-linked immunosorbent assay (ELISA), High-performance liquid chromatography (HPLC), and Gas chromatography-mass spectrometry (GC-MS), are sensitive but they are time-consuming, expensive, and labor-intensive. In this research, near-infrared (NIR) hyperspectral imaging technique combined with regression coefficient of partial least squares regression (PLSR) model was used to detect melamine particles in milk powders easily and quickly. NIR hyperspectral reflectance imaging data in the spectral range of 990-1700nm were acquired from melamine-milk powder mixture samples prepared at various concentrations ranging from 0.02% to 1%. PLSR models were developed to correlate the spectral data (independent variables) with melamine concentration (dependent variables) in melamine-milk powder mixture samples. PLSR models applying various pretreatment methods were used to reconstruct the two-dimensional PLS images. PLS images were converted to the binary images to detect the suspected melamine pixels in milk powder. As the melamine concentration was increased, the numbers of suspected melamine pixels of binary images were also increased. These results suggested that NIR hyperspectral imaging technique and the PLSR model can be regarded as an effective tool to detect melamine particles in milk powders. Copyright © 2016 Elsevier B.V. All rights reserved.

A local equation for differential diagnosis of β-thalassemia trait and iron deficiency anemia by logistic regression analysis in Southeast Iran.

PubMed

Sargolzaie, Narjes; Miri-Moghaddam, Ebrahim

2014-01-01

The most common differential diagnosis of β-thalassemia (β-thal) trait is iron deficiency anemia. Several red blood cell equations were introduced during different studies for differential diagnosis between β-thal trait and iron deficiency anemia. Due to genetic variations in different regions, these equations cannot be useful in all population. The aim of this study was to determine a native equation with high accuracy for differential diagnosis of β-thal trait and iron deficiency anemia for the Sistan and Baluchestan population by logistic regression analysis. We selected 77 iron deficiency anemia and 100 β-thal trait cases. We used binary logistic regression analysis and determined best equations for probability prediction of β-thal trait against iron deficiency anemia in our population. We compared diagnostic values and receiver operative characteristic (ROC) curve related to this equation and another 10 published equations in discriminating β-thal trait and iron deficiency anemia. The binary logistic regression analysis determined the best equation for best probability prediction of β-thal trait against iron deficiency anemia with area under curve (AUC) 0.998. Based on ROC curves and AUC, Green & King, England & Frazer, and then Sirdah indices, respectively, had the most accuracy after our equation. We suggest that to get the best equation and cut-off in each region, one needs to evaluate specific information of each region, specifically in areas where populations are homogeneous, to provide a specific formula for differentiating between β-thal trait and iron deficiency anemia.

A new method for constructing networks from binary data

NASA Astrophysics Data System (ADS)

van Borkulo, Claudia D.; Borsboom, Denny; Epskamp, Sacha; Blanken, Tessa F.; Boschloo, Lynn; Schoevers, Robert A.; Waldorp, Lourens J.

2014-08-01

Network analysis is entering fields where network structures are unknown, such as psychology and the educational sciences. A crucial step in the application of network models lies in the assessment of network structure. Current methods either have serious drawbacks or are only suitable for Gaussian data. In the present paper, we present a method for assessing network structures from binary data. Although models for binary data are infamous for their computational intractability, we present a computationally efficient model for estimating network structures. The approach, which is based on Ising models as used in physics, combines logistic regression with model selection based on a Goodness-of-Fit measure to identify relevant relationships between variables that define connections in a network. A validation study shows that this method succeeds in revealing the most relevant features of a network for realistic sample sizes. We apply our proposed method to estimate the network of depression and anxiety symptoms from symptom scores of 1108 subjects. Possible extensions of the model are discussed.

Self-rated health and health-strengthening factors in community-living frail older people.

PubMed

Ebrahimi, Zahra; Dahlin-Ivanoff, Synneve; Eklund, Kajsa; Jakobsson, Annika; Wilhelmson, Katarina

2015-04-01

The aim of this study was to analyse the explanatory power of variables measuring health-strengthening factors for self-rated health among community-living frail older people. Frailty is commonly constructed as a multi-dimensional geriatric syndrome ascribed to the multi-system deterioration of the reserve capacity in older age. Frailty in older people is associated with decreased physical and psychological well-being. However, knowledge about the experiences of health in frail older people is still limited. The design of the study was cross-sectional. The data were collected between October 2008 and November 2010 through face-to-face structured interviews with older people aged 65-96 years (N = 161). Binary logistic regression was used to analyse whether a set of explanatory relevant variables is associated with self-rated health. The results from the final model showed that satisfaction with one's ability to take care of oneself, having 10 or fewer symptoms and not feeling lonely had the best explanatory power for community-living frail older peoples' experiences of good health. The results indicate that a multi-disciplinary approach is desirable, where the focus should not only be on medical problems but also on providing supportive services to older people to maintain their independence and experiences of health despite frailty. © 2014 John Wiley & Sons Ltd.

Excess Risk of Temporomandibular Disorder Associated with Cigarette Smoking in Young Adults

PubMed Central

Sanders, Anne E.; Slade, Gary D.; Maixner, William; Nackley, Andrea G.; Diatchenko, Luda; By, Kunthel; Miller, Vanessa E.

2011-01-01

Evidence suggests that the effect of cigarette smoking on chronic pain is stronger in younger than older adults. This case control study investigated whether age modified an effect of smoking on temporomandibular disorder (TMD) in 299 females aged 18–60 years. It also investigated the extent to which this relationship was explained by psychological profile, inflammatory response and allergy. Cases were defined using the Research Diagnostic Criteria for Temporomandibular Disorders based on clinical examination. Psychological profile was evaluated using standardized instruments. Inflammatory response was evaluated with 11 cytokines isolated in plasma. History of allergy conditions was self-reported. Odds ratios (OR) for the effect of smoking were calculated using binary logistic regression. Stratified analyses and the likelihood ratio test examined effect modification by smoking. Compared to non-smokers, ever smokers aged <30 years had higher odds of TMD (OR =4.14, 95% CI: 1.57, 11.35) than older adults (OR =1.23, 95% CI: 0.55, 2.78) (P (effect modification) =0.038). Adjustment for psychological profile, cytokines and history of allergy-like conditions attenuated the effect by 45% to statistical non-significance. The main finding was reproduced with secondary analyses of two nationally-representative surveys of adults conducted in the U.S. and Australia. PMID:22036516

Gender and age inequalities in regular sports participation: a cross-national study of 25 European countries.

PubMed

Van Tuyckom, Charlotte; Scheerder, Jeroen; Bracke, Piet

2010-08-01

This article provides a unique opportunity to compare gender inequalities in sports participation across Europe, and the extent to which this varies by age using large, cross-sections of the population. The Eurobarometer Survey 62.0 (carried out in 2004 at the request of the European Commission and covering the adult population of 25 European member states, N = 23,909) was used to analyse differences in regular sports participation by gender and by age in the different countries. For the majority of countries, the occurrence of regular sporting activity was less than 40%. Additionally, binary logistic regression analyses identified significant gender differences in sports participation in 12 countries. In Belgium, France, Greece, Latvia, Lithuania, Slovakia, Spain, and the UK, men were more likely to report being regularly active in sports than women, whereas in Denmark, Finland, Sweden, and the Netherlands the opposite was true. Moreover, the extent to which these gender inequalities differ by age varies considerably across countries. The results imply that: (i) in some European countries more efforts must be undertaken to promote the original goals of the Sport for All Charter, and (ii) to achieve more female participation in sports will require different policy responses in the diverse European member states.

Depression and incident dementia. An 8-year population-based prospective study.

PubMed

Luppa, Melanie; Luck, Tobias; Ritschel, Franziska; Angermeyer, Matthias C; Villringer, Arno; Riedel-Heller, Steffi G

2013-01-01

The aim of the study was to investigate the impact of depression (categorical diagnosis; major depression, MD) and depressive symptoms (dimensional diagnosis and symptom patterns) on incident dementia in the German general population. Within the Leipzig Longitudinal Study of the Aged (LEILA 75+), a representative sample of 1,265 individuals aged 75 years and older were interviewed every 1.5 years over 8 years (mean observation time 4.3 years; mean number of visits 4.2). Cox proportional hazards and binary logistic regressions were used to estimate the effect of baseline depression and depressive symptoms on incident dementia. The incidence of dementia was 48 per 1,000 person-years (95% confidence interval (CI) 45-51). Depressive symptoms (Hazard ratio HR 1.03, 95% CI 1.01-1.05), and in particular mood-related symptoms (HR 1.08, 95% CI 1.03-1.14), showed a significant impact on the incidence of dementia only in univariate analysis, but not after adjustment for cognitive and functional impairment. MD showed only a significant impact on incidence of dementia in Cox proportional hazards regression, but not in binary logistic regression models. The present study using different diagnostic measures of depression on future dementia found no clear significant associations of depression and incident dementia. Further in-depth investigation would help to understand the nature of depression in the context of incident dementia.

Psychological trauma symptoms and Type 2 diabetes prevalence, glucose control, and treatment modality among American Indians in the Strong Heart Family Study

PubMed Central

Jacob, Michelle M.; Gonzales, Kelly L.; Calhoun, Darren; Beals, Janette; Muller, Clemma Jacobsen; Goldberg, Jack; Nelson, Lonnie; Welty, Thomas K.; Howard, Barbara V.

2013-01-01

Aims The aims of this paper are to examine the relationship between psychological trauma symptoms and Type 2 diabetes prevalence, glucose control, and treatment modality among 3,776 American Indians in Phase V of the Strong Heart Family Study. Methods This cross-sectional analysis measured psychological trauma symptoms using the National Anxiety Disorder Screening Day instrument, diabetes by American Diabetes Association criteria, and treatment modality by four categories: no medication, oral medication only, insulin only, or both oral medication and insulin. We used binary logistic regression to evaluate the association between psychological trauma symptoms and diabetes prevalence. We used ordinary least squares regression to evaluate the association between psychological trauma symptoms and glucose control. We used binary logistic regression to model the association of psychological trauma symptoms with treatment modality. Results Neither diabetes prevalence (22-31%; p = 0.19) nor control (8.0-8.6; p = 0.25) varied significantly by psychological trauma symptoms categories. However, diabetes treatment modality was associated with psychological trauma symptoms categories, as people with greater burden used either no medication, or both oral and insulin medications (odds ratio = 3.1, p < 0.001). Conclusions The positive relationship between treatment modality and psychological trauma symptoms suggests future research investigate patient and provider treatment decision making. PMID:24051029

A simple measure of cognitive reserve is relevant for cognitive performance in MS patients.

PubMed

Della Corte, Marida; Santangelo, Gabriella; Bisecco, Alvino; Sacco, Rosaria; Siciliano, Mattia; d'Ambrosio, Alessandro; Docimo, Renato; Cuomo, Teresa; Lavorgna, Luigi; Bonavita, Simona; Tedeschi, Gioacchino; Gallo, Antonio

2018-05-04

Cognitive reserve (CR) contributes to preserve cognition despite brain damage. This theory has been applied to multiple sclerosis (MS) to explain the partial relationship between cognition and MRI markers of brain pathology. Our aim was to determine the relationship between two measures of CR and cognition in MS. One hundred and forty-seven MS patients were enrolled. Cognition was assessed using the Rao's Brief Repeatable Battery and the Stroop Test. CR was measured as the vocabulary subtest of the WAIS-R score (VOC) and the number of years of formal education (EDU). Regression analysis included raw score data on each neuropsychological (NP) test as dependent variables and demographic/clinical parameters, VOC, and EDU as independent predictors. A binary logistic regression analysis including clinical/CR parameters as covariates and absence/presence of cognitive deficits as dependent variables was performed too. VOC, but not EDU, was strongly correlated with performances at all ten NP tests. EDU was correlated with executive performances. The binary logistic regression showed that only the Expanded Disability Status Scale (EDSS) and VOC were independently correlated with the presence/absence of CD. The lower the VOC and/or the higher the EDSS, the higher the frequency of CD. In conclusion, our study supports the relevance of CR in subtending cognitive performances and the presence of CD in MS patients.

Methods for analyzing matched designs with double controls: excess risk is easily estimated and misinterpreted when evaluating traffic deaths.

PubMed

Redelmeier, Donald A; Tibshirani, Robert J

2018-06-01

To demonstrate analytic approaches for matched studies where two controls are linked to each case and events are accumulating counts rather than binary outcomes. A secondary intent is to clarify the distinction between total risk and excess risk (unmatched vs. matched perspectives). We review past research testing whether elections can lead to increased traffic risks. The results are reinterpreted by analyzing both the total count of individuals in fatal crashes and the excess count of individuals in fatal crashes, each time accounting for the matched double controls. Overall, 1,546 individuals were in fatal crashes on the 10 election days (average = 155/d), and 2,593 individuals were in fatal crashes on the 20 control days (average = 130/d). Poisson regression of total counts yielded a relative risk of 1.19 (95% confidence interval: 1.12-1.27). Poisson regression of excess counts yielded a relative risk of 3.22 (95% confidence interval: 2.72-3.80). The discrepancy between analyses of total counts and excess counts replicated with alternative statistical models and was visualized in graphical displays. Available approaches provide methods for analyzing count data in matched designs with double controls and help clarify the distinction between increases in total risk and increases in excess risk. Copyright © 2018 Elsevier Inc. All rights reserved.

Socio-economic Correlates of Malnutrition among Married Women in Bangladesh.

PubMed

Mostafa Kamal, S M; Md Aynul, Islam

2010-12-01

This paper examines the prevalence and socio-economic correlates of malnutrition among ever married non-pregnant women of reproductive age of Bangladesh using a nationally representative weighted sample of 10,145. Body mass index was used to measure nutritional status. Both bivariate and multivariate statistical analyses were employed to assess the relationship between socio-economic characteristics and women's nutritional status. Overall, 28.5% of the women were found to be underweight. The fixed effect multivariate binary logistic regression analysis yielded significantly increased risk of underweight for the young, currently working, non-Muslim, rural residents, widowed, divorced or separated women. Significant wide variations of malnourishment prevailed in the administrative regions of the country. Wealth index and women's education were the most important determinants of underweight. The multivariate logistic regression analysis revealed that the risk of being underweight was almost seven times higher (OR=6.76, 95% CI=5.20-8.80) among women with no formal education as compared to those with higher education and the likelihood of underweight was significantly (p<0.001) 5.2 times (OR=5.23, 95% CI=4.51-6.07) in the poorest as compared to their richest counterparts. Poverty alleviation programmes should be strengthened targeting the poor. Effective policies, information and health education programmes for women are required to ensure adequate access to health services and for them to understand the components of a healthy diet.

Alcohol use, risky sexual behavior, and condom possession among bar patrons.

PubMed

Chaney, Beth H; Vail-Smith, Karen; Martin, Ryan J; Cremeens-Matthews, Jennifer

2016-09-01

The current study seeks to: 1) assess the relationship between alcohol consumption and intentions to engage in unprotected sex in an uncontrolled environment, and 2) to identify if covariates (race, age, sex, breath alcohol content (BrAC), intentions to engage in sex, hazardous drinking rates) are significant predictors of condom possession during time of uncontrolled alcohol consumption. Data were collected from 917 bar patrons to assess alcohol use using the Alcohol Use Disorders Identification Test (AUDIT-C), BrAC levels, intentions to engage in risky sex, and condom possession. Correlational analysis and hierarchical binary logistic regression was conducted using SPSS. Correlational analyses indicated a negative relationship between AUDIT-C scores (r=-0.115, p=0.001), BrAC (r=-0.08, p=0.015), and intentions to use a condom. Over 70% of participants intended to use a condom if they engaged in sex; however, only 28.4% had a condom to use. The regression analysis indicated the predictive model (χ(2)=114.5, df=8, p<0.001) was statistically significant, and correctly classified 72.9% of those in possession of a condom. Alcohol consumption was associated with intentions to have unprotected sex; however, intentions to engage in protected sex and condom possession were higher for males and those with higher BrAC levels. Copyright © 2016 Elsevier Ltd. All rights reserved.

Economic Adversity Transitions From Childhood to Older Adulthood Are Differentially Associated With Later-Life Physical Performance Measures in Men and Women in Middle and High-Income Sites.

PubMed

Hwang, Phoebe W; Dos Santos Gomes, Cristiano; Auais, Mohammad; Braun, Kathryn L; Guralnik, Jack M; Pirkle, Catherine M

2017-10-01

This study examines the relationship between economic adversity transitions from childhood to older adulthood and older adulthood physical performance among 1,998 community-dwelling older adults from five demographically diverse sites from middle and high-income countries. The principal exposure variable was economic adversity transition. No adversity encompassed not experiencing poverty in both childhood and older adulthood, improved described having only experienced poverty in childhood, worsened captured having experienced poverty in older adulthood, and severe is having experienced poverty in both childhood and older adulthood. The short physical performance battery (SPPB) was used for outcome measures. Analyses of the continuous SPPB score used linear regression, while analysis of a binary outcome (SPPB < 8 vs. ≥8) used Poisson regression models with robust error variance, both adjusting for sex, education, and site location. In sex-stratified models, the SPPB < 8 prevalence rate ratio (PRR) was higher for the severe (PRR: 2.80, 95% confidence interval [CI] = [1.70, 4.61]), worsened (PRR: 2.40, 95% CI = [1.41, 4.09]), and improved (PRR: 1.82, 95% CI = [1.11, 3.01]) groups, compared with those with no adversity in childhood or as adults, but only for females. Findings from this study indicate that persistent economic adversity has a negative effect on older adult physical performance, especially among women.

Knowledge, awareness, and behaviors of endocrinologists and dentists for the relationship between diabetes and periodontitis.

PubMed

Lin, Hanxiao; Zhang, Hua; Yan, Yuxia; Liu, Duan; Zhang, Ruyi; Liu, Yeungyeung; Chen, Pei; Zhang, Jincai; Xuan, Dongying

2014-12-01

This study aimed to compare the opinions of dentists and endocrinologists regarding diabetes mellitus (DM) and periodontitis, and to investigate the possible effects on their practice. Cross-sectional data were collected from 297 endocrinologists and 134 dentists practicing in southern China using two separated questionnaires. Questions were close-ended or Likert-scaled. Statistical analyses were done by descriptive statistics, bivariate and binary logistic regression analysis. Compared with endocrinologists, dentists presented more favorable attitudes for the relationship of DM and periodontitis (P<0.001). 61.2% of dentists reported they would frequently refer patients with severe periodontitis for DM evaluation, while only 26.6% of endocrinologists reported they would frequently advise patients with DM to visit a dentist. Nearly all of the respondents (94.4%) agreed that the interdisciplinary collaboration should be strengthened. The logistic regression analysis exhibited that respondents with more favorable attitudes were more likely to advise a dental visit (P=0.003) or to screen for DM (P=0.006). Endocrinologists and dentists are not equally equipped with the knowledge about the relationship between DM and periodontitis, and there is a wide gap between their practice and the current evidence, especially for endocrinologists. It's urgent to take measures to develop the interdisciplinary education and collaboration among the health care providers. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Secondary sex ratio in Greece: evidence of an influence by father's occupational exposure.

PubMed

Alexopoulos, Evangelos C; Alamanos, Yannis

2007-11-01

Several medical, occupational and environmental paternal exposures have been suggested to be associated with low offspring sex ratios. The purpose of this study was to analyse trends and variations in the secondary sex ratio in Greece during the last 50 years and among different occupational groups of male employees of a shipyard. Data were retrieved from National Statistics Agency databases through the period 1955-2005, and linear regression was administered to examine the evolution of the sex ratio of newborns. In addition, 587 male shipyard employees with 1,012 children were included in the study. Binary logistic regression analysis was conducted to study the influence of father's job title on offspring sex ratio. Total births in Greece declined by ~30% between the mid 1950s and 1980, while little change in sex ratio occurred. In contrast, while between 1980 and 2000, the birth rate continued to decline at the same rate (by ~30%), there appeared to be a trend toward a decrease in sex ratio. The groups of sandblasters/painters and of ship carpenters showed a significantly lower proportion of boys among newborn children. Data from men working in a Greek shipyard suggest that the trend toward a decrease in secondary sex ratio observed in this country may be accounted for by a decrease in male births associated with specific workplace exposures of the father.

Global optimization of small bimetallic Pd-Co binary nanoalloy clusters: a genetic algorithm approach at the DFT level.

PubMed

Aslan, Mikail; Davis, Jack B A; Johnston, Roy L

2016-03-07

The global optimisation of small bimetallic PdCo binary nanoalloys are systematically investigated using the Birmingham Cluster Genetic Algorithm (BCGA). The effect of size and composition on the structures, stability, magnetic and electronic properties including the binding energies, second finite difference energies and mixing energies of Pd-Co binary nanoalloys are discussed. A detailed analysis of Pd-Co structural motifs and segregation effects is also presented. The maximal mixing energy corresponds to Pd atom compositions for which the number of mixed Pd-Co bonds is maximised. Global minimum clusters are distinguished from transition states by vibrational frequency analysis. HOMO-LUMO gap, electric dipole moment and vibrational frequency analyses are made to enable correlation with future experiments.

Missing binary data extraction challenges from Cochrane reviews in mental health and Campbell reviews with implications for empirical research.

PubMed

Spineli, Loukia M

2017-12-01

Tο report challenges encountered during the extraction process from Cochrane reviews in mental health and Campbell reviews and to indicate their implications on the empirical performance of different methods to handle missingness. We used a collection of meta-analyses on binary outcomes collated from a previous work on missing outcome data. To evaluate the accuracy of their extraction, we developed specific criteria pertaining to the reporting of missing outcome data in systematic reviews. Using the most popular methods to handle missing binary outcome data, we investigated the implications of the accuracy of the extracted meta-analysis on the random-effects meta-analysis results. Of 113 meta-analyses from Cochrane reviews, 60 (53%) were judged as "unclearly" extracted (ie, no information on the outcome of completers but available information on how missing participants were handled) and 42 (37%) as "unacceptably" extracted (ie, no information on the outcome of completers as well as no information on how missing participants were handled). For the remaining meta-analyses, it was judged that data were "acceptably" extracted (ie, information on the completers' outcome was provided for all trials). Overall, "unclear" extraction overestimated the magnitude of the summary odds ratio and the between-study variance and additionally inflated the uncertainty of both meta-analytical parameters. The only eligible Campbell review was judged as "unclear." Depending on the extent of missingness, the reporting quality of the systematic reviews can greatly affect the accuracy of the extracted meta-analyses and by extent, the empirical performance of different methods to handle missingness. Copyright © 2017 John Wiley & Sons, Ltd.

Spectral analysis of a family of binary inflation rules

NASA Astrophysics Data System (ADS)

Baake, Michael; Grimm, Uwe; Mañibo, Neil

2018-01-01

The family of primitive binary substitutions defined by 1 \\mapsto 0 \\mapsto 0 1^m with m\\in N is investigated. The spectral type of the corresponding diffraction measure is analysed for its geometric realisation with prototiles (intervals) of natural length. Apart from the well-known Fibonacci inflation (m=1 ), the inflation rules either have integer inflation factors, but non-constant length, or are of non-Pisot type. We show that all of them have singular diffraction, either of pure point type or essentially singular continuous.

Predictors of Gender Inequalities in the Rank of Full Professor

ERIC Educational Resources Information Center

Heijstra, Thamar; Bjarnason, Thoroddur; Rafnsdóttir, Gudbjörg Linda

2015-01-01

This article examines whether age, work-related, and family-related predictors explain differences in the academic advancement of women and men in Iceland. Survey data were analyzed by binary logistic regression. The findings put that women climb the academic career ladder at a slower pace than men. This finding puts one of the widely known…

South Texas Mexican American Use of Traditional Folk and Mainstream Alternative Therapies

ERIC Educational Resources Information Center

Martinez, Leslie N.

2009-01-01

A telephone survey was conducted with a large sample of Mexican Americans from border (n = 1,001) and nonborder (n = 1,030) regions in Texas. Patterns of traditional folk and mainstream complementary and alternative medicine (CAM) use were analyzed with two binary logistic regressions, using gender, self-rated health, confidence in medical…

Propensity of University Students in the Region of Antofagasta, Chile to Create Enterprise

ERIC Educational Resources Information Center

Romani, Gianni; Didonet, Simone; Contuliano, Sue-Hellen; Portilla, Rodrigo

2013-01-01

The authors aim to discuss the propensity or intention to create enterprise among university students in the region of Antofagasta, Chile, and to analyze the factors that influence the step from desire to intention. 681 students were surveyed. The data were analyzed by binary logistical regression. The results show that curriculum is among the…

Generalized Partial Least Squares Approach for Nominal Multinomial Logit Regression Models with a Functional Covariate

ERIC Educational Resources Information Center

Albaqshi, Amani Mohammed H.

2017-01-01

Functional Data Analysis (FDA) has attracted substantial attention for the last two decades. Within FDA, classifying curves into two or more categories is consistently of interest to scientists, but multi-class prediction within FDA is challenged in that most classification tools have been limited to binary response applications. The functional…

A cross-sectional assessment of health-related quality of life in Chinese patients with chronic hepatitis c virus infection with EQ-5D.

PubMed

Huang, Rui; Rao, Huiying; Shang, Jia; Chen, Hong; Li, Jun; Xie, Qing; Gao, Zhiliang; Wang, Lei; Wei, Jia; Jiang, Jianning; Sun, Jian; Jiang, Jiaji; Wei, Lai

2018-06-15

Hepatitis C virus (HCV) infection is one of the most common liver infections, with a decrement in HRQoL of HCV patients. This study aims to assess Health-related quality of life (HRQoL) in Chinese patients with chronic HCV infection, and to identify significant predictors of the HRQoL in these patients of China. In this cross-sectional observational study, treatment-naïve Han ethnic adults with chronic HCV infection were enrolled. Adopting European Quality of Life scale (EQ-5D) and EuroQOL visual analogue scale (EQ-VAS) were used to qualify HRQoL. Results were reported in descriptive analyses to describe sociodemographic and clinical characteristics. Multiple linear regression analysis was applied to investigate the associations of these variables with HRQoL. Binary logistic regression analysis was performed to identify associations of these variables with HRQoL by dimensions of EQ-5D. Nine hundred ninety-seven patients were enrolled in the study [median age 46.0 (37.0, 56.0) years; male 54.8%]. Mean EQ-5D index and EQ-VAS score were 0.780 ± 0.083 and 77.2 ± 14.8. Multiple Linear regression analysis showed that income (< 2000 RMB, β = - 0.134; 2000-4999 RMB, β = - 0.085), moderate or severe symptoms of discomfort (more than one symptoms, β = - 0.090), disease profile (cirrhosis, β = - 0.114), hyperlipidemia (β = - 0.065) and depression (β = - 0.065) were independently associated with EQ-5D index. Residence (the west, β = 0.087), income (< 2000 RMB, β = - 0.129; 2000-4999 RMB, β = - 0.052), moderate or severe symptoms of discomfort (more than one symptoms, β = - 0.091), disease profile and depression (β = - 0.316) were the influencing factors on EQ-VAS. Binary logistic regression indicated that disease profile and clinical depression were the major influencing factors on all five dimensions of EQ-5D. In this cross-sectional assessment of HCV patients in China, we indicated HRQoL of Chinese HCV patients. Significant negative associations between HRQoL and sociodemographic and clinical factors such as moderate or severe symptoms of discomfort, disease profile and depression emerged. We have to focus on optimally managing care of HCV patients and improving their HRQoL. ClinicalTrials.gov identifier NCT01293279. Date of registration: February 10, 2011.

Associations between national viral hepatitis policies/programmes and country-level socioeconomic factors: a sub-analysis of data from the 2013 WHO viral hepatitis policy report.

PubMed

Lazarus, Jeffrey V; Sperle, Ida; Safreed-Harmon, Kelly; Gore, Charles; Cebolla, Beatriz; Spina, Alexander

2017-07-26

As more countries worldwide develop national viral hepatitis strategies, it is important to ask whether context-specific factors affect their decision-making. This study aimed to determine whether country-level socioeconomic factors are associated with viral hepatitis programmes and policy responses across WHO Member States (MS). WHO MS focal points completed a questionnaire on national viral hepatitis policies. This secondary analysis of data reported in the 2013 Global Policy Report on the Prevention and Control of Viral Hepatitis in WHO Member States used logistic regression to examine associations between four survey questions and four socioeconomic factors: country income level, Human Development Index (HDI), health expenditure and physician density. This analysis included 119 MS. MS were more likely to have routine viral hepatitis surveillance and to have a national strategy and/or policy/guidelines for preventing infection in healthcare settings if they were in the higher binary categories for income level, HDI, health expenditure and physician density. In multivariable analyses, the only significant finding was a positive association between having routine surveillance and being in the higher binary HDI category (adjusted odds ratio 26; 95% confidence interval 2.0-340). Countries with differing socioeconomic status indicators did not appear to differ greatly regarding the existence of key national policies and programmes. A more nuanced understanding of the multifaceted interactions of socioeconomic factors, health policy, service delivery and health outcomes is needed to support country-level efforts to eliminate viral hepatitis.

Spectroscopic and DFT study of solvent effects on the electronic absorption spectra of sulfamethoxazole in neat and binary solvent mixtures

NASA Astrophysics Data System (ADS)

Almandoz, M. C.; Sancho, M. I.; Blanco, S. E.

2014-01-01

The solvatochromic behavior of sulfamethoxazole (SMX) was investigated using UV-vis spectroscopy and DFT methods in neat and binary solvent mixtures. The spectral shifts of this solute were correlated with the Kamlet and Taft parameters (α, β and π*). Multiple lineal regression analysis indicates that both specific hydrogen-bond interaction and non specific dipolar interaction play an important role in the position of the absorption maxima in neat solvents. The simulated absorption spectra using TD-DFT methods were in good agreement with the experimental ones. Binary mixtures consist of cyclohexane (Cy)-ethanol (EtOH), acetonitrile (ACN)-dimethylsulfoxide (DMSO), ACN-dimethylformamide (DMF), and aqueous mixtures containing as co-solvents DMSO, ACN, EtOH and MeOH. Index of preferential solvation was calculated as a function of solvent composition and non-ideal characteristics are observed in all binary mixtures. In ACN-DMSO and ACN-DMF mixtures, the results show that the solvents with higher polarity and hydrogen bond donor ability interact preferentially with the solute. In binary mixtures containing water, the SMX molecules are solvated by the organic co-solvent (DMSO or EtOH) over the whole composition range. Synergistic effect is observed in the case of ACN-H2O and MeOH-H2O, indicating that at certain concentrations solvents interact to form association complexes, which should be more polar than the individual solvents of the mixture.

Single nucleotide polymorphisms in the CD40 gene associate with the disease susceptibility and severity in knee osteoarthritis in the Chinese Han population: a case-control study.

PubMed

Deng, Zhen-Han; Sun, Ming-Hua; Li, Yu-Sheng; Luo, Wei; Zhang, Fang-Jie; Tian, Jian; Wu, Ping; Xiao, Wen-Feng

2017-03-21

This study explored the association between single nucleotide polymorphisms (SNPs) in the CD40 gene, rs4810485 G > T and rs1883832 C > T, as well as disease susceptibility and severity in knee osteoarthritis (KOA) in the Chinese Han population. Peripheral venous blood was collected from 133 KOA patients (KOA group) and 143 healthy people (control group) from December 2012 to November 2013. The patients in the KOA group were classified into mild, moderate and severe groups according to disease severity. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was used to test the genotypes of all subjects. Binary logistic regression analyses were performed to analyze the risk factors for KOA. The KOA group was significantly different from the control group in living environment (P < 0.05). The KOA group had a lower frequency of TT genotype and T allele distribution of rs4810485 G > T compared with the control group, and rs4810485 G > T TT genotype and T allele may associate with low incidence of KOA (all P < 0.05). Besides, T allele and mutant homozygous TT genotype of rs1883832 C > T increased the susceptibility to KOA. Genotype and allele distribution of rs4810485 G > T and rs1883832 C > T were significantly different among the mild, moderate and severe groups (P < 0.05). There were more patients with rs4810485 G > T GG genotype and rs1883832 C > T TT genotype in the severe group than other genotypes of these two SNPs. According to binary logistic regression analysis, rs4810485 G > T TT genotype could alleviate disease severity in KOA, rs1883832 C > T TT genotype increase the severity of KOA and living environment is an important external factor that affects KOA severity. These data provide evidences that rs4810485 G > T and rs1883832 C > T in the CD40 gene may be associated with disease susceptibility and severity in KOA.

Phenotypes of comorbidity in OSAS patients: combining categorical principal component analysis with cluster analysis.

PubMed

Vavougios, George D; George D, George; Pastaka, Chaido; Zarogiannis, Sotirios G; Gourgoulianis, Konstantinos I

2016-02-01

Phenotyping obstructive sleep apnea syndrome's comorbidity has been attempted for the first time only recently. The aim of our study was to determine phenotypes of comorbidity in obstructive sleep apnea syndrome patients employing a data-driven approach. Data from 1472 consecutive patient records were recovered from our hospital's database. Categorical principal component analysis and two-step clustering were employed to detect distinct clusters in the data. Univariate comparisons between clusters included one-way analysis of variance with Bonferroni correction and chi-square tests. Predictors of pairwise cluster membership were determined via a binary logistic regression model. The analyses revealed six distinct clusters: A, 'healthy, reporting sleeping related symptoms'; B, 'mild obstructive sleep apnea syndrome without significant comorbidities'; C1: 'moderate obstructive sleep apnea syndrome, obesity, without significant comorbidities'; C2: 'moderate obstructive sleep apnea syndrome with severe comorbidity, obesity and the exclusive inclusion of stroke'; D1: 'severe obstructive sleep apnea syndrome and obesity without comorbidity and a 33.8% prevalence of hypertension'; and D2: 'severe obstructive sleep apnea syndrome with severe comorbidities, along with the highest Epworth Sleepiness Scale score and highest body mass index'. Clusters differed significantly in apnea-hypopnea index, oxygen desaturation index; arousal index; age, body mass index, minimum oxygen saturation and daytime oxygen saturation (one-way analysis of variance P < 0.0001). Binary logistic regression indicated that older age, greater body mass index, lower daytime oxygen saturation and hypertension were associated independently with an increased risk of belonging in a comorbid cluster. Six distinct phenotypes of obstructive sleep apnea syndrome and its comorbidities were identified. Mapping the heterogeneity of the obstructive sleep apnea syndrome may help the early identification of at-risk groups. Finally, determining predictors of comorbidity for the moderate and severe strata of these phenotypes implies a need to take these factors into account when considering obstructive sleep apnea syndrome treatment options. © 2015 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.

A novel early risk assessment tool for detecting clinical outcomes in patients with heat-related illness (J-ERATO score): Development and validation in independent cohorts in Japan.

PubMed

Hayashida, Kei; Kondo, Yutaka; Hifumi, Toru; Shimazaki, Junya; Oda, Yasutaka; Shiraishi, Shinichiro; Fukuda, Tatsuma; Sasaki, Junichi; Shimizu, Keiki

2018-01-01

We sought to develop a novel risk assessment tool to predict the clinical outcomes after heat-related illness. Prospective, multicenter observational study. Patients who transferred to emergency hospitals in Japan with heat-related illness were registered. The sample was divided into two parts: 60% to construct the score and 40% to validate it. A binary logistic regression model was used to predict hospital admission as a primary outcome. The resulting model was transformed into a scoring system. A total of 3,001 eligible patients were analyzed. There was no difference in variables between development and validation cohorts. Based on the result of a logistic regression model in the development phase (n = 1,805), the J-ERATO score was defined as the sum of the six binary components in the prehospital setting (respiratory rate≥22 /min, Glasgow coma scale<15, systolic blood pressure≤100 mmHg, heart rate≥100 bpm, body temperature≥38°C, and age≥65 y), for a total score ranging from 0 to 6. In the validation phase (n = 1,196), the score had excellent discrimination (C-statistic 0.84; 95% CI 0.79-0.89, p<0.0001) and calibration (P>0.2 by Hosmer-Lemeshow test). The observed proportion of hospital admission increased with increasing J-ERATO score (score = 0, 5.0%; score = 1, 15.0%; score = 2, 24.6%; score = 3, 38.6%; score = 4, 68.0%; score = 5, 85.2%; score = 6, 96.4%). Multivariate analyses showed that the J-ERATO score was an independent positive predictor of hospital admission (adjusted OR, 2.43; 95% CI, 2.06-2.87; P<0.001), intensive care unit (ICU) admission (3.73; 2.95-4.72; P<0.001) and in-hospital mortality (1.65; 1.18-2.32; P = 0.004). The J-ERATO score is simply assessed and can facilitate the identification of patients with higher risk of heat-related hospitalization. This scoring system is also significantly associated with the higher likelihood of ICU admission and in-hospital mortality after heat-related hospitalization.

A comparison of adaptive sampling designs and binary spatial models: A simulation study using a census of Bromus inermis

USGS Publications Warehouse

Irvine, Kathryn M.; Thornton, Jamie; Backus, Vickie M.; Hohmann, Matthew G.; Lehnhoff, Erik A.; Maxwell, Bruce D.; Michels, Kurt; Rew, Lisa

2013-01-01

Commonly in environmental and ecological studies, species distribution data are recorded as presence or absence throughout a spatial domain of interest. Field based studies typically collect observations by sampling a subset of the spatial domain. We consider the effects of six different adaptive and two non-adaptive sampling designs and choice of three binary models on both predictions to unsampled locations and parameter estimation of the regression coefficients (species–environment relationships). Our simulation study is unique compared to others to date in that we virtually sample a true known spatial distribution of a nonindigenous plant species, Bromus inermis. The census of B. inermis provides a good example of a species distribution that is both sparsely (1.9 % prevalence) and patchily distributed. We find that modeling the spatial correlation using a random effect with an intrinsic Gaussian conditionally autoregressive prior distribution was equivalent or superior to Bayesian autologistic regression in terms of predicting to un-sampled areas when strip adaptive cluster sampling was used to survey B. inermis. However, inferences about the relationships between B. inermis presence and environmental predictors differed between the two spatial binary models. The strip adaptive cluster designs we investigate provided a significant advantage in terms of Markov chain Monte Carlo chain convergence when trying to model a sparsely distributed species across a large area. In general, there was little difference in the choice of neighborhood, although the adaptive king was preferred when transects were randomly placed throughout the spatial domain.

Categorical QSAR models for skin sensitization based on local lymph node assay measures and both ground and excited state 4D-fingerprint descriptors

NASA Astrophysics Data System (ADS)

Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Santos-Filho, Osvaldo A.; Esposito, Emilio X.; Hopfinger, Anton J.; Tseng, Yufeng J.

2008-06-01

In previous studies we have developed categorical QSAR models for predicting skin-sensitization potency based on 4D-fingerprint (4D-FP) descriptors and in vivo murine local lymph node assay (LLNA) measures. Only 4D-FP derived from the ground state (GMAX) structures of the molecules were used to build the QSAR models. In this study we have generated 4D-FP descriptors from the first excited state (EMAX) structures of the molecules. The GMAX, EMAX and the combined ground and excited state 4D-FP descriptors (GEMAX) were employed in building categorical QSAR models. Logistic regression (LR) and partial least square coupled logistic regression (PLS-CLR), found to be effective model building for the LLNA skin-sensitization measures in our previous studies, were used again in this study. This also permitted comparison of the prior ground state models to those involving first excited state 4D-FP descriptors. Three types of categorical QSAR models were constructed for each of the GMAX, EMAX and GEMAX datasets: a binary model (2-state), an ordinal model (3-state) and a binary-binary model (two-2-state). No significant differences exist among the LR 2-state model constructed for each of the three datasets. However, the PLS-CLR 3-state and 2-state models based on the EMAX and GEMAX datasets have higher predictivity than those constructed using only the GMAX dataset. These EMAX and GMAX categorical models are also more significant and predictive than corresponding models built in our previous QSAR studies of LLNA skin-sensitization measures.

Noise exposure-response relationships established from repeated binary observations: Modeling approaches and applications.

PubMed

Schäffer, Beat; Pieren, Reto; Mendolia, Franco; Basner, Mathias; Brink, Mark

2017-05-01

Noise exposure-response relationships are used to estimate the effects of noise on individuals or a population. Such relationships may be derived from independent or repeated binary observations, and modeled by different statistical methods. Depending on the method by which they were established, their application in population risk assessment or estimation of individual responses may yield different results, i.e., predict "weaker" or "stronger" effects. As far as the present body of literature on noise effect studies is concerned, however, the underlying statistical methodology to establish exposure-response relationships has not always been paid sufficient attention. This paper gives an overview on two statistical approaches (subject-specific and population-averaged logistic regression analysis) to establish noise exposure-response relationships from repeated binary observations, and their appropriate applications. The considerations are illustrated with data from three noise effect studies, estimating also the magnitude of differences in results when applying exposure-response relationships derived from the two statistical approaches. Depending on the underlying data set and the probability range of the binary variable it covers, the two approaches yield similar to very different results. The adequate choice of a specific statistical approach and its application in subsequent studies, both depending on the research question, are therefore crucial.

Serial binary interval ratios improve rhythm reproduction.

PubMed

Wu, Xiang; Westanmo, Anders; Zhou, Liang; Pan, Junhao

2013-01-01

Musical rhythm perception is a natural human ability that involves complex cognitive processes. Rhythm refers to the organization of events in time, and musical rhythms have an underlying hierarchical metrical structure. The metrical structure induces the feeling of a beat and the extent to which a rhythm induces the feeling of a beat is referred to as its metrical strength. Binary ratios are the most frequent interval ratio in musical rhythms. Rhythms with hierarchical binary ratios are better discriminated and reproduced than rhythms with hierarchical non-binary ratios. However, it remains unclear whether a superiority of serial binary over non-binary ratios in rhythm perception and reproduction exists. In addition, how different types of serial ratios influence the metrical strength of rhythms remains to be elucidated. The present study investigated serial binary vs. non-binary ratios in a reproduction task. Rhythms formed with exclusively binary (1:2:4:8), non-binary integer (1:3:5:6), and non-integer (1:2.3:5.3:6.4) ratios were examined within a constant meter. The results showed that the 1:2:4:8 rhythm type was more accurately reproduced than the 1:3:5:6 and 1:2.3:5.3:6.4 rhythm types, and the 1:2.3:5.3:6.4 rhythm type was more accurately reproduced than the 1:3:5:6 rhythm type. Further analyses showed that reproduction performance was better predicted by the distribution pattern of event occurrences within an inter-beat interval, than by the coincidence of events with beats, or the magnitude and complexity of interval ratios. Whereas rhythm theories and empirical data emphasize the role of the coincidence of events with beats in determining metrical strength and predicting rhythm performance, the present results suggest that rhythm processing may be better understood when the distribution pattern of event occurrences is taken into account. These results provide new insights into the mechanisms underlining musical rhythm perception.

Serial binary interval ratios improve rhythm reproduction

PubMed Central

Wu, Xiang; Westanmo, Anders; Zhou, Liang; Pan, Junhao

2013-01-01

Musical rhythm perception is a natural human ability that involves complex cognitive processes. Rhythm refers to the organization of events in time, and musical rhythms have an underlying hierarchical metrical structure. The metrical structure induces the feeling of a beat and the extent to which a rhythm induces the feeling of a beat is referred to as its metrical strength. Binary ratios are the most frequent interval ratio in musical rhythms. Rhythms with hierarchical binary ratios are better discriminated and reproduced than rhythms with hierarchical non-binary ratios. However, it remains unclear whether a superiority of serial binary over non-binary ratios in rhythm perception and reproduction exists. In addition, how different types of serial ratios influence the metrical strength of rhythms remains to be elucidated. The present study investigated serial binary vs. non-binary ratios in a reproduction task. Rhythms formed with exclusively binary (1:2:4:8), non-binary integer (1:3:5:6), and non-integer (1:2.3:5.3:6.4) ratios were examined within a constant meter. The results showed that the 1:2:4:8 rhythm type was more accurately reproduced than the 1:3:5:6 and 1:2.3:5.3:6.4 rhythm types, and the 1:2.3:5.3:6.4 rhythm type was more accurately reproduced than the 1:3:5:6 rhythm type. Further analyses showed that reproduction performance was better predicted by the distribution pattern of event occurrences within an inter-beat interval, than by the coincidence of events with beats, or the magnitude and complexity of interval ratios. Whereas rhythm theories and empirical data emphasize the role of the coincidence of events with beats in determining metrical strength and predicting rhythm performance, the present results suggest that rhythm processing may be better understood when the distribution pattern of event occurrences is taken into account. These results provide new insights into the mechanisms underlining musical rhythm perception. PMID:23964258

The mechanical properties of high speed GTAW weld and factors of nonlinear multiple regression model under external transverse magnetic field

NASA Astrophysics Data System (ADS)

Lu, Lin; Chang, Yunlong; Li, Yingmin; He, Youyou

2013-05-01

A transverse magnetic field was introduced to the arc plasma in the process of welding stainless steel tubes by high-speed Tungsten Inert Gas Arc Welding (TIG for short) without filler wire. The influence of external magnetic field on welding quality was investigated. 9 sets of parameters were designed by the means of orthogonal experiment. The welding joint tensile strength and form factor of weld were regarded as the main standards of welding quality. A binary quadratic nonlinear regression equation was established with the conditions of magnetic induction and flow rate of Ar gas. The residual standard deviation was calculated to adjust the accuracy of regression model. The results showed that, the regression model was correct and effective in calculating the tensile strength and aspect ratio of weld. Two 3D regression models were designed respectively, and then the impact law of magnetic induction on welding quality was researched.

The logistic model for predicting the non-gonoactive Aedes aegypti females.

PubMed

Reyes-Villanueva, Filiberto; Rodríguez-Pérez, Mario A

2004-01-01

To estimate, using logistic regression, the likelihood of occurrence of a non-gonoactive Aedes aegypti female, previously fed human blood, with relation to body size and collection method. This study was conducted in Monterrey, Mexico, between 1994 and 1996. Ten samplings of 60 mosquitoes of Ae. aegypti females were carried out in three dengue endemic areas: six of biting females, two of emerging mosquitoes, and two of indoor resting females. Gravid females, as well as those with blood in the gut were removed. Mosquitoes were taken to the laboratory and engorged on human blood. After 48 hours, ovaries were dissected to register whether they were gonoactive or non-gonoactive. Wing-length in mm was an indicator for body size. The logistic regression model was used to assess the likelihood of non-gonoactivity, as a binary variable, in relation to wing-length and collection method. Of the 600 females, 164 (27%) remained non-gonoactive, with a wing-length range of 1.9-3.2 mm, almost equal to that of all females (1.8-3.3 mm). The logistic regression model showed a significant likelihood of a female remaining non-gonoactive (Y=1). The collection method did not influence the binary response, but there was an inverse relationship between non-gonoactivity and wing-length. Dengue vector populations from Monterrey, Mexico display a wide-range body size. Logistic regression was a useful tool to estimate the likelihood for an engorged female to remain non-gonoactive. The necessity for a second blood meal is present in any female, but small mosquitoes are more likely to bite again within a 2-day interval, in order to attain egg maturation. The English version of this paper is available too at: http://www.insp.mx/salud/index.html.

Acculturation and healthy lifestyle habits among Hispanics in United States-Mexico border communities.

PubMed

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.

A general method for handling missing binary outcome data in randomized controlled trials.

PubMed

Jackson, Dan; White, Ian R; Mason, Dan; Sutton, Stephen

2014-12-01

The analysis of randomized controlled trials with incomplete binary outcome data is challenging. We develop a general method for exploring the impact of missing data in such trials, with a focus on abstinence outcomes. We propose a sensitivity analysis where standard analyses, which could include 'missing = smoking' and 'last observation carried forward', are embedded in a wider class of models. We apply our general method to data from two smoking cessation trials. A total of 489 and 1758 participants from two smoking cessation trials. The abstinence outcomes were obtained using telephone interviews. The estimated intervention effects from both trials depend on the sensitivity parameters used. The findings differ considerably in magnitude and statistical significance under quite extreme assumptions about the missing data, but are reasonably consistent under more moderate assumptions. A new method for undertaking sensitivity analyses when handling missing data in trials with binary outcomes allows a wide range of assumptions about the missing data to be assessed. In two smoking cessation trials the results were insensitive to all but extreme assumptions. © 2014 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.

Survey for δ Sct components in eclipsing binaries and new correlations between pulsation frequency and fundamental stellar characteristics

NASA Astrophysics Data System (ADS)

Liakos, A.; Niarchos, P.; Soydugan, E.; Zasche, P.

2012-05-01

CCD observations of 68 eclipsing binary systems, candidates for containing δ Scuti components, were obtained. Their light curves are analysed using the PERIOD04 software for possible pulsational behaviour. For the systems QY Aql, CZ Aqr, TY Cap, WY Cet, UW Cyg, HL Dra, HZ Dra, AU Lac, CL Lyn and IO UMa, complete light curves were observed due to the detection of a pulsating component. All of them, except QY Aql and IO UMa, are analysed with modern astronomical softwares in order to determine their geometrical and pulsational characteristics. Spectroscopic observations of WY Cet and UW Cyg were used to estimate the spectral class of their primary components, while for HZ Dra radial velocities of its primary were measured. O - C diagram analysis was performed for the cases showing peculiar orbital period variations, namely CZ Aqr, TY Cap, WY Cet and UW Cyg, with the aim of obtaining a comprehensive picture of these systems. An updated catalogue of 74 close binaries including a δ Scuti companion is presented. Moreover, a connection between orbital and pulsation periods, as well as a correlation between evolutionary status and dominant pulsation frequency for these systems, is discussed.

As(V) and Sb(V) co-adsorption onto ferrihydrite: synergistic effect of Sb(V) on As(V) under competitive conditions.

PubMed

Wu, Debo; Sun, Sheng-Peng; He, Minghe; Wu, Zhangxiong; Xiao, Jie; Chen, Xiao Dong; Wu, Winston Duo

2018-05-01

Competitive adsorption of As(V) and Sb(V) at environmentally relevant concentrations onto ferrihydrite was investigated. Batch experiments and XPS analyses confirmed that in a binary system, the presence of Sb(V) exhibited a slight synergistic effect on As(V) adsorption. XPS analyses showed that As(V) and Sb(V) adsorption led to obvious diminishment of Fe-O-Fe and Fe-O-H bonds respectively. At pH of 9, a more significant decrease of Fe-O-Fe was observed in the binary system than that in a single system, indicating that As(V) displayed an even stronger interaction with lattice oxygen atoms under competitive conditions. Basically, ionic strength demonstrated a negligible or positive influence on As(V) and Sb(V) adsorption in binary system. Study of adsorption sequence also indicated that the presence of Sb(V) showed a promotion effect on As(V) adsorption at neutral pHs. Considering that co-contamination of As and Sb in waters has been of great concern throughout the world, our findings contributed to a better understanding of their distribution, mobility, and fate in environment.

Logistic random effects regression models: a comparison of statistical packages for binary and ordinal outcomes

PubMed Central

2011-01-01

Background Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. Methods We used individual patient data from 8509 patients in 231 centers with moderate and severe Traumatic Brain Injury (TBI) enrolled in eight Randomized Controlled Trials (RCTs) and three observational studies. We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS) as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. We then compared the implementations of frequentist and Bayesian methods to estimate the fixed and random effects. Frequentist approaches included R (lme4), Stata (GLLAMM), SAS (GLIMMIX and NLMIXED), MLwiN ([R]IGLS) and MIXOR, Bayesian approaches included WinBUGS, MLwiN (MCMC), R package MCMCglmm and SAS experimental procedure MCMC. Three data sets (the full data set and two sub-datasets) were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. For the ordinal outcome in the full data set also a proportional odds model with a random center effect was fitted. Results The packages gave similar parameter estimates for both the fixed and random effects and for the binary (and ordinal) models for the main study and when based on a relatively large number of level-1 (patient level) data compared to the number of level-2 (hospital level) data. However, when based on relatively sparse data set, i.e. when the numbers of level-1 and level-2 data units were about the same, the frequentist and Bayesian approaches showed somewhat different results. The software implementations differ considerably in flexibility, computation time, and usability. There are also differences in the availability of additional tools for model evaluation, such as diagnostic plots. The experimental SAS (version 9.2) procedure MCMC appeared to be inefficient. Conclusions On relatively large data sets, the different software implementations of logistic random effects regression models produced similar results. Thus, for a large data set there seems to be no explicit preference (of course if there is no preference from a philosophical point of view) for either a frequentist or Bayesian approach (if based on vague priors). The choice for a particular implementation may largely depend on the desired flexibility, and the usability of the package. For small data sets the random effects variances are difficult to estimate. In the frequentist approaches the MLE of this variance was often estimated zero with a standard error that is either zero or could not be determined, while for Bayesian methods the estimates could depend on the chosen "non-informative" prior of the variance parameter. The starting value for the variance parameter may be also critical for the convergence of the Markov chain. PMID:21605357

Predicting High School Students' Interest in Majoring in a STEM Field: Insight into High School Students' Postsecondary Plans

ERIC Educational Resources Information Center

Lichtenberger, Eric; George-Jackson, Casey

2013-01-01

This study examined how various individual, family, and school level contextual factors impact the likelihood of planning to major in one of the science, technology, engineering, or mathematics (STEM) fields for high school students. A binary logistic regression model was developed to determine the extent to which each of the covariates helped to…

Community-Based Juvenile Reentry Services: The Effects of Service Dosage on Juvenile and Adult Recidivism

ERIC Educational Resources Information Center

Abrams, Laura S.; Terry, Diane; Franke, Todd M.

2011-01-01

In this study the authors examined the influence of length of participation in a community-based reentry program on the odds of reconviction in the juvenile and adult criminal justice systems. A structured telephone survey of reentry program alumni was conducted with 75 transition-age (18-25 year-old) young men. Binary logistic regression analysis…

Predicators of Success for Undergraduate Students Reinstated after an Academic Dismissal at a Small Midwest Private University Campus

ERIC Educational Resources Information Center

Meador, Ryan E.

2012-01-01

This study examined students who successfully applied for reinstatement after being academically dismissed for the first time in order to discover indicators of future success. This study examined 666 students' appeals filed at the DeVry University Kansas City campus between 2004 and 2009. Binary logistic regression was used to discover if a…

Experiences That Predict Early Career Teacher Commitment to and Retention in High-Poverty Urban Schools

ERIC Educational Resources Information Center

Whipp, Joan L.; Geronime, Lara

2017-01-01

Correlation analysis was used to analyze what experiences before and during teacher preparation for 72 graduates of an urban teacher education program were associated with urban commitment, first job location, and retention in urban schools for 3 or more years. Binary logistic regression was then used to analyze whether urban K-12 schooling,…

The cost of acquiring public hunting access on family forests lands

Treesearch

Michael A. Kilgore; Stephanie A. Snyder; Joesph M. Schertz; Steven J. Taff

2008-01-01

To address the issue of declining access to private forest land in the United States for hunting, over 1,000 Minnesota family forest owners were surveyed to estimate the cost of acquiring non-exclusive public hunting access rights. The results indicate landowner interest in selling access rights is extremely modest. Using binary logistic regression, the mean annual...

Exploring the Effects of Managerial Ownership on the Decision to Go Private: A Behavioral Agency Model Approach

ERIC Educational Resources Information Center

Valenti, Alix; Schneider, Marguerite

2012-01-01

This paper utilizes the behavioral agency model to investigate why many formerly public companies have been converted to privately held corporations. Using a matched pairs sample and categorical binary regression, and controlling for effects found in previous studies, we explore how the equity ownership of those entrusted to manage firms, the…

Understanding the Gap between Cognitive Abilities and Daily Living Skills in Adolescents with Autism Spectrum Disorders with Average Intelligence

ERIC Educational Resources Information Center

Duncan, Amie W.; Bishop, Somer L.

2015-01-01

Daily living skills standard scores on the Vineland Adaptive Behavior Scales-2nd edition were examined in 417 adolescents from the Simons Simplex Collection. All participants had at least average intelligence and a diagnosis of autism spectrum disorder. Descriptive statistics and binary logistic regressions were used to examine the prevalence and…

Sociodemographic Barriers to Early Detection of Autism: Screening and Evaluation Using the M-CHAT, M-CHAT-R, and Follow-Up

ERIC Educational Resources Information Center

Khowaja, Meena K.; Hazzard, Ann P.; Robins, Diana L.

2015-01-01

Parents (n = 11,845) completed the Modified Checklist for Autism in Toddlers (or its latest revision) at pediatric visits. Using sociodemographic predictors of maternal education and race, binary logistic regressions were utilized to examine differences in autism screening, diagnostic evaluation participation rates and outcomes, and reasons for…

The Effect of Participating in Indiana's Twenty-First Century Scholars Program on College Enrollments

ERIC Educational Resources Information Center

Toutkoushian, Robert K.; Hossler, Don; DesJardins, Stephen L.; McCall, Brian; Gonzalez Canche, Manuel S.

2015-01-01

Our study adds to prior work on Indiana's Twenty-first Century Scholars(TFCS) program by focusing on whether participating in--rather than completing--the program affects the likelihood of students going to college and where they initially enrolled. We first employ binary and multinomial logistic regression to obtain estimates of the impact of the…

Sample size adjustments for varying cluster sizes in cluster randomized trials with binary outcomes analyzed with second-order PQL mixed logistic regression.

PubMed

Candel, Math J J M; Van Breukelen, Gerard J P

2010-06-30

Adjustments of sample size formulas are given for varying cluster sizes in cluster randomized trials with a binary outcome when testing the treatment effect with mixed effects logistic regression using second-order penalized quasi-likelihood estimation (PQL). Starting from first-order marginal quasi-likelihood (MQL) estimation of the treatment effect, the asymptotic relative efficiency of unequal versus equal cluster sizes is derived. A Monte Carlo simulation study shows this asymptotic relative efficiency to be rather accurate for realistic sample sizes, when employing second-order PQL. An approximate, simpler formula is presented to estimate the efficiency loss due to varying cluster sizes when planning a trial. In many cases sampling 14 per cent more clusters is sufficient to repair the efficiency loss due to varying cluster sizes. Since current closed-form formulas for sample size calculation are based on first-order MQL, planning a trial also requires a conversion factor to obtain the variance of the second-order PQL estimator. In a second Monte Carlo study, this conversion factor turned out to be 1.25 at most. (c) 2010 John Wiley & Sons, Ltd.

A binary genetic programing model for teleconnection identification between global sea surface temperature and local maximum monthly rainfall events

NASA Astrophysics Data System (ADS)

Danandeh Mehr, Ali; Nourani, Vahid; Hrnjica, Bahrudin; Molajou, Amir

2017-12-01

The effectiveness of genetic programming (GP) for solving regression problems in hydrology has been recognized in recent studies. However, its capability to solve classification problems has not been sufficiently explored so far. This study develops and applies a novel classification-forecasting model, namely Binary GP (BGP), for teleconnection studies between sea surface temperature (SST) variations and maximum monthly rainfall (MMR) events. The BGP integrates certain types of data pre-processing and post-processing methods with conventional GP engine to enhance its ability to solve both regression and classification problems simultaneously. The model was trained and tested using SST series of Black Sea, Mediterranean Sea, and Red Sea as potential predictors as well as classified MMR events at two locations in Iran as predictand. Skill of the model was measured in regard to different rainfall thresholds and SST lags and compared to that of the hybrid decision tree-association rule (DTAR) model available in the literature. The results indicated that the proposed model can identify potential teleconnection signals of surrounding seas beneficial to long-term forecasting of the occurrence of the classified MMR events.

Predicting the "graduate on time (GOT)" of PhD students using binary logistics regression model

NASA Astrophysics Data System (ADS)

Shariff, S. Sarifah Radiah; Rodzi, Nur Atiqah Mohd; Rahman, Kahartini Abdul; Zahari, Siti Meriam; Deni, Sayang Mohd

2016-10-01

Malaysian government has recently set a new goal to produce 60,000 Malaysian PhD holders by the year 2023. As a Malaysia's largest institution of higher learning in terms of size and population which offers more than 500 academic programmes in a conducive and vibrant environment, UiTM has taken several initiatives to fill up the gap. Strategies to increase the numbers of graduates with PhD are a process that is challenging. In many occasions, many have already identified that the struggle to get into the target set is even more daunting, and that implementation is far too ideal. This has further being progressing slowly as the attrition rate increases. This study aims to apply the proposed models that incorporates several factors in predicting the number PhD students that will complete their PhD studies on time. Binary Logistic Regression model is proposed and used on the set of data to determine the number. The results show that only 6.8% of the 2014 PhD students are predicted to graduate on time and the results are compared wih the actual number for validation purpose.

The likelihood of achieving quantified road safety targets: a binary logistic regression model for possible factors.

PubMed

Sze, N N; Wong, S C; Lee, C Y

2014-12-01

In past several decades, many countries have set quantified road safety targets to motivate transport authorities to develop systematic road safety strategies and measures and facilitate the achievement of continuous road safety improvement. Studies have been conducted to evaluate the association between the setting of quantified road safety targets and road fatality reduction, in both the short and long run, by comparing road fatalities before and after the implementation of a quantified road safety target. However, not much work has been done to evaluate whether the quantified road safety targets are actually achieved. In this study, we used a binary logistic regression model to examine the factors - including vehicle ownership, fatality rate, and national income, in addition to level of ambition and duration of target - that contribute to a target's success. We analyzed 55 quantified road safety targets set by 29 countries from 1981 to 2009, and the results indicate that targets that are in progress and with lower level of ambitions had a higher likelihood of eventually being achieved. Moreover, possible interaction effects on the association between level of ambition and the likelihood of success are also revealed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Meta-analysis of haplotype-association studies: comparison of methods and empirical evaluation of the literature

PubMed Central

2011-01-01

Background Meta-analysis is a popular methodology in several fields of medical research, including genetic association studies. However, the methods used for meta-analysis of association studies that report haplotypes have not been studied in detail. In this work, methods for performing meta-analysis of haplotype association studies are summarized, compared and presented in a unified framework along with an empirical evaluation of the literature. Results We present multivariate methods that use summary-based data as well as methods that use binary and count data in a generalized linear mixed model framework (logistic regression, multinomial regression and Poisson regression). The methods presented here avoid the inflation of the type I error rate that could be the result of the traditional approach of comparing a haplotype against the remaining ones, whereas, they can be fitted using standard software. Moreover, formal global tests are presented for assessing the statistical significance of the overall association. Although the methods presented here assume that the haplotypes are directly observed, they can be easily extended to allow for such an uncertainty by weighting the haplotypes by their probability. Conclusions An empirical evaluation of the published literature and a comparison against the meta-analyses that use single nucleotide polymorphisms, suggests that the studies reporting meta-analysis of haplotypes contain approximately half of the included studies and produce significant results twice more often. We show that this excess of statistically significant results, stems from the sub-optimal method of analysis used and, in approximately half of the cases, the statistical significance is refuted if the data are properly re-analyzed. Illustrative examples of code are given in Stata and it is anticipated that the methods developed in this work will be widely applied in the meta-analysis of haplotype association studies. PMID:21247440

An epidemiological survey on road traffic crashes in Iran: application of the two logistic regression models.

PubMed

Bakhtiyari, Mahmood; Mehmandar, Mohammad Reza; Mirbagheri, Babak; Hariri, Gholam Reza; Delpisheh, Ali; Soori, Hamid

2014-01-01

Risk factors of human-related traffic crashes are the most important and preventable challenges for community health due to their noteworthy burden in developing countries in particular. The present study aims to investigate the role of human risk factors of road traffic crashes in Iran. Through a cross-sectional study using the COM 114 data collection forms, the police records of almost 600,000 crashes occurred in 2010 are investigated. The binary logistic regression and proportional odds regression models are used. The odds ratio for each risk factor is calculated. These models are adjusted for known confounding factors including age, sex and driving time. The traffic crash reports of 537,688 men (90.8%) and 54,480 women (9.2%) are analysed. The mean age is 34.1 ± 14 years. Not maintaining eyes on the road (53.7%) and losing control of the vehicle (21.4%) are the main causes of drivers' deaths in traffic crashes within cities. Not maintaining eyes on the road is also the most frequent human risk factor for road traffic crashes out of cities. Sudden lane excursion (OR = 9.9, 95% CI: 8.2-11.9) and seat belt non-compliance (OR = 8.7, CI: 6.7-10.1), exceeding authorised speed (OR = 17.9, CI: 12.7-25.1) and exceeding safe speed (OR = 9.7, CI: 7.2-13.2) are the most significant human risk factors for traffic crashes in Iran. The high mortality rate of 39 people for every 100,000 population emphasises on the importance of traffic crashes in Iran. Considering the important role of human risk factors in traffic crashes, struggling efforts are required to control dangerous driving behaviours such as exceeding speed, illegal overtaking and not maintaining eyes on the road.

Smooth Scalar-on-Image Regression via Spatial Bayesian Variable Selection

PubMed Central

Goldsmith, Jeff; Huang, Lei; Crainiceanu, Ciprian M.

2013-01-01

We develop scalar-on-image regression models when images are registered multidimensional manifolds. We propose a fast and scalable Bayes inferential procedure to estimate the image coefficient. The central idea is the combination of an Ising prior distribution, which controls a latent binary indicator map, and an intrinsic Gaussian Markov random field, which controls the smoothness of the nonzero coefficients. The model is fit using a single-site Gibbs sampler, which allows fitting within minutes for hundreds of subjects with predictor images containing thousands of locations. The code is simple and is provided in less than one page in the Appendix. We apply this method to a neuroimaging study where cognitive outcomes are regressed on measures of white matter microstructure at every voxel of the corpus callosum for hundreds of subjects. PMID:24729670

A stratification approach using logit-based models for confounder adjustment in the study of continuous outcomes.

PubMed

Tan, Chuen Seng; Støer, Nathalie C; Chen, Ying; Andersson, Marielle; Ning, Yilin; Wee, Hwee-Lin; Khoo, Eric Yin Hao; Tai, E-Shyong; Kao, Shih Ling; Reilly, Marie

2017-01-01

The control of confounding is an area of extensive epidemiological research, especially in the field of causal inference for observational studies. Matched cohort and case-control study designs are commonly implemented to control for confounding effects without specifying the functional form of the relationship between the outcome and confounders. This paper extends the commonly used regression models in matched designs for binary and survival outcomes (i.e. conditional logistic and stratified Cox proportional hazards) to studies of continuous outcomes through a novel interpretation and application of logit-based regression models from the econometrics and marketing research literature. We compare the performance of the maximum likelihood estimators using simulated data and propose a heuristic argument for obtaining the residuals for model diagnostics. We illustrate our proposed approach with two real data applications. Our simulation studies demonstrate that our stratification approach is robust to model misspecification and that the distribution of the estimated residuals provides a useful diagnostic when the strata are of moderate size. In our applications to real data, we demonstrate that parity and menopausal status are associated with percent mammographic density, and that the mean level and variability of inpatient blood glucose readings vary between medical and surgical wards within a national tertiary hospital. Our work highlights how the same class of regression models, available in most statistical software, can be used to adjust for confounding in the study of binary, time-to-event and continuous outcomes.

Regression analysis for solving diagnosis problem of children's health

NASA Astrophysics Data System (ADS)

Cherkashina, Yu A.; Gerget, O. M.

2016-04-01

The paper includes results of scientific researches. These researches are devoted to the application of statistical techniques, namely, regression analysis, to assess the health status of children in the neonatal period based on medical data (hemostatic parameters, parameters of blood tests, the gestational age, vascular-endothelial growth factor) measured at 3-5 days of children's life. In this paper a detailed description of the studied medical data is given. A binary logistic regression procedure is discussed in the paper. Basic results of the research are presented. A classification table of predicted values and factual observed values is shown, the overall percentage of correct recognition is determined. Regression equation coefficients are calculated, the general regression equation is written based on them. Based on the results of logistic regression, ROC analysis was performed, sensitivity and specificity of the model are calculated and ROC curves are constructed. These mathematical techniques allow carrying out diagnostics of health of children providing a high quality of recognition. The results make a significant contribution to the development of evidence-based medicine and have a high practical importance in the professional activity of the author.

Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

PubMed

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.

Mass-Luminosity Relations for Rapid and Slow Rotators.

NASA Astrophysics Data System (ADS)

Malkov, O. Yu.

2006-08-01

Comparing the radii of eclipsing binaries components and single stars we have found a noticeable difference between observational parameters of B0V-G0V components of eclipsing binaries and those of single stars of the corresponding spectral type. This difference was confirmed by re-analysing the results of independent investigations published in the literature. Larger radii and higher temperatures of A-F eclipsing binaries can be explained by synchronization of such stars in close systems that prevents them to rotate rapidly. So, we have found that the mass-luminosity relation based on eclipsing binary data cannot be used to derive the initial mass function of single stars. While our current knowledge of the empirical mass-luminosity relation for intermediate-mass (1.5 to 10 m[*]) stars is based exclusively on data from eclipsing binaries, knowledge of the mass-luminosity relation should come from dynamical mass determinations of visual binaries, combined with spatially resolved precise photometry. Then the initial mass function should be revised for m>1.5m[*]. Data were collected on fundamental parameters of stars with masses m > 1.5.m [*]). They are components of binaries with P > 15^d and consequently are not synchronised with the orbital periods and presumably are rapid rotators. These stars are believed to evolve similarly with single stars, so these data allow us to construct mass-luminosity and other relations that can more confidently be used for statistical and astrophysical investigations of single stars than so called standard relations, based on data on detached main-sequence double-lined short-period eclipsing binaries. Mass-luminosity, mass-temperature and mass-radius relations of single stars are presented, as well as their HR diagram.

Error-analysis and comparison to analytical models of numerical waveforms produced by the NRAR Collaboration

NASA Astrophysics Data System (ADS)

Hinder, Ian; Buonanno, Alessandra; Boyle, Michael; Etienne, Zachariah B.; Healy, James; Johnson-McDaniel, Nathan K.; Nagar, Alessandro; Nakano, Hiroyuki; Pan, Yi; Pfeiffer, Harald P.; Pürrer, Michael; Reisswig, Christian; Scheel, Mark A.; Schnetter, Erik; Sperhake, Ulrich; Szilágyi, Bela; Tichy, Wolfgang; Wardell, Barry; Zenginoğlu, Anıl; Alic, Daniela; Bernuzzi, Sebastiano; Bode, Tanja; Brügmann, Bernd; Buchman, Luisa T.; Campanelli, Manuela; Chu, Tony; Damour, Thibault; Grigsby, Jason D.; Hannam, Mark; Haas, Roland; Hemberger, Daniel A.; Husa, Sascha; Kidder, Lawrence E.; Laguna, Pablo; London, Lionel; Lovelace, Geoffrey; Lousto, Carlos O.; Marronetti, Pedro; Matzner, Richard A.; Mösta, Philipp; Mroué, Abdul; Müller, Doreen; Mundim, Bruno C.; Nerozzi, Andrea; Paschalidis, Vasileios; Pollney, Denis; Reifenberger, George; Rezzolla, Luciano; Shapiro, Stuart L.; Shoemaker, Deirdre; Taracchini, Andrea; Taylor, Nicholas W.; Teukolsky, Saul A.; Thierfelder, Marcus; Witek, Helvi; Zlochower, Yosef

2013-01-01

The Numerical-Relativity-Analytical-Relativity (NRAR) collaboration is a joint effort between members of the numerical relativity, analytical relativity and gravitational-wave data analysis communities. The goal of the NRAR collaboration is to produce numerical-relativity simulations of compact binaries and use them to develop accurate analytical templates for the LIGO/Virgo Collaboration to use in detecting gravitational-wave signals and extracting astrophysical information from them. We describe the results of the first stage of the NRAR project, which focused on producing an initial set of numerical waveforms from binary black holes with moderate mass ratios and spins, as well as one non-spinning binary configuration which has a mass ratio of 10. All of the numerical waveforms are analysed in a uniform and consistent manner, with numerical errors evaluated using an analysis code created by members of the NRAR collaboration. We compare previously-calibrated, non-precessing analytical waveforms, notably the effective-one-body (EOB) and phenomenological template families, to the newly-produced numerical waveforms. We find that when the binary's total mass is ˜100-200M⊙, current EOB and phenomenological models of spinning, non-precessing binary waveforms have overlaps above 99% (for advanced LIGO) with all of the non-precessing-binary numerical waveforms with mass ratios ⩽4, when maximizing over binary parameters. This implies that the loss of event rate due to modelling error is below 3%. Moreover, the non-spinning EOB waveforms previously calibrated to five non-spinning waveforms with mass ratio smaller than 6 have overlaps above 99.7% with the numerical waveform with a mass ratio of 10, without even maximizing on the binary parameters.

Bayesian inference for unidirectional misclassification of a binary response trait.

PubMed

Xia, Michelle; Gustafson, Paul

2018-03-15

When assessing association between a binary trait and some covariates, the binary response may be subject to unidirectional misclassification. Unidirectional misclassification can occur when revealing a particular level of the trait is associated with a type of cost, such as a social desirability or financial cost. The feasibility of addressing misclassification is commonly obscured by model identification issues. The current paper attempts to study the efficacy of inference when the binary response variable is subject to unidirectional misclassification. From a theoretical perspective, we demonstrate that the key model parameters possess identifiability, except for the case with a single binary covariate. From a practical standpoint, the logistic model with quantitative covariates can be weakly identified, in the sense that the Fisher information matrix may be near singular. This can make learning some parameters difficult under certain parameter settings, even with quite large samples. In other cases, the stronger identification enables the model to provide more effective adjustment for unidirectional misclassification. An extension to the Poisson approximation of the binomial model reveals the identifiability of the Poisson and zero-inflated Poisson models. For fully identified models, the proposed method adjusts for misclassification based on learning from data. For binary models where there is difficulty in identification, the method is useful for sensitivity analyses on the potential impact from unidirectional misclassification. Copyright © 2017 John Wiley & Sons, Ltd.

Binary stars in the Galactic thick disc

NASA Astrophysics Data System (ADS)

Izzard, Robert G.; Preece, Holly; Jofre, Paula; Halabi, Ghina M.; Masseron, Thomas; Tout, Christopher A.

2018-01-01

The combination of asteroseismologically measured masses with abundances from detailed analyses of stellar atmospheres challenges our fundamental knowledge of stars and our ability to model them. Ancient red-giant stars in the Galactic thick disc are proving to be most troublesome in this regard. They are older than 5 Gyr, a lifetime corresponding to an initial stellar mass of about 1.2 M⊙. So why do the masses of a sizeable fraction of thick-disc stars exceed 1.3 M⊙, with some as massive as 2.3 M⊙? We answer this question by considering duplicity in the thick-disc stellar population using a binary population-nucleosynthesis model. We examine how mass transfer and merging affect the stellar mass distribution and surface abundances of carbon and nitrogen. We show that a few per cent of thick-disc stars can interact in binary star systems and become more massive than 1.3 M⊙. Of these stars, most are single because they are merged binaries. Some stars more massive than 1.3 M⊙ form in binaries by wind mass transfer. We compare our results to a sample of the APOKASC data set and find reasonable agreement except in the number of these thick-disc stars more massive than 1.3 M⊙. This problem is resolved by the use of a logarithmically flat orbital-period distribution and a large binary fraction.

Causal analysis of ordinal treatments and binary outcomes under truncation by death.

PubMed

Wang, Linbo; Richardson, Thomas S; Zhou, Xiao-Hua

2017-06-01

It is common that in multi-arm randomized trials, the outcome of interest is "truncated by death," meaning that it is only observed or well-defined conditioning on an intermediate outcome. In this case, in addition to pairwise contrasts, the joint inference for all treatment arms is also of interest. Under a monotonicity assumption we present methods for both pairwise and joint causal analyses of ordinal treatments and binary outcomes in presence of truncation by death. We illustrate via examples the appropriateness of our assumptions in different scientific contexts.

Novel spectrophotometric methods for simultaneous determination of timolol and dorzolamide in their binary mixture.

PubMed

Lotfy, Hayam Mahmoud; Hegazy, Maha A; Rezk, Mamdouh R; Omran, Yasmin Rostom

2014-05-21

Two smart and novel spectrophotometric methods namely; absorbance subtraction (AS) and amplitude modulation (AM) were developed and validated for the determination of a binary mixture of timolol maleate (TIM) and dorzolamide hydrochloride (DOR) in presence of benzalkonium chloride without prior separation, using unified regression equation. Additionally, simple, specific, accurate and precise spectrophotometric methods manipulating ratio spectra were developed and validated for simultaneous determination of the binary mixture namely; simultaneous ratio subtraction (SRS), ratio difference (RD), ratio subtraction (RS) coupled with extended ratio subtraction (EXRS), constant multiplication method (CM) and mean centering of ratio spectra (MCR). The proposed spectrophotometric procedures do not require any separation steps. Accuracy, precision and linearity ranges of the proposed methods were determined and the specificity was assessed by analyzing synthetic mixtures of both drugs. They were applied to their pharmaceutical formulation and the results obtained were statistically compared to that of a reported spectrophotometric method. The statistical comparison showed that there is no significant difference between the proposed methods and the reported one regarding both accuracy and precision. Copyright © 2014 Elsevier B.V. All rights reserved.

Circumbinary discs: Numerical and physical behaviour

NASA Astrophysics Data System (ADS)

Thun, Daniel; Kley, Wilhelm; Picogna, Giovanni

2017-08-01

Aims: Discs around a central binary system play an important role in star and planet formation and in the evolution of galactic discs. These circumbinary discs are strongly disturbed by the time varying potential of the binary system and display a complex dynamical evolution that is not well understood. Our goal is to investigate the impact of disc and binary parameters on the dynamical aspects of the disc. Methods: We study the evolution of circumbinary discs under the gravitational influence of the binary using two-dimensional hydrodynamical simulations. To distinguish between physical and numerical effects we apply three hydrodynamical codes. First we analyse in detail numerical issues concerning the conditions at the boundaries and grid resolution. We then perform a series of simulations with different binary parameters (eccentricity, mass ratio) and disc parameters (viscosity, aspect ratio) starting from a reference model with Kepler-16 parameters. Results: Concerning the numerical aspects we find that the length of the inner grid radius and the binary semi-major axis must be comparable, with free outflow conditions applied such that mass can flow onto the central binary. A closed inner boundary leads to unstable evolutions. We find that the inner disc turns eccentric and precesses for all investigated physical parameters. The precession rate is slow with periods (Tprec) starting at around 500 binary orbits (Tbin) for high viscosity and a high aspect ratio H/R where the inner hole is smaller and more circular. Reducing α and H/R increases the gap size and Tprec reaches 2500 Tbin. For varying binary mass ratios qbin the gap size remains constant, whereas Tprec decreases with increasing qbin. For varying binary eccentricities ebin we find two separate branches in the gap size and eccentricity diagram. The bifurcation occurs at around ecrit ≈ 0.18 where the gap is smallest with the shortest Tprec. For ebin lower and higher than ecrit, the gap size and Tprec increase. Circular binaries create the most eccentric discs. Movies associated to Figs. 1 and 8 are available at http://www.aanda.org

Detecting nonsense for Chinese comments based on logistic regression

NASA Astrophysics Data System (ADS)

Zhuolin, Ren; Guang, Chen; Shu, Chen

2016-07-01

To understand cyber citizens' opinion accurately from Chinese news comments, the clear definition on nonsense is present, and a detection model based on logistic regression (LR) is proposed. The detection of nonsense can be treated as a binary-classification problem. Besides of traditional lexical features, we propose three kinds of features in terms of emotion, structure and relevance. By these features, we train an LR model and demonstrate its effect in understanding Chinese news comments. We find that each of proposed features can significantly promote the result. In our experiments, we achieve a prediction accuracy of 84.3% which improves the baseline 77.3% by 7%.

Regression trees for predicting mortality in patients with cardiovascular disease: What improvement is achieved by using ensemble-based methods?

PubMed Central

Austin, Peter C; Lee, Douglas S; Steyerberg, Ewout W; Tu, Jack V

2012-01-01

In biomedical research, the logistic regression model is the most commonly used method for predicting the probability of a binary outcome. While many clinical researchers have expressed an enthusiasm for regression trees, this method may have limited accuracy for predicting health outcomes. We aimed to evaluate the improvement that is achieved by using ensemble-based methods, including bootstrap aggregation (bagging) of regression trees, random forests, and boosted regression trees. We analyzed 30-day mortality in two large cohorts of patients hospitalized with either acute myocardial infarction (N = 16,230) or congestive heart failure (N = 15,848) in two distinct eras (1999–2001 and 2004–2005). We found that both the in-sample and out-of-sample prediction of ensemble methods offered substantial improvement in predicting cardiovascular mortality compared to conventional regression trees. However, conventional logistic regression models that incorporated restricted cubic smoothing splines had even better performance. We conclude that ensemble methods from the data mining and machine learning literature increase the predictive performance of regression trees, but may not lead to clear advantages over conventional logistic regression models for predicting short-term mortality in population-based samples of subjects with cardiovascular disease. PMID:22777999

High speed rail and coastal tourism: Identifying passenger profiles and travel behaviour

PubMed Central

Ortuño, Armando

2017-01-01

In this paper, we characterise tourists most likely to visit a coastal destination by high-speed rail (HSR). Our data came from a survey conducted among HSR passengers during 2014’s high season (July and August) at Spain’s Camp de Tarragona and Alicante Stations, each of which is near a mass tourism destination on the Mediterranean coast: the Costa Daurada and the Costa Blanca, respectively. We used responses to the survey, which presented binary discrete-choice situations, to construct a database necessary for a logistic regression model that allowed us to examine how passenger profile, trip characteristics, and stay conditions influenced the use of HSR services on visits to each coastal destination. Results highlighted significant differences in the profiles of tourists who arrived at each destination by HSR and, in turn, that no specific tourist profile is associated with HSR, even for two stations that serve sunny beach destinations. Among its implications, to analyse travellers that HSR can attract, it is vital to consider the specific characteristics of each destination and its current market. PMID:28644893

Improving Consumer Satisfaction with Addiction Treatment: An Analysis of Alumni Preferences.

PubMed

Sanghani, Ruchi M; Moler, Alexander K

2015-01-01

Objective. The primary objective of this investigation is to determine which individual and aggregate factors of residential addiction treatment centers are most significant influencers of alumni satisfaction. Design. Survey targeted alumni of residential addiction treatment facilities. Alumni were queried through a survey, which utilized Likert-scale matrices and binary response options: 379 respondents met the completion threshold. Alumni rated amenities and individual and group counseling factors; additionally, respondents provided feedback on two satisfaction proxies: cost worthiness and future recommendations. Descriptive and relational analyses were conducted, with the latter utilizing logistic regression models. Results. Individual factors' scores of group counseling, and overall aggregate group counseling score, are most enthusiastically positive. Group counseling is also the most significant influencer of satisfaction. Other significant influencers of satisfaction are met expectations for individual counseling and psychiatric care offerings. Conclusions. While individual counseling and facility amenities should not be ignored, group counseling may be the most significant influencer of alumni satisfaction. Long-term outcomes are not single-faceted; however, treatment providers should be encouraged to invest in high-quality group counseling offerings in order to best satisfy, and thereby empower, clients.

High speed rail and coastal tourism: Identifying passenger profiles and travel behaviour.

PubMed

Gutiérrez, Aaron; Ortuño, Armando

2017-01-01

In this paper, we characterise tourists most likely to visit a coastal destination by high-speed rail (HSR). Our data came from a survey conducted among HSR passengers during 2014's high season (July and August) at Spain's Camp de Tarragona and Alicante Stations, each of which is near a mass tourism destination on the Mediterranean coast: the Costa Daurada and the Costa Blanca, respectively. We used responses to the survey, which presented binary discrete-choice situations, to construct a database necessary for a logistic regression model that allowed us to examine how passenger profile, trip characteristics, and stay conditions influenced the use of HSR services on visits to each coastal destination. Results highlighted significant differences in the profiles of tourists who arrived at each destination by HSR and, in turn, that no specific tourist profile is associated with HSR, even for two stations that serve sunny beach destinations. Among its implications, to analyse travellers that HSR can attract, it is vital to consider the specific characteristics of each destination and its current market.

Effects of spatial location and household wealth on health insurance subscription among women in Ghana.

PubMed

Kumi-Kyereme, Akwasi; Amo-Adjei, Joshua

2013-06-17

This study compares ownership of health insurance among Ghanaian women with respect to wealth status and spatial location. We explore the overarching research question by employing geographic and proxy means targeting through interactive analysis of wealth status and spatial issues. The paper draws on the 2008 Ghana Demographic and Health Survey. Bivariate descriptive analysis coupled with binary logistic regression estimation technique was used to analyse the data. By wealth status, the likelihood of purchasing insurance was significantly higher among respondents from the middle, richer and richest households compared to the poorest (reference category) and these differences widened more profoundly in the Northern areas after interacting wealth with zone of residence. Among women at the bottom of household wealth (poorest and poorer), there were no statistically significant differences in insurance subscription in all the areas. The results underscore the relevance of geographic and proxy means targeting in identifying populations who may be need of special interventions as part of the efforts to increase enrolment as well as means of social protection against the vulnerable.

Neurocognitive functioning in children with developmental dyslexia and attention-deficit/hyperactivity disorder: Multiple deficits and diagnostic accuracy.

PubMed

Moura, Octávio; Pereira, Marcelino; Alfaiate, Cláudia; Fernandes, Eva; Fernandes, Boavida; Nogueira, Susana; Moreno, Joana; Simões, Mário R

2017-04-01

This study aimed to investigate the neurocognitive functioning of children with developmental dyslexia (DD) and attention-deficit/hyperactivity disorder (ADHD). Four groups of children between the ages of 8 and 10 years participated in the study: typically developing children (TDC; N = 34), children with DD-only (N = 32), children with ADHD-only (N = 32), and children with DD+ADHD (N = 18). Children with DD and ADHD exhibited significant weaknesses on almost all neurocognitive measures compared with TDC. Large effect sizes were observed for naming speed and phonological awareness. The comorbid group showed deficits consistent with both DD and ADHD without additional impairments. Results from binary logistic regression and receiver-operating characteristic (ROC) curve analyses suggested that some neurocognitive measures revealed an adequate sensitivity for the clinical diagnosis of both neurodevelopmental disorders. Specifically, naming speed and phonological awareness were the strongest predictors to correctly discriminate both disorders. Taken together, the results lend support to the multiple cognitive deficit hypothesis showing a considerable overlap of neurocognitive deficits between both disorders.

Effects of spatial location and household wealth on health insurance subscription among women in Ghana

PubMed Central

2013-01-01

Background This study compares ownership of health insurance among Ghanaian women with respect to wealth status and spatial location. We explore the overarching research question by employing geographic and proxy means targeting through interactive analysis of wealth status and spatial issues. Methods The paper draws on the 2008 Ghana Demographic and Health Survey. Bivariate descriptive analysis coupled with binary logistic regression estimation technique was used to analyse the data. Results By wealth status, the likelihood of purchasing insurance was significantly higher among respondents from the middle, richer and richest households compared to the poorest (reference category) and these differences widened more profoundly in the Northern areas after interacting wealth with zone of residence. Among women at the bottom of household wealth (poorest and poorer), there were no statistically significant differences in insurance subscription in all the areas. Conclusions The results underscore the relevance of geographic and proxy means targeting in identifying populations who may be need of special interventions as part of the efforts to increase enrolment as well as means of social protection against the vulnerable. PMID:23768255

Improving Consumer Satisfaction with Addiction Treatment: An Analysis of Alumni Preferences

PubMed Central

Sanghani, Ruchi M.; Moler, Alexander K.

2015-01-01

Objective. The primary objective of this investigation is to determine which individual and aggregate factors of residential addiction treatment centers are most significant influencers of alumni satisfaction. Design. Survey targeted alumni of residential addiction treatment facilities. Alumni were queried through a survey, which utilized Likert-scale matrices and binary response options: 379 respondents met the completion threshold. Alumni rated amenities and individual and group counseling factors; additionally, respondents provided feedback on two satisfaction proxies: cost worthiness and future recommendations. Descriptive and relational analyses were conducted, with the latter utilizing logistic regression models. Results. Individual factors' scores of group counseling, and overall aggregate group counseling score, are most enthusiastically positive. Group counseling is also the most significant influencer of satisfaction. Other significant influencers of satisfaction are met expectations for individual counseling and psychiatric care offerings. Conclusions. While individual counseling and facility amenities should not be ignored, group counseling may be the most significant influencer of alumni satisfaction. Long-term outcomes are not single-faceted; however, treatment providers should be encouraged to invest in high-quality group counseling offerings in order to best satisfy, and thereby empower, clients. PMID:26483986

Cumulative traumas and psychosis: an analysis of the national comorbidity survey and the British Psychiatric Morbidity Survey.

PubMed

Shevlin, Mark; Houston, James E; Dorahy, Martin J; Adamson, Gary

2008-01-01

Previous research has shown that traumatic life events are associated with a diagnosis of psychosis. Rather than focus on particular events, this study aimed to estimate the effect of cumulative traumatic experiences on psychosis. The study was based on 2 large community samples (The National Comorbidity Survey [NCS], The British Psychiatric Morbidity Survey [BPMS]). All analyses were conducted using hierarchical binary logistic regression, with psychosis diagnosis as the dependent variable. Background demographic variables were included in the first block, in addition to alcohol/drug dependence and depression. A variable indicating the number of traumas experienced was entered in the second block. Experiencing 2 or more trauma types significantly predicted psychosis, and there appeared to be a dose-response type relationship. Particular traumatic experiences have been implicated in the etiology of psychosis. Consistent with previous research, molestation and physical abuse were significant predictors of psychosis using the NCS, whereas for the BPMS, serious injury or assault and violence in the home were statistically significant. This study indicated the added risk of multiple traumatic experiences.

Cumulative Traumas and Psychosis: an Analysis of the National Comorbidity Survey and the British Psychiatric Morbidity Survey

PubMed Central

Shevlin, Mark; Houston, James E.; Dorahy, Martin J.; Adamson, Gary

2008-01-01

Previous research has shown that traumatic life events are associated with a diagnosis of psychosis. Rather than focus on particular events, this study aimed to estimate the effect of cumulative traumatic experiences on psychosis. The study was based on 2 large community samples (The National Comorbidity Survey [NCS], The British Psychiatric Morbidity Survey [BPMS]). All analyses were conducted using hierarchical binary logistic regression, with psychosis diagnosis as the dependent variable. Background demographic variables were included in the first block, in addition to alcohol/drug dependence and depression. A variable indicating the number of traumas experienced was entered in the second block. Experiencing 2 or more trauma types significantly predicted psychosis, and there appeared to be a dose-response type relationship. Particular traumatic experiences have been implicated in the etiology of psychosis. Consistent with previous research, molestation and physical abuse were significant predictors of psychosis using the NCS, whereas for the BPMS, serious injury or assault and violence in the home were statistically significant. This study indicated the added risk of multiple traumatic experiences. PMID:17586579

Linear regression metamodeling as a tool to summarize and present simulation model results.

PubMed

Jalal, Hawre; Dowd, Bryan; Sainfort, François; Kuntz, Karen M

2013-10-01

Modelers lack a tool to systematically and clearly present complex model results, including those from sensitivity analyses. The objective was to propose linear regression metamodeling as a tool to increase transparency of decision analytic models and better communicate their results. We used a simplified cancer cure model to demonstrate our approach. The model computed the lifetime cost and benefit of 3 treatment options for cancer patients. We simulated 10,000 cohorts in a probabilistic sensitivity analysis (PSA) and regressed the model outcomes on the standardized input parameter values in a set of regression analyses. We used the regression coefficients to describe measures of sensitivity analyses, including threshold and parameter sensitivity analyses. We also compared the results of the PSA to deterministic full-factorial and one-factor-at-a-time designs. The regression intercept represented the estimated base-case outcome, and the other coefficients described the relative parameter uncertainty in the model. We defined simple relationships that compute the average and incremental net benefit of each intervention. Metamodeling produced outputs similar to traditional deterministic 1-way or 2-way sensitivity analyses but was more reliable since it used all parameter values. Linear regression metamodeling is a simple, yet powerful, tool that can assist modelers in communicating model characteristics and sensitivity analyses.

Introduction to methodology of dose-response meta-analysis for binary outcome: With application on software.

PubMed

Zhang, Chao; Jia, Pengli; Yu, Liu; Xu, Chang

2018-05-01

Dose-response meta-analysis (DRMA) is widely applied to investigate the dose-specific relationship between independent and dependent variables. Such methods have been in use for over 30 years and are increasingly employed in healthcare and clinical decision-making. In this article, we give an overview of the methodology used in DRMA. We summarize the commonly used regression model and the pooled method in DRMA. We also use an example to illustrate how to employ a DRMA by these methods. Five regression models, linear regression, piecewise regression, natural polynomial regression, fractional polynomial regression, and restricted cubic spline regression, were illustrated in this article to fit the dose-response relationship. And two types of pooling approaches, that is, one-stage approach and two-stage approach are illustrated to pool the dose-response relationship across studies. The example showed similar results among these models. Several dose-response meta-analysis methods can be used for investigating the relationship between exposure level and the risk of an outcome. However the methodology of DRMA still needs to be improved. © 2018 Chinese Cochrane Center, West China Hospital of Sichuan University and John Wiley & Sons Australia, Ltd.

The most plausible explanation of the cyclic period changes in close binaries: the case of the RS CVn-type binary WW Dra

NASA Astrophysics Data System (ADS)

Liao, W.-P.; Qian, S.-B.

2010-07-01

Cyclic period changes are a fairly common phenomenon in close binary systems and are usually explained as being caused either by the magnetic activity of one or both components or by the light travel time effect (LTTE) of a third body. We searched the orbital period changes in 182 EA-type (including the 101 Algol systems used by Hall), 43 EB-type and 53 EW-type binaries with known mass ratio and spectral type of the secondary component. We reproduced and improved the diagram in Hall according to the new collected data. Our plots do not support the conclusion derived by Hall that cyclic period changes are restricted to binaries having a secondary component with spectral type later than F5. The presence of period changes among systems with a secondary component of early type indicates that magnetic activity is one, but not the only, cause of the period variation. It is discovered that cyclic period changes, probably resulting from the presence of a third body, are more frequent in EW-type binaries among close systems. Therefore, the most plausible explanation of the cyclic period changes is the LTTE through the presence of a third body. Using the century-long historical record of the times of light minimum, we analysed the cyclic period change in the Algol binary WW Dra. It is found that the orbital period of the binary shows a ~112.2-yr cyclic variation with an amplitude of ~0.1977d. The cyclic oscillation can be attributed to the LTTE by means of a third body with a mass no less than 6.43Msolar. However, no spectral lines of the third body were discovered, indicating that it may be a candidate black hole. The third body is orbiting the binary at a distance closer than 14.4 au and may play an important role in the evolution of this system.

Does office space occupation matter? The role of the number of persons per enclosed office space, psychosocial work characteristics, and environmental satisfaction in the physical and mental health of employees.

PubMed

Herbig, B; Schneider, A; Nowak, D

2016-10-01

The study examined the effects of office space occupation, psychosocial work characteristics, and environmental satisfaction on physical and mental health of office workers in small-sized and open-plan offices as well as possible underlying mechanisms. Office space occupation was characterized as number of persons per one enclosed office space. A total of 207 office employees with similar jobs in offices with different space occupation were surveyed regarding their work situation (psychosocial work characteristics, satisfaction with privacy, acoustics, and control) and health (psychosomatic complaints, irritation, mental well-being, and work ability). Binary logistic and linear regression analyses as well as bootstrapped mediation analyses were used to determine associations and underlying mechanisms. Employee health was significantly associated with all work characteristics. Psychosocial work stressors had the strongest relation to physical and mental health (OR range: 1.66-3.72). The effect of office space occupation on employee health was mediated by stressors and environmental satisfaction, but not by psychosocial work resources. As assumed by sociotechnical approaches, a higher number of persons per enclosed office space was associated with adverse health effects. However, the strongest associations were found with psychosocial work stressors. When revising office design, a holistic approach to work (re)design is needed. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The Impact of Adherence and Instillation Proficiency of Topical Glaucoma Medications on Intraocular Pressure.

PubMed

Atey, Tesfay Mehari; Shibeshi, Workineh; T Giorgis, Abeba; Asgedom, Solomon Weldegebreal

2017-01-01

The possible sequel of poorly controlled intraocular pressure (IOP) includes treatment failure, unnecessary medication use, and economic burden on patients with glaucoma. To assess the impact of adherence and instillation technique on IOP control. A cross-sectional study was conducted on 359 glaucoma patients in Menelik II Hospital from June 1 to July 31, 2015. After conducting a Q-Q analysis, multiple binary logistic analyses, linear regression analyses, and two-tailed paired t-test were conducted to compare IOP in the baseline versus current measurements. Intraocular pressure was controlled in 59.6% of the patients and was relatively well controlled during the study period (mean ( M ) = 17.911 mmHg, standard deviation ( S ) = 0.323) compared to the baseline ( M = 20.866 mmHg, S = 0.383, t (358) = -6.70, p < 0.0001). A unit increase in the administration technique score resulted in a 0.272 mmHg decrease in IOP ( p = 0.03). Moreover, primary angle-closure glaucoma (adjusted odds ratio (AOR) = 0.347, 95% confidence interval (CI): 0.144-0.836) and two medications (AOR = 1.869, 95% CI: 1.259-9.379) were factors affecting IOP. Good instillation technique of the medications was correlated with a reduction in IOP. Consequently, regular assessment of the instillation technique and IOP should be done for better management of the disease.

IMPACT: Investigating the impact of Models of Practice for Allied health Care in subacuTe settings. A protocol for a quasi-experimental mixed methods study of cost effectiveness and outcomes for patients exposed to different models of allied health care.

PubMed

Coker, Freya; Williams, Cylie M; Taylor, Nicholas F; Caspers, Kirsten; McAlinden, Fiona; Wilton, Anita; Shields, Nora; Haines, Terry P

2018-05-10

This protocol considers three allied health staffing models across public health subacute hospitals. This quasi-experimental mixed-methods study, including qualitative process evaluation, aims to evaluate the impact of additional allied health services in subacute care, in rehabilitation and geriatric evaluation management settings, on patient, health service and societal outcomes. This health services research will analyse outcomes of patients exposed to different allied health models of care at three health services. Each health service will have a control ward (routine care) and an intervention ward (additional allied health). This project has two parts. Part 1: a whole of site data extraction for included wards. Outcome measures will include: length of stay, rate of readmissions, discharge destinations, community referrals, patient feedback and staff perspectives. Part 2: Functional Independence Measure scores will be collected every 2-3 days for the duration of 60 patient admissions.Data from part 1 will be analysed by linear regression analysis for continuous outcomes using patient-level data and logistic regression analysis for binary outcomes. Qualitative data will be analysed using a deductive thematic approach. For part 2, a linear mixed model analysis will be conducted using therapy service delivery and days since admission to subacute care as fixed factors in the model and individual participant as a random factor. Graphical analysis will be used to examine the growth curve of the model and transformations. The days since admission factor will be used to examine non-linear growth trajectories to determine if they lead to better model fit. Findings will be disseminated through local reports and to the Department of Health and Human Services Victoria. Results will be presented at conferences and submitted to peer-reviewed journals. The Monash Health Human Research Ethics committee approved this multisite research (HREC/17/MonH/144 and HREC/17/MonH/547). © 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.

Interleukin-6 is associated with chronic hyperglycemia and insulin resistance in patients after acute pancreatitis.

PubMed

Gillies, Nicola; Pendharkar, Sayali A; Asrani, Varsha M; Mathew, Juby; Windsor, John A; Petrov, Maxim S

2016-01-01

Diabetes is a pervasive disease, with a mounting prevalence and burden on health care systems. Under this collective term of diabetes falls diabetes after diseases of the exocrine pancreas, a condition which was previously under-recognised and often mislabeled as type 2 diabetes mellitus and is now increasingly acknowledged as a stand-alone entity. However, there is a paucity of clinical studies investigating the underlying pathophysiology of diabetes after acute pancreatitis, the most frequent disease of the pancreas. This study aimed to investigate the role of adipocytokines in glucose metabolism after acute pancreatitis. This was a cross-sectional follow-up study of a patient cohort diagnosed with acute pancreatitis. Fasting venous blood samples were collected to analyse markers of glucose metabolism (fasting blood glucose, haemoglobin A1c, homeostasis model assessment (HOMA-IR) as a measure of insulin resistance) and adypocytokines (adiponectin, interleukin-6, leptin, monocyte chemoattractant protein-1, retinol binding protein-4, resistin, and tumor necrosis factor-α). Participants were categorized into two groups: normoglycemia after acute pancreatitis and chronic hyperglycemia after acute pancreatitis (CHAP). Binary logistic regression and linear regression analyses were used to investigate the association between each of the adipocytokines and markers of glucose metabolism. Potential confounders were adjusted for in multivariate analyses. A total of 83 patients with acute pancreatitis were included, of whom 19 developed CHAP. Interleukin-6 was significantly associated with CHAP in both unadjusted and adjusted models (p = 0.030 and p = 0.018, respectively). Further, it was also significantly associated with HOMA-IR in both unadjusted and adjusted models (p = 0.029 and p = 0.037, respectively). Other adipocytokines were not significantly associated with markers of glucose metabolism. Interleukin-6 appears to be implicated in the development of chronic hyperglycemia and insulin resistance in patients after acute pancreatitis. It may become a potential target in the prevention and early treatment of diabetes after diseases of the exocrine pancreas. Copyright © 2016 IAP and EPC. Published by Elsevier B.V. All rights reserved.

Predicting tree species presence and basal area in Utah: A comparison of stochastic gradient boosting, generalized additive models, and tree-based methods

Treesearch

Gretchen G. Moisen; Elizabeth A. Freeman; Jock A. Blackard; Tracey S. Frescino; Niklaus E. Zimmermann; Thomas C. Edwards

2006-01-01

Many efforts are underway to produce broad-scale forest attribute maps by modelling forest class and structure variables collected in forest inventories as functions of satellite-based and biophysical information. Typically, variants of classification and regression trees implemented in Rulequest's© See5 and Cubist (for binary and continuous responses,...

Modeling Student Performance in Mathematics Using Binary Logistic Regression at Selected Secondary Schools a Case Study of Mtwara Municipality and Ilemela District

ERIC Educational Resources Information Center

Mabula, Salyungu

2015-01-01

This study investigated the performance of secondary school students in Mathematics at the Selected Secondary Schools in Mtwara Municipality and Ilemela District by Absenteeism, Conduct, Type of School and Gender as explanatory Factors. The data used in the study was collected from documented records of 250 form three students with 1:1 gender…

Factors That Contributed to Gifted Students' Success on STEM Pathways: The Role of Race, Personal Interests, and Aspects of High School Experience

ERIC Educational Resources Information Center

Steenbergen-Hu, Saiying; Olszewski-Kubilius, Paula

2017-01-01

In this study, we conducted binary logistic regression on survey data collected from 244 past participants of a Talent Search program who attended regular high schools but supplemented their regular high school education with enriched or accelerated math and science learning activities. The participants completed an online survey 4 to 6 years…

Diagnostic accuracy of serum antibodies to human papillomavirus type 16 early antigens in the detection of human papillomavirus-related oropharyngeal cancer.

PubMed

Dahlstrom, Kristina R; Anderson, Karen S; Field, Matthew S; Chowell, Diego; Ning, Jing; Li, Nan; Wei, Qingyi; Li, Guojun; Sturgis, Erich M

2017-12-15

Because of the current epidemic of human papillomavirus (HPV)-related oropharyngeal cancer (OPC), a screening strategy is urgently needed. The presence of serum antibodies to HPV-16 early (E) antigens is associated with an increased risk for OPC. The purpose of this study was to evaluate the diagnostic accuracy of antibodies to a panel of HPV-16 E antigens in screening for OPC. This case-control study included 378 patients with OPC, 153 patients with nonoropharyngeal head and neck cancer (non-OPC), and 782 healthy control subjects. The tumor HPV status was determined with p16 immunohistochemistry and HPV in situ hybridization. HPV-16 E antibody levels in serum were identified with an enzyme-linked immunosorbent assay. A trained binary logistic regression model based on the combination of all E antigens was predefined and applied to the data set. The sensitivity and specificity of the assay for distinguishing HPV-related OPC from controls were calculated. Logistic regression analysis was used to calculate odds ratios with 95% confidence intervals for the association of head and neck cancer with the antibody status. Of the 378 patients with OPC, 348 had p16-positive OPC. HPV-16 E antibody levels were significantly higher among patients with p16-positive OPC but not among patients with non-OPC or among controls. Serology showed high sensitivity and specificity for HPV-related OPC (binary classifier: 83% sensitivity and 99% specificity for p16-positive OPC). A trained binary classification algorithm that incorporates information about multiple E antibodies has high sensitivity and specificity and may be advantageous for risk stratification in future screening trials. Cancer 2017;123:4886-94. © 2017 American Cancer Society. © 2017 American Cancer Society.

Combining binary decision tree and geostatistical methods to estimate snow distribution in a mountain watershed

USGS Publications Warehouse

Balk, Benjamin; Elder, Kelly

2000-01-01

We model the spatial distribution of snow across a mountain basin using an approach that combines binary decision tree and geostatistical techniques. In April 1997 and 1998, intensive snow surveys were conducted in the 6.9‐km2 Loch Vale watershed (LVWS), Rocky Mountain National Park, Colorado. Binary decision trees were used to model the large‐scale variations in snow depth, while the small‐scale variations were modeled through kriging interpolation methods. Binary decision trees related depth to the physically based independent variables of net solar radiation, elevation, slope, and vegetation cover type. These decision tree models explained 54–65% of the observed variance in the depth measurements. The tree‐based modeled depths were then subtracted from the measured depths, and the resulting residuals were spatially distributed across LVWS through kriging techniques. The kriged estimates of the residuals were added to the tree‐based modeled depths to produce a combined depth model. The combined depth estimates explained 60–85% of the variance in the measured depths. Snow densities were mapped across LVWS using regression analysis. Snow‐covered area was determined from high‐resolution aerial photographs. Combining the modeled depths and densities with a snow cover map produced estimates of the spatial distribution of snow water equivalence (SWE). This modeling approach offers improvement over previous methods of estimating SWE distribution in mountain basins.

Multicomponent ionic liquid CMC prediction.

PubMed

Kłosowska-Chomiczewska, I E; Artichowicz, W; Preiss, U; Jungnickel, C

2017-09-27

We created a model to predict CMC of ILs based on 704 experimental values published in 43 publications since 2000. Our model was able to predict CMC of variety of ILs in binary or ternary system in a presence of salt or alcohol. The molecular volume of IL (V m ), solvent-accessible surface (Ŝ), solvation enthalpy (Δ solv G ∞ ), concentration of salt (C s ) or alcohol (C a ) and their molecular volumes (V ms and V ma , respectively) were chosen as descriptors, and Kernel Support Vector Machine (KSVM) and Evolutionary Algorithm (EA) as regression methodologies to create the models. Data was split into training and validation set (80/20) and subjected to bootstrap aggregation. KSVM provided better fit with average R 2 of 0.843, and MSE of 0.608, whereas EA resulted in R 2 of 0.794 and MSE of 0.973. From the sensitivity analysis it was shown that V m and Ŝ have the highest impact on ILs micellization in both binary and ternary systems, however surprisingly in the presence of alcohol the V m becomes insignificant/irrelevant. Micelle stabilizing or destabilizing influence of the descriptors depends upon the additives. Previous attempts at modelling the CMC of ILs was generally limited to small number of ILs in simplified (binary) systems. We however showed successful prediction of the CMC over a range of different systems (binary and ternary).

Comorbid thyroid disease in patients with major depressive disorder - results from the European Group for the Study of Resistant Depression (GSRD).

PubMed

Fugger, Gernot; Dold, Markus; Bartova, Lucie; Kautzky, Alexander; Souery, Daniel; Mendlewicz, Julien; Serretti, Alessandro; Zohar, Joseph; Montgomery, Stuart; Frey, Richard; Kasper, Siegfried

2018-06-01

This multicenter study of the European Group for the Study of Resistant Depression (GSRD) aimed to explore the association between major depressive disorder (MDD) and comorbid thyroid disease. A total number of 1410 patients` characteristics in terms of demographic and clinical information were compared between MDD subjects with and without concurrent thyroid disease using descriptive statistics, analyses of covariance (ANCOVA) and binary logistic regression analyses. We determined a point prevalence rate for comorbid hypothyroidism of 13.2% and 1.6% for comorbid hyperthyroidism respectively. Patients with MDD+comorbid hypothyroidism were significantly older, more likely to be female, inpatient and suffering from other comorbid chronic somatic conditions. Furthermore, MADRS score at onset of the current depressive episode was significantly higher, psychotic features of depression were more likely pronounced. Overall, patients in the MDD+comorbid hypothyroidism group were rather treated with a combination of drugs, for example, pregabalin, antipsychotic drugs and mood stabilizers. In the MDD+comorbid hyperthyroidism group patients were significantly older, of Caucasian origin and diagnosed with other somatic comorbidities. In conclusion, our analyses suggest that abnormal thyroid function, especially hypothyroidism, is linked to depression severity and associated with distinct psychopathologic features of depression. However, comorbid thyroid disease has no influence on treatment response. A combination or augmentation of psychopharmacological drugs, especially with antipsychotics, mood stabilizers and pregabalin is more likely in patients with hypothyroid conditions. Thyroid disorder is frequently found in combination with other chronic somatic diseases including hypertension and heart disease. Copyright © 2018 Elsevier B.V. and ECNP. All rights reserved.

Brief Motivational Interventions Are Associated With Reductions in Alcohol-Impaired Driving Among College Drinkers.

PubMed

Teeters, Jenni B; Borsari, Brian; Martens, Matthew P; Murphy, James G

2015-09-01

Alcohol-impaired (AI) driving among college students remains a significant public health concern and may be the single most risky drinking outcome among young adults. Brief motivational interventions (BMIs) have been shown to reduce alcohol use and problems, but their specific efficacy for decreasing AI driving among college students is unknown. The present study analyzed data from three randomized controlled trials of BMI (Murphy et al., 2010: n = 74; Borsari et al., 2012: n = 530; and Martens et al., 2013: n = 365) to evaluate whether BMIs are associated with reductions in AI driving among college student drinkers. Participants in all three studies were randomized to BMI or control conditions. Participants reported whether they had driven under the influence (yes/no) following the BMI over the follow-up period. Separate binary logistic regression analyses were conducted for each study. For Studies 1 and 2, these analyses revealed that a BMI was significantly associated with reductions in AI driving at the final (6-month and 9-month, respectively) follow-up compared with the control condition. For Study 3, analyses revealed that a single-component BMI focused on the correction of misperceptions of descriptive norms was significantly associated with reductions in AI driving compared with the control group at the final (6-month) followup, whereas a single-component BMI focused on the use of protective behavioral strategies was not. Change in drinking level did not mediate the relationship between the condition and the change in AI driving. Counselor-administered BMIs that include descriptive normative feedback are associated with significant reductions in AI driving compared with control.

Teenage pregnancy and long-term mental health outcomes among Indigenous women in Canada.

PubMed

Xavier, Chloé G; Brown, Hilary K; Benoit, Anita C

2018-06-01

Our objectives were to (1) compare the risks for poor long-term mental health outcomes among indigenous women with and without a teenage pregnancy and (2) determine if community and cultural factors modify this risk. We conducted a secondary analysis of the 2012 Aboriginal Peoples Survey. Respondents were women aged 25 to 49 years who had given birth to at least one child. Teenage mothers (age at first birth 13 to 19 years; n = 1330) were compared to adult mothers (age at first birth 20 years or older; n = 2630). Mental health outcomes were psychological distress, mental health status, suicide ideation/attempt, and alcohol consumption. To address objective 1, we used binary logistic regression analyses before and after controlling for covariates. To address objective 2, we tested the significance of interaction terms between teenage pregnancy status and effect measure modifiers. In unadjusted analyses, teenage pregnancy was associated with increased risk for poor/fair mental health [odds ratio (OR) 1.77, 95% confidence interval (CI) 1.24-2.53] and suicide attempt/ideation (OR 1.95, 95% CI 1.07-3.54). However, the associations were not statistically significant after adjusting for demographic, socioeconomic, environmental, and health covariates. Teenage pregnancy was not associated with increased risk for high psychological distress or heavy alcohol consumption in unadjusted or adjusted analyses. The interaction term for involvement in cultural activities was statistically significant for poor/fair mental health; however, after stratification, ORs were non-significant. Among indigenous mothers, teenage pregnancy was less important than broader social and health circumstances in predicting long-term mental health.

Use of conservative and surgical foot care in an inception cohort of patients with rheumatoid arthritis.

PubMed

Backhouse, Michael R; Keenan, Anne-Maree; Hensor, Elizabeth M A; Young, Adam; James, David; Dixey, Josh; Williams, Peter; Prouse, Peter; Gough, Andrew; Helliwell, Philip S; Redmond, Anthony C

2011-09-01

To describe conservative and surgical foot care in patients with RA in England and explore factors that predict the type of foot care received. Use of podiatry and type of foot surgery were outcomes recorded in an inception cohort involving nine rheumatology centres that recruited patients with RA between 1986 and 1998 across England. Associations between patient-specific factors and service use were identified using univariate logistic regression analyses. The independence of these associations was then verified through multiple binary logistic regression modelling. Data were collected on 1237 patients with RA [66.9% females, mean (s.d.) age at disease onset = 54.36 (14.18) years, median DAS = 4.09 (1st quartile = 3.04, 3rd quartile = 5.26), median HAQ = 1 (0.50, 1.63)]. Interventions involving the feet in the cohort were low with only 364 (30%) out of 1218 receiving podiatry and 47 (4%) out of 1237 patients having surgery. At baseline, female gender, increasing age at onset, being RF positive and higher DAS scores were each independently associated with increased odds of seeing a podiatrist. Gender, age of onset and baseline DAS were independently associated with the odds of having foot surgery. Despite the known high prevalence of foot pathologies in RA, only one-third of this cohort accessed podiatry. While older females were more likely to access podiatry care and younger patients surgery, the majority of the RA population did not access any foot care.

Mobile phone use during driving: Effects on speed and effectiveness of driver compensatory behaviour.

PubMed

Choudhary, Pushpa; Velaga, Nagendra R

2017-09-01

This study analysed and modelled the effects of conversation and texting (each with two difficulty levels) on driving performance of Indian drivers in terms of their mean speed and accident avoiding abilities; and further explored the relationship between speed reduction strategy of the drivers and their corresponding accident frequency. 100 drivers of three different age groups (young, mid-age and old-age) participated in the simulator study. Two sudden events of Indian context: unexpected crossing of pedestrians and joining of parked vehicles from road side, were simulated for estimating the accident probabilities. Generalized linear mixed models approach was used for developing linear regression models for mean speed and binary logistic regression models for accident probability. The results of the models showed that the drivers significantly compensated the increased workload by reducing their mean speed by 2.62m/s and 5.29m/s in the presence of conversation and texting tasks respectively. The logistic models for accident probabilities showed that the accident probabilities increased by 3 and 4 times respectively when the drivers were conversing or texting on a phone during driving. Further, the relationship between the speed reduction patterns and their corresponding accident frequencies showed that all the drivers compensated differently; but, among all the drivers, only few drivers, who compensated by reducing the speed by 30% or more, were able to fully offset the increased accident risk associated with the phone use. Copyright © 2017 Elsevier Ltd. All rights reserved.

RISK FACTORS FOR CONTACT LENS INDUCED PAPILLARY CONJUNCTIVITIS ASSOCIATED WITH SILICONE HYDROGEL CONTACT LENS WEAR

PubMed Central

Tagliaferri, Angela; Love, Thomas E.; Szczotka-Flynn, Loretta

2014-01-01

BACKGROUND Contact lens induced papillary conjunctivitis (CLPC) continues to be a major cause of dropout during contact lens extended wear. This retrospective study explores risk factors for the development of CLPC during silicone hydrogel lens extended wear. METHODS Data from 205 subjects enrolled in the Longitudinal Analysis of Silicone Hydrogel Contact Lens (LASH) study wearing lotrafilcon A silicone hydrogel lenses for up to 30 days of continuous wear were used to determine risk factors for CLPC in this secondary analysis of the main cohort. The main covariates of interest included substantial lens-associated bacterial bioburden, and topographically determined lens base curve-to-cornea fitting relationships. Additional covariates of interest included history of prior adverse events, time of year, race, education level, gender and other subject demographics. Statistical analyses included univariate logistic regression to assess the impact of potential risk factors on the binary CLPC outcome, and Cox proportional hazards regression to describe the impact of those factors on time-to-CLPC diagnosis. RESULTS Across 12 months of follow-up, 52 subjects (25%) experienced CLPC. No associations were found between CLPC development and the presence of bacterial bioburden, lens-to-cornea fitting relationships, history of prior adverse events, gender or race. CLPC development followed the same seasonal trends as the local peaks in environmental allergans. CONCLUSIONS Lens fit and biodeposits, in the form of lens associated bacterial bioburden, were not associated with the development of CLPC during extended wear with lotrafilcon A silicone hydrogel lenses. PMID:24681609

Influence of management of variables, sampling zones and land units on LR analysis for landslide spatial prevision

NASA Astrophysics Data System (ADS)

Greco, R.; Sorriso-Valvo, M.

2013-09-01

Several authors, according to different methodological approaches, have employed logistic Regression (LR), a multivariate statistical analysis adopted to assess the spatial probability of landslide, even though its fundamental principles have remained unaltered. This study aims at assessing the influence of some of these methodological approaches on the performance of LR, through a series of sensitivity analyses developed over a test area of about 300 km2 in Calabria (southern Italy). In particular, four types of sampling (1 - the whole study area; 2 - transects running parallel to the general slope direction of the study area with a total surface of about 1/3 of the whole study area; 3 - buffers surrounding the phenomena with a 1/1 ratio between the stable and the unstable area; 4 - buffers surrounding the phenomena with a 1/2 ratio between the stable and the unstable area), two variable coding modes (1 - grouped variables; 2 - binary variables), and two types of elementary land (1 - cells units; 2 - slope units) units have been tested. The obtained results must be considered as statistically relevant in all cases (Aroc values > 70%), thus confirming the soundness of the LR analysis which maintains high predictive capacities notwithstanding the features of input data. As for the area under investigation, the best performing methodological choices are the following: (i) transects produced the best results (0 < P(y) ≤ 93.4%; Aroc = 79.5%); (ii) as for sampling modalities, binary variables (0 < P(y) ≤ 98.3%; Aroc = 80.7%) provide better performance than ordinated variables; (iii) as for the choice of elementary land units, slope units (0 < P(y) ≤ 100%; Aroc = 84.2%) have obtained better results than cells matrix.

Choosing appropriate analysis methods for cluster randomised cross-over trials with a binary outcome.

PubMed

Morgan, Katy E; Forbes, Andrew B; Keogh, Ruth H; Jairath, Vipul; Kahan, Brennan C

2017-01-30

In cluster randomised cross-over (CRXO) trials, clusters receive multiple treatments in a randomised sequence over time. In such trials, there is usual correlation between patients in the same cluster. In addition, within a cluster, patients in the same period may be more similar to each other than to patients in other periods. We demonstrate that it is necessary to account for these correlations in the analysis to obtain correct Type I error rates. We then use simulation to compare different methods of analysing a binary outcome from a two-period CRXO design. Our simulations demonstrated that hierarchical models without random effects for period-within-cluster, which do not account for any extra within-period correlation, performed poorly with greatly inflated Type I errors in many scenarios. In scenarios where extra within-period correlation was present, a hierarchical model with random effects for cluster and period-within-cluster only had correct Type I errors when there were large numbers of clusters; with small numbers of clusters, the error rate was inflated. We also found that generalised estimating equations did not give correct error rates in any scenarios considered. An unweighted cluster-level summary regression performed best overall, maintaining an error rate close to 5% for all scenarios, although it lost power when extra within-period correlation was present, especially for small numbers of clusters. Results from our simulation study show that it is important to model both levels of clustering in CRXO trials, and that any extra within-period correlation should be accounted for. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Normal evaporation of binary alloys

NASA Technical Reports Server (NTRS)

Li, C. H.

1972-01-01

In the study of normal evaporation, it is assumed that the evaporating alloy is homogeneous, that the vapor is instantly removed, and that the alloy follows Raoult's law. The differential equation of normal evaporation relating the evaporating time to the final solute concentration is given and solved for several important special cases. Uses of the derived equations are exemplified with a Ni-Al alloy and some binary iron alloys. The accuracy of the predicted results are checked by analyses of actual experimental data on Fe-Ni and Ni-Cr alloys evaporated at 1600 C, and also on the vacuum purification of beryllium. These analyses suggest that the normal evaporation equations presented here give satisfactory results that are accurate to within an order of magnitude of the correct values, even for some highly concentrated solutions. Limited diffusion and the resultant surface solute depletion or enrichment appear important in the extension of this normal evaporation approach.

Kepler observations of the asteroseismic binary HD 176465

NASA Astrophysics Data System (ADS)

White, T. R.; Benomar, O.; Silva Aguirre, V.; Ball, W. H.; Bedding, T. R.; Chaplin, W. J.; Christensen-Dalsgaard, J.; Garcia, R. A.; Gizon, L.; Stello, D.; Aigrain, S.; Antia, H. M.; Appourchaux, T.; Bazot, M.; Campante, T. L.; Creevey, O. L.; Davies, G. R.; Elsworth, Y. P.; Gaulme, P.; Handberg, R.; Hekker, S.; Houdek, G.; Howe, R.; Huber, D.; Karoff, C.; Marques, J. P.; Mathur, S.; McQuillan, A.; Metcalfe, T. S.; Mosser, B.; Nielsen, M. B.; Régulo, C.; Salabert, D.; Stahn, T.

2017-05-01

Binary star systems are important for understanding stellar structure and evolution, and are especially useful when oscillations can be detected and analysed with asteroseismology. However, only four systems are known in which solar-like oscillations are detected in both components. Here, we analyse the fifth such system, HD 176465, which was observed by Kepler. We carefully analysed the system's power spectrum to measure individual mode frequencies, adapting our methods where necessary to accommodate the fact that both stars oscillate in a similar frequency range. We also modelled the two stars independently by fitting stellar models to the frequencies and complementaryparameters. We are able to cleanly separate the oscillation modes in both systems. The stellar models produce compatible ages and initial compositions for the stars, as is expected from their common and contemporaneous origin. Combining the individual ages, the system is about 3.0 ± 0.5 Gyr old. The two components of HD 176465 are young physically-similar oscillating solar analogues, the first such system to be found, and provide important constraints for stellar evolution and asteroseismology.

The Role of Binarity in the Angular Momentum Evolution of M Dwarfs

NASA Astrophysics Data System (ADS)

Stauffer, John; Rebull, Luisa; K2 clusters team

2018-01-01

We have analysed K2 light curves for of order a thousand low mass stars in each of the 8 Myr old Upper Sco association, the 125 Myr age Pleiades open cluster and the ~700 Myr old Praesepe cluster. A very large fraction of these stars show well-determined rotation periods with K2, and where the star is a binary, we usually are able to determine periods for both stars. In Upper Sco, where there are ~150 M dwarf binaries with K2 light curves, the binary stars have periods that are much shorter on average and much closer to each other than would be true if drawn at random from the Upper Sco M dwarf single stars. The same is true in the Pleiades,though the size of the differences from the single M dwarf population is smaller. By Praesepe age, the M dwarf binaries are still somewhat rapidly rotating but their period differences are not significantly different from what would be true if drawn by chance from the singles.

Sample size calculations for case-control studies

Cancer.gov

This R package can be used to calculate the required samples size for unconditional multivariate analyses of unmatched case-control studies. The sample sizes are for a scalar exposure effect, such as binary, ordinal or continuous exposures. The sample sizes can also be computed for scalar interaction effects. The analyses account for the effects of potential confounder variables that are also included in the multivariate logistic model.

Improving the analysis of composite endpoints in rare disease trials.

PubMed

McMenamin, Martina; Berglind, Anna; Wason, James M S

2018-05-22

Composite endpoints are recommended in rare diseases to increase power and/or to sufficiently capture complexity. Often, they are in the form of responder indices which contain a mixture of continuous and binary components. Analyses of these outcomes typically treat them as binary, thus only using the dichotomisations of continuous components. The augmented binary method offers a more efficient alternative and is therefore especially useful for rare diseases. Previous work has indicated the method may have poorer statistical properties when the sample size is small. Here we investigate small sample properties and implement small sample corrections. We re-sample from a previous trial with sample sizes varying from 30 to 80. We apply the standard binary and augmented binary methods and determine the power, type I error rate, coverage and average confidence interval width for each of the estimators. We implement Firth's adjustment for the binary component models and a small sample variance correction for the generalized estimating equations, applying the small sample adjusted methods to each sub-sample as before for comparison. For the log-odds treatment effect the power of the augmented binary method is 20-55% compared to 12-20% for the standard binary method. Both methods have approximately nominal type I error rates. The difference in response probabilities exhibit similar power but both unadjusted methods demonstrate type I error rates of 6-8%. The small sample corrected methods have approximately nominal type I error rates. On both scales, the reduction in average confidence interval width when using the adjusted augmented binary method is 17-18%. This is equivalent to requiring a 32% smaller sample size to achieve the same statistical power. The augmented binary method with small sample corrections provides a substantial improvement for rare disease trials using composite endpoints. We recommend the use of the method for the primary analysis in relevant rare disease trials. We emphasise that the method should be used alongside other efforts in improving the quality of evidence generated from rare disease trials rather than replace them.

Metastable phase in binary and ternary 12-carat gold alloys at low temperature

NASA Astrophysics Data System (ADS)

Lamiri, Imene; Abdelbaky, Mohammed S. M.; Hamana, Djamel; García-Granda, Santiago

2018-04-01

Low temperature phase transitions in 12-carat gold alloys have been investigated for binary Au-Cu and ternary Au-Cu-Ag compositions. The thermal analyses investigations using differential scanning calorimetry (DSC) and the dilatometry were performed in the 50–300 °C temperature range in order to detect the structural transformations. The thermal analyses were carried out on annealed samples at 700 °C for two hour followed by water quenching. They reveal an important new reaction for both used compositions and both thermal techniques confirm each other. This reaction has been assessed as pre-ordering reaction. SEM and STM imaging were performed on annealed samples at 700 °C for two hours and water quenched followed by a heating from room temperature up to the temperature of the new peaks obtained in the thermal study. The imaging reveals the relationship between the pre-ordering reaction and the surface aspect presented in the fact of dendrite precipitates. A series of SEM observation have been performed in order to follow the kinetic of the observed precipitates by the way of several series of heating up, from 140 to 220 °C for the binary composition and from 100 to 180 °C for the ternary composition. Furthermore, this study shows that the silver accelerates the ordering reaction.

Data-analysis driven comparison of analytic and numerical coalescing binary waveforms: Nonspinning case

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pan Yi; Buonanno, Alessandra; McWilliams, Sean T.

2008-01-15

We compare waveforms obtained by numerically evolving nonspinning binary black holes to post-Newtonian (PN) template families currently used in the search for gravitational waves by ground-based detectors. We find that the time-domain 3.5PN template family, which includes the inspiral phase, has fitting factors (FFs) {>=}0.96 for binary systems with total mass M=10-20M{sub {center_dot}}. The time-domain 3.5PN effective-one-body template family, which includes the inspiral, merger, and ring-down phases, gives satisfactory signal-matching performance with FFs {>=}0.96 for binary systems with total mass M=10-120M{sub {center_dot}}. If we introduce a cutoff frequency properly adjusted to the final black-hole ring-down frequency, we find that themore » frequency-domain stationary-phase-approximated template family at 3.5PN order has FFs {>=}0.96 for binary systems with total mass M=10-20M{sub {center_dot}}. However, to obtain high matching performances for larger binary masses, we need to either extend this family to unphysical regions of the parameter space or introduce a 4PN order coefficient in the frequency-domain gravitational wave (GW) phase. Finally, we find that the phenomenological Buonanno-Chen-Vallisneri family has FFs {>=}0.97 with total mass M=10-120M{sub {center_dot}}. The main analyses use the noise-spectral density of LIGO, but several tests are extended to VIRGO and advanced LIGO noise-spectral densities.« less

Analysis of 45-years of Eclipse Timings of the Hyades (K2 V+ DA) Eclipsing Binary V471 Tauri

NASA Astrophysics Data System (ADS)

Marchioni, Lucas; Guinan, Edward; Engle, Scott

2018-01-01

V471 Tau is an important detached 0.521-day eclipsing binary composed of a K2 V and a hot DA white dwarf star. This system resides in the Hyades star cluster located approximately 153 Ly from us. V471 Tau is considered to be the end-product of common-envelope binary star evolution and is currently a pre-CV system. V471 Tau serves as a valuable astrophysical laboratory for studying stellar evolution, white dwarfs, stellar magnetic dynamos, and possible detection of low mass companions using the Light Travel Time (LTT) Effects. Since its discovery as an eclipsing binary in 1970, photometry has been carried out and many eclipse timings have been determined. We have performed an analysis of the available photometric data available on V471 Tauri. The binary system has been the subject of analyses regarding the orbital period. From this analysis several have postulated the existence of a third body in the form of a brown dwarf that is causing periodic variations in the system’s apparent period. In this study we combine ground based data with photometry secured recently from the Kepler K2 mission. After detrending and phasing the available data, we are able to compare the changing period of the eclipsing binary system against predictions on the existence of this third body. The results of the analysis will be presented. This research is sponsored by grants from NASA and NSF for which we are very grateful.

VizieR Online Data Catalog: AR Sco VLA radio observations (Stanway+, 2018)

NASA Astrophysics Data System (ADS)

Stanway, E. R.; Marsh, T. R.; Chote, P.; Gaensicke, B. T.; Steeghs, D.; Wheatley, P. J.

2018-02-01

Time series VLA radio observations were undertaken of the highly variable white dwarf binary AR Scorpii. These were analysed for periodicity, spectral behaviour and other characteristics. Here we present time series data in the Stokes I parameter at three frequencies. These were centred at 1.5GHz (1GHz bandwidth), 5GHz (2GHz bandwidth) and 9GHz (2GHz bandwidth). The AR Sco binary is unresolved at these frequencies. In the case of the 1.5GHz data, fluxes have been deconvolved with those of a neighbouring object. (3 data files).

Assessment of various supervised learning algorithms using different performance metrics

NASA Astrophysics Data System (ADS)

Susheel Kumar, S. M.; Laxkar, Deepak; Adhikari, Sourav; Vijayarajan, V.

2017-11-01

Our work brings out comparison based on the performance of supervised machine learning algorithms on a binary classification task. The supervised machine learning algorithms which are taken into consideration in the following work are namely Support Vector Machine(SVM), Decision Tree(DT), K Nearest Neighbour (KNN), Naïve Bayes(NB) and Random Forest(RF). This paper mostly focuses on comparing the performance of above mentioned algorithms on one binary classification task by analysing the Metrics such as Accuracy, F-Measure, G-Measure, Precision, Misclassification Rate, False Positive Rate, True Positive Rate, Specificity, Prevalence.

Identifying predictive features in drug response using machine learning: opportunities and challenges.

PubMed

Vidyasagar, Mathukumalli

2015-01-01

This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction problems are divided into two categories: sparse classification and sparse regression. In classification, the clinical parameter to be predicted is binary, whereas in regression, the parameter is a real number. Well-known methods for both classes of problems are briefly discussed. These include the SVM (support vector machine) for classification and various algorithms such as ridge regression, LASSO (least absolute shrinkage and selection operator), and EN (elastic net) for regression. In addition, several well-established methods that do not directly fall into machine learning theory are also reviewed, including neural networks, PAM (pattern analysis for microarrays), SAM (significance analysis for microarrays), GSEA (gene set enrichment analysis), and k-means clustering. Several references indicative of the application of these methods to cancer biology are discussed.

A randomised controlled trial of flow driver and bubble continuous positive airway pressure in preterm infants in a resource-limited setting.

PubMed

Mazmanyan, P; Mellor, K; Doré, C J; Modi, N

2016-01-01

The variable-flow flow driver (FD; EME) and continuous-flow bubble (Fisher-Paykel) continuous positive airway pressure (CPAP) systems are widely used. As these differ in cost and technical requirements, determining comparative efficacy is important particularly where resources are limited. We performed a randomised, controlled, equivalence trial of CPAP systems. We specified the margin of equivalence as 2 days. We analysed binary variables by logistical regression adjusted for gestation, and log transformed continuous variables by multiple linear regression adjusted for gestation, sex and antenatal steroids. A neonatal unit with no blood gas analyser or surfactant availability and limited X-ray and laboratory facilities Neonates <37 weeks of gestation. We provided CPAP at delivery followed by randomisation to FD or bubble (B). Primary outcome included total days receiving CPAP; secondary outcomes included days receiving CPAP, supplemental oxygen, ventilation, death, pneumothorax and nasal excoriation. We randomised 125 infants (B 66, FD 59). Differences in infant outcomes on B and FD were not statistically significant. The median (range) for CPAP days for survivors was B 0.8 (0.04 to 17.5), FD 0.5 (0.04 to 5.3). B:FD (95% CI) ratios were CPAP days 1.3 (0.9 to 2.1), CPAP plus supplementary oxygen days 1.2 (0.7 to 1.9). B:FD (95% CI) ORs were death 2.3 (0.2 to 28), ventilation 2.1 (0.5 to 9), nasal excoriation 1.2 (0.2 to 8) and pneumothorax 2.4 (0.2 to 26). In a resource-limited setting we found B CPAP equivalent to FD CPAP in the total number of days receiving CPAP within a margin of 2 days. ISRCTN22578364. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Social inequalities and dental caries in six-year-old children from the Netherlands.

PubMed

van der Tas, Justin T; Kragt, Lea; Elfrink, Marlies E C; Bertens, Loes C M; Jaddoe, Vincent W V; Moll, Henriëtte A; Ongkosuwito, Edwin M; Wolvius, Eppo B

2017-07-01

The purpose of our study was to investigate the association of different socioeconomic and sociodemographic factors with dental caries in six-year-old children. Furthermore, we applied a district based approach to explore the distribution of dental caries among districts of low and high socioeconomic position (SEP). In our cross-sectional study 5189 six-year-olds were included. This study was embedded in a prospective population-based birth cohort study in Rotterdam, the Netherlands, the Generation R Study. Parental education level, parental employment status, net household income, single parenting, and teenage pregnancy were considered as indicators for SEP. Dental caries was scored on intraoral photographs by using the decayed, missing, and filled teeth (dmft) index. We compared children without caries (dmft=0) to children with mild caries (dmft=1-3) or severe caries (dmft >3). Multinomial logistic regression analyses and binary logistic regression analyses were performed to study the association between SEP and caries, and between district and caries, respectively. Only maternal education level remained significantly associated with mild caries after adjusting for all other SEP-indicators. Paternal educational level, parental employment status, and household income additionally served as independent indicators of SEP in children with severe caries. Furthermore, living in more disadvantaged districts was significantly associated with higher odds of dental caries. Dental caries is more prevalent among six-year-old children with a low SEP, which is also visible at the district level. Maternal educational level is the most important indicator of SEP in the association with caries. Our results should raise concerns about the existing social inequalities in dental caries and should encourage development of dental caries prevention strategies. New knowledge about the distribution of oral health inequalities between districts should be used to target the right audience for these strategies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Socioeconomic status is positively associated with measures of adiposity and insulin resistance, but inversely associated with dyslipidaemia in Colombian children

PubMed Central

Buitrago-Lopez, Adriana; van den Hooven, Edith H; Rueda-Clausen, Christian F; Serrano, Norma; Ruiz, Alvaro J; Pereira, Mark A; Mueller, Noel T

2015-01-01

Background Low socioeconomic status (SES) has been associated with higher risk of cardiometabolic diseases in developed societies, but investigation of SES and cardiometabolic risk in children in less economically developed populations is sparse. We aimed to examine associations among SES and cardiometabolic risk factors in Colombian children. Methods We used data from a population-based study of 1282 children aged 6–10 years from Bucaramanga, Colombia. SES was classified according to household wealth, living conditions and access to public utilities. Anthropometric and biochemical parameters were measured at a clinic visit. Cardiometabolic risk factors were analysed continuously using linear regression and as binary outcomes—according to established paediatric cut points—using logistic regression to calculate OR and 95% CIs. Results Mean age of the children was 8.4 (SD 1.4) and 51.1% of the sample were boys. Odds of overweight/obesity, abdominal obesity and insulin resistance were greater among higher SES. Compared with the lowest SES stratum, children in the highest SES had higher odds of overweight/obesity (OR=3.25, 95% CI 1.89 to 5.57), abdominal obesity (OR=2.74, 95% CI 1.41 to 5.31) and insulin resistance (OR=2.60, 95% CI 1.81 to 3.71). In contrast, children in the highest SES had lower odds of hypertriglyceridaemia (triglycerides ≥90th centile; OR=0.28, 95% CI 0.14 to 0.54) and low (≤10th centile) high-density lipoprotein (HDL) cholesterol (OR=0.35, 95% CI 0.15 to 0.78). Conclusions In Colombian children, SES is directly associated with obesity and insulin resistance, but inversely associated with dyslipidaemia (hypertriglyceridaemia and low HDL cholesterol). Our findings highlight the need to analyse cardiometabolic risk factors separately in children and to carefully consider a population's level of economic development when studying their social determinants of cardiometabolic disease. PMID:25691273

Binary Logistic Regression Analysis in Assessment and Identifying Factors That Influence Students' Academic Achievement: The Case of College of Natural and Computational Science, Wolaita Sodo University, Ethiopia

ERIC Educational Resources Information Center

Zewude, Bereket Tessema; Ashine, Kidus Meskele

2016-01-01

An attempt has been made to assess and identify the major variables that influence student academic achievement at college of natural and computational science of Wolaita Sodo University in Ethiopia. Study time, peer influence, securing first choice of department, arranging study time outside class, amount of money received from family, good life…

Linking primary study data with administrative and claims data in a German cohort study on work, age, health and work participation: is there a consent bias?

PubMed

Stallmann, C; Swart, E; Robra, B-P; March, S

2017-09-01

We analysed the degree and impact of consent bias in the prospective study 'leben in der Arbeit (lidA)' after linking primary interview data with claims data from German statutory health insurance funds as well as with administrative data provided by the German Federal Employment Agency. Prospective cohort study. Within two study waves (2011, 2014) primary data were collected based on computer-assisted personal interviews. During interview informed consent to data linkage was obtained. We used binary logistic regression analyses with participants' consent for record linkage as the dependent variable calculating odds ratios (ORs) and 95% confidence intervals (95% CIs) for independent variables. Several sociodemographic, socio-economic and work-related factors were modelled as potential determinants of consent. A total of 4244 participants took part in both waves. After excluding invalid consent, 4178 participants were included in the analysis. About 3918 (93.8%) of these participants gave their consent to link their primary data with data from at least one source. Within regression analyses only moderate bias was found due to region of residence, apprenticeship, professional affiliations, income and number of diseases. Participants from former West Germany were less likely to have their study data linked with both data sources (OR 0.63 [95% CI 0.42-0.96]) than those from the former East Germany. Participants with no information on income were more likely to refuse consent to both data sources compared to the reference group (net income: under EUR 1000; OR 0.15 [95% CI 0.08-0.30]). Respondents with two (OR 1.37 [95% CI 1.06-1.77]) or three and more diseases (OR 1.30 [95% CI 1.02-1.66]) diagnosed by a doctor agreed more frequently to linking both data sources than participants without disease. There is just a small proportion of variance in consenting explained by the models (R 2 : 0.063-0.085). Also, only small changes of factors' prevalence were observed in consenters. For the first time in Germany, the lidA-study links primary survey data with health claims and administrative employment data. We conclude that there is only a minor relation between the analysed factors and consent behaviour of the participants. A linked data set may be used in further analyses without substantial biases. Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Minimizing effects of methodological decisions on interpretation and prediction in species distribution studies: An example with background selection

USGS Publications Warehouse

Jarnevich, Catherine S.; Talbert, Marian; Morisette, Jeffrey T.; Aldridge, Cameron L.; Brown, Cynthia; Kumar, Sunil; Manier, Daniel; Talbert, Colin; Holcombe, Tracy R.

2017-01-01

Evaluating the conditions where a species can persist is an important question in ecology both to understand tolerances of organisms and to predict distributions across landscapes. Presence data combined with background or pseudo-absence locations are commonly used with species distribution modeling to develop these relationships. However, there is not a standard method to generate background or pseudo-absence locations, and method choice affects model outcomes. We evaluated combinations of both model algorithms (simple and complex generalized linear models, multivariate adaptive regression splines, Maxent, boosted regression trees, and random forest) and background methods (random, minimum convex polygon, and continuous and binary kernel density estimator (KDE)) to assess the sensitivity of model outcomes to choices made. We evaluated six questions related to model results, including five beyond the common comparison of model accuracy assessment metrics (biological interpretability of response curves, cross-validation robustness, independent data accuracy and robustness, and prediction consistency). For our case study with cheatgrass in the western US, random forest was least sensitive to background choice and the binary KDE method was least sensitive to model algorithm choice. While this outcome may not hold for other locations or species, the methods we used can be implemented to help determine appropriate methodologies for particular research questions.

Social Impact of Stigma Regarding Tuberculosis Hindering Adherence to Treatment: A Cross Sectional Study Involving Tuberculosis Patients in Rajshahi City, Bangladesh.

PubMed

Chowdhury, Md Rocky Khan; Rahman, Md Shafiur; Mondal, Md Nazrul Islam; Sayem, Abu; Billah, Baki

2015-01-01

Stigma, considered a social disease, is more apparent in developing societies which are driven by various social affairs, and influences adherence to treatment. The aim of the present study was to examine levels of social stigma related to tuberculosis (TB) in sociodemographic context and identify the effects of sociodemographic factors on stigma. The study sample consisted of 372 TB patients. Data were collected using stratified sampling with simple random sampling techniques. T tests, chi-square tests, and binary logistic regression analysis were performed to examine correlations between stigma and sociodemographic variables. Approximately 85.9% of patients had experienced stigma. The most frequent indicator of the stigma experienced by patients involved problems taking part in social programs (79.5%). Mean levels of stigma were significantly higher in women (55.5%), illiterate individuals (60.8%), and villagers (60.8%) relative to those of other groups. Chi-square tests revealed that education, monthly family income, and type of patient (pulmonary and extrapulmonary) were significantly associated with stigma. Binary logistic regression analysis demonstrated that stigma was influenced by sex, education, and type of patient. Stigma is one of the most important barriers to treatment adherence. Therefore, in interventions that aim to reduce stigma, strong collaboration between various institutions is essential.

The Mantel-Haenszel procedure revisited: models and generalizations.

PubMed

Fidler, Vaclav; Nagelkerke, Nico

2013-01-01

Several statistical methods have been developed for adjusting the Odds Ratio of the relation between two dichotomous variables X and Y for some confounders Z. With the exception of the Mantel-Haenszel method, commonly used methods, notably binary logistic regression, are not symmetrical in X and Y. The classical Mantel-Haenszel method however only works for confounders with a limited number of discrete strata, which limits its utility, and appears to have no basis in statistical models. Here we revisit the Mantel-Haenszel method and propose an extension to continuous and vector valued Z. The idea is to replace the observed cell entries in strata of the Mantel-Haenszel procedure by subject specific classification probabilities for the four possible values of (X,Y) predicted by a suitable statistical model. For situations where X and Y can be treated symmetrically we propose and explore the multinomial logistic model. Under the homogeneity hypothesis, which states that the odds ratio does not depend on Z, the logarithm of the odds ratio estimator can be expressed as a simple linear combination of three parameters of this model. Methods for testing the homogeneity hypothesis are proposed. The relationship between this method and binary logistic regression is explored. A numerical example using survey data is presented.

The Mantel-Haenszel Procedure Revisited: Models and Generalizations

PubMed Central

Fidler, Vaclav; Nagelkerke, Nico

2013-01-01

Several statistical methods have been developed for adjusting the Odds Ratio of the relation between two dichotomous variables X and Y for some confounders Z. With the exception of the Mantel-Haenszel method, commonly used methods, notably binary logistic regression, are not symmetrical in X and Y. The classical Mantel-Haenszel method however only works for confounders with a limited number of discrete strata, which limits its utility, and appears to have no basis in statistical models. Here we revisit the Mantel-Haenszel method and propose an extension to continuous and vector valued Z. The idea is to replace the observed cell entries in strata of the Mantel-Haenszel procedure by subject specific classification probabilities for the four possible values of (X,Y) predicted by a suitable statistical model. For situations where X and Y can be treated symmetrically we propose and explore the multinomial logistic model. Under the homogeneity hypothesis, which states that the odds ratio does not depend on Z, the logarithm of the odds ratio estimator can be expressed as a simple linear combination of three parameters of this model. Methods for testing the homogeneity hypothesis are proposed. The relationship between this method and binary logistic regression is explored. A numerical example using survey data is presented. PMID:23516463

Predicting allergic contact dermatitis: a hierarchical structure activity relationship (SAR) approach to chemical classification using topological and quantum chemical descriptors

NASA Astrophysics Data System (ADS)

Basak, Subhash C.; Mills, Denise; Hawkins, Douglas M.

2008-06-01

A hierarchical classification study was carried out based on a set of 70 chemicals—35 which produce allergic contact dermatitis (ACD) and 35 which do not. This approach was implemented using a regular ridge regression computer code, followed by conversion of regression output to binary data values. The hierarchical descriptor classes used in the modeling include topostructural (TS), topochemical (TC), and quantum chemical (QC), all of which are based solely on chemical structure. The concordance, sensitivity, and specificity are reported. The model based on the TC descriptors was found to be the best, while the TS model was extremely poor.

The effect of disorder of small spheres on the photonic properties of the inverse binary NaCl-like structure

NASA Astrophysics Data System (ADS)

Pattabhiraman, Harini; Dijkstra, Marjolein

2017-09-01

Inverse opal structures are experimentally realisable photonic band gap materials. They suffer from the drawback of possessing band gaps that are extremely susceptible to structural disorders. A binary colloidal NaCl lattice, which is also experimentally realisable, is a promising alternative to these opals. In this work, we systematically analyse the effect of structural disorder of the small spheres on the photonic properties of an inverse binary NaCl lattice with a size ratio of 0.30 between the small and large spheres. The types of structural disorders studied include the position of the small spheres in the octahedral void of the large spheres, polydispersity in size of the small spheres, and the fraction of small spheres in the crystal. We find a low susceptibility of the band gap of the inverse NaCl lattice to the disorder of the small spheres.

The scent of mixtures: rules of odour processing in ants

PubMed Central

Perez, Margot; Giurfa, Martin; d'Ettorre, Patrizia

2015-01-01

Natural odours are complex blends of numerous components. Understanding how animals perceive odour mixtures is central to multiple disciplines. Here we focused on carpenter ants, which rely on odours in various behavioural contexts. We studied overshadowing, a phenomenon that occurs when animals having learnt a binary mixture respond less to one component than to the other, and less than when this component was learnt alone. Ants were trained individually with alcohols and aldehydes varying in carbon-chain length, either as single odours or binary mixtures. They were then tested with the mixture and the components. Overshadowing resulted from the interaction between chain length and functional group: alcohols overshadowed aldehydes, and longer chain lengths overshadowed shorter ones; yet, combinations of these factors could cancel each other and suppress overshadowing. Our results show how ants treat binary olfactory mixtures and set the basis for predictive analyses of odour perception in insects. PMID:25726692

BVR{sub c}I{sub c} observations and analyses on V2421 Cygni, a precontact W UMa binary

DOE Office of Scientific and Technical Information (OSTI.GOV)

Samec, R. G.; Shebs, Travis S.; Faulkner, D. R.

2014-01-01

We present the first precision BVRI light curves, synthetic light curve solutions, and a period study for the high amplitude solar type binary, V2421 Cygni. The light curves have the appearance of an Algol (EA) type; however, it is made up of dwarf solar type components in a detached mode with a period of only 0.6331 days with an amplitude of about a full magnitude, i.e., it is a precontact W UMa binary. Flare-like disruptions occur in the light curves following the primary and secondary eclipses possibly due to the line-of-sight track of a gas stream. An associated stream spotmore » and splash spot cause bright equatorial spots on the stellar surface of the primary star. The more massive star is the gainer, making this system a classic, albeit dwarf, Algol.« less

QTest: Quantitative Testing of Theories of Binary Choice.

PubMed

Regenwetter, Michel; Davis-Stober, Clintin P; Lim, Shiau Hong; Guo, Ying; Popova, Anna; Zwilling, Chris; Cha, Yun-Shil; Messner, William

2014-01-01

The goal of this paper is to make modeling and quantitative testing accessible to behavioral decision researchers interested in substantive questions. We provide a novel, rigorous, yet very general, quantitative diagnostic framework for testing theories of binary choice. This permits the nontechnical scholar to proceed far beyond traditionally rather superficial methods of analysis, and it permits the quantitatively savvy scholar to triage theoretical proposals before investing effort into complex and specialized quantitative analyses. Our theoretical framework links static algebraic decision theory with observed variability in behavioral binary choice data. The paper is supplemented with a custom-designed public-domain statistical analysis package, the QTest software. We illustrate our approach with a quantitative analysis using published laboratory data, including tests of novel versions of "Random Cumulative Prospect Theory." A major asset of the approach is the potential to distinguish decision makers who have a fixed preference and commit errors in observed choices from decision makers who waver in their preferences.

Absolute Parameters for the F-type Eclipsing Binary BW Aquarii

NASA Astrophysics Data System (ADS)

Maxted, P. F. L.

2018-05-01

BW Aqr is a bright eclipsing binary star containing a pair of F7V stars. The absolute parameters of this binary (masses, radii, etc.) are known to good precision so they are often used to test stellar models, particularly in studies of convective overshooting. ... Maxted & Hutcheon (2018) analysed the Kepler K2 data for BW Aqr and noted that it shows variability between the eclipses that may be caused by tidally induced pulsations. ... Table 1 shows the absolute parameters for BW Aqr derived from an improved analysis of the Kepler K2 light curve plus the RV measurements from both Imbert (1979) and Lester & Gies (2018). ... The values in Table 1 with their robust error estimates from the standard deviation of the mean are consistent with the values and errors from Maxted & Hutcheon (2018) based on the PPD calculated using emcee for a fit to the entire K2 light curve.

Theory of Metastable State Relaxation in a Gravitational Field for Non-Critical Binary Systems with Non-Conserved Order Parameter

NASA Technical Reports Server (NTRS)

Izmailov, Alexander F.; Myerson, Allan S.

1993-01-01

A new mathematical ansatz is developed for solution of the time-dependent Ginzburg-Landau nonlinear partial differential equation describing metastable state relaxation in binary (solute+solvent) non-critical solutions with non-conserved scalar order parameter in presence of a gravitational field. It has been demonstrated analytically that in such systems metastability initiates heterogeneous solute redistribution which results in the formation of a non-equilibrium singly-periodic spatial solute structure in the new solute-rich phase. The critical radius of nucleation and the induction time in these systems are gravity-dependent. It has also been proved that metastable state relaxation in vertical columns of supersaturated non-critical binary solutions leads to formation of the solute concentration gradient. Analytical expression for this concentration gradient is found and analysed. It is concluded that gravity can initiate phase separation (nucleation or spinodal decomposition).

A model of the evaporation of binary-fuel clusters of drops

NASA Technical Reports Server (NTRS)

Harstad, K.; Bellan, J.

1991-01-01

A formulation has been developed to describe the evaporation of dense or dilute clusters of binary-fuel drops. The binary fuel is assumed to be made of a solute and a solvent whose volatility is much lower than that of the solute. Convective flow effects, inducing a circulatory motion inside the drops, are taken into account, as well as turbulence external to the cluster volume. Results obtained with this model show that, similar to the conclusions for single isolated drops, the evaporation of the volatile is controlled by liquid mass diffusion when the cluster is dilute. In contrast, when the cluster is dense, the evaporation of the volatile is controlled by surface layer stripping, that is, by the regression rate of the drop, which is in fact controlled by the evaporation rate of the solvent. These conclusions are in agreement with existing experimental observations. Parametric studies show that these conclusions remain valid with changes in ambient temperature, initial slip velocity between drops and gas, initial drop size, initial cluster size, initial liquid mass fraction of the solute, and various combinations of solvent and solute. The implications of these results for computationally intensive combustor calculations are discussed.

Pathways for diffusion in the potential energy landscape of the network glass former SiO2

NASA Astrophysics Data System (ADS)

Niblett, S. P.; Biedermann, M.; Wales, D. J.; de Souza, V. K.

2017-10-01

We study the dynamical behaviour of a computer model for viscous silica, the archetypal strong glass former, and compare its diffusion mechanism with earlier studies of a fragile binary Lennard-Jones liquid. Three different methods of analysis are employed. First, the temperature and time scale dependence of the diffusion constant is analysed. Negative correlation of particle displacements influences transport properties in silica as well as in fragile liquids. We suggest that the difference between Arrhenius and super-Arrhenius diffusive behaviour results from competition between the correlation time scale and the caging time scale. Second, we analyse the dynamics using a geometrical definition of cage-breaking transitions that was proposed previously for fragile glass formers. We find that this definition accurately captures the bond rearrangement mechanisms that control transport in open network liquids, and reproduces the diffusion constants accurately at low temperatures. As the same method is applicable to both strong and fragile glass formers, we can compare correlation time scales in these two types of systems. We compare the time spent in chains of correlated cage breaks with the characteristic caging time and find that correlations in the fragile binary Lennard-Jones system persist for an order of magnitude longer than those in the strong silica system. We investigate the origin of the correlation behaviour by sampling the potential energy landscape for silica and comparing it with the binary Lennard-Jones model. We find no qualitative difference between the landscapes, but several metrics suggest that the landscape of the fragile liquid is rougher and more frustrated. Metabasins in silica are smaller than those in binary Lennard-Jones and contain fewer high-barrier processes. This difference probably leads to the observed separation of correlation and caging time scales.

Empirical Identification of Hierarchies.

ERIC Educational Resources Information Center

McCormick, Douglas; And Others

Outlining a cluster procedure which maximizes specific criteria while building scales from binary measures using a sequential, agglomerative, overlapping, non-hierarchic method results in indices giving truer results than exploratory facotr analyses or multidimensional scaling. In a series of eleven figures, patterns within cluster histories…

Estimating the Probability of Rare Events Occurring Using a Local Model Averaging.

PubMed

Chen, Jin-Hua; Chen, Chun-Shu; Huang, Meng-Fan; Lin, Hung-Chih

2016-10-01

In statistical applications, logistic regression is a popular method for analyzing binary data accompanied by explanatory variables. But when one of the two outcomes is rare, the estimation of model parameters has been shown to be severely biased and hence estimating the probability of rare events occurring based on a logistic regression model would be inaccurate. In this article, we focus on estimating the probability of rare events occurring based on logistic regression models. Instead of selecting a best model, we propose a local model averaging procedure based on a data perturbation technique applied to different information criteria to obtain different probability estimates of rare events occurring. Then an approximately unbiased estimator of Kullback-Leibler loss is used to choose the best one among them. We design complete simulations to show the effectiveness of our approach. For illustration, a necrotizing enterocolitis (NEC) data set is analyzed. © 2016 Society for Risk Analysis.

Updated O-C Diagrams for Several Bright HW Vir Binaries Observed with the Evryscope

NASA Astrophysics Data System (ADS)

Corcoran, Kyle A.; Barlow, Brad; Corbett, Hank; Fors, Octavi; Howard, Ward S.; Law, Nicholas; Ratzloff, Jeff

2018-01-01

HW Vir systems are eclipsing, post-common-envelope binaries consisting of a hot subdwarf star and a cooler M dwarf or brown dwarf companion. They show a strong reflection effect and have characteristically short orbital periods of only a few hours, allowing observers to detect multiple eclipses per night. Observed minus calculated (O-C) studies allow one to measure miniscule variations in the orbital periods of these systems by comparing observed eclipse timings to a calculated ephemeris. This technique is useful for detecting period changes due to secular evolution of the binary, gravitational wave emission, or reflex motion from an orbiting circumbinary object. Numerous eclipse timings obtained over several years are vital to the proper interpretation and analysis of O-C diagrams. The Evryscope – an array of twenty-four individual telescopes built by UNC and deployed on Cerro Tololo – images the entire Southern sky once every two minutes, producing an insurmountable amount of data for objects brighter than 16th magnitude. The cadence with which Evryscope exposes makes it an unparalleled tool for O-C analyses of HW Vir binaries; it will catalogue thousands of eclipses over the next several years. Here we present updated O-C diagrams for several HW Vir binaries using recent measurements from the Evryscope. We also use observations of AA Dor, an incredibly stable astrophysical clock, to characterize the accuracy of the Evryscope’s timestamps.

Automated particle identification through regression analysis of size, shape and colour

NASA Astrophysics Data System (ADS)

Rodriguez Luna, J. C.; Cooper, J. M.; Neale, S. L.

2016-04-01

Rapid point of care diagnostic tests and tests to provide therapeutic information are now available for a range of specific conditions from the measurement of blood glucose levels for diabetes to card agglutination tests for parasitic infections. Due to a lack of specificity these test are often then backed up by more conventional lab based diagnostic methods for example a card agglutination test may be carried out for a suspected parasitic infection in the field and if positive a blood sample can then be sent to a lab for confirmation. The eventual diagnosis is often achieved by microscopic examination of the sample. In this paper we propose a computerized vision system for aiding in the diagnostic process; this system used a novel particle recognition algorithm to improve specificity and speed during the diagnostic process. We will show the detection and classification of different types of cells in a diluted blood sample using regression analysis of their size, shape and colour. The first step is to define the objects to be tracked by a Gaussian Mixture Model for background subtraction and binary opening and closing for noise suppression. After subtracting the objects of interest from the background the next challenge is to predict if a given object belongs to a certain category or not. This is a classification problem, and the output of the algorithm is a Boolean value (true/false). As such the computer program should be able to "predict" with reasonable level of confidence if a given particle belongs to the kind we are looking for or not. We show the use of a binary logistic regression analysis with three continuous predictors: size, shape and color histogram. The results suggest this variables could be very useful in a logistic regression equation as they proved to have a relatively high predictive value on their own.

Using a binary logistic regression method and GIS for evaluating and mapping the groundwater spring potential in the Sultan Mountains (Aksehir, Turkey)

NASA Astrophysics Data System (ADS)

Ozdemir, Adnan

2011-07-01

SummaryThe purpose of this study is to produce a groundwater spring potential map of the Sultan Mountains in central Turkey, based on a logistic regression method within a Geographic Information System (GIS) environment. Using field surveys, the locations of the springs (440 springs) were determined in the study area. In this study, 17 spring-related factors were used in the analysis: geology, relative permeability, land use/land cover, precipitation, elevation, slope, aspect, total curvature, plan curvature, profile curvature, wetness index, stream power index, sediment transport capacity index, distance to drainage, distance to fault, drainage density, and fault density map. The coefficients of the predictor variables were estimated using binary logistic regression analysis and were used to calculate the groundwater spring potential for the entire study area. The accuracy of the final spring potential map was evaluated based on the observed springs. The accuracy of the model was evaluated by calculating the relative operating characteristics. The area value of the relative operating characteristic curve model was found to be 0.82. These results indicate that the model is a good estimator of the spring potential in the study area. The spring potential map shows that the areas of very low, low, moderate and high groundwater spring potential classes are 105.586 km 2 (28.99%), 74.271 km 2 (19.906%), 101.203 km 2 (27.14%), and 90.05 km 2 (24.671%), respectively. The interpretations of the potential map showed that stream power index, relative permeability of lithologies, geology, elevation, aspect, wetness index, plan curvature, and drainage density play major roles in spring occurrence and distribution in the Sultan Mountains. The logistic regression approach has not yet been used to delineate groundwater potential zones. In this study, the logistic regression method was used to locate potential zones for groundwater springs in the Sultan Mountains. The evolved model was found to be in strong agreement with the available groundwater spring test data. Hence, this method can be used routinely in groundwater exploration under favourable conditions.

ζ1 + ζ2 Reticuli binary system: a puzzling chromospheric activity pattern

NASA Astrophysics Data System (ADS)

Flores, M.; Saffe, C.; Buccino, A.; Jaque Arancibia, M.; González, J. F.; Nuñez, N. E.; Jofré, E.

2018-05-01

We perform, for the first time, a detailed long-term activity study of the binary system ζ Ret. We use all available HARPS spectra obtained between the years 2003 and 2016. We build a time series of the Mount Wilson S index for both stars, then we analyse these series by using Lomb-Scargle periodograms. The components ζ1 Ret and ζ2 Ret that belong to this binary system are physically very similar to each other and also similar to our Sun, which makes it a remarkable system. We detect in the solar-analogue star ζ2 Ret a long-term activity cycle with a period of ˜10 yr, similar to the solar one (˜11 yr). It is worthwhile to mention that this object satisfies previous criteria for a flat star and for a cycling star simultaneously. Another interesting feature of this binary system is a high ˜0.220 dex difference between the average log (R^' }_HK) activity levels of both stars. Our study clearly shows that ζ1 Ret is significantly more active than ζ2 Ret. In addition, ζ1 Ret shows an erratic variability in its stellar activity. In this work, we explore different scenarios trying to explain this rare behaviour in a pair of coeval stars, which could help to explain the difference in this and other binary systems. From these results, we also warn that for the development of activity-age calibrations (which commonly use binary systems and/or stellar clusters as calibrators) the whole history of activity available for the stars involved should be taken into account.

Patterns of medicinal plant use: an examination of the Ecuadorian Shuar medicinal flora using contingency table and binomial analyses.

PubMed

Bennett, Bradley C; Husby, Chad E

2008-03-28

Botanical pharmacopoeias are non-random subsets of floras, with some taxonomic groups over- or under-represented. Moerman [Moerman, D.E., 1979. Symbols and selectivity: a statistical analysis of Native American medical ethnobotany, Journal of Ethnopharmacology 1, 111-119] introduced linear regression/residual analysis to examine these patterns. However, regression, the commonly-employed analysis, suffers from several statistical flaws. We use contingency table and binomial analyses to examine patterns of Shuar medicinal plant use (from Amazonian Ecuador). We first analyzed the Shuar data using Moerman's approach, modified to better meet requirements of linear regression analysis. Second, we assessed the exact randomization contingency table test for goodness of fit. Third, we developed a binomial model to test for non-random selection of plants in individual families. Modified regression models (which accommodated assumptions of linear regression) reduced R(2) to from 0.59 to 0.38, but did not eliminate all problems associated with regression analyses. Contingency table analyses revealed that the entire flora departs from the null model of equal proportions of medicinal plants in all families. In the binomial analysis, only 10 angiosperm families (of 115) differed significantly from the null model. These 10 families are largely responsible for patterns seen at higher taxonomic levels. Contingency table and binomial analyses offer an easy and statistically valid alternative to the regression approach.

Low-Level Stratus Prediction Using Binary Statistical Regression: A Progress Report Using Moffett Field Data.

DTIC Science & Technology

1983-12-01

analysis; such work is not reported here. It seems pos- sible that a robust principle component analysis may he informa- tive (see Gnanadesikan (1977...Statistics in Atmospheric Sciences, American Meteorological Soc., Boston, Mass. (1979) pp. 46-48. a Gnanadesikan , R., Methods for Statistical Data...North Carolina Chapel Hill, NC 20742 Dr. R. Gnanadesikan Bell Telephone Lab Murray Hill, NJ 07733 -%.. *5%a: *1 *15 I ,, - . . , ,, ... . . . . . . NO

Period variations of Algol-type eclipsing binaries AD And, TWCas and IV Cas

NASA Astrophysics Data System (ADS)

Parimucha, Štefan; Gajdoš, Pavol; Kudak, Viktor; Fedurco, Miroslav; Vaňko, Martin

2018-04-01

We present new analyses of variations in O – C diagrams of three Algol-type eclipsing binary stars: AD And, TW Cas and IV Cas. We have used all published minima times (including visual and photographic) as well as newly determined ones from our and SuperWasp observations. We determined orbital parameters of 3rd bodies in the systems with statistically significant errors, using our code based on genetic algorithms and Markov chain Monte Carlo simulations. We confirmed the multiple nature of AD And and the triple-star model of TW Cas, and we proposed a quadruple-star model of IV Cas.

The quest for a universal definition of polytrauma: a trauma registry-based validation study.

PubMed

Butcher, Nerida E; D'Este, Catherine; Balogh, Zsolt J

2014-10-01

A pilot validation recommended defining polytrauma as patients with an Abbreviated Injury Scale (AIS) score greater than 2 in at least two Injury Severity Score (ISS) body regions (2 × AIS score > 2). This study aimed to validate this definition on larger data set. We hypothesized that patients defined by the 2 × AIS score > 2 cutoff have worse outcomes and use more resources than those without 2 × AIS score > 2 and that this would therefore be a better definition of polytrauma. Patients injured between 2009 and 2011, with complete documentation of AIS by New South Wales Trauma Registry and 16 years and older were selected. Age and sex were obtained in addition to outcomes of ISS, hospital length of stay (LOS), intensive care unit (ICU) admission, ICU LOS, and mortality. We compared demographic characteristics and outcomes between patients with ISS greater than 15 who did and did not meet the 2 × AIS score > 2 definition. We then undertook regression analyses (logistic regression for binary outcomes [ICU admission and death] and linear regression for hospital and ICU LOS) to compare outcomes for patients with and without 2 × AIS score > 2, adjusting for sex and age categories. In the adjusted analyses, patients with 2 × AIS score > 2 had twice the odds of being admitted to the ICU compared with those without 2 × AIS score > 2 (odds ratio, 2.5; 95% confidence interval [CI], 2.2-2.8) and 1.7 times the odds of dying (95% CI, 1.4-2.0; p < 0.001 for both models). Patients with 2 × AIS score > 2 also had a mean difference of 1.5 days longer stay in the hospital compared with those without 2 × AIS score > 2 (95% CI, 1.4-1.7) and 1.6 days longer ICU stay (95% CI, 1.4-1.8; p < 0.001 for all models). Patients with 2 × AIS score > 2 had higher mortality, more frequent ICU admissions, and longer hospital and ICU stay than those without 2 × AIS score > 2 and represents a superior definition to the definitions for polytrauma currently in use. Diagnostic test/ criteria, level III.

Collisional redistribution of radiation. II - The effects of degeneracy on the equations of motion for the density matrix. III - The equation of motion for the correlation function and the scattered spectrum

NASA Technical Reports Server (NTRS)

Burnett, K.; Cooper, J.

1980-01-01

The effect of correlations between an absorber atom and perturbers in the binary-collision approximation are applied to degenerate atomic systems. A generalized absorption profile which specifies the final state of the atom after an absorption event is related to the total intensities of Rayleigh scattering and fluorescence from the atom. It is suggested that additional dynamical information to that obtainable from ordinary absorption experiments is required in order to describe redistributed atomic radiation. The scattering of monochromatic radiation by a degenerate atom is computed in a binary-collision approximation; an equation of motion is derived for the correlation function which is valid outside the quantum-regression regime. Solutions are given for the weak-field conditions in terms of generalized absorption and emission profiles that depend on the indices of the atomic multipoles.

A comparative study of the use of powder X-ray diffraction, Raman and near infrared spectroscopy for quantification of binary polymorphic mixtures of piracetam.

PubMed

Croker, Denise M; Hennigan, Michelle C; Maher, Anthony; Hu, Yun; Ryder, Alan G; Hodnett, Benjamin K

2012-04-07

Diffraction and spectroscopic methods were evaluated for quantitative analysis of binary powder mixtures of FII(6.403) and FIII(6.525) piracetam. The two polymorphs of piracetam could be distinguished using powder X-ray diffraction (PXRD), Raman and near-infrared (NIR) spectroscopy. The results demonstrated that Raman and NIR spectroscopy are most suitable for quantitative analysis of this polymorphic mixture. When the spectra are treated with the combination of multiplicative scatter correction (MSC) and second derivative data pretreatments, the partial least squared (PLS) regression model gave a root mean square error of calibration (RMSEC) of 0.94 and 0.99%, respectively. FIII(6.525) demonstrated some preferred orientation in PXRD analysis, making PXRD the least preferred method of quantification. Copyright © 2012 Elsevier B.V. All rights reserved.

Two-Part and Related Regression Models for Longitudinal Data

PubMed Central

Farewell, V.T.; Long, D.L.; Tom, B.D.M.; Yiu, S.; Su, L.

2017-01-01

Statistical models that involve a two-part mixture distribution are applicable in a variety of situations. Frequently, the two parts are a model for the binary response variable and a model for the outcome variable that is conditioned on the binary response. Two common examples are zero-inflated or hurdle models for count data and two-part models for semicontinuous data. Recently, there has been particular interest in the use of these models for the analysis of repeated measures of an outcome variable over time. The aim of this review is to consider motivations for the use of such models in this context and to highlight the central issues that arise with their use. We examine two-part models for semicontinuous and zero-heavy count data, and we also consider models for count data with a two-part random effects distribution. PMID:28890906

The As-Cu-Ni System: A Chemical Thermodynamic Model for Ancient Recycling

NASA Astrophysics Data System (ADS)

Sabatini, Benjamin J.

2015-12-01

This article is the first thermodynamically reasoned ancient metal system assessment intended for use by archaeologists and archaeometallurgists to aid in the interpretation of remelted/recycled copper alloys composed of arsenic and copper, and arsenic, copper, and nickel. These models are meant to fulfill two main purposes: first, to be applied toward the identification of progressive and regressive temporal changes in artifact chemistry that would have occurred due to recycling, and second, to provide thermodynamic insight into why such metal combinations existed in antiquity. Built on well-established thermodynamics, these models were created using a combination of custom-written software and published binary thermodynamic systems data adjusted to within the boundary conditions of 1200°C and 1 atm. Using these parameters, the behavior of each element and their likelihood of loss in the binaries As-Cu, As-Ni, Cu-Ni, and ternary As-Cu-Ni, systems, under assumed ancient furnace conditions, was determined.

Brief Motivational Interventions Are Associated With Reductions in Alcohol-Impaired Driving Among College Drinkers

PubMed Central

Teeters, Jenni B.; Borsari, Brian; Martens, Matthew P.; Murphy, James G.

2015-01-01

Objective: Alcohol-impaired (AI) driving among college students remains a significant public health concern and may be the single most risky drinking outcome among young adults. Brief motivational interventions (BMIs) have been shown to reduce alcohol use and problems, but their specific efficacy for decreasing AI driving among college students is unknown. The present study analyzed data from three randomized controlled trials of BMI (Murphy et al., 2010: n = 74; Borsari et al., 2012: n = 530; and Martens et al., 2013: n = 365) to evaluate whether BMIs are associated with reductions in AI driving among college student drinkers. Method: Participants in all three studies were randomized to BMI or control conditions. Participants reported whether they had driven under the influence (yes/no) following the BMI over the follow-up period. Results: Separate binary logistic regression analyses were conducted for each study. For Studies 1 and 2, these analyses revealed that a BMI was significantly associated with reductions in AI driving at the final (6-month and 9-month, respectively) follow-up compared with the control condition. For Study 3, analyses revealed that a single-component BMI focused on the correction of misperceptions of descriptive norms was significantly associated with reductions in AI driving compared with the control group at the final (6-month) follow-up, whereas a single-component BMI focused on the use of protective behavioral strategies was not. Change in drinking level did not mediate the relationship between the condition and the change in AI driving. Conclusions: Counselor-administered BMIs that include descriptive normative feedback are associated with significant reductions in AI driving compared with control. PMID:26402350

Neighborhood deprivation is strongly associated with participation in a population-based health check.

PubMed

Bender, Anne Mette; Kawachi, Ichiro; Jørgensen, Torben; Pisinger, Charlotta

2015-01-01

We sought to examine whether neighborhood deprivation is associated with participation in a large population-based health check. Such analyses will help answer the question whether health checks, which are designed to meet the needs of residents in deprived neighborhoods, may increase participation and prove to be more effective in preventing disease. In Europe, no study has previously looked at the association between neighborhood deprivation and participation in a population-based health check. The study population comprised 12,768 persons invited for a health check including screening for ischemic heart disease and lifestyle counseling. The study population was randomly drawn from a population of 179,097 persons living in 73 neighborhoods in Denmark. Data on neighborhood deprivation (percentage with basic education, with low income and not in work) and individual socioeconomic position were retrieved from national administrative registers. Multilevel regression analyses with log links and binary distributions were conducted to obtain relative risks, intraclass correlation coefficients and proportional change in variance. Large differences between neighborhoods existed in both deprivation levels and neighborhood health check participation rate (mean 53%; range 35-84%). In multilevel analyses adjusted for age and sex, higher levels of all three indicators of neighborhood deprivation and a deprivation score were associated with lower participation in a dose-response fashion. Persons living in the most deprived neighborhoods had up to 37% decreased probability of participating compared to those living in the least deprived neighborhoods. Inclusion of individual socioeconomic position in the model attenuated the neighborhood deprivation coefficients, but all except for income deprivation remained statistically significant. Neighborhood deprivation was associated with participation in a population-based health check in a dose-response manner, in which increasing neighborhood deprivation was associated with decreasing participation. This suggests the need to develop preventive health checks tailored to deprived neighborhoods.

Patient-reported safety incidents in older patients with long-term conditions: a large cross-sectional study

PubMed Central

Panagioti, Maria; Blakeman, Thomas; Hann, Mark; Bower, Peter

2017-01-01

Background Increasing evidence suggests that patient safety is a serious concern for older patients with long-term conditions. Despite this, there is a lack of research on safety incidents encountered by this patient group. In this study, we sought to examine patient reports of safety incidents and factors associated with reports of safety incidents in older patients with long-term conditions. Methods The baseline cross-sectional data from a longitudinal cohort study were analysed. Older patients (n=3378 aged 65 years and over) with a long-term condition registered in general practices were included in the study. The main outcome was patient-reported safety incidents including availability and appropriateness of medical tests and prescription of wrong types or doses of medication. Binary univariate and multivariate logistic regression analyses were undertaken to examine factors associated with patient-reported safety incidents. Results Safety incidents were reported by 11% of the patients. Four factors were significantly associated with patient-reported safety incidents in multivariate analyses. The experience of multiple long-term conditions (OR=1.09, 95% CI 1.05 to 1.13), a probable diagnosis of depression (OR=1.36, 95% CI 1.06 to 1.74) and greater relational continuity of care (OR=1.28, 95% CI 1.08 to 1.52) were associated with increased odds for patient-reported safety incidents. Perceived greater support and involvement in self-management was associated with lower odds for patient-reported safety incidents (OR=0.95, 95% CI 0.93 to 0.97). Conclusions We found that older patients with multimorbidity and depression are more likely to report experiences of patient safety incidents. Improving perceived support and involvement of patients in their care may help prevent patient-reported safety incidents. PMID:28559454

Retrospective Analysis of Radiological Recurrence Patterns in Glioblastoma, Their Prognostic Value And Association to Postoperative Infarct Volume.

PubMed

Bette, Stefanie; Barz, Melanie; Huber, Thomas; Straube, Christoph; Schmidt-Graf, Friederike; Combs, Stephanie E; Delbridge, Claire; Gerhardt, Julia; Zimmer, Claus; Meyer, Bernhard; Kirschke, Jan S; Boeckh-Behrens, Tobias; Wiestler, Benedikt; Gempt, Jens

2018-03-14

Recent studies suggested that postoperative hypoxia might trigger invasive tumor growth, resulting in diffuse/multifocal recurrence patterns. Aim of this study was to analyze distinct recurrence patterns and their association to postoperative infarct volume and outcome. 526 consecutive glioblastoma patients were analyzed, of which 129 met our inclusion criteria: initial tumor diagnosis, surgery, postoperative diffusion-weighted imaging and tumor recurrence during follow-up. Distinct patterns of contrast-enhancement at initial diagnosis and at first tumor recurrence (multifocal growth/progression, contact to dura/ventricle, ependymal spread, local/distant recurrence) were recorded by two blinded neuroradiologists. The association of radiological patterns to survival and postoperative infarct volume was analyzed by uni-/multivariate survival analyses and binary logistic regression analysis. With increasing postoperative infarct volume, patients were significantly more likely to develop multifocal recurrence, recurrence with contact to ventricle and contact to dura. Patients with multifocal recurrence (Hazard Ratio (HR) 1.99, P = 0.010) had significantly shorter OS, patients with recurrent tumor with contact to ventricle (HR 1.85, P = 0.036), ependymal spread (HR 2.97, P = 0.004) and distant recurrence (HR 1.75, P = 0.019) significantly shorter post-progression survival in multivariate analyses including well-established prognostic factors like age, Karnofsky Performance Score (KPS), therapy, extent of resection and patterns of primary tumors. Postoperative infarct volume might initiate hypoxia-mediated aggressive tumor growth resulting in multifocal and diffuse recurrence patterns and impaired survival.

Bullying as a Stressor in Mid-Adolescent Girls and Boys-Associations with Perceived Stress, Recurrent Pain, and Salivary Cortisol.

PubMed

Östberg, Viveca; Låftman, Sara B; Modin, Bitte; Lindfors, Petra

2018-02-20

Bullying involves repeated exposure to negative actions while also invoking a power asymmetry between the involved parties. From a stress perspective, being bullied can be seen as a severe and chronic stressor, and an everyday social-evaluative threat, coupled with a shortage of effective social resources for dealing with this particular stressor. The aim of this study was to investigate whether exposure to bullying among mid-adolescent girls and boys is associated with subjective and objective stress-related outcomes in terms of perceived stress, recurrent pain, and salivary cortisol. The data came from the School Stress and Support Study (TriSSS) including students in grades 8-9 in two schools in Stockholm, Sweden, in 2010 (study sample n = 392; cortisol subsample n = 198). Bullying was self-reported and measured by multiple items. The statistical analyses included binary logistic and linear (OLS) regression. Being bullied was associated with greater perceived stress and an increased risk of recurrent pain, among both boys and girls. Also, bullied students had lower cortisol output (AUC G ) and lower cortisol awakening response (CAR G ) as compared to those who were not bullied. Gender-stratified analyses demonstrated that these associations were statistically significant for boys but not for girls. In conclusion, this study demonstrated that being bullied was related to both subjective and objective stress markers among mid-adolescent girls and boys, pointing to the necessity of continuously working against bullying.

The Impact of Adherence and Instillation Proficiency of Topical Glaucoma Medications on Intraocular Pressure

PubMed Central

Shibeshi, Workineh; T. Giorgis, Abeba; Asgedom, Solomon Weldegebreal

2017-01-01

Background The possible sequel of poorly controlled intraocular pressure (IOP) includes treatment failure, unnecessary medication use, and economic burden on patients with glaucoma. Objective To assess the impact of adherence and instillation technique on IOP control. Methods A cross-sectional study was conducted on 359 glaucoma patients in Menelik II Hospital from June 1 to July 31, 2015. After conducting a Q-Q analysis, multiple binary logistic analyses, linear regression analyses, and two-tailed paired t-test were conducted to compare IOP in the baseline versus current measurements. Results Intraocular pressure was controlled in 59.6% of the patients and was relatively well controlled during the study period (mean (M) = 17.911 mmHg, standard deviation (S) = 0.323) compared to the baseline (M = 20.866 mmHg, S = 0.383, t (358) = −6.70, p < 0.0001). A unit increase in the administration technique score resulted in a 0.272 mmHg decrease in IOP (p = 0.03). Moreover, primary angle-closure glaucoma (adjusted odds ratio (AOR) = 0.347, 95% confidence interval (CI): 0.144–0.836) and two medications (AOR = 1.869, 95% CI: 1.259–9.379) were factors affecting IOP. Conclusion Good instillation technique of the medications was correlated with a reduction in IOP. Consequently, regular assessment of the instillation technique and IOP should be done for better management of the disease. PMID:29104803

Photometric Analyses of the Short-Period Contact Binaries HY Pavonis, AW Virginis, and BP Velorum

NASA Astrophysics Data System (ADS)

Lapasset, Emilio; Gomez, Mercedes; Farinas, Raul

1996-04-01

We present BV light curve synthetic analyses of three short period contact (W UMa) binaries: HY Pavonis (P ~0.35 days), AW Virginis (P ~0.35 days), and BP Velorum (P ~0.26 days). Different possible configurations for a wide range of the mass ratio were explored in each case making use of the Wilson-Divinney code. The photometric parameters of the systems were determined from the synthetic light curve solutions that best fit the observations. AW Vir has two components of very similar temperatures and therefore the subtype (A or W) remains undetermined. HY Pav and BP Vel are best modeled by W-type configurations and the asymmetries in the light curves are reproduced by introducing cool spots on the more massive secondary components. Even when BP Vel lies in the region of the open cluster Cr 173, its distance modulus, in principle, rules it out as a cluster member. (SECTION: Stars)

Three quantitative approaches to the diagnosis of abdominal pain in children: practical applications of decision theory.

PubMed

Klein, M D; Rabbani, A B; Rood, K D; Durham, T; Rosenberg, N M; Bahr, M J; Thomas, R L; Langenburg, S E; Kuhns, L R

2001-09-01

The authors compared 3 quantitative methods for assisting clinicians in the differential diagnosis of abdominal pain in children, where the most common important endpoint is whether the patient has appendicitis. Pretest probability in different age and sex groups were determined to perform Bayesian analysis, binary logistic regression was used to determine which variables were statistically significantly likely to contribute to a diagnosis, and recursive partitioning was used to build decision trees with quantitative endpoints. The records of all children (1,208) seen at a large urban emergency department (ED) with a chief complaint of abdominal pain were immediately reviewed retrospectively (24 to 72 hours after the encounter). Attempts were made to contact all the patients' families to determine an accurate final diagnosis. A total of 1,008 (83%) families were contacted. Data were analyzed by calculation of the posttest probability, recursive partitioning, and binary logistic regression. In all groups the most common diagnosis was abdominal pain (ICD-9 Code 789). After this, however, the order of the most common final diagnoses for abdominal pain varied significantly. The entire group had a pretest probability of appendicitis of 0.06. This varied with age and sex from 0.02 in boys 2 to 5 years old to 0.16 in boys older than 12 years. In boys age 5 to 12, recursive partitioning and binary logistic regression agreed on guarding and anorexia as important variables. Guarding and tenderness were important in girls age 5 to 12. In boys age greater than 12, both agreed on guarding and anorexia. Using sensitivities and specificities from the literature, computed tomography improved the posttest probability for the group from.06 to.33; ultrasound improved it from.06 to.48; and barium enema improved it from.06 to.58. Knowing the pretest probabilities in a specific population allows the physician to evaluate the likely diagnoses first. Other quantitative methods can help judge how much importance a certain criterion should have in the decision making and how much a particular test is likely to influence the probability of a correct diagnosis. It now should be possible to make these sophisticated quantitative methods readily available to clinicians via the computer. Copyright 2001 by W.B. Saunders Company.

Use of conservative and surgical foot care in an inception cohort of patients with rheumatoid arthritis

PubMed Central

Keenan, Anne-Maree; Hensor, Elizabeth M. A.; Young, Adam; James, David; Dixey, Josh; Williams, Peter; Prouse, Peter; Gough, Andrew; Helliwell, Philip S.; Redmond, Anthony C.

2011-01-01

Objectives. To describe conservative and surgical foot care in patients with RA in England and explore factors that predict the type of foot care received. Methods. Use of podiatry and type of foot surgery were outcomes recorded in an inception cohort involving nine rheumatology centres that recruited patients with RA between 1986 and 1998 across England. Associations between patient-specific factors and service use were identified using univariate logistic regression analyses. The independence of these associations was then verified through multiple binary logistic regression modelling. Results. Data were collected on 1237 patients with RA [66.9% females, mean (s.d.) age at disease onset = 54.36 (14.18) years, median DAS = 4.09 (1st quartile = 3.04, 3rd quartile = 5.26), median HAQ = 1 (0.50, 1.63)]. Interventions involving the feet in the cohort were low with only 364 (30%) out of 1218 receiving podiatry and 47 (4%) out of 1237 patients having surgery. At baseline, female gender, increasing age at onset, being RF positive and higher DAS scores were each independently associated with increased odds of seeing a podiatrist. Gender, age of onset and baseline DAS were independently associated with the odds of having foot surgery. Conclusions. Despite the known high prevalence of foot pathologies in RA, only one-third of this cohort accessed podiatry. While older females were more likely to access podiatry care and younger patients surgery, the majority of the RA population did not access any foot care. PMID:21504991

Use of Multiple Regression and Use-Availability Analyses in Determining Habitat Selection by Gray Squirrels (Sciurus Carolinensis)

Treesearch

John W. Edwards; Susan C. Loeb; David C. Guynn

1994-01-01

Multiple regression and use-availability analyses are two methods for examining habitat selection. Use-availability analysis is commonly used to evaluate macrohabitat selection whereas multiple regression analysis can be used to determine microhabitat selection. We compared these techniques using behavioral observations (n = 5534) and telemetry locations (n = 2089) of...

Burnout syndrome in nurses working in palliative care units: An analysis of associated factors.

PubMed

Rizo-Baeza, Mercedes; Mendiola-Infante, Susana Virginia; Sepehri, Armina; Palazón-Bru, Antonio; Gil-Guillén, Vicente Francisco; Cortés-Castell, Ernesto

2018-01-01

To analyse the association between psychological, labour and demographic factors and burnout in palliative care nursing. There is a lack of published research evaluating burnout in palliative care nursing. This observational cross-sectional study involved 185 palliative care nurses in Mexico. The primary variables were burnout defined by its three dimensions (emotional exhaustion, depersonalization and personal accomplishment). As secondary variables, psychological, labour and demographic factors were considered. A binary logistic regression model was constructed to determine factors associated with burnout. A total of 69 nurses experienced high emotional exhaustion (37.3%), 65 had high depersonalization (35.1%) and 70 had low personal performance (37.8%). A higher proportion of burnout was found in the participants who were single parents, working >8 hr per day, with a medium/high workload, a lack of a high professional quality of life and a self-care deficit. Our multivariate models were very accurate in explaining burnout in palliative care nurses. These models must be externally validated to predict burnout and prevent future complications of the syndrome accurately. Nurses who present the factors found should be the focus of interventions to reduce work stress. © 2017 John Wiley & Sons Ltd.

Factors Influencing Farmers' Willingness to Participate in the Conversion of Cultivated Land to Wetland Program in Sanjiang National Nature Reserve, China

NASA Astrophysics Data System (ADS)

Zhang, Chunli; Robinson, Daniel; Wang, Jing; Liu, Jibin; Liu, Xiaohui; Tong, Lianjun

2011-01-01

Sanjiang National Nature Reserve (NNR) is a state-owned natural wetland in China that has suffered severe degradation due to cultivation and wetland reclamation by farmers. As a consequence, the conversion of cultivated land to wetlands (CCW) was proposed by the government of Heilongjiang province and the United Nations Development Programme/Global Environment Facility (UNDP/GEF) project team in 2007. We suggest that voluntary participation in the CCW could be an important tool for accomplishing the integrated objectives of wetland conservation and local development. The purpose of this study was to examine the main factors that influence farmers' willingness to participate in the CCW through a field investigation and a questionnaire. Based on the data from our questionnaire, which provided an effective sample of 310 households in 11 villages, the influencing factors of farmers' willingness to participate were analyzed through binary logistic regression analyses. It was concluded that age, education, the amount of cultivated land, geographical location, and the perceived benefits and risks were important factors for participation. Furthermore, suggestions for improving the wetland compensation system and providing alternative livelihoods are proposed to strengthen participation.

School Collective Efficacy and Bullying Behaviour: A Multilevel Study.

PubMed

Olsson, Gabriella; Låftman, Sara Brolin; Modin, Bitte

2017-12-20

As with other forms of violent behaviour, bullying is the result of multiple influences acting on different societal levels. Yet the majority of studies on bullying focus primarily on the characteristics of individual bullies and bullied. Fewer studies have explored how the characteristics of central contexts in young people's lives are related to bullying behaviour over and above the influence of individual-level characteristics. This study explores how teacher-rated school collective efficacy is related to student-reported bullying behaviour (traditional and cyberbullying victimization and perpetration). A central focus is to explore if school collective efficacy is related similarly to both traditional bullying and cyberbullying. Analyses are based on combined information from two independent data collections conducted in 2016 among 11th grade students ( n = 6067) and teachers ( n = 1251) in 58 upper secondary schools in Stockholm. The statistical method used is multilevel modelling, estimating two-level binary logistic regression models. The results demonstrate statistically significant between-school differences in all outcomes, except traditional bullying perpetration. Strong school collective efficacy is related to less traditional bullying perpetration and less cyberbullying victimization and perpetration, indicating that collective norm regulation and school social cohesion may contribute to reducing the occurrence of bullying.

School Collective Efficacy and Bullying Behaviour: A Multilevel Study

PubMed Central

Olsson, Gabriella; Låftman, Sara Brolin; Modin, Bitte

2017-01-01

As with other forms of violent behaviour, bullying is the result of multiple influences acting on different societal levels. Yet the majority of studies on bullying focus primarily on the characteristics of individual bullies and bullied. Fewer studies have explored how the characteristics of central contexts in young people’s lives are related to bullying behaviour over and above the influence of individual-level characteristics. This study explores how teacher-rated school collective efficacy is related to student-reported bullying behaviour (traditional and cyberbullying victimization and perpetration). A central focus is to explore if school collective efficacy is related similarly to both traditional bullying and cyberbullying. Analyses are based on combined information from two independent data collections conducted in 2016 among 11th grade students (n = 6067) and teachers (n = 1251) in 58 upper secondary schools in Stockholm. The statistical method used is multilevel modelling, estimating two-level binary logistic regression models. The results demonstrate statistically significant between-school differences in all outcomes, except traditional bullying perpetration. Strong school collective efficacy is related to less traditional bullying perpetration and less cyberbullying victimization and perpetration, indicating that collective norm regulation and school social cohesion may contribute to reducing the occurrence of bullying. PMID:29261114

Mobility one week after a hip fracture - can it be predicted?

PubMed

Fitzgerald, Michelle; Blake, Catherine; Askin, David; Quinlan, John; Coughlan, Tara; Cunningham, Caitriona

2018-05-01

Better patient outcomes and more efficient healthcare could be achieved by predicting post hip fracture function at an early stage. This study aimed to identify independent predictors of mobility outcome one week post hip fracture surgery. All hip fracture inpatients (n=77) were included in this 6 month prospective observational cohort study. Predictor variables were obtained on the first postoperative day and included premorbid function using the New Mobility Score (NMS). Mobility outcome measures one week postoperatively included the Cumulated Ambulatory Score (CAS). Data were analysed with SPSS using binary multiple logistic regression analysis RESULTS: Patients who fell outdoors (OR 3.848; 95% CI, 1.053-14.061), had no delay to surgery (OR 5.472; 95% CI, 1.073-27.907) and had high pre-fracture function (OR3.366; 95% CI, 1.042-10.879) were predicted to achieve independent mobility (CAS = 6) one week postoperatively. Fall location, time to surgery and baseline function predict independent mobility one week after hip fracture, and can be used for early rehabilitation stratification. The NMS and CAS are recommended as standardised hip fracture clinical measures. Orthogeriatric and physiotherapy service initiatives may improve early functional outcome. Copyright © 2017. Published by Elsevier Ltd.

Relationship between lifestyle choices and hyperuricemia in Chinese men and women.

PubMed

Liu, Li; Lou, Shanshan; Xu, Ke; Meng, Zhaowei; Zhang, Qing; Song, Kun

2013-02-01

We aimed to explore correlations between lifestyle choices and hyperuricemia in a large Chinese population, emphasizing the differences from opposite sex. Ten thousand four hundred fifty subjects were randomly recruited from Tianjin municipality in China. Hyperuricemia was defined as serum uric acid >420 μmol/L for men and >360 μmol/L for women. Demographic data, highest education degree, work type, commuting means, smoking and drinking status, exercise frequency, and quantitative assessments of dietary factors were collected. Anthropometric measurements and fasting blood tests were performed. Statistical analyses were conducted. Total hyperuricemic prevalence was 12.89 %, with male significantly higher than female. Body mass index, waist circumference, serum indices, and age displayed high correlation coefficients, and most lifestyle factors also showed significant correlations as well. Binary logistic regression models showed odds ratio of developing hyperuricemia were much greater in males than in females by eating habits. However, physical activity-related lifestyle choices tended to cast much greater influences on the likelihood of hyperuricemia in females. Lifestyle choices and hyperuricemia are closely related. For males, eating habits have greater influences on the likelihood of developing hyperuricemia. For females, lifestyle factors like work type, commuting method, and exercise have such effects.

How adolescent subjective health and satisfaction with weight and body shape are related to participation in sports.

PubMed

Dyremyhr, Ase Eriksen; Diaz, Esperanza; Meland, Eivind

2014-01-01

Physical exercise has positive effects on health. However, its associations with self-rated health and body image, which are important predictors for adolescents' wellbeing and later morbidity, are complex. Cross-sectional survey among 2527 Norwegian adolescents. We examined the relations between self-reported gender, body size, amount and type of exercise and measures of self-rated health, drive for thinness, and desire to change body, with binary logistic regression analyses. Girls and overweight students reported to a greater extent than their peers impaired self-rated health, weight concerns, and desire to change their body. Increasing amount of time spent on sports was related to improved self-rated health in a dose-response manner. Both girls and boys who engaged in individual sports with an advantage of leanness, but only girls engaged in team sports, reported an increased desire to change the body. However, weight concern was not related to amount or type of sports. Physical exercise is positively related to self-reported health but has negative associations with body image for many adolescents. Health promotion efforts should consider this paradox and stimulate physical activity and sports along with body acceptance.

Linking Syndemic Stress and Behavioral Indicators of Main Partner HIV Transmission Risk in Gay Male Couples.

PubMed

Starks, Tyrel J; Tuck, Andrew N; Millar, Brett M; Parsons, Jeffrey T

2016-02-01

The purpose of the current study was to examine whether syndemic stress in partnered gay men might undermine communication processes essential to the utilization of negotiated safety and other harm reduction strategies that rely on partners' HIV status disclosure. Participants included 100 gay male couples (N = 200 individuals) living in the U.S., who responded to an online survey. Participants completed measures of five syndemic factors (depression, poly-drug use, childhood sexual abuse, intimate partner violence, and sexual compulsivity). They also reported on whether condoms were used during first intercourse together and the timing of first condomless anal intercourse (CAI) relative to HIV disclosure in their relationship. Results of binary logistic regression analyses supported the hypothesis that the sum of partners' syndemic stress was negatively associated with condom use at first intercourse and with HIV disclosure prior to first CAI. Syndemic stress may contribute to HIV transmission risk between main partners in part because it accelerates the progression to CAI and interferes with communication processes central to harm reduction strategies utilized by gay men in relationships. Implications for prevention strategies and couples interventions, such as couples HIV counseling and testing, that facilitate communication skill-building, are discussed.

Health insurance subscription among women in reproductive age in Ghana: do socio-demographics matter?

PubMed

Amu, Hubert; Dickson, Kwamena Sekyi

2016-12-01

Premised that health insurance schemes in Africa have only been introduced recently and continue evolving, various concerns have been raised regarding their effectiveness in improving utilisation of orthodox health care and the reduction of out-of-pocket expenditures for their population, particularly women. To examine the effects of socio-demographics on health insurance subscription among women in Ghana. The study draws on the 2014 Ghana Demographic and Health Survey. Bivariate descriptive analysis and binary logistic regression were used to analyse the data. Wealth status, age, religion, birth parity, marriage and ecological zone were found to have significantly predicted health insurance subscription among women in reproductive age in Ghana. Urban dwellers, women who are nulliparous, those with no or low levels of education, African traditionalists and the poor were those who largely did not subscribe to the scheme. The findings underscore the need for the National Health Insurance Authority to carry out more education in association with the National Commission for Civic Education and the Information Services Department to recruit more urban dwellers, nulliparous women, those with no or low levels of education, African traditionalists and the poor unto the scheme.

An analysis of lethal and sublethal interactions among type I and type II pyrethroid pesticide mixtures using standard Hyalella azteca water column toxicity tests.

PubMed

Hoffmann, Krista Callinan; Deanovic, Linda; Werner, Inge; Stillway, Marie; Fong, Stephanie; Teh, Swee

2016-10-01

A novel 2-tiered analytical approach was used to characterize and quantify interactions between type I and type II pyrethroids in Hyalella azteca using standardized water column toxicity tests. Bifenthrin, permethrin, cyfluthrin, and lambda-cyhalothrin were tested in all possible binary combinations across 6 experiments. All mixtures were analyzed for 4-d lethality, and 2 of the 6 mixtures (permethrin-bifenthrin and permethrin-cyfluthrin) were tested for subchronic 10-d lethality and sublethal effects on swimming motility and growth. Mixtures were initially analyzed for interactions using regression analyses, and subsequently compared with the additive models of concentration addition and independent action to further characterize mixture responses. Negative interactions (antagonistic) were significant in 2 of the 6 mixtures tested, including cyfluthrin-bifenthrin and cyfluthrin-permethrin, but only on the acute 4-d lethality endpoint. In both cases mixture responses fell between the additive models of concentration addition and independent action. All other mixtures were additive across 4-d lethality, and bifenthrin-permethrin and cyfluthrin-permethrin were also additive in terms of subchronic 10-d lethality and sublethal responses. Environ Toxicol Chem 2016;35:2542-2549. © 2016 SETAC. © 2016 SETAC.

Linking syndemic stress and behavioral indicators of main partner HIV transmission risk in gay male couples

PubMed Central

Starks, Tyrel J.; Tuck, Andrew N.; Millar, Brett M.; Parsons, Jeffrey T.

2016-01-01

The purpose of the current study was to examine whether syndemic stress in partnered gay men might undermine communication processes essential to the utilization of negotiated safety and other harm reduction strategies that rely on partners’ HIV status disclosure. Participants included 100 gay male couples (N = 200 individuals) living in the U.S., who responded to an online survey. Participants completed measures of five syndemic factors (depression, poly-drug use, childhood sexual abuse, intimate partner violence, and sexual compulsivity). They also reported on whether condoms were used during first intercourse together and the timing of first condomless anal intercourse (CAI) relative to HIV disclosure in their relationship. Results of binary logistic regression analyses supported the hypothesis that the sum of partners’ syndemic stress was negatively associated with condom use at first intercourse and with HIV disclosure prior to first CAI. Syndemic stress may contribute to HIV transmission risk between main partners in part because it accelerates the progression to CAI and interferes with communication processes central to harm reduction strategies utilized by gay men in relationships. Implications for prevention strategies and couples interventions, such as couples HIV counseling and testing, that facilitate communication skill-building, are discussed. PMID:26552658

[Day hospitals--predictors for utilisation and quality expectations from the perspective of family caregivers of dementia patients].

PubMed

Donath, Carolin; Bleich, Stefan; Grässel, Elmar

2009-05-01

To relieve the burden on family caregivers of dementia patients, the utilisation of day hospitals should be increased. Therefore, the predictive variables for utilisation as well as family caregivers' views regarding the quality of day hospitals must be investigated. The cross-sectional study was carried out as an anonymous, written survey of family caregivers of dementia patients in four regions of Germany. Quantitative and qualitative data from 404 family caregivers was analysed using binary logistic regression analysis and qualitative content analysis, respectively. In addition, 11 day hospital managers were interviewed concerning their quality concepts. The only significant predictor for the utilisation of day hospitals is the estimate of how helpful this support is for the family caregiver's situation. Those who have already had experiences with a day hospital expressed a wish for medical and psychiatric care by "well-trained" staff and a reasonable form of occupation for the dementia patient. In order to increase utilisation, family caregivers must be convinced of the advantages of using day hospitals. A day hospital that combines both activating occupational therapy and medical care by well-trained staff is what family caregivers wish most for their care-receivers.

Maternal dietary diversity and odds of low birth weight: empirical findings from India.

PubMed

Rammohan, Anu; Goli, Srinivas; Singh, Deepti; Ganguly, Dibyasree; Singh, Uma

2018-06-19

India has the highest proportion of low birth weight (LBW) babies born in the developing world. Poor maternal nutrition during pregnancy is associated with adverse infant health outcomes. The main objective of this paper was to assess the socioeconomic factors associated with dietary diversity among pregnant women and to investigate the association between maternal dietary diversity and LBW among their babies. The data for these analyses were derived from a survey conducted in November and December, 2014 among 230 women who had newly delivered in hospitals in Uttar Pradesh, the largest Indian state which has the poorest maternal outcomes in the country. The results from multivariate binary logistic regression model indicated that low maternal education and economic status was significantly associated with poor dietary diversity among participants. Also, women with low maternal dietary diversity had a significantly higher proportion of LBW babies compared to those in the medium to high dietary diversity categories. From a policy perspective, these findings suggest that continuous tracking of pregnant women's nutritional needs through existing monitoring systems, e.g., the Nutrition Resource Platform and Health Management Information System, and necessary interventions through Integrated Child Development Services may yield better results, thereby, addressing maternal under-nutrition and LBW.

Factors Influencing Consumer Purchase Decisions for Health-Promoting Goods and Services in Malaysia

PubMed Central

CHEAH, Yong Kang

2014-01-01

Background: In the context of global increases in the prevalence of non-communicable diseases, the objective of the present study is to investigate the factors affecting individuals’ decisions to use health-promoting goods and services. Methods: The Third National Health and Morbidity Survey (NHMS III), consisting of 30992 respondents, was analysed. The Pearson chi-square test was applied to compare the distribution of categorical variables. A binary logistic regression model was used to assess the likelihood of using health-promoting goods and services. Results: Age, income, gender, ethnicity, education, marital status, location of residence, job characteristics, and being diagnosed with hypercholesterolemia were significantly associated with use of health-promoting goods and services. In contrast, young individuals, low income earners, males, Indians and others, the less-educated, single individuals, rural dwellers, the unemployed and individuals with hypercholesterolemia were less likely to use health-promoting goods and services than others. Conclusion: Socio-demographic and health factors played an important role in affecting the use of health-promoting goods and services. Based on these factors, several intervention measures with the intent of increasing the use of health-promoting goods and services were suggested, if only applicable to Malaysians. PMID:25897281

Factors associated with adult poisoning in northern Malaysia: a case-control study.

PubMed

Fathelrahman, A I; Ab Rahman, A F; Zain, Z Mohd; Tengku, M A

2006-04-01

Data on adult risk factors associated with drug or chemical poisonings in Malaysia are scarce. The objective of the study was to identify possible risk factors associated with adult admissions to the Penang General Hospital (PGH) due to chemical poisoning and/or drug overdose. The present study was a case-control study, conducted over 18 weeks. One hundred acutely poisoned adult patients admitted to PGH during the period from September 2003 to February 2004 were considered as cases. Two hundred patients admitted to the same medical wards for other illnesses, during the same period, were matched for age and gender with the poisoned cases and thus selected as controls. McNemar test and binary logistic were used for univariate analysis and logistic regression analysis for multivariate analyses. The odds ratio (OR) and its 95% confidence interval (95% CI) were calculated for each predictor variable. Positive histories of psychiatric illness and previous poisoning, problems in boy/girl friend relationships, family problems, marital problems, Indian ethnicity, Chinese ethnicity, living in rented houses and living in a household with less than five people were significant risk factors associated with adult admissions due to poisoning.

Pre-treatment plasma proteomic markers associated with survival in oesophageal cancer

PubMed Central

Kelly, P; Paulin, F; Lamont, D; Baker, L; Clearly, S; Exon, D; Thompson, A

2012-01-01

Background: The incidence of oesophageal adenocarcinoma is increasing worldwide but survival remains poor. Neoadjuvant chemotherapy can improve survival, but prognostic and predictive biomarkers are required. This study built upon preclinical approaches to identify prognostic plasma proteomic markers in oesophageal cancer. Methods: Plasma samples collected before and during the treatment of oesophageal cancer and non-cancer controls were analysed by surface-enhanced laser desorption/ionisation time-of-flight (SELDI-TOF) mass spectroscopy (MS). Protein peaks were identified by MS in tryptic digests of purified fractions. Associations between peak intensities obtained in the spectra and clinical endpoints (survival, disease-free survival) were tested by univariate (Fisher's exact test) and multivariate analysis (binary logistic regression). Results: Plasma protein peaks were identified that differed significantly (P<0.05, ANOVA) between the oesophageal cancer and control groups at baseline. Three peaks, confirmed as apolipoprotein A-I, serum amyloid A and transthyretin, in baseline (pre-treatment) samples were associated by univariate and multivariate analysis with disease-free survival and overall survival. Conclusion: Plasma proteins can be detected prior to treatment for oesophageal cancer that are associated with outcome and merit testing as prognostic and predictive markers of response to guide chemotherapy in oesophageal cancer. PMID:22294182

Pre-treatment plasma proteomic markers associated with survival in oesophageal cancer.

PubMed

Kelly, P; Paulin, F; Lamont, D; Baker, L; Clearly, S; Exon, D; Thompson, A

2012-02-28

The incidence of oesophageal adenocarcinoma is increasing worldwide but survival remains poor. Neoadjuvant chemotherapy can improve survival, but prognostic and predictive biomarkers are required. This study built upon preclinical approaches to identify prognostic plasma proteomic markers in oesophageal cancer. Plasma samples collected before and during the treatment of oesophageal cancer and non-cancer controls were analysed by surface-enhanced laser desorption/ionisation time-of-flight (SELDI-TOF) mass spectroscopy (MS). Protein peaks were identified by MS in tryptic digests of purified fractions. Associations between peak intensities obtained in the spectra and clinical endpoints (survival, disease-free survival) were tested by univariate (Fisher's exact test) and multivariate analysis (binary logistic regression). Plasma protein peaks were identified that differed significantly (P<0.05, ANOVA) between the oesophageal cancer and control groups at baseline. Three peaks, confirmed as apolipoprotein A-I, serum amyloid A and transthyretin, in baseline (pre-treatment) samples were associated by univariate and multivariate analysis with disease-free survival and overall survival. Plasma proteins can be detected prior to treatment for oesophageal cancer that are associated with outcome and merit testing as prognostic and predictive markers of response to guide chemotherapy in oesophageal cancer.

Predicting binary, discrete and continued lncRNA-disease associations via a unified framework based on graph regression.

PubMed

Shi, Jian-Yu; Huang, Hua; Zhang, Yan-Ning; Long, Yu-Xi; Yiu, Siu-Ming

2017-12-21

In human genomes, long non-coding RNAs (lncRNAs) have attracted more and more attention because their dysfunctions are involved in many diseases. However, the associations between lncRNAs and diseases (LDA) still remain unknown in most cases. While identifying disease-related lncRNAs in vivo is costly, computational approaches are promising to not only accelerate the possible identification of associations but also provide clues on the underlying mechanism of various lncRNA-caused diseases. Former computational approaches usually only focus on predicting new associations between lncRNAs having known associations with diseases and other lncRNA-associated diseases. They also only work on binary lncRNA-disease associations (whether the pair has an association or not), which cannot reflect and reveal other biological facts, such as the number of proteins involved in LDA or how strong the association is (i.e., the intensity of LDA). To address abovementioned issues, we propose a graph regression-based unified framework (GRUF). In particular, our method can work on lncRNAs, which have no previously known disease association and diseases that have no known association with any lncRNAs. Also, instead of only a binary answer for the association, our method tries to uncover more biological relationship between a pair of lncRNA and disease, which may provide better clues for researchers. We compared GRUF with three state-of-the-art approaches and demonstrated the superiority of GRUF, which achieves 5%~16% improvement in terms of the area under the receiver operating characteristic curve (AUC). GRUF also provides a predicted confidence score for the predicted LDA, which reveals the significant correlation between the score and the number of RNA-Binding Proteins involved in LDAs. Lastly, three out of top-5 LDA candidates generated by GRUF in novel prediction are verified indirectly by medical literature and known biological facts. The proposed GRUF has two advantages over existing approaches. Firstly, it can be used to work on lncRNAs that have no known disease association and diseases that have no known association with any lncRNAs. Secondly, instead of providing a binary answer (with or without association), GRUF works for both discrete and continued LDA, which help revealing the pathological implications between lncRNAs and diseases.

Classifying machinery condition using oil samples and binary logistic regression

NASA Astrophysics Data System (ADS)

Phillips, J.; Cripps, E.; Lau, John W.; Hodkiewicz, M. R.

2015-08-01

The era of big data has resulted in an explosion of condition monitoring information. The result is an increasing motivation to automate the costly and time consuming human elements involved in the classification of machine health. When working with industry it is important to build an understanding and hence some trust in the classification scheme for those who use the analysis to initiate maintenance tasks. Typically "black box" approaches such as artificial neural networks (ANN) and support vector machines (SVM) can be difficult to provide ease of interpretability. In contrast, this paper argues that logistic regression offers easy interpretability to industry experts, providing insight to the drivers of the human classification process and to the ramifications of potential misclassification. Of course, accuracy is of foremost importance in any automated classification scheme, so we also provide a comparative study based on predictive performance of logistic regression, ANN and SVM. A real world oil analysis data set from engines on mining trucks is presented and using cross-validation we demonstrate that logistic regression out-performs the ANN and SVM approaches in terms of prediction for healthy/not healthy engines.

Modeling the dynamics of urban growth using multinomial logistic regression: a case study of Jiayu County, Hubei Province, China

NASA Astrophysics Data System (ADS)

Nong, Yu; Du, Qingyun; Wang, Kun; Miao, Lei; Zhang, Weiwei

2008-10-01

Urban growth modeling, one of the most important aspects of land use and land cover change study, has attracted substantial attention because it helps to comprehend the mechanisms of land use change thus helps relevant policies made. This study applied multinomial logistic regression to model urban growth in the Jiayu county of Hubei province, China to discover the relationship between urban growth and the driving forces of which biophysical and social-economic factors are selected as independent variables. This type of regression is similar to binary logistic regression, but it is more general because the dependent variable is not restricted to two categories, as those previous studies did. The multinomial one can simulate the process of multiple land use competition between urban land, bare land, cultivated land and orchard land. Taking the land use type of Urban as reference category, parameters could be estimated with odds ratio. A probability map is generated from the model to predict where urban growth will occur as a result of the computation.

First trimester vaginal bleeding and adverse pregnancy outcomes among Chinese women: from a large cohort study in China.

PubMed

Sun, Lu; Tao, Fangbiao; Hao, Jiahu; Su, Puyu; Liu, Fang; Xu, Rong

2012-08-01

To examine the effect of first trimester vaginal bleeding on adverse pregnancy outcomes including preterm delivery, low birth weight and small for gestational age. This is a prospective population-based cohort study. A questionnaire survey was conducted on 4342 singleton pregnancies by trained doctors. Binary logistic regression was used to estimate risk ratios (RRs) and 95% confidence intervals (95% CI). Vaginal bleeding occurred among 1050 pregnant women, the incidence of vaginal bleeding was 24.2%, 37.4% of whom didn't see a doctor, 62.6% of whom saw a doctor for vaginal bleeding. Binary logistic regression demonstrated that bleeding with seeing a doctor was significantly associated with preterm birth (RR 1.84, 95% CI 1.25-2.69) and bleeding without seeing a doctor was related to increased of low birth weight (RR 2.52, 95% CI 1.34-4.75) and was 1.97-fold increased of small for gestational age (RR 1.97, 95% CI 1.19-3.25). These results suggest that first trimester vaginal bleeding is an increased risk of low birth weight, preterm delivery and small for gestational age. Find ways to reduce the risk of vaginal bleeding and lower vaginal bleeding rate may be helpful to reduce the incidence of preterm birth, low birth weight and small for gestational age.

National health insurance subscription and maternal healthcare utilisation across mothers' wealth status in Ghana.

PubMed

Ameyaw, Edward Kwabena; Kofinti, Raymond Elikplim; Appiah, Francis

2017-12-01

This study is against the backdrop that despite the forty-nine percent decline in Maternal Mortality Rate in Ghana, the situation still remains high averaging 319 per 100,000 live births between 2011 and 2015. To examine the relationship between National Health Insurance and maternal healthcare utilisation across three main wealth quintiles (Poor, Middle and Rich). The study employed data from the 2014 Ghana Demographic and Health Survey. Both descriptive analysis and binary logistic regression were conducted. Descriptively, rich women had high antenatal attendance and health facility deliveries represented by 96.5% and 95.6% respectively. However, the binary logistic regression results revealed that poor women owning NHIS are 7% (CI = 1.76-2.87) more likely to make at least four antenatal care visits compared to women in the middle wealth quintile (5%, CI = 2.12-4.76) and rich women (2%, CI = 1.14-4.14). Similarly, poor women who owned the NHIS are 14% (CI = 1.42-2.13) likely to deliver in health facility than women in the middle and rich wealth quintile. The study has vindicated the claim that NHIS Scheme is pro-poor in Ghana. The Ministry of Health should target women in the rural area to be enrolled on the NHIS to improve maternal healthcare utilisation since poverty is principally a rural phenomenon in Ghana.

Risk estimation using probability machines

PubMed Central

2014-01-01

Background Logistic regression has been the de facto, and often the only, model used in the description and analysis of relationships between a binary outcome and observed features. It is widely used to obtain the conditional probabilities of the outcome given predictors, as well as predictor effect size estimates using conditional odds ratios. Results We show how statistical learning machines for binary outcomes, provably consistent for the nonparametric regression problem, can be used to provide both consistent conditional probability estimation and conditional effect size estimates. Effect size estimates from learning machines leverage our understanding of counterfactual arguments central to the interpretation of such estimates. We show that, if the data generating model is logistic, we can recover accurate probability predictions and effect size estimates with nearly the same efficiency as a correct logistic model, both for main effects and interactions. We also propose a method using learning machines to scan for possible interaction effects quickly and efficiently. Simulations using random forest probability machines are presented. Conclusions The models we propose make no assumptions about the data structure, and capture the patterns in the data by just specifying the predictors involved and not any particular model structure. So they do not run the same risks of model mis-specification and the resultant estimation biases as a logistic model. This methodology, which we call a “risk machine”, will share properties from the statistical machine that it is derived from. PMID:24581306

Cerebrovascular risk factors for patients with cerebral watershed infarction: A case-control study based on computed tomography angiography in a population from Southwest China.

PubMed

Dong, Mei-Xue; Hu, Ling; Huang, Yuan-Jun; Xu, Xiao-Min; Liu, Yang; Wei, You-Dong

2017-07-01

To determine cerebrovascular risk factors for patients with cerebral watershed infarction (CWI) from Southwest China.Patients suffering from acute ischemic stroke were categorized into internal CWI (I-CWI), external CWI (E-CWI), or non-CWI (patients without CWI) groups. Clinical data were collected and degrees of steno-occlusion of all cerebral arteries were scored. Arteries associated with the circle of Willis were also assessed. Data were compared using Pearson chi-squared tests for categorical data and 1-way analysis of variance with Bonferroni post hoc tests for continuous data, as appropriate. Multivariate binary logistic regression analysis was performed to determine independent cerebrovascular risk factors for CWI.Compared with non-CWI, I-CWI had higher degrees of steno-occlusion of the ipsilateral middle cerebral artery, ipsilateral carotid artery, and contralateral middle cerebral artery. E-CWI showed no significant differences. All the 3 arteries were independent cerebrovascular risk factors for I-CWI confirmed by multivariate binary logistic regression analysis. I-CWI had higher degrees of steno-occlusion of the ipsilateral middle cerebral artery compared with E-CWI. No significant differences were found among arteries associated with the circle of Willis.The ipsilateral middle cerebral artery, carotid artery, and contralateral middle cerebral artery were independent cerebrovascular risk factors for I-CWI. No cerebrovascular risk factor was identified for E-CWI.

A binary logistic regression model with complex sampling design of unmet need for family planning among all women aged (15-49) in Ethiopia.

PubMed

Workie, Demeke Lakew; Zike, Dereje Tesfaye; Fenta, Haile Mekonnen; Mekonnen, Mulusew Admasu

2017-09-01

Unintended pregnancy related to unmet need is a worldwide problem that affects societies. The main objective of this study was to identify the prevalence and determinants of unmet need for family planning among women aged (15-49) in Ethiopia. The Performance Monitoring and Accountability2020/Ethiopia was conducted in April 2016 at round-4 from 7494 women with two-stage-stratified sampling. Bi-variable and multi-variable binary logistic regression model with complex sampling design was fitted. The prevalence of unmet-need for family planning was 16.2% in Ethiopia. Women between the age range of 15-24 years were 2.266 times more likely to have unmet need family planning compared to above 35 years. Women who were currently married were about 8 times more likely to have unmet need family planning compared to never married women. Women who had no under-five child were 0.125 times less likely to have unmet need family planning compared to those who had more than two-under-5. The key determinants of unmet need family planning in Ethiopia were residence, age, marital-status, education, household members, birth-events and number of under-5 children. Thus the Government of Ethiopia would take immediate steps to address the causes of high unmet need for family planning among women.

Risk estimation using probability machines.

PubMed

Dasgupta, Abhijit; Szymczak, Silke; Moore, Jason H; Bailey-Wilson, Joan E; Malley, James D

2014-03-01

Logistic regression has been the de facto, and often the only, model used in the description and analysis of relationships between a binary outcome and observed features. It is widely used to obtain the conditional probabilities of the outcome given predictors, as well as predictor effect size estimates using conditional odds ratios. We show how statistical learning machines for binary outcomes, provably consistent for the nonparametric regression problem, can be used to provide both consistent conditional probability estimation and conditional effect size estimates. Effect size estimates from learning machines leverage our understanding of counterfactual arguments central to the interpretation of such estimates. We show that, if the data generating model is logistic, we can recover accurate probability predictions and effect size estimates with nearly the same efficiency as a correct logistic model, both for main effects and interactions. We also propose a method using learning machines to scan for possible interaction effects quickly and efficiently. Simulations using random forest probability machines are presented. The models we propose make no assumptions about the data structure, and capture the patterns in the data by just specifying the predictors involved and not any particular model structure. So they do not run the same risks of model mis-specification and the resultant estimation biases as a logistic model. This methodology, which we call a "risk machine", will share properties from the statistical machine that it is derived from.

Human Epidermal Growth Factor Receptor 2 Expression in Unresectable Gastric Cancers: Relationship with CT Characteristics.

PubMed

Lee, Jeong Sub; Kim, Se Hyung; Im, Seock-Ah; Kim, Min A; Han, Joon Koo

2017-01-01

To retrospectively analyze the qualitative CT features that correlate with human epidermal growth factor receptor 2 (HER2)-expression in pathologically-proven gastric cancers. A total of 181 patients with pathologically-proven unresectable gastric cancers with HER2-expression (HER2-positive [n = 32] and negative [n = 149]) were included. CT features of primary gastric and metastatic tumors were reviewed. The prevalence of each CT finding was compared in both groups. Thereafter, binary logistic regression determined the most significant differential CT features. Clinical outcomes were compared using Kaplan-Meier method. HER2-postive cancers showed lower clinical T stage (21.9% vs. 8.1%; p = 0.015), hyperattenuation on portal phase (62.5% vs. 30.9%; p = 0.003), and was more frequently metastasized to the liver (62.5% vs. 32.2%; p = 0.001), than HER2-negative cancers. On binary regression analysis, hyperattenuation of the tumor (odds ratio [OR], 4.68; p < 0.001) and hepatic metastasis (OR, 4.43; p = 0.001) were significant independent factors that predict HER2-positive cancers. Median survival of HER2-positive cancers (13.7 months) was significantly longer than HER2-negative cancers (9.6 months) ( p = 0.035). HER2-positive gastric cancers show less-advanced T stage, hyperattenuation on the portal phase, and frequently metastasize to the liver, as compared to HER2-negative cancers.

Probing the size of extra dimensions with gravitational wave astronomy

NASA Astrophysics Data System (ADS)

Yagi, Kent; Tanahashi, Norihiro; Tanaka, Takahiro

2011-04-01

In the Randall-Sundrum II braneworld model, it has been conjectured, according to the AdS/CFT correspondence, that a brane-localized black hole (BH) larger than the bulk AdS curvature scale ℓ cannot be static, and it is dual to a four-dimensional BH emitting Hawking radiation through some quantum fields. In this scenario, the number of the quantum field species is so large that this radiation changes the orbital evolution of a BH binary. We derived the correction to the gravitational waveform phase due to this effect and estimated the upper bounds on ℓ by performing Fisher analyses. We found that the Deci-Hertz Interferometer Gravitational Wave Observatory and the Big Bang Observatory (DECIGO/BBO) can give a stronger constraint than the current tabletop result by detecting gravitational waves from small mass BH/BH and BH/neutron star (NS) binaries. Furthermore, DECIGO/BBO is expected to detect 105 BH/NS binaries per year. Taking this advantage, we find that DECIGO/BBO can actually measure ℓ down to ℓ=0.33μm for a 5 yr observation if we know that binaries are circular a priori. This is about 40 times smaller than the upper bound obtained from the tabletop experiment. On the other hand, when we take eccentricities into binary parameters, the detection limit weakens to ℓ=1.5μm due to strong degeneracies between ℓ and eccentricities. We also derived the upper bound on ℓ from the expected detection number of extreme mass ratio inspirals with LISA and BH/NS binaries with DECIGO/BBO, extending the discussion made recently by McWilliams [Phys. Rev. Lett. 104, 141601 (2010)PRLTAO0031-900710.1103/PhysRevLett.104.141601]. We found that these less robust constraints are weaker than the ones from phase differences.

Multi-epoch observations with high spatial resolution of multiple T Tauri systems

NASA Astrophysics Data System (ADS)

Csépány, Gergely; van den Ancker, Mario; Ábrahám, Péter; Köhler, Rainer; Brandner, Wolfgang; Hormuth, Felix; Hiss, Hector

2017-07-01

Context. In multiple pre-main-sequence systems the lifetime of circumstellar discs appears to be shorter than around single stars, and the actual dissipation process may depend on the binary parameters of the systems. Aims: We report high spatial resolution observations of multiple T Tauri systems at optical and infrared wavelengths. We determine whether the components are gravitationally bound and orbital motion is visible, derive orbital parameters, and investigate possible correlations between the binary parameters and disc states. Methods: We selected 18 T Tau multiple systems (16 binary and two triple systems, yielding 16 + 2 × 2 = 20 binary pairs) in the Taurus-Auriga star-forming region from a previous survey, with spectral types from K1 to M5 and separations from 0.22″ (31 AU) to 5.8″ (814 AU). We analysed data acquired in 2006-07 at Calar Alto using the AstraLux lucky imaging system, along with data from SPHERE and NACO at the VLT, and from the literature. Results: We found ten pairs to orbit each other, five pairs that may show orbital motion, and five likely common proper motion pairs. We found no obvious correlation between the stellar parameters and binary configuration. The 10 μm infra-red excess varies between 0.1 and 7.2 mag (similar to the distribution in single stars, where it is between 1.7 and 9.1), implying that the presence of the binary star does not greatly influence the emission from the inner disc. Conclusions: We have detected orbital motion in young T Tauri systems over a timescale of ≈ 20 yr. Further observations with even longer temporal baseline will provide crucial information on the dynamics of these young stellar systems.

Interactivity in Prosodic Representations in Children

ERIC Educational Resources Information Center

Goffman, Lisa; Westover, Stefanie

2013-01-01

The aim of this study was to determine, using speech error and articulatory analyses, whether the binary distinction between iambs and trochees should be extended to include additional prosodic subcategories. Adults, children who are normally developing, and children with specific language impairment (SLI) participated. Children with SLI were…

Adverse effects of maternal lead levels on birth outcomes in the ALSPAC study: a prospective birth cohort study.

PubMed

Taylor, C M; Golding, J; Emond, A M

2015-02-01

To study the associations of prenatal blood lead levels (B-Pb) with pregnancy outcomes in a large cohort of mother-child pairs in the UK. Prospective birth cohort study. Avon area of Bristol, UK. Pregnant women enrolled in the Avon Longitudinal Study of Parents and Children (ALSPAC). Whole blood samples were collected and analysed by inductively coupled plasma dynamic reaction cell mass spectrometry (n = 4285). Data collected on the infants included anthropometric variables and gestational age at delivery. Linear regression models for continuous outcomes and logistic regression models for categorical outcomes were adjusted for covariates including maternal height, smoking, parity, sex of the baby and gestational age. Birthweight, head circumference and crown-heel length, preterm delivery and low birthweight. The mean blood lead level (B-Pb) was 3.67 ± 1.47 μg/dl. B-Pb ≥ 5 μg/dl significantly increased the risk of preterm delivery (adjusted odds ratio [OR] 2.00 95% confidence interval [95% CI] 1.35-3.00) but not of having a low birthweight baby (adjusted OR 1.37, 95% CI 0.86-2.18) in multivariable binary logistic models. Increasing B-Pb was significantly associated with reductions in birth weight (β -13.23, 95% CI -23.75 to -2.70), head circumference (β -0.04, 95% CI -0.07 to -0.06) and crown-heel length (β -0.05, 95% CI -0.10 to -0.00) in multivariable linear regression models. There was evidence for adverse effects of maternal B-Pb on the incidence of preterm delivery, birthweight, head circumference and crown-heel length, but not on the incidence of low birthweight, in this group of women. © 2014 The Authors. BJOG An International Journal of Obstetrics and Gynaecology published by John Wiley & Sons Ltd on behalf of Royal College of Obstetricians and Gynaecologists.

Explaining Match Outcome During The Men’s Basketball Tournament at The Olympic Games

PubMed Central

Leicht, Anthony S.; Gómez, Miguel A.; Woods, Carl T.

2017-01-01

In preparation for the Olympics, there is a limited opportunity for coaches and athletes to interact regularly with team performance indicators providing important guidance to coaches for enhanced match success at the elite level. This study examined the relationship between match outcome and team performance indicators during men’s basketball tournaments at the Olympic Games. Twelve team performance indicators were collated from all men’s teams and matches during the basketball tournament of the 2004-2016 Olympic Games (n = 156). Linear and non-linear analyses examined the relationship between match outcome and team performance indicator characteristics; namely, binary logistic regression and a conditional interference (CI) classification tree. The most parsimonious logistic regression model retained ‘assists’, ‘defensive rebounds’, ‘field-goal percentage’, ‘fouls’, ‘fouls against’, ‘steals’ and ‘turnovers’ (delta AIC <0.01; Akaike weight = 0.28) with a classification accuracy of 85.5%. Conversely, four performance indicators were retained with the CI classification tree with an average classification accuracy of 81.4%. However, it was the combination of ‘field-goal percentage’ and ‘defensive rebounds’ that provided the greatest probability of winning (93.2%). Match outcome during the men’s basketball tournaments at the Olympic Games was identified by a unique combination of performance indicators. Despite the average model accuracy being marginally higher for the logistic regression analysis, the CI classification tree offered a greater practical utility for coaches through its resolution of non-linear phenomena to guide team success. Key points A unique combination of team performance indicators explained 93.2% of winning observations in men’s basketball at the Olympics. Monitoring of these team performance indicators may provide coaches with the capability to devise multiple game plans or strategies to enhance their likelihood of winning. Incorporation of machine learning techniques with team performance indicators may provide a valuable and strategic approach to explain patterns within multivariate datasets in sport science. PMID:29238245

Multivariate Bayesian analysis of Gaussian, right censored Gaussian, ordered categorical and binary traits using Gibbs sampling

PubMed Central

Korsgaard, Inge Riis; Lund, Mogens Sandø; Sorensen, Daniel; Gianola, Daniel; Madsen, Per; Jensen, Just

2003-01-01

A fully Bayesian analysis using Gibbs sampling and data augmentation in a multivariate model of Gaussian, right censored, and grouped Gaussian traits is described. The grouped Gaussian traits are either ordered categorical traits (with more than two categories) or binary traits, where the grouping is determined via thresholds on the underlying Gaussian scale, the liability scale. Allowances are made for unequal models, unknown covariance matrices and missing data. Having outlined the theory, strategies for implementation are reviewed. These include joint sampling of location parameters; efficient sampling from the fully conditional posterior distribution of augmented data, a multivariate truncated normal distribution; and sampling from the conditional inverse Wishart distribution, the fully conditional posterior distribution of the residual covariance matrix. Finally, a simulated dataset was analysed to illustrate the methodology. This paper concentrates on a model where residuals associated with liabilities of the binary traits are assumed to be independent. A Bayesian analysis using Gibbs sampling is outlined for the model where this assumption is relaxed. PMID:12633531

MUCHFUSS - Massive Unseen Companions to Hot Faint Underluminous Stars from SDSS

NASA Astrophysics Data System (ADS)

Geier, S.; Schaffenroth, V.; Hirsch, H.; Tillich, A.; Heber, U.; Maxted, P. F. L.; Østensen, R. H.; Barlow, B. N.; O'Toole, S. J.; Kupfer, T.; Marsh, T.; Gänsicke, B.; Napiwotzki, R.; Cordes, O.; Müller, S.; Classen, L.; Ziegerer, E.; Drechsel, H.

2012-06-01

The project Massive Unseen Companions to Hot Faint Underluminous Stars from SDSS (MUCHFUSS) aims at finding hot subdwarf stars with massive compact companions (white dwarfs with masses M>1.0 M⊙, neutron stars or black holes). The existence of such systems is predicted by binary evolution calculations and some candidate systems have been found. We identified ≃1100 hot subdwarf stars from the Sloan Digital Sky Survey (SDSS). Stars with high velocities have been reobserved and individual SDSS spectra have been analysed. About 70 radial velocity variable subdwarfs have been selected as good candidates for follow-up time resolved spectroscopy to derive orbital parameters and photometric follow-up to search for features like eclipses in the light curves. Up to now we found nine close binary sdBs with short orbital periods ranging from ≃0.07 d to 1.5 d. Two of them are eclipsing binaries with companions that are most likely of substellar nature.

Observing gravitational-wave transient GW150914 with minimal assumptions

NASA Astrophysics Data System (ADS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allocca, A.; Altin, P. A.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Arceneaux, C. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Babak, S.; Bacon, P.; Bader, M. K. M.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bavigadda, V.; Bazzan, M.; Behnke, B.; Bejger, M.; Bell, A. S.; Bell, C. J.; Berger, B. K.; Bergman, J.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Birney, R.; Biscans, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackburn, L.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, S.; Bock, O.; Bodiya, T. P.; Boer, M.; Bogaert, G.; Bogan, C.; Bohe, A.; Bojtos, P.; Bond, C.; Bondu, F.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brown, N. M.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderón Bustillo, J.; Callister, T.; Calloni, E.; Camp, J. B.; Cannon, K. C.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Casanueva Diaz, J.; Casentini, C.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Cerboni Baiardi, L.; Cerretani, G.; Cesarini, E.; Chakraborty, R.; Chatterji, S.; Chalermsongsak, T.; Chamberlin, S. J.; Chan, M.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Chen, H. Y.; Chen, Y.; Cheng, C.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, S.; Chung, S.; Ciani, G.; Clara, F.; Clark, J. A.; Clark, M.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Collette, C. G.; Cominsky, L.; Constancio, M.; Conte, A.; Conti, L.; Cook, D.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, C. A.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J.-P.; Countryman, S. T.; Couvares, P.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Craig, K.; Creighton, J. D. E.; Cripe, J.; Crowder, S. G.; Cumming, A.; Cunningham, L.; Cuoco, E.; Dal Canton, T.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Darman, N. S.; Dattilo, V.; Dave, I.; Daveloza, H. P.; Davier, M.; Davies, G. S.; Daw, E. J.; Day, R.; DeBra, D.; Debreczeni, G.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dereli, H.; Dergachev, V.; DeRosa, R. T.; De Rosa, R.; DeSalvo, R.; Dhurandhar, S.; Díaz, M. C.; Di Fiore, L.; Di Giovanni, M.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Virgilio, A.; Dojcinoski, G.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Douglas, R.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Engels, W.; Essick, R. C.; Etzel, T.; Evans, M.; Evans, T. M.; Everett, R.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.; Fang, Q.; Farinon, S.; Farr, B.; Farr, W. M.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fiorucci, D.; Fisher, R. P.; Flaminio, R.; Fletcher, M.; Fournier, J.-D.; Franco, S.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fricke, T. T.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H. A. G.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S. G.; Garufi, F.; Gatto, A.; Gaur, G.; Gehrels, N.; Gemme, G.; Gendre, B.; Genin, E.; Gennai, A.; George, J.; Gergely, L.; Germain, V.; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.; Glaefke, A.; Goetz, E.; Goetz, R.; Gondan, L.; González, G.; Gonzalez Castro, J. M.; Gopakumar, A.; Gordon, N. A.; Gorodetsky, M. L.; Gossan, S. E.; Gosselin, M.; Gouaty, R.; Graef, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Haas, R.; Hacker, J. J.; Hall, B. R.; Hall, E. D.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Hartman, M. T.; Haster, C.-J.; Haughian, K.; Healy, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hinder, I.; Hoak, D.; Hodge, K. A.; Hofman, D.; Hollitt, S. E.; Holt, K.; Holz, D. E.; Hopkins, P.; Hosken, D. J.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huang, S.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Idrisy, A.; Indik, N.; Ingram, D. R.; Inta, R.; Isa, H. N.; Isac, J.-M.; Isi, M.; Islas, G.; Isogai, T.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jang, H.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Haris, K.; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Karki, S.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kawazoe, F.; Kéfélian, F.; Kehl, M. S.; Keitel, D.; Kelley, D. B.; Kells, W.; Kennedy, R.; Key, J. S.; Khalaidovski, A.; Khalili, F. Y.; Khan, I.; Khan, S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, C.; Kim, J.; Kim, K.; Kim, Nam-Gyu; Kim, Namjun; Kim, Y.-M.; King, E. J.; King, P. J.; Kinsey, M.; Kinzel, D. L.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Koehlenbeck, S. M.; Kokeyama, K.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Kringel, V.; Królak, A.; Krueger, C.; Kuehn, G.; Kumar, P.; Kuo, L.; Kutynia, A.; Lackey, B. D.; Laguna, P.; Landry, M.; Lange, J.; Lantz, B.; Lasky, P. D.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lebigot, E. O.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Lee, K.; Lenon, A.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Levine, B. M.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Lockerbie, N. A.; Logue, J.; Lombardi, A. L.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lück, H.; Lundgren, A. P.; Luo, J.; Lynch, R.; Ma, Y.; MacDonald, T.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña-Sandoval, F.; Magee, R. M.; Mageswaran, M.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandel, I.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martin, R. M.; Martynov, D. V.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Melatos, A.; Mendell, G.; Mendoza-Gandara, D.; Mercer, R. A.; Merilh, E.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B. C.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, C. L.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Murphy, D. J.; Murray, P. G.; Mytidis, A.; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Necula, V.; Nedkova, K.; Nelemans, G.; Neri, M.; Neunzert, A.; Newton, G.; Nguyen, T. T.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; O'Shaughnessy, R.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Page, J.; Paris, H. R.; Parker, W.; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Patrick, Z.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perreca, A.; Phelps, M.; Piccinni, O.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poggiani, R.; Popolizio, P.; Post, A.; Powell, J.; Prasad, J.; Predoi, V.; Premachandra, S. S.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Qin, J.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rakhmanov, M.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Read, J.; Reed, C. M.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Ricci, F.; Riles, K.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, R.; Romanov, G.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sanchez, E. J.; Sandberg, V.; Sandeen, B.; Sanders, J. R.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Schilling, R.; Schmidt, J.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, E.; Schuette, D.; Schutz, B. F.; Scott, J.; Scott, S. M.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Serna, G.; Setyawati, Y.; Sevigny, A.; Shaddock, D. A.; Shah, S.; Shahriar, M. S.; Shaltev, M.; Shao, Z.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sigg, D.; Silva, A. D.; Simakov, D.; Singer, A.; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, J. R.; Smith, N. D.; Smith, R. J. E.; Son, E. J.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stone, R.; Strain, K. A.; Straniero, N.; Stratta, G.; Strauss, N. A.; Strigin, S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sutton, P. J.; Swinkels, B. L.; Szczepańczyk, M. J.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tápai, M.; Tarabrin, S. P.; Taracchini, A.; Taylor, R.; Theeg, T.; Thirugnanasambandam, M. P.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Tomlinson, C.; Tonelli, M.; Torres, C. V.; Torrie, C. I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trifirò, D.; Tringali, M. C.; Trozzo, L.; Tse, M.; Turconi, M.; Tuyenbayev, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; Van Den Broeck, C.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Vass, S.; Vasúth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Verkindt, D.; Vetrano, F.; Viceré, A.; Vinciguerra, S.; Vine, D. J.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, M.; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, M.; Wang, X.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.; Weßels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; White, D. J.; Whiting, B. F.; Williams, D.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Worden, J.; Wright, J. L.; Wu, G.; Yablon, J.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, H.; Yvert, M.; ZadroŻny, A.; Zangrando, L.; Zanolin, M.; Zendri, J.-P.; Zevin, M.; Zhang, F.; Zhang, L.; Zhang, M.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, X. J.; Zucker, M. E.; Zuraw, S. E.; Zweizig, J.; LIGO Scientific Collaboration; Virgo Collaboration

2016-06-01

The gravitational-wave signal GW150914 was first identified on September 14, 2015, by searches for short-duration gravitational-wave transients. These searches identify time-correlated transients in multiple detectors with minimal assumptions about the signal morphology, allowing them to be sensitive to gravitational waves emitted by a wide range of sources including binary black hole mergers. Over the observational period from September 12 to October 20, 2015, these transient searches were sensitive to binary black hole mergers similar to GW150914 to an average distance of ˜600 Mpc . In this paper, we describe the analyses that first detected GW150914 as well as the parameter estimation and waveform reconstruction techniques that initially identified GW150914 as the merger of two black holes. We find that the reconstructed waveform is consistent with the signal from a binary black hole merger with a chirp mass of ˜30 M⊙ and a total mass before merger of ˜70 M⊙ in the detector frame.

QTest: Quantitative Testing of Theories of Binary Choice

PubMed Central

Regenwetter, Michel; Davis-Stober, Clintin P.; Lim, Shiau Hong; Guo, Ying; Popova, Anna; Zwilling, Chris; Cha, Yun-Shil; Messner, William

2014-01-01

The goal of this paper is to make modeling and quantitative testing accessible to behavioral decision researchers interested in substantive questions. We provide a novel, rigorous, yet very general, quantitative diagnostic framework for testing theories of binary choice. This permits the nontechnical scholar to proceed far beyond traditionally rather superficial methods of analysis, and it permits the quantitatively savvy scholar to triage theoretical proposals before investing effort into complex and specialized quantitative analyses. Our theoretical framework links static algebraic decision theory with observed variability in behavioral binary choice data. The paper is supplemented with a custom-designed public-domain statistical analysis package, the QTest software. We illustrate our approach with a quantitative analysis using published laboratory data, including tests of novel versions of “Random Cumulative Prospect Theory.” A major asset of the approach is the potential to distinguish decision makers who have a fixed preference and commit errors in observed choices from decision makers who waver in their preferences. PMID:24999495

SOCIOECONOMIC AND DEMOGRAPHIC VARIATION IN NUTRITIONAL STATUS OF UNDER-FIVE BANGLADESHI CHILDREN AND TREND OVER THE TWELVE-YEAR PERIOD 1996-2007.

PubMed

Mohsena, Masuda; Goto, Rie; Mascie-Taylor, C G Nicholas

2017-03-01

The nutritional status of under-five-year-old children is a sensitive indicator of a country's health status as well as economic condition. The objectives of this study were to analyse trends in the nutritional status in Bangladeshi children over the period 1996-2007 and to examine the associations between nutritional and socioeconomic status variables. Bangladesh Demographic Health Surveys (BDHS) were the source of data, and a total of 16,278 children were examined. The Z-scores of the children were analysed as continuous as well as categorical variables (stunted, underweight and wasted). The socioeconomic status variables used were region, urban-rural residence, education and occupation of the parents, house type and household possession score. A series of General Linear Model and Sequential Linear and Binary Logistic Regression analyses were done to assess the relationship between demographic and socioeconomic variables and nutritional status. The trends of Z-scores were analysed by survey, as well as by child birth cohort. Region, house type, educational level of parents and household possession score showed significant associations with all three Z-scores of children after removing the effects of age, period of DHS and other explanatory variables in the model. No significant sex difference was observed between any of the Z-scores. There were improvements in mean WAZ and HAZ between 1996 and 2007 but deterioration in mean WHZ over this period. The obesity rate was below 2% in 2007, although the absolute numbers of obese children had nearly doubled in this 12-year period. Children from poorer households showed greater improvement than their better-off counterparts. The study reveals that over the years there has been substantial improvement in nutritional status of under-five children in Bangladesh and the main gains have been amongst the lower socioeconomic groups; it is also evident that malnutrition in Bangladesh is a multidimensional problem, like poverty itself, and warrants a proper policy mix and programme intervention.

Levels and determinants of complementary feeding based on meal frequency among children of 6 to 23 months in Bangladesh.

PubMed

Chowdhury, Mohammad Rocky Khan; Rahman, Md Shafiur; Khan, Md Mobarak Hossain

2016-09-07

Information concerning complementary feeding (CF) practice during infancy and early childhood is still scarce in Bangladesh. Therefore, this study aimed to estimate the level of CF among children of 6-23 months and identify individual, household and community level determinants in Bangladesh. Secondary data from the Bangladesh Demographic Health Survey (BDHS) 2011 was used. A total of 2,373 children aged 6-23 months were selected. A simplified index called "dimension index" was used to estimate the level of CF. The score of this index was used either as continuous or categorical dependent variables. The highest score based on dimension index is associated to an adequate CF. Statistical analyses and tests were guided by types of variables. Finally, multivariable logistic regression (binary and multinomial) analyses were performed to identify the significant determinants of CF. The overall level of CF among children of 6-23 months was low. More than 90 % of children experienced either no (2.9 %) or inadequate CF (92.7 %). According to bivariable analyses, mean levels of CF as well as percentages of no/inadequate CF were significantly lower among children of the youngest age group, uneducated parents, unemployed/laborer fathers, socio-economically poor families, food insecure families and rural areas. No weekly exposure to mass media (namely watching TV and reading newspapers/magazines) also revealed significant associations with CF. However, only few variables remained significant for adequate CF in the multivariable logistic regression analysis. For example, the likelihood of experiencing adequate CF was significantly lower among children of 6-11 months (OR: 0.22, 95 % CI: 0.10-0.47), children of illiterate fathers (OR: 0.32, 95 % CI: 0.11-0.95) and socio-economically middle-class families (OR: 0.28, 95 % CI: 0.09-0.86) as compared to their reference categories. A high level of inadequate CF leading to malnutrition may cause serious health problems among children of 6-23 months in Bangladesh. Vulnerable groups of children (e.g., the children aged 6 to 11 months and children of illiterate fathers), who received low levels of adequate CF, should be targeted by government and other stakeholders while developing strategies and interventions in order to improve overall situation of CF in Bangladesh.

A chance-constrained stochastic approach to intermodal container routing problems.

PubMed

Zhao, Yi; Liu, Ronghui; Zhang, Xi; Whiteing, Anthony

2018-01-01

We consider a container routing problem with stochastic time variables in a sea-rail intermodal transportation system. The problem is formulated as a binary integer chance-constrained programming model including stochastic travel times and stochastic transfer time, with the objective of minimising the expected total cost. Two chance constraints are proposed to ensure that the container service satisfies ship fulfilment and cargo on-time delivery with pre-specified probabilities. A hybrid heuristic algorithm is employed to solve the binary integer chance-constrained programming model. Two case studies are conducted to demonstrate the feasibility of the proposed model and to analyse the impact of stochastic variables and chance-constraints on the optimal solution and total cost.

A chance-constrained stochastic approach to intermodal container routing problems

PubMed Central

Zhao, Yi; Zhang, Xi; Whiteing, Anthony

2018-01-01

We consider a container routing problem with stochastic time variables in a sea-rail intermodal transportation system. The problem is formulated as a binary integer chance-constrained programming model including stochastic travel times and stochastic transfer time, with the objective of minimising the expected total cost. Two chance constraints are proposed to ensure that the container service satisfies ship fulfilment and cargo on-time delivery with pre-specified probabilities. A hybrid heuristic algorithm is employed to solve the binary integer chance-constrained programming model. Two case studies are conducted to demonstrate the feasibility of the proposed model and to analyse the impact of stochastic variables and chance-constraints on the optimal solution and total cost. PMID:29438389

An appraisal of convergence failures in the application of logistic regression model in published manuscripts.

PubMed

Yusuf, O B; Bamgboye, E A; Afolabi, R F; Shodimu, M A

2014-09-01

Logistic regression model is widely used in health research for description and predictive purposes. Unfortunately, most researchers are sometimes not aware that the underlying principles of the techniques have failed when the algorithm for maximum likelihood does not converge. Young researchers particularly postgraduate students may not know why separation problem whether quasi or complete occurs, how to identify it and how to fix it. This study was designed to critically evaluate convergence issues in articles that employed logistic regression analysis published in an African Journal of Medicine and medical sciences between 2004 and 2013. Problems of quasi or complete separation were described and were illustrated with the National Demographic and Health Survey dataset. A critical evaluation of articles that employed logistic regression was conducted. A total of 581 articles was reviewed, of which 40 (6.9%) used binary logistic regression. Twenty-four (60.0%) stated the use of logistic regression model in the methodology while none of the articles assessed model fit. Only 3 (12.5%) properly described the procedures. Of the 40 that used the logistic regression model, the problem of convergence occurred in 6 (15.0%) of the articles. Logistic regression tends to be poorly reported in studies published between 2004 and 2013. Our findings showed that the procedure may not be well understood by researchers since very few described the process in their reports and may be totally unaware of the problem of convergence or how to deal with it.

Some Predicted and Unpredicted Changes in Higher Education.

ERIC Educational Resources Information Center

Williams, Bruce

1996-01-01

Predictions made in 1978 about Australian higher education are re-examined. Very inaccurate enrollment predictions are attributed to unforeseen demand and supply influences. The end to the binary system of higher education, a major change in 1989, was not predicted. However, early analyses of relationships between education, employment, and…

Likelihoods for fixed rank nomination networks

PubMed Central

HOFF, PETER; FOSDICK, BAILEY; VOLFOVSKY, ALEX; STOVEL, KATHERINE

2014-01-01

Many studies that gather social network data use survey methods that lead to censored, missing, or otherwise incomplete information. For example, the popular fixed rank nomination (FRN) scheme, often used in studies of schools and businesses, asks study participants to nominate and rank at most a small number of contacts or friends, leaving the existence of other relations uncertain. However, most statistical models are formulated in terms of completely observed binary networks. Statistical analyses of FRN data with such models ignore the censored and ranked nature of the data and could potentially result in misleading statistical inference. To investigate this possibility, we compare Bayesian parameter estimates obtained from a likelihood for complete binary networks with those obtained from likelihoods that are derived from the FRN scheme, and therefore accommodate the ranked and censored nature of the data. We show analytically and via simulation that the binary likelihood can provide misleading inference, particularly for certain model parameters that relate network ties to characteristics of individuals and pairs of individuals. We also compare these different likelihoods in a data analysis of several adolescent social networks. For some of these networks, the parameter estimates from the binary and FRN likelihoods lead to different conclusions, indicating the importance of analyzing FRN data with a method that accounts for the FRN survey design. PMID:25110586

On the use of higher order wave forms in the search for gravitational waves emitted by compact binary coalescences

NASA Astrophysics Data System (ADS)

McKechan, David J. A.

2010-11-01

This thesis concerns the use, in gravitational wave data analysis, of higher order wave form models of the gravitational radiation emitted by compact binary coalescences. We begin with an introductory chapter that includes an overview of the theory of general relativity, gravitational radiation and ground-based interferometric gravitational wave detectors. We then discuss, in Chapter 2, the gravitational waves emitted by compact binary coalescences, with an explanation of higher order waveforms and how they differ from leading order waveforms we also introduce the post-Newtonian formalism. In Chapter 3 the method and results of a gravitational wave search for low mass compact binary coalescences using a subset of LIGO's 5th science run data are presented and in the subsequent chapter we examine how one could use higher order waveforms in such analyses. We follow the development of a new search algorithm that incorporates higher order waveforms with promising results for detection efficiency and parameter estimation. In Chapter 5, a new method of windowing time-domain waveforms that offers benefit to gravitational wave searches is presented. The final chapter covers the development of a game designed as an outreach project to raise public awareness and understanding of the search for gravitational waves.

Two W-subtype contact binaries: GQ Boo and V1367 Tau

NASA Astrophysics Data System (ADS)

Zhang, Jia; Qian, Sheng-Bang; Han, Zhong-Tao; Wu, Yue

2017-04-01

Two contact binaries, GQ Boo and V1367 Tau, were observed and analysed with a new method to obtain the absolute parameters. The light-curve analysis shows that both of them are obvious W-subtype contact binaries, with much more massive but apparently cooler components (M2/M1 ≃ 2 and 4, T2/T1 ≃ 0.95 and 0.94). The orbital periods were studied using the O-C diagrams, and it is thought that the minima timings were heavily affected by the longstanding magnetic activities on the star surface, so the minima timings cannot represent the real period changes. The mass-radius relationships were proposed by the light-curve analysis alone, which is equivalent to the mean density. The density and temperature can determine the other absolute parameters in most of the time. With the almost complete star parameter space provided by PARSEC, approximate masses and radii were obtained (0.52 ± 0.08 M⊙ and 1.01 ± 0.15 M⊙ for GQ Boo, and 0.22 ± 0.01 M⊙ and 0.92 ± 0.06 M⊙ for V1367 Tau). The mass-radius relationship is a neglected useful tool to calculate the mass and radius, especially for the detached binaries.

Crystallization and preliminary X-ray analysis of binary and ternary complexes of Haloferax mediterranei glucose dehydrogenase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Esclapez, Julia; Britton, K. Linda; Baker, Patrick J.

2005-08-01

Single crystals of binary and ternary complexes of wild-type and D38C mutant H. mediterranei glucose dehydrogenase have been obtained by the hanging-drop vapour-diffusion method. Haloferax mediterranei glucose dehydrogenase (EC 1.1.1.47) belongs to the medium-chain alcohol dehydrogenase superfamily and requires zinc for catalysis. In the majority of these family members, the catalytic zinc is tetrahedrally coordinated by the side chains of a cysteine, a histidine, a cysteine or glutamate and a water molecule. In H. mediterranei glucose dehydrogenase, sequence analysis indicates that the zinc coordination is different, with the invariant cysteine replaced by an aspartate residue. In order to analyse themore » significance of this replacement and to contribute to an understanding of the role of the metal ion in catalysis, a range of binary and ternary complexes of the wild-type and a D38C mutant protein have been crystallized. For most of the complexes, crystals belonging to space group I222 were obtained using sodium/potassium citrate as a precipitant. However, for the binary and non-productive ternary complexes with NADPH/Zn, it was necessary to replace the citrate with 2-methyl-2,4-pentanediol. Despite the radical change in conditions, the crystals thus formed were isomorphous.« less

Asteroseismology of KIC 7107778: a binary comprising almost identical subgiants

NASA Astrophysics Data System (ADS)

Li, Yaguang; Bedding, Timothy R.; Li, Tanda; Bi, Shaolan; Murphy, Simon J.; Corsaro, Enrico; Chen, Li; Tian, Zhijia

2018-05-01

We analyse an asteroseismic binary system: KIC 7107778, a non-eclipsing, unresolved target, with solar-like oscillations in both components. We used Kepler short cadence time series spanning nearly 2 yr to obtain the power spectrum. Oscillation mode parameters were determined using Bayesian inference and a nested sampling Monte Carlo algorithm with the DIAMONDS package. The power profiles of the two components fully overlap, indicating their close similarity. We modelled the two stars with MESA and calculated oscillation frequencies with GYRE. Stellar fundamental parameters (mass, radius, and age) were estimated by grid modelling with atmospheric parameters and the oscillation frequencies of l = 0, 2 modes as constraints. Most l = 1 mixed modes were identified with models searched using a bisection method. Stellar parameters for the two sub-giant stars are MA = 1.42 ± 0.06 M⊙, MB = 1.39 ± 0.03 M⊙, RA = 2.93 ± 0.05 R⊙, RB = 2.76 ± 0.04 R⊙, tA = 3.32 ± 0.54 Gyr and tB = 3.51 ± 0.33 Gyr. The mass difference of the system is ˜1 per cent. The results confirm their simultaneous birth and evolution, as is expected from binary formation. KIC 7107778 comprises almost identical twins, and is the first asteroseismic sub-giant binary to be detected.

The massive multiple system HD 64315

NASA Astrophysics Data System (ADS)

Lorenzo, J.; Simón-Díaz, S.; Negueruela, I.; Vilardell, F.; Garcia, M.; Evans, C. J.; Montes, D.

2017-10-01

Context. The O6 Vn star HD 64315 is believed to belong to the star-forming region known as NGC 2467, but previous distance estimates do not support this association. Moreover, it has been identified as a spectroscopic binary, but existing data support contradictory values for its orbital period. Aims: We explore the multiple nature of this star with the aim of determining its distance, and understanding its connection to NGC 2467. Methods: A total of 52 high-resolution spectra have been gathered over a decade. We use their analysis, in combination with the photometric data from All Sky Automated Survey and Hipparcos catalogues, to conclude that HD 64315 is composed of at least two spectroscopic binaries, one of which is an eclipsing binary. We have developed our own program to fit four components to the combined line shapes. Once the four radial velocities were derived, we obtained a model to fit the radial-velocity curves using the Spectroscopic Binary Orbit Program (SBOP). We then implemented the radial velocities of the eclipsing binary and the light curves in the Wilson-Devinney code iteratively to derive stellar parameters for its components. We were also able to analyse the non-eclipsing binary, and to derive minimum masses for its components which dominate the system flux. Results: HD 64315 contains two binary systems, one of which is an eclipsing binary. The two binaries are separated by 0.09 arcsec (or 500 AU) if the most likely distance to the system, 5 kpc, is considered. The presence of fainter companions is not excluded by current observations. The non-eclipsing binary (HD 64315 AaAb) has a period of 2.70962901 ± 0.00000021 d. Its components are hotter than those of the eclipsing binary, and dominate the appearance of the system. The eclipsing binary (HD 64315 BaBb) has a shorter period of 1.0189569 ± 0.0000008 d. We derive masses of 14.6 ± 2.3 M⊙ for both components of the BaBb system. They are almost identical; both stars are overfilling their respective Roche lobes, and share a common envelope in an overcontact configuration. The non-eclipsing binary is a detached system composed of two stars with spectral types around O6 V with minimum masses of 10.8 M⊙ and 10.2 M⊙, and likely masses ≈ 30 M⊙. Conclusions: HD 64315 provides a cautionary tale about high-mass star isolation and multiplicity. Its total mass is likely above 90M⊙, but it seems to have formed without an accompanying cluster. It contains one the most massive overcontact binaries known, a likely merger progenitor in a very wide multiple system. Based on observations obtained at the European Southern Observatory under programmes 078.D-0665(A), 082-D.0136 and 093.A-9001(A). Based on observations made with the Nordic Optical Telescope, operated on the island of La Palma jointly by Denmark, Finland, Iceland, Norway, and Sweden, in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias.

The use of segmented regression in analysing interrupted time series studies: an example in pre-hospital ambulance care.

PubMed

Taljaard, Monica; McKenzie, Joanne E; Ramsay, Craig R; Grimshaw, Jeremy M

2014-06-19

An interrupted time series design is a powerful quasi-experimental approach for evaluating effects of interventions introduced at a specific point in time. To utilize the strength of this design, a modification to standard regression analysis, such as segmented regression, is required. In segmented regression analysis, the change in intercept and/or slope from pre- to post-intervention is estimated and used to test causal hypotheses about the intervention. We illustrate segmented regression using data from a previously published study that evaluated the effectiveness of a collaborative intervention to improve quality in pre-hospital ambulance care for acute myocardial infarction (AMI) and stroke. In the original analysis, a standard regression model was used with time as a continuous variable. We contrast the results from this standard regression analysis with those from segmented regression analysis. We discuss the limitations of the former and advantages of the latter, as well as the challenges of using segmented regression in analysing complex quality improvement interventions. Based on the estimated change in intercept and slope from pre- to post-intervention using segmented regression, we found insufficient evidence of a statistically significant effect on quality of care for stroke, although potential clinically important effects for AMI cannot be ruled out. Segmented regression analysis is the recommended approach for analysing data from an interrupted time series study. Several modifications to the basic segmented regression analysis approach are available to deal with challenges arising in the evaluation of complex quality improvement interventions.

Cascaded face alignment via intimacy definition feature

NASA Astrophysics Data System (ADS)

Li, Hailiang; Lam, Kin-Man; Chiu, Man-Yau; Wu, Kangheng; Lei, Zhibin

2017-09-01

Recent years have witnessed the emerging popularity of regression-based face aligners, which directly learn mappings between facial appearance and shape-increment manifolds. We propose a random-forest based, cascaded regression model for face alignment by using a locally lightweight feature, namely intimacy definition feature. This feature is more discriminative than the pose-indexed feature, more efficient than the histogram of oriented gradients feature and the scale-invariant feature transform feature, and more compact than the local binary feature (LBF). Experimental validation of our algorithm shows that our approach achieves state-of-the-art performance when testing on some challenging datasets. Compared with the LBF-based algorithm, our method achieves about twice the speed, 20% improvement in terms of alignment accuracy and saves an order of magnitude on memory requirement.

A FORTRAN technique for correlating a circular environmental variable with a linear physiological variable in the sugar maple.

PubMed

Pease, J M; Morselli, M F

1987-01-01

This paper deals with a computer program adapted to a statistical method for analyzing an unlimited quantity of binary recorded data of an independent circular variable (e.g. wind direction), and a linear variable (e.g. maple sap flow volume). Circular variables cannot be statistically analyzed with linear methods, unless they have been transformed. The program calculates a critical quantity, the acrophase angle (PHI, phi o). The technique is adapted from original mathematics [1] and is written in Fortran 77 for easier conversion between computer networks. Correlation analysis can be performed following the program or regression which, because of the circular nature of the independent variable, becomes periodic regression. The technique was tested on a file of approximately 4050 data pairs.

Gender Gaps in Mathematics, Science and Reading Achievements in Muslim Countries: Evidence from Quantile Regression Analyses

ERIC Educational Resources Information Center

Shafiq, M. Najeeb

2011-01-01

Using quantile regression analyses, this study examines gender gaps in mathematics, science, and reading in Azerbaijan, Indonesia, Jordan, the Kyrgyz Republic, Qatar, Tunisia, and Turkey among 15 year-old students. The analyses show that girls in Azerbaijan achieve as well as boys in mathematics and science and overachieve in reading. In Jordan,…

Comparison of intervention effects in split-mouth and parallel-arm randomized controlled trials: a meta-epidemiological study

PubMed Central

2014-01-01

Background Split-mouth randomized controlled trials (RCTs) are popular in oral health research. Meta-analyses frequently include trials of both split-mouth and parallel-arm designs to derive combined intervention effects. However, carry-over effects may induce bias in split- mouth RCTs. We aimed to assess whether intervention effect estimates differ between split- mouth and parallel-arm RCTs investigating the same questions. Methods We performed a meta-epidemiological study. We systematically reviewed meta- analyses including both split-mouth and parallel-arm RCTs with binary or continuous outcomes published up to February 2013. Two independent authors selected studies and extracted data. We used a two-step approach to quantify the differences between split-mouth and parallel-arm RCTs: for each meta-analysis. First, we derived ratios of odds ratios (ROR) for dichotomous data and differences in standardized mean differences (∆SMD) for continuous data; second, we pooled RORs or ∆SMDs across meta-analyses by random-effects meta-analysis models. Results We selected 18 systematic reviews, for 15 meta-analyses with binary outcomes (28 split-mouth and 28 parallel-arm RCTs) and 19 meta-analyses with continuous outcomes (28 split-mouth and 28 parallel-arm RCTs). Effect estimates did not differ between split-mouth and parallel-arm RCTs (mean ROR, 0.96, 95% confidence interval 0.52–1.80; mean ∆SMD, 0.08, -0.14–0.30). Conclusions Our study did not provide sufficient evidence for a difference in intervention effect estimates derived from split-mouth and parallel-arm RCTs. Authors should consider including split-mouth RCTs in their meta-analyses with suitable and appropriate analysis. PMID:24886043

A general framework for the use of logistic regression models in meta-analysis.

PubMed

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.

Predictive distributions for between-study heterogeneity and simple methods for their application in Bayesian meta-analysis

PubMed Central

Turner, Rebecca M; Jackson, Dan; Wei, Yinghui; Thompson, Simon G; Higgins, Julian P T

2015-01-01

Numerous meta-analyses in healthcare research combine results from only a small number of studies, for which the variance representing between-study heterogeneity is estimated imprecisely. A Bayesian approach to estimation allows external evidence on the expected magnitude of heterogeneity to be incorporated. The aim of this paper is to provide tools that improve the accessibility of Bayesian meta-analysis. We present two methods for implementing Bayesian meta-analysis, using numerical integration and importance sampling techniques. Based on 14 886 binary outcome meta-analyses in the Cochrane Database of Systematic Reviews, we derive a novel set of predictive distributions for the degree of heterogeneity expected in 80 settings depending on the outcomes assessed and comparisons made. These can be used as prior distributions for heterogeneity in future meta-analyses. The two methods are implemented in R, for which code is provided. Both methods produce equivalent results to standard but more complex Markov chain Monte Carlo approaches. The priors are derived as log-normal distributions for the between-study variance, applicable to meta-analyses of binary outcomes on the log odds-ratio scale. The methods are applied to two example meta-analyses, incorporating the relevant predictive distributions as prior distributions for between-study heterogeneity. We have provided resources to facilitate Bayesian meta-analysis, in a form accessible to applied researchers, which allow relevant prior information on the degree of heterogeneity to be incorporated. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:25475839

The VLT-FLAMES Tarantula Survey. XIX. B-type supergiants: Atmospheric parameters and nitrogen abundances to investigate the role of binarity and the width of the main sequence

NASA Astrophysics Data System (ADS)

McEvoy, C. M.; Dufton, P. L.; Evans, C. J.; Kalari, V. M.; Markova, N.; Simón-Díaz, S.; Vink, J. S.; Walborn, N. R.; Crowther, P. A.; de Koter, A.; de Mink, S. E.; Dunstall, P. R.; Hénault-Brunet, V.; Herrero, A.; Langer, N.; Lennon, D. J.; Maíz Apellániz, J.; Najarro, F.; Puls, J.; Sana, H.; Schneider, F. R. N.; Taylor, W. D.

2015-03-01

Context. Model atmosphere analyses have been previously undertaken for both Galactic and extragalactic B-type supergiants. By contrast, little attention has been given to a comparison of the properties of single supergiants and those that are members of multiple systems. Aims: Atmospheric parameters and nitrogen abundances have been estimated for all the B-type supergiants identified in the VLT-FLAMES Tarantula survey. These include both single targets and binary candidates. The results have been analysed to investigate the role of binarity in the evolutionary history of supergiants. Methods: tlusty non-local thermodynamic equilibrium (LTE) model atmosphere calculations have been used to determine atmospheric parameters and nitrogen abundances for 34 single and 18 binary supergiants. Effective temperatures were deduced using the silicon balance technique, complemented by the helium ionisation in the hotter spectra. Surface gravities were estimated using Balmer line profiles and microturbulent velocities deduced using the silicon spectrum. Nitrogen abundances or upper limits were estimated from the N ii spectrum. The effects of a flux contribution from an unseen secondary were considered for the binary sample. Results: We present the first systematic study of the incidence of binarity for a sample of B-type supergiants across the theoretical terminal age main sequence (TAMS). To account for the distribution of effective temperatures of the B-type supergiants it may be necessary to extend the TAMS to lower temperatures. This is also consistent with the derived distribution of mass discrepancies, projected rotational velocities and nitrogen abundances, provided that stars cooler than this temperature are post-red supergiant objects. For all the supergiants in the Tarantula and in a previous FLAMES survey, the majority have small projected rotational velocities. The distribution peaks at about 50 km s-1 with 65% in the range 30 km s-1 ≤ vesini ≤ 60 km s-1. About ten per cent have larger vesini (≥100 km s-1), but surprisingly these show little or no nitrogen enhancement. All the cooler supergiants have low projected rotational velocities of ≤70 km s-1and high nitrogen abundance estimates, implying that either bi-stability braking or evolution on a blue loop may be important. Additionally, there is a lack of cooler binaries, possibly reflecting the small sample sizes. Single-star evolutionary models, which include rotation, can account for all of the nitrogen enhancement in both the single and binary samples. The detailed distribution of nitrogen abundances in the single and binary samples may be different, possibly reflecting differences in their evolutionary history. Conclusions: The first comparative study of single and binary B-type supergiants has revealed that the main sequence may be significantly wider than previously assumed, extending to Teff = 20 000 K. Some marginal differences in single and binary atmospheric parameters and abundances have been identified, possibly implying non-standard evolution for some of the sample. This sample as a whole has implications for several aspects of our understanding of the evolutionary status of blue supergiants. Tables 1, 4, 7 are available in electronic form at http://www.aanda.org

What We Have Learned from the Recent Meta-analyses on Diagnostic Methods for Atherosclerotic Plaque Regression.

PubMed

Biondi-Zoccai, Giuseppe; Mastrangeli, Simona; Romagnoli, Enrico; Peruzzi, Mariangela; Frati, Giacomo; Roever, Leonardo; Giordano, Arturo

2018-01-17

Atherosclerosis has major morbidity and mortality implications globally. While it has often been considered an irreversible degenerative process, recent evidence provides compelling proof that atherosclerosis can be reversed. Plaque regression is however difficult to appraise and quantify, with competing diagnostic methods available. Given the potential of evidence synthesis to provide clinical guidance, we aimed to review recent meta-analyses on diagnostic methods for atherosclerotic plaque regression. We identified 8 meta-analyses published between 2015 and 2017, including 79 studies and 14,442 patients, followed for a median of 12 months. They reported on atherosclerotic plaque regression appraised with carotid duplex ultrasound, coronary computed tomography, carotid magnetic resonance, coronary intravascular ultrasound, and coronary optical coherence tomography. Overall, all meta-analyses showed significant atherosclerotic plaque regression with lipid-lowering therapy, with the most notable effects on echogenicity, lipid-rich necrotic core volume, wall/plaque volume, dense calcium volume, and fibrous cap thickness. Significant interactions were found with concomitant changes in low density lipoprotein cholesterol, high density lipoprotein cholesterol, and C-reactive protein levels, and with ethnicity. Atherosclerotic plaque regression and conversion to a stable phenotype is possible with intensive medical therapy and can be demonstrated in patients using a variety of non-invasive and invasive imaging modalities.

Modelling of capital asset pricing by considering the lagged effects

NASA Astrophysics Data System (ADS)

Sukono; Hidayat, Y.; Bon, A. Talib bin; Supian, S.

2017-01-01

In this paper the problem of modelling the Capital Asset Pricing Model (CAPM) with the effect of the lagged is discussed. It is assumed that asset returns are analysed influenced by the market return and the return of risk-free assets. To analyse the relationship between asset returns, the market return, and the return of risk-free assets, it is conducted by using a regression equation of CAPM, and regression equation of lagged distributed CAPM. Associated with the regression equation lagged CAPM distributed, this paper also developed a regression equation of Koyck transformation CAPM. Results of development show that the regression equation of Koyck transformation CAPM has advantages, namely simple as it only requires three parameters, compared with regression equation of lagged distributed CAPM.

Binary Logistic Regression Versus Boosted Regression Trees in Assessing Landslide Susceptibility for Multiple-Occurring Regional Landslide Events: Application to the 2009 Storm Event in Messina (Sicily, southern Italy).

NASA Astrophysics Data System (ADS)

Lombardo, L.; Cama, M.; Maerker, M.; Parisi, L.; Rotigliano, E.

2014-12-01

This study aims at comparing the performances of Binary Logistic Regression (BLR) and Boosted Regression Trees (BRT) methods in assessing landslide susceptibility for multiple-occurrence regional landslide events within the Mediterranean region. A test area was selected in the north-eastern sector of Sicily (southern Italy), corresponding to the catchments of the Briga and the Giampilieri streams both stretching for few kilometres from the Peloritan ridge (eastern Sicily, Italy) to the Ionian sea. This area was struck on the 1st October 2009 by an extreme climatic event resulting in thousands of rapid shallow landslides, mainly of debris flows and debris avalanches types involving the weathered layer of a low to high grade metamorphic bedrock. Exploiting the same set of predictors and the 2009 landslide archive, BLR- and BRT-based susceptibility models were obtained for the two catchments separately, adopting a random partition (RP) technique for validation; besides, the models trained in one of the two catchments (Briga) were tested in predicting the landslide distribution in the other (Giampilieri), adopting a spatial partition (SP) based validation procedure. All the validation procedures were based on multi-folds tests so to evaluate and compare the reliability of the fitting, the prediction skill, the coherence in the predictor selection and the precision of the susceptibility estimates. All the obtained models for the two methods produced very high predictive performances, with a general congruence between BLR and BRT in the predictor importance. In particular, the research highlighted that BRT-models reached a higher prediction performance with respect to BLR-models, for RP based modelling, whilst for the SP-based models the difference in predictive skills between the two methods dropped drastically, converging to an analogous excellent performance. However, when looking at the precision of the probability estimates, BLR demonstrated to produce more robust models in terms of selected predictors and coefficients, as well as of dispersion of the estimated probabilities around the mean value for each mapped pixel. The difference in the behaviour could be interpreted as the result of overfitting effects, which heavily affect decision tree classification more than logistic regression techniques.

[A strategy for assessing environmental influence on airway allergy using a regression binary tree-based method].

PubMed

Yoshioka, Fumi; Azuma, Emiko; Nakajima, Takae; Hashimoto, Masafumi; Toyoshima, Kyoichiro; Komachi, Yoshio

2004-08-01

To clarify the living environment factors that increase the risk of allergic sensitization to house dust mites, we applied a regression binary tree-based method (CART, Classification & Regression Trees) to an epidemiological study on airway allergy. The utility of the tree map in personal sanitary guidance for preventing allergic sensitization was examined with respect to feasibility and validity. A questionnaire was given to 386 healthy adult women, asking them about their individual living environments. Also, blood samples were collected to measure Dermatophagoides pteronyssinus (Dp)-specific IgE, the presence/absence of Dp-sensitization being expressed as positive/negative. The questionnaire consisted of nine items on (1) home ventilation by keeping windows open, (2) personal or family smoking habits, (3) use of air conditioners in hot weather, (4) type of flooring (tatami/wooden/carpet) in the living room, (5) visible mold proliferation in the kitchen, (6) type of housing (concrete/wooden), (7) residential area (heavy or light traffic area) (8) heating system (use of unventilated combustion appliances), and (9) frequency of cleaning (every day or less often). There also were queries on the past history of airway allergic diseases, such as bronchial asthma and allergic rhinitis. CART and a multivariate logistic regression analysis (MLRA) were performed. The subjects were first classified into two groups, with and without a history of airway allergic diseases (Groups WPH and WOPH). In each group, the involvement of living environment factors in Dp-sensitization was examined using CART and MLRA. In the MLRA study, individual living environment factors showed promotional or suppressive effects on Dp-sensitization with differences between the two groups. With respect to the CART results, the two groups were first split by the factor that had the most significant odds ratio for MLRA. In Group WPH, which had a Dp-sensitization risk of 19.5%, the first split was by the factor of visible mold proliferation in the kitchen into the factor-present group with a risk value of 45.5% and the factor-absent group with 13.5%. The mold proliferation group was split with reference to frequent cleaning, and the risk rose to 75% in the factor-absent group and to 100% when family smoking habits were reported. Group WOPH (the risk: 10.8%) was first split into two groups according to the use of air conditioners in hot weather for more than 6 hours a day or less, which showed risk values of 16.7% and 6.9%, respectively. The risk of the group that intensively used air conditioners fell to 8.3% with tatami as flooring in the living room, and, if others, rose to 20.8%. The risk of the factor-lacking group fell to 4.0% without wooden flooring. CART analysis enables us to express complex relationships between living environment factors and Dp-sensitization simply by a binary regression tree, pointing to preventive strategies that can be flexibly changed according to the individual living environments of the subjects.

The cross-validated AUC for MCP-logistic regression with high-dimensional data.

PubMed

Jiang, Dingfeng; Huang, Jian; Zhang, Ying

2013-10-01

We propose a cross-validated area under the receiving operator characteristic (ROC) curve (CV-AUC) criterion for tuning parameter selection for penalized methods in sparse, high-dimensional logistic regression models. We use this criterion in combination with the minimax concave penalty (MCP) method for variable selection. The CV-AUC criterion is specifically designed for optimizing the classification performance for binary outcome data. To implement the proposed approach, we derive an efficient coordinate descent algorithm to compute the MCP-logistic regression solution surface. Simulation studies are conducted to evaluate the finite sample performance of the proposed method and its comparison with the existing methods including the Akaike information criterion (AIC), Bayesian information criterion (BIC) or Extended BIC (EBIC). The model selected based on the CV-AUC criterion tends to have a larger predictive AUC and smaller classification error than those with tuning parameters selected using the AIC, BIC or EBIC. We illustrate the application of the MCP-logistic regression with the CV-AUC criterion on three microarray datasets from the studies that attempt to identify genes related to cancers. Our simulation studies and data examples demonstrate that the CV-AUC is an attractive method for tuning parameter selection for penalized methods in high-dimensional logistic regression models.

Attitude and Behavior Factors Associated with Front-of-Package Label Use with Label Users Making Accurate Product Nutrition Assessments.

PubMed

Roseman, Mary G; Joung, Hyun-Woo; Littlejohn, Emily I

2018-05-01

Front-of-package (FOP) labels are increasing in popularity on retail products. Reductive FOP labels provide nutrient-specific information, whereas evaluative FOP labels summarize nutrient information through icons. Better understanding of consumer behavior regarding FOP labels is beneficial to increasing consumer use of nutrition labeling when making grocery purchasing decisions. We aimed to determine FOP label format effectiveness in aiding consumers at assessing nutrient density of food products. In addition, we sought to determine relationships between FOP label use and attitude toward healthy eating, diet self-assessment, self-reported health and nutrition knowledge, and label and shopping behaviors. A between-subjects experimental design was employed. Participants were randomly assigned to one of four label conditions: Facts Up Front, Facts Up Front Extended, a binary symbol, and no-label control. One hundred sixty-one US primary grocery shoppers, aged 18 to 69 years. Participants were randomly invited to the online study. Participants in one of four label condition groups viewed three product categories (cereal, dairy, and snacks) with corresponding questions. Adults' nutrition assessment of food products based on different FOP label formats, along with label use and attitude toward healthy eating, diet self-assessment, self-reported health and nutrition knowledge, and label and shopping behaviors. Data analyses included descriptive statistics, χ 2 tests, and logistical regression. Significant outcomes were set to α=.05. Participants selected the more nutrient-dense product in the snack food category when it contained an FOP label. Subjective health and nutrition knowledge and frequency of selecting food for healthful reasons were associated with FOP label use (P<0.01 and P<0.05, respectively). Both Facts Up Front (reductive) and binary (evaluative) FOP labels appear effective for nutrition assessment of snack products compared with no label. Specific attitude and behavior factors were associated with label use. Copyright © 2018 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Examining the association between livestock ownership typologies and child nutrition in the Luangwa Valley, Zambia

PubMed Central

Kassa, Lea; Young, Sera L.; Travis, Alexander J.

2018-01-01

Objective To investigate the association between livestock ownership and dietary diversity, animal-source food consumption, height-for-age z-score, and stunting among children living in wildlife “buffer zones” of Zambia’s Luangwa Valley using a novel livestock typology approach. Methods We conducted a cross-sectional study of 838 children aged 6–36 months. Households were categorized into typologies based on the types and numbers of animals owned, ranging from no livestock to large numbers of mixed livestock. We used multilevel mixed-effects linear and logistic regression to examine the association between livestock typologies and four nutrition-related outcomes of interest. Results were compared with analyses using more common binary and count measures of livestock ownership. Results No measure of livestock ownership was significantly associated with children’s odds of animal-source food consumption, child height-for-age z-score, or stunting odds. Livestock ownership Type 2 (having a small number of poultry) was surprisingly associated with decreased child dietary diversity (β = -0.477; p<0.01) relative to owning no livestock. Similarly, in comparison models, chicken ownership was negatively associated with dietary diversity (β = -0.320; p<0.01), but increasing numbers of chickens were positively associated with dietary diversity (β = 0.022; p<0.01). Notably, neither child dietary diversity nor animal-source food consumption was significantly associated with height, perhaps due to unusually high prevalences of morbidities. Conclusions Our novel typologies methodology allowed for an efficient and a more in-depth examination of the differential impact of livestock ownership patterns compared to typical binary or count measures of livestock ownership. We found that these patterns were not positively associated with child nutrition outcomes in this context. Development and conservation programs focusing on livestock must carefully consider the complex, context-specific relationship between livestock ownership and nutrition outcomes–including how livestock are utilized by the target population–when attempting to use livestock as a means of improving child nutrition. PMID:29408920

Examining the association between livestock ownership typologies and child nutrition in the Luangwa Valley, Zambia.

PubMed

Dumas, Sarah E; Kassa, Lea; Young, Sera L; Travis, Alexander J

2018-01-01

To investigate the association between livestock ownership and dietary diversity, animal-source food consumption, height-for-age z-score, and stunting among children living in wildlife "buffer zones" of Zambia's Luangwa Valley using a novel livestock typology approach. We conducted a cross-sectional study of 838 children aged 6-36 months. Households were categorized into typologies based on the types and numbers of animals owned, ranging from no livestock to large numbers of mixed livestock. We used multilevel mixed-effects linear and logistic regression to examine the association between livestock typologies and four nutrition-related outcomes of interest. Results were compared with analyses using more common binary and count measures of livestock ownership. No measure of livestock ownership was significantly associated with children's odds of animal-source food consumption, child height-for-age z-score, or stunting odds. Livestock ownership Type 2 (having a small number of poultry) was surprisingly associated with decreased child dietary diversity (β = -0.477; p<0.01) relative to owning no livestock. Similarly, in comparison models, chicken ownership was negatively associated with dietary diversity (β = -0.320; p<0.01), but increasing numbers of chickens were positively associated with dietary diversity (β = 0.022; p<0.01). Notably, neither child dietary diversity nor animal-source food consumption was significantly associated with height, perhaps due to unusually high prevalences of morbidities. Our novel typologies methodology allowed for an efficient and a more in-depth examination of the differential impact of livestock ownership patterns compared to typical binary or count measures of livestock ownership. We found that these patterns were not positively associated with child nutrition outcomes in this context. Development and conservation programs focusing on livestock must carefully consider the complex, context-specific relationship between livestock ownership and nutrition outcomes-including how livestock are utilized by the target population-when attempting to use livestock as a means of improving child nutrition.

Modelling the growth kinetics of Kocuria marina DAGII as a function of single and binary substrate during batch production of β-Cryptoxanthin.

PubMed

Mitra, Ruchira; Chaudhuri, Surabhi; Dutta, Debjani

2017-01-01

In the present investigation, growth kinetics of Kocuria marina DAGII during batch production of β-Cryptoxanthin (β-CRX) was studied by considering the effect of glucose and maltose as a single and binary substrate. The importance of mixed substrate over single substrate has been emphasised in the present study. Different mathematical models namely, the Logistic model for cell growth, the Logistic mass balance equation for substrate consumption and the Luedeking-Piret model for β-CRX production were successfully implemented. Model-based analyses for the single substrate experiments suggested that the concentrations of glucose and maltose higher than 7.5 and 10.0 g/L, respectively, inhibited the growth and β-CRX production by K. marina DAGII. The Han and Levenspiel model and the Luong product inhibition model accurately described the cell growth in glucose and maltose substrate systems with a R 2 value of 0.9989 and 0.9998, respectively. The effect of glucose and maltose as binary substrate was further investigated. The binary substrate kinetics was well described using the sum-kinetics with interaction parameters model. The results of production kinetics revealed that the presence of binary substrate in the cultivation medium increased the biomass and β-CRX yield significantly. This study is a first time detailed investigation on kinetic behaviours of K. marina DAGII during β-CRX production. The parameters obtained in the study might be helpful for developing strategies for commercial production of β-CRX by K. marina DAGII.

The O-type eclipsing contact binary LY Aurigae - member of a quadruple system

NASA Astrophysics Data System (ADS)

Mayer, Pavel; Drechsel, Horst; Harmanec, Petr; Yang, Stephenson; Šlechta, Miroslav

2013-11-01

The eclipsing binary LY Aur (O9 II + O9 III) belongs to the rare class of early-type contact systems. We obtained 23 new spectra at the Ondřejov and Dominion Astrophysical Observatories, which were analysed with four older Calar Alto and one ELODIE archive spectra. A new result of this study is that the visual companion of LY Aur - the spectral lines of which are clearly seen in our spectra - is also an SB1 binary having an orbital period of 20.46d, an eccentric orbit, and a radial velocity semi-amplitude of 33 km s-1. The Hα line blend contains an emission component, which shows dependence on the orbital phase of the eclipsing system, with the strongest emission around the secondary eclipse. Revised elements of the eclipsing binary and the orbital solution of the companion binary are determined from our set of spectra and new light-curve solutions of the eclipsing pair. The mass of the primary of 25.5 M⊙ agrees well with its spectral type, whereas the secondary mass of 14 M⊙ is smaller than expected. From an O-C analysis of the minimum times of LY Aur that span more than 40 years, we found that the orbital period is decreasing, indicating the presence of interaction processes. The system is likely in a phase of non-conservative mass exchange. Based on spectral observations collected at the German-Spanish Observatory, Calar Alto, Spain; Dominion Astrophysical Observatory, Canada; Ondřejov Observatory, Czech Republic, and an archival Haute Provence Observatory ELODIE spectrum.

A Strategy for Replacing Sum Scoring

ERIC Educational Resources Information Center

Ramsay, James O.; Wiberg, Marie

2017-01-01

This article promotes the use of modern test theory in testing situations where sum scores for binary responses are now used. It directly compares the efficiencies and biases of classical and modern test analyses and finds an improvement in the root mean squared error of ability estimates of about 5% for two designed multiple-choice tests and…

Clusters of anthropometric indicators of body fat associated with maximum oxygen uptake in adolescents

PubMed Central

2018-01-01

Introduction The aim of this study was to evaluate different clusters of anthropometric indicators (body mass index | BMI |, waist circumference | WC |, waist-to-height ratio | WHtR |, triceps skinfold |TR SF|, subscapular skinfold |SE SF|, sum of the triceps and subscapular skinfolds | ΣTR + SE |, and sum of the triceps, subscapular and suprailiac folds | ΣTR + SE + SI|) associated with the VO2max levels in adolescents. Methods The study included 1,132 adolescents (aged 14–19 years) enrolled in public schools of São José, Santa Catarina, Brazil, in the 2014 academic year. The dependent variable was the cluster of anthropometric indicators (BMI, WC, WHtR, TR SF, SE SF, SI SF, ΣTR + SE and ΣTR + SE + SI) of excess body fat. The independent variable was maximum oxygen uptake (VO2max), estimated by the modified Canadian aerobic fitness test—mCAFT. Control variables were: age, skin color, economic level, maternal education, physical activity and sexual maturation. Multinomial logistic regression was used for associations between the dependent and independent variables. Binary logistic regression was performed to identify the association between adolescents with all anthropometric indicators in excess and independent variables. Results One in ten adolescents presented all anthropometric indicators of excess body fat. Multinomial regression showed that with each increase of one VO2max unit, the odds of adolescents having three, four, five or more anthropometric indicators of excess body fat decreased by 0.92, 0.85 and 0.73 times, respectively. In the binary regression, this fact was reconfirmed, demonstrating that with each increase of one VO2max unit, the odds of adolescents having simultaneously the eight anthropometric indicators of excess body fat decreased by 0.55. Conclusion It was concluded that with each increase of one VO2max unit, adolescents decreased the odds of simultaneously presenting three or more anthropometric indicators of excess body fat, regardless of biological, economic and lifestyle factors. In addition, the present study identified that one in ten adolescents had all anthropometric indicators of excess body fat. PMID:29534098

Clusters of anthropometric indicators of body fat associated with maximum oxygen uptake in adolescents.

PubMed

Gonçalves, Eliane Cristina de Andrade; Nunes, Heloyse Elaine Gimenes; Silva, Diego Augusto Santos

2018-01-01

The aim of this study was to evaluate different clusters of anthropometric indicators (body mass index | BMI |, waist circumference | WC |, waist-to-height ratio | WHtR |, triceps skinfold |TR SF|, subscapular skinfold |SE SF|, sum of the triceps and subscapular skinfolds | ΣTR + SE |, and sum of the triceps, subscapular and suprailiac folds | ΣTR + SE + SI|) associated with the VO2max levels in adolescents. The study included 1,132 adolescents (aged 14-19 years) enrolled in public schools of São José, Santa Catarina, Brazil, in the 2014 academic year. The dependent variable was the cluster of anthropometric indicators (BMI, WC, WHtR, TR SF, SE SF, SI SF, ΣTR + SE and ΣTR + SE + SI) of excess body fat. The independent variable was maximum oxygen uptake (VO2max), estimated by the modified Canadian aerobic fitness test-mCAFT. Control variables were: age, skin color, economic level, maternal education, physical activity and sexual maturation. Multinomial logistic regression was used for associations between the dependent and independent variables. Binary logistic regression was performed to identify the association between adolescents with all anthropometric indicators in excess and independent variables. One in ten adolescents presented all anthropometric indicators of excess body fat. Multinomial regression showed that with each increase of one VO2max unit, the odds of adolescents having three, four, five or more anthropometric indicators of excess body fat decreased by 0.92, 0.85 and 0.73 times, respectively. In the binary regression, this fact was reconfirmed, demonstrating that with each increase of one VO2max unit, the odds of adolescents having simultaneously the eight anthropometric indicators of excess body fat decreased by 0.55. It was concluded that with each increase of one VO2max unit, adolescents decreased the odds of simultaneously presenting three or more anthropometric indicators of excess body fat, regardless of biological, economic and lifestyle factors. In addition, the present study identified that one in ten adolescents had all anthropometric indicators of excess body fat.

Quantitative Structure – Property Relationship Modeling of Remote Liposome Loading Of Drugs

PubMed Central

Cern, Ahuva; Golbraikh, Alexander; Sedykh, Aleck; Tropsha, Alexander; Barenholz, Yechezkel; Goldblum, Amiram

2012-01-01

Remote loading of liposomes by trans-membrane gradients is used to achieve therapeutically efficacious intra-liposome concentrations of drugs. We have developed Quantitative Structure Property Relationship (QSPR) models of remote liposome loading for a dataset including 60 drugs studied in 366 loading experiments internally or elsewhere. Both experimental conditions and computed chemical descriptors were employed as independent variables to predict the initial drug/lipid ratio (D/L) required to achieve high loading efficiency. Both binary (to distinguish high vs. low initial D/L) and continuous (to predict real D/L values) models were generated using advanced machine learning approaches and five-fold external validation. The external prediction accuracy for binary models was as high as 91–96%; for continuous models the mean coefficient R2 for regression between predicted versus observed values was 0.76–0.79. We conclude that QSPR models can be used to identify candidate drugs expected to have high remote loading capacity while simultaneously optimizing the design of formulation experiments. PMID:22154932

Multivariate meta-analysis using individual participant data

PubMed Central

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2016-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment–covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. PMID:26099484

Use of principal-component, correlation, and stepwise multiple-regression analyses to investigate selected physical and hydraulic properties of carbonate-rock aquifers

USGS Publications Warehouse

Brown, C. Erwin

1993-01-01

Correlation analysis in conjunction with principal-component and multiple-regression analyses were applied to laboratory chemical and petrographic data to assess the usefulness of these techniques in evaluating selected physical and hydraulic properties of carbonate-rock aquifers in central Pennsylvania. Correlation and principal-component analyses were used to establish relations and associations among variables, to determine dimensions of property variation of samples, and to filter the variables containing similar information. Principal-component and correlation analyses showed that porosity is related to other measured variables and that permeability is most related to porosity and grain size. Four principal components are found to be significant in explaining the variance of data. Stepwise multiple-regression analysis was used to see how well the measured variables could predict porosity and (or) permeability for this suite of rocks. The variation in permeability and porosity is not totally predicted by the other variables, but the regression is significant at the 5% significance level. ?? 1993.

Clustering of Risk Factors for Non-Communicable Diseases among Adolescents from Southern Brazil.

PubMed

Nunes, Heloyse Elaine Gimenes; Gonçalves, Eliane Cristina de Andrade; Vieira, Jéssika Aparecida Jesus; Silva, Diego Augusto Santos

2016-01-01

The aim of this study was to investigate the simultaneous presence of risk factors for non-communicable diseases and the association of these risk factors with demographic and economic factors among adolescents from southern Brazil. The study included 916 students (14-19 years old) enrolled in the 2014 school year at state schools in São José, Santa Catarina, Brazil. Risk factors related to lifestyle (i.e., physical inactivity, excessive alcohol consumption, smoking, sedentary behaviour and unhealthy diet), demographic variables (sex, age and skin colour) and economic variables (school shift and economic level) were assessed through a questionnaire. Simultaneous behaviours were assessed by the ratio between observed and expected prevalences of risk factors for non-communicable diseases. The clustering of risk factors was analysed by multinomial logistic regression. The clusters of risk factors that showed a higher prevalence were analysed by binary logistic regression. The clustering of two, three, four, and five risk factors were found in 22.2%, 49.3%, 21.7% and 3.1% of adolescents, respectively. Subgroups that were more likely to have both behaviours of physical inactivity and unhealthy diet simultaneously were mostly composed of girls (OR = 3.03, 95% CI = 1.57-5.85) and those with lower socioeconomic status (OR = 1.83, 95% CI = 1.05-3.21); simultaneous physical inactivity, excessive alcohol consumption, sedentary behaviour and unhealthy diet were mainly observed among older adolescents (OR = 1.49, 95% CI = 1.05-2.12). Subgroups less likely to have both behaviours of sedentary behaviour and unhealthy diet were mostly composed of girls (OR = 0.58, 95% CI = 0.38-0.89); simultaneous physical inactivity, sedentary behaviour and unhealthy diet were mainly observed among older individuals (OR = 0.66, 95% CI = 0.49-0.87) and those of the night shift (OR = 0.59, 95% CI = 0.43-0.82). Adolescents had a high prevalence of simultaneous risk factors for NCDs. Demographic (gender and age) and economic (school shift) variables were associated with the most prevalent simultaneous behaviours among adolescents.

Clustering of Risk Factors for Non-Communicable Diseases among Adolescents from Southern Brazil

PubMed Central

2016-01-01

Introduction The aim of this study was to investigate the simultaneous presence of risk factors for non-communicable diseases and the association of these risk factors with demographic and economic factors among adolescents from southern Brazil. Methods The study included 916 students (14–19 years old) enrolled in the 2014 school year at state schools in São José, Santa Catarina, Brazil. Risk factors related to lifestyle (i.e., physical inactivity, excessive alcohol consumption, smoking, sedentary behaviour and unhealthy diet), demographic variables (sex, age and skin colour) and economic variables (school shift and economic level) were assessed through a questionnaire. Simultaneous behaviours were assessed by the ratio between observed and expected prevalences of risk factors for non-communicable diseases. The clustering of risk factors was analysed by multinomial logistic regression. The clusters of risk factors that showed a higher prevalence were analysed by binary logistic regression. Results The clustering of two, three, four, and five risk factors were found in 22.2%, 49.3%, 21.7% and 3.1% of adolescents, respectively. Subgroups that were more likely to have both behaviours of physical inactivity and unhealthy diet simultaneously were mostly composed of girls (OR = 3.03, 95% CI = 1.57–5.85) and those with lower socioeconomic status (OR = 1.83, 95% CI = 1.05–3.21); simultaneous physical inactivity, excessive alcohol consumption, sedentary behaviour and unhealthy diet were mainly observed among older adolescents (OR = 1.49, 95% CI = 1.05–2.12). Subgroups less likely to have both behaviours of sedentary behaviour and unhealthy diet were mostly composed of girls (OR = 0.58, 95% CI = 0.38–0.89); simultaneous physical inactivity, sedentary behaviour and unhealthy diet were mainly observed among older individuals (OR = 0.66, 95% CI = 0.49–0.87) and those of the night shift (OR = 0.59, 95% CI = 0.43–0.82). Conclusion Adolescents had a high prevalence of simultaneous risk factors for NCDs. Demographic (gender and age) and economic (school shift) variables were associated with the most prevalent simultaneous behaviours among adolescents. PMID:27434023

Socioeconomic status is positively associated with measures of adiposity and insulin resistance, but inversely associated with dyslipidaemia in Colombian children.

PubMed

Buitrago-Lopez, Adriana; van den Hooven, Edith H; Rueda-Clausen, Christian F; Serrano, Norma; Ruiz, Alvaro J; Pereira, Mark A; Mueller, Noel T

2015-06-01

Low socioeconomic status (SES) has been associated with higher risk of cardiometabolic diseases in developed societies, but investigation of SES and cardiometabolic risk in children in less economically developed populations is sparse. We aimed to examine associations among SES and cardiometabolic risk factors in Colombian children. We used data from a population-based study of 1282 children aged 6-10 years from Bucaramanga, Colombia. SES was classified according to household wealth, living conditions and access to public utilities. Anthropometric and biochemical parameters were measured at a clinic visit. Cardiometabolic risk factors were analysed continuously using linear regression and as binary outcomes-according to established paediatric cut points-using logistic regression to calculate OR and 95% CIs. Mean age of the children was 8.4 (SD 1.4) and 51.1% of the sample were boys. Odds of overweight/obesity, abdominal obesity and insulin resistance were greater among higher SES. Compared with the lowest SES stratum, children in the highest SES had higher odds of overweight/obesity (OR=3.25, 95% CI 1.89 to 5.57), abdominal obesity (OR=2.74, 95% CI 1.41 to 5.31) and insulin resistance (OR=2.60, 95% CI 1.81 to 3.71). In contrast, children in the highest SES had lower odds of hypertriglyceridaemia (triglycerides ≥90th centile; OR=0.28, 95% CI 0.14 to 0.54) and low (≤10th centile) high-density lipoprotein (HDL) cholesterol (OR=0.35, 95% CI 0.15 to 0.78). In Colombian children, SES is directly associated with obesity and insulin resistance, but inversely associated with dyslipidaemia (hypertriglyceridaemia and low HDL cholesterol). Our findings highlight the need to analyse cardiometabolic risk factors separately in children and to carefully consider a population's level of economic development when studying their social determinants of cardiometabolic disease. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

The relationship between nut intake and risk of colorectal cancer: a case control study.

PubMed

Lee, Jeeyoo; Shin, Aesun; Oh, Jae Hwan; Kim, Jeongseon

2018-03-07

Nut consumption is known to reduce the risk of obesity, diabetes mellitus, and cardiovascular disease. However, in previous studies, portion sizes and categories of nut consumption have varied, and few studies have assessed the association between colorectal cancer risk and nut consumption. In this study, we investigated the relationship between nut consumption and colorectal cancer risk. A case-control study was conducted among 923 colorectal cancer patients and 1846 controls recruited from the National Cancer Center in Korea. Information on dietary intake was collected using a semi-quantitative food frequency questionnaire with 106 items, including peanuts, pine nuts, and almonds (as 1 food item). Nut consumption was categorized as none, < 1 serving per week, 1-3 servings per week, and ≥3 servings per week. A binary logistic regression model was used to estimate odds ratios (OR) and their 95% confidence intervals (CI) for the association between nut consumption and colorectal cancer risk, and a polytomous logistic regression model was used for sub-site analyses. High nut consumption was strongly associated with reduced risk of colorectal cancer among women (adjusted ORs: 0.30, 95%CI: 0.15-0.60 for the ≥3 servings per week group vs. none). A similar inverse association was observed for men (adjusted ORs: 0.28, 95% CI: 0.17-0.47). In sub-site analyses, adjusted ORs (95% CIs) comparing the ≥3 servings per week group vs none were 0.25 (0.09-0.70) for proximal colon cancer, 0.39 (0.19-0.80) for distal colon cancer, and 0.23 (0.12-0.46) for rectal cancer among men. An inverse association was also found among women for distal colon cancer (OR: 0.13, 95% CI: 0.04-0.48) and rectal cancer (OR: 0.40, 95% CI: 0.17-0.95). We found a statistically significant association between high frequency of nut consumption and reduced risk of colorectal cancer. This association was observed for all sub-sites of the colon and rectum among both men and women, with the exception of proximal colon cancer for women.

Rural-urban disparity in oral health-related quality of life.

PubMed

Gaber, Amal; Galarneau, Chantal; Feine, Jocelyne S; Emami, Elham

2018-04-01

The objective of this population-based cross-sectional study was to estimate rural-urban disparity in the oral health-related quality of life (OHRQoL) of the Quebec adult population. A 2-stage sampling design was used to collect data from the 1788 parents/caregivers of schoolchildren living in the 8 regions of the province of Quebec in Canada. Andersen's behavioural model for health services utilization was used as a conceptual framework. Place of residency was defined according to the Statistics Canada Census Metropolitan Area and Census Agglomeration Influenced Zone classification. The outcome of interest was OHRQoL measured using the Oral Health Impact Profile (OHIP)-14 validated questionnaire. Data weighting was applied, and the prevalence, extent and severity of negative oral health impacts were calculated. Statistical analyses included descriptive statistics, bivariate analyses and binary logistic regression. The prevalence of poor oral health-related quality life (OHRQoL) was statistically higher in rural areas than in urban zones (P = .02). Rural residents reported a significantly higher prevalence of negative daily-life impacts in pain, psychological discomfort and social disability OHIP domains (P < .05). Additionally, the rural population showed a greater number of negative oral health impacts (P = .03). There was no significant rural-urban difference in the severity of poor oral health. Logistic regression indicated that the prevalence of poor OHRQoL was significantly related to place of residency (OR = 1.6; 95% CI = 1.1-2.5; P = .022), perceived oral health (OR = 9.4; 95% CI = 5.7-15.5; P < .001), dental treatment needs factors (perceived need for dental treatment, pain, dental care seeking) (OR = 8.7; 95% CI = 4.8-15.6; P < .001) and education (OR = 2.7; 95% CI = 1.8-3.9; P < .001). The results of this study suggest a potential difference in OHRQoL of Quebec rural and urban populations, and a need to develop strategies to promote oral health outcomes, specifically for rural residents. Further studies are needed to confirm these results. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Measures and Relative Motions of Some Mostly F. G. W. Struve Doubles

NASA Astrophysics Data System (ADS)

Wiley, E. O.

2012-04-01

Measures of 59 pairs of double stars with long observational histories using "lucky imaging" techniques are reported. Relative motions of 59 pairs are investigated using histories of observation, scatter plots of relative motion, ordinary least-squares (OLS) and total proper motion analyses performed in "R," an open source programming language. A scatter plot of the coefficient of determinations derived from the OLS y|epoch and OLS x|epoch clearly separates common proper motion pairs from optical pairs and what are termed "long-period binary candidates." Differences in proper motion separate optical pairs from long-term binary candidates. An Appendix is provided that details how to use known rectilinear pairs as calibration pairs for the program REDUC.

The protection motivation theory within the stages of the transtheoretical model - stage-specific interplay of variables and prediction of exercise stage transitions.

PubMed

Lippke, Sonia; Plotnikoff, Ronald C

2009-05-01

Two different theories of health behaviour have been chosen with the aim of theory integration: a continuous theory (protection motivation theory, PMT) and a stage model (transtheoretical model, TTM). This is the first study to test whether the stages of the TTM moderate the interrelation of PMT-variables and the mediation of motivation, as well as PMT-variables' interactions in predicting stage transitions. Hypotheses were tested regarding (1) mean patterns, stage pair-comparisons and nonlinear trends using ANOVAs; (2) prediction-patterns for the different stage groups employing multi-group structural equation modelling (MSEM) and nested model analyses; and (3) stage transitions using binary logistic regression analyses. Adults (N=1,602) were assessed over a 6 month period on their physical activity stages, PMT-variables and subsequent behaviour. (1) Particular mean differences and nonlinear trends in all test variables were found. (2) The PMT adequately fitted the five stage groups. The MSEM revealed that covariances within threat appraisal and coping appraisal were invariant and all other constrains were stage-specific, i.e. stage was a moderator. Except for self-efficacy, motivation fully mediated the relationship between the social-cognitive variables and behaviour. (3) Predicting stage transitions with the PMT-variables underscored the importance of self-efficacy. Only when threat appraisal and coping appraisal were high, stage movement was more likely in the preparation stage. Results emphasize stage-specific differences of the PMT mechanisms, and hence, support the stage construct. The findings may guide further theory building and research integrating different theoretical approaches.

[Poverty, public transfers and health: An analysis on self-rated health of social benefit recipients in Germany].

PubMed

Pförtner, T-K; Schumann, N

2016-09-01

Prevention and reduction of poverty are key elements of social welfare policy in Germany. This study is the first analysis of self-rated health of individuals that escape poverty by benefiting form public transfers. Analyses are based on the German Socio-economic Panel (GSOEP) of 2010. Self-rated health was based on subjective assessment of general health status. Subjects were directly asked about receipt of public transfers. Income poverty was based on the equalized disposable income and is applied to a threshold of 60% of the median-based average income. We analyzed the association between self-rated health and pre- and post-transfer poverty by means of descriptive analyses and binary logistic regression. After adjusting for age, we found a significantly higher risk of poor self-rated health among those who escaped income poverty due to the receipt of social transfers compared to others (ORWomen: 1.85; 95%-CI: 1.27-2.69; ORMen: 2.57; 95%-CI: 1.63-4.05), in particular to those at risk of post-transfer poverty. These poverty-related inequalities in health were predominantly explained by nationality, occupational status, household type and long-term care within the household. This study provides first evidence that the receipt of public transfers is associated with increased risk of poor health in the light of impending income-poverty. This study adds to the current debate about the social and health implications of public transfers in the relationship between poverty and health. © Georg Thieme Verlag KG Stuttgart · New York.

Prediction of Methotrexate Clinical Response in Portuguese Rheumatoid Arthritis Patients: Implication of MTHFR rs1801133 and ATIC rs4673993 Polymorphisms

PubMed Central

Lima, Aurea; Monteiro, Joaquim; Bernardes, Miguel; Sousa, Hugo; Azevedo, Rita; Seabra, Vitor; Medeiros, Rui

2014-01-01

Objective. Methotrexate (MTX), the most used drug in rheumatoid arthritis (RA) treatment, showing variability in clinical response, is often associated with genetic polymorphisms. This study aimed to elucidate the role of methylenetetrahydrofolate reductase (MTHFR) C677T and aminoimidazole carboxamide adenosine ribonucleotide transformylase (ATIC) T675C polymorphisms and clinicopathological variables in clinical response to MTX in Portuguese RA patients. Methods. Study included 233 RA patients treated with MTX for at least six months. MTHFR C677T and ATIC T675C polymorphisms were genotyped and clinicopathological variables were collected. Statistical analyses were performed and binary logistic regression method adjusted to possible confounding variables. Results. Multivariate analyses demonstrated that MTHFR 677TT (OR = 4.63; P = 0.013) and ATIC 675T carriers (OR = 5.16; P = 0.013) were associated with over 4-fold increased risk for nonresponse. For clinicopathological variables, noncurrent smokers (OR = 7.98; P = 0.001), patients positive to anti-cyclic citrullinated peptide (OR = 3.53; P = 0.004) and antinuclear antibodies (OR = 2.28; P = 0.045), with higher health assessment questionnaire score (OR = 2.42; P = 0.007), and nonsteroidal anti-inflammatory drug users (OR = 2.77; P = 0.018) were also associated with nonresponse. Contrarily, subcutaneous administration route (OR = 0.11; P < 0.001) was associated with response. Conclusion. Our study suggests that MTHFR C677T and ATIC T675C genotyping combined with clinicopathological data may help to identify patients whom will not benefit from MTX treatment and, therefore, assist clinicians in personalizing RA treatment. PMID:24967362

The rate of adherence to urate-lowering therapy and associated factors in Chinese gout patients: a cross-sectional study.

PubMed

Yin, Rulan; Cao, Haixia; Fu, Ting; Zhang, Qiuxiang; Zhang, Lijuan; Li, Liren; Gu, Zhifeng

2017-07-01

The aim of this study was to assess adherence rate and predictors of non-adherence with urate-lowering therapy (ULT) in Chinese gout patients. A cross-sectional study was administered to 125 gout patients using the Compliance Questionnaire on Rheumatology (CQR) for adherence to ULT. Patients were asked to complete the Treatment Satisfaction Questionnaire for Medication version II, Health Assessment Questionnaire, Confidence in Gout Treatment Questionnaire, Gout Knowledge Questionnaire, Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and 36-Item Short Form Health Survey. Data were analyzed by independent sample t test, rank sum test, Chi-square analysis as well as binary stepwise logistic regression modeling. The data showed that the rate of adherence (CQR ≥80%) to ULT was 9.6% in our investigated gout patients. Adherence was associated with functional capacity, gout-related knowledge, satisfaction with medication, confidence in gout treatment and mental components summary. Multivariable analysis of binary stepwise logistic regression identified gout-related knowledge and satisfaction of effectiveness with medication was the independent risk factors of medication non-adherence. Patients unaware of gout-related knowledge, or with low satisfaction of effectiveness with medication, were more likely not to adhere to ULT. Non-adherence to ULT among gout patients is exceedingly common, particularly in patients unaware of gout-related knowledge, or with low satisfaction of effectiveness with medication. These findings could help medical personnel develop useful interventions to improve gout patients' medication adherence.

Financial performance monitoring of the technical efficiency of critical access hospitals: a data envelopment analysis and logistic regression modeling approach.

PubMed

Wilson, Asa B; Kerr, Bernard J; Bastian, Nathaniel D; Fulton, Lawrence V

2012-01-01

From 1980 to 1999, rural designated hospitals closed at a disproportionally high rate. In response to this emergent threat to healthcare access in rural settings, the Balanced Budget Act of 1997 made provisions for the creation of a new rural hospital--the critical access hospital (CAH). The conversion to CAH and the associated cost-based reimbursement scheme significantly slowed the closure rate of rural hospitals. This work investigates which methods can ensure the long-term viability of small hospitals. This article uses a two-step design to focus on a hypothesized relationship between technical efficiency of CAHs and a recently developed set of financial monitors for these entities. The goal is to identify the financial performance measures associated with efficiency. The first step uses data envelopment analysis (DEA) to differentiate efficient from inefficient facilities within a data set of 183 CAHs. Determining DEA efficiency is an a priori categorization of hospitals in the data set as efficient or inefficient. In the second step, DEA efficiency is the categorical dependent variable (efficient = 0, inefficient = 1) in the subsequent binary logistic regression (LR) model. A set of six financial monitors selected from the array of 20 measures were the LR independent variables. We use a binary LR to test the null hypothesis that recently developed CAH financial indicators had no predictive value for categorizing a CAH as efficient or inefficient, (i.e., there is no relationship between DEA efficiency and fiscal performance).

Hierarchical faunal filters: An approach to assessing effects of habitat and nonnative species on native fishes

USGS Publications Warehouse

Quist, M.C.; Rahel, F.J.; Hubert, W.A.

2005-01-01

Understanding factors related to the occurrence of species across multiple spatial and temporal scales is critical to the conservation and management of native fishes, especially for those species at the edge of their natural distribution. We used the concept of hierarchical faunal filters to provide a framework for investigating the influence of habitat characteristics and normative piscivores on the occurrence of 10 native fishes in streams of the North Platte River watershed in Wyoming. Three faunal filters were developed for each species: (i) large-scale biogeographic, (ii) local abiotic, and (iii) biotic. The large-scale biogeographic filter, composed of elevation and stream-size thresholds, was used to determine the boundaries within which each species might be expected to occur. Then, a local abiotic filter (i.e., habitat associations), developed using binary logistic-regression analysis, estimated the probability of occurrence of each species from features such as maximum depth, substrate composition, submergent aquatic vegetation, woody debris, and channel morphology (e.g., amount of pool habitat). Lastly, a biotic faunal filter was developed using binary logistic regression to estimate the probability of occurrence of each species relative to the abundance of nonnative piscivores in a reach. Conceptualising fish assemblages within a framework of hierarchical faunal filters is simple and logical, helps direct conservation and management activities, and provides important information on the ecology of fishes in the western Great Plains of North America. ?? Blackwell Munksgaard, 2004.

Racial residential segregation and preterm birth: built environment as a mediator.

PubMed

Anthopolos, Rebecca; Kaufman, Jay S; Messer, Lynne C; Miranda, Marie Lynn

2014-05-01

Racial residential segregation has been associated with preterm birth. Few studies have examined mediating pathways, in part because, with binary outcomes, indirect effects estimated from multiplicative models generally lack causal interpretation. We develop a method to estimate additive-scale natural direct and indirect effects from logistic regression. We then evaluate whether segregation operates through poor-quality built environment to affect preterm birth. To estimate natural direct and indirect effects, we derive risk differences from logistic regression coefficients. Birth records (2000-2008) for Durham, North Carolina, were linked to neighborhood-level measures of racial isolation and a composite construct of poor-quality built environment. We decomposed the total effect of racial isolation on preterm birth into direct and indirect effects. The adjusted total effect of an interquartile increase in racial isolation on preterm birth was an extra 27 preterm events per 1000 births (risk difference = 0.027 [95% confidence interval = 0.007 to 0.047]). With poor-quality built environment held at the level it would take under isolation at the 25th percentile, the direct effect of an interquartile increase in isolation was 0.022 (-0.001 to 0.042). Poor-quality built environment accounted for 35% (11% to 65%) of the total effect. Our methodology facilitates the estimation of additive-scale natural effects with binary outcomes. In this study, the total effect of racial segregation on preterm birth was partially mediated by poor-quality built environment.

Socioeconomic and Demographic Disparities in Knowledge of Reproductive Healthcare among Female University Students in Bangladesh

PubMed Central

Islam Mondal, Md. Nazrul; Nasir Ullah, Md. Monzur Morshad; Khan, Md. Nuruzzaman; Islam, Mohammad Zamirul; Islam, Md. Nurul; Moni, Sabiha Yasmin; Hoque, Md. Nazrul; Rahman, Md. Mashiur

2015-01-01

Background: Reproductive health (RH) is a critical component of women’s health and overall well-being around the world, especially in developing countries. We examine the factors that determine knowledge of RH care among female university students in Bangladesh. Methods: Data on 300 female students were collected from Rajshahi University, Bangladesh through a structured questionnaire using purposive sampling technique. The data were used for univariate analysis, to carry out the description of the variables; bivariate analysis was used to examine the associations between the variables; and finally, multivariate analysis (binary logistic regression model) was used to examine and fit the model and interpret the parameter estimates, especially in terms of odds ratios. Results: The results revealed that more than one-third (34.3%) respondents do not have sufficient knowledge of RH care. The χ2-test identified the significant (p < 0.05) associations between respondents’ knowledge of RH care with respondents’ age, education, family type, watching television; and knowledge about pregnancy, family planning, and contraceptive use. Finally, the binary logistic regression model identified respondents’ age, education, family type; and knowledge about family planning, and contraceptive use as the significant (p < 0.05) predictors of RH care. Conclusions and Global Health Implications: Knowledge of RH care among female university students was found unsatisfactory. Government and concerned organizations should promote and strengthen various health education programs to focus on RH care especially for the female university students in Bangladesh. PMID:27622005

Factors associated with trait anger level of juvenile offenders in Hubei province: A binary logistic regression analysis.

PubMed

Tang, Li-Na; Ye, Xiao-Zhou; Yan, Qiu-Ge; Chang, Hong-Juan; Ma, Yu-Qiao; Liu, De-Bin; Li, Zhi-Gen; Yu, Yi-Zhen

2017-02-01

The risk factors of high trait anger of juvenile offenders were explored through questionnaire study in a youth correctional facility of Hubei province, China. A total of 1090 juvenile offenders in Hubei province were investigated by self-compiled social-demographic questionnaire, Childhood Trauma Questionnaire (CTQ), and State-Trait Anger Expression Inventory-II (STAXI-II). The risk factors were analyzed by chi-square tests, correlation analysis, and binary logistic regression analysis with SPSS 19.0. A total of 1082 copies of valid questionnaires were collected. High trait anger group (n=316) was defined as those who scored in the upper 27th percentile of STAXI-II trait anger scale (TAS), and the rest were defined as low trait anger group (n=766). The risk factors associated with high level of trait anger included: childhood emotional abuse, childhood sexual abuse, step family, frequent drug abuse, and frequent internet using (P<0.05 or P<0.01). Birth sequence, number of sibling, ranking in the family, identity of the main care-taker, the education level of care-taker, educational style of care-taker, family income, relationship between parents, social atmosphere of local area, frequent drinking, and frequent smoking did not predict to high level of trait anger (P>0.05). It was suggested that traumatic experience in childhood and unhealthy life style may significantly increase the level of trait anger in adulthood. The risk factors of high trait anger and their effects should be taken into consideration seriously.

Characterization of serum microRNAs profile of PCOS and identification of novel non-invasive biomarkers.

PubMed

Long, Wei; Zhao, Chun; Ji, Chenbo; Ding, Hongjuan; Cui, Yugui; Guo, Xirong; Shen, Rong; Liu, Jiayin

2014-01-01

Polycystic ovary syndrome (PCOS), the most common endocrinopathy in women of reproductive age, is characterized by polycystic ovaries, chronic anovulation, hyperandrogenism and insulin resistance. Despite the high prevalence of hyperandrogenemia, a definitive endocrine marker for PCOS has so far not been identified. Circulating miRNAs have recently been shown to serve as diagnostic/prognostic biomarkers in patients with cancers. Our current study focused on the altered expression of serum miRNAs and their correlation with PCOS. We systematically used the TaqMan Low Density Array followed by individual quantitative reverse transcription polymerase chain reaction assays to identify and validate the expression of serum miRNAs of PCOS patients. The expression levels of three miRNAs (miR-222, miR-146a and miR-30c) were significantly increased in PCOS patients with respect to the controls in our discovery evaluation and followed validation. The area under the receiver operating characteristic (ROC) curve (AUC) is 0.799, 0.706, and 0.688, respectively. The combination of the three miRNAs using multiple logistic regression analysis showed a larger AUC (0.852) that was more efficient for the diagnosis of PCOS. In addition, logistic binary regression analyses show miR-222 is positively associated with serum insulin, while miR-146a is negatively associated with serum testosterone. Furthermore, bioinformatics analysis indicated that the predicted targets function of the three miRNAs mainly involved in the metastasis, cell cycle, apoptosis and endocrine. Serum miRNAs are differentially expressed between PCOS patients and controls. We identified and validated a class of three serum miRNAs that could act as novel non-invasive biomarkers for diagnosis of PCOS. These miRNAs may be involved in the pathogenesis of PCOS. © 2014 S. Karger AG, Basel.

Metformin for treatment of antipsychotic-induced amenorrhea and weight gain in women with first-episode schizophrenia: a double-blind, randomized, placebo-controlled study.

PubMed

Wu, Ren-Rong; Jin, Hua; Gao, Keming; Twamley, Elizabeth W; Ou, Jian-Jun; Shao, Ping; Wang, Juan; Guo, Xiao-Feng; Davis, John M; Chan, Philip K; Zhao, Jing-Ping

2012-08-01

Data on the treatment of antipsychotic-induced amenorrhea, particularly when occurring with weight gain, are limited. The authors investigated the efficacy and safety of metformin in the treatment of antipsychotic-induced amenorrhea and weight gain in women with first-episode schizophrenia. Eighty-four women (ages 18-40 years) with first-episode schizophrenia who suffered from amenorrhea during antipsychotic treatment were randomly assigned, in a double-blind study design, to receive 1000 mg/day of metformin or placebo in addition to their antipsychotic treatment for 6 months. The primary outcome measures were restoration of menstruation and change in body weight and body mass index (BMI). Secondary outcome measures were changes in levels of prolactin, luteinizing hormone (LH), follicle-stimulating hormone (FSH), estradiol, and testosterone; in fasting levels of insulin and glucose; in LH/FSH ratio; and in insulin resistance index. Repeated mixed models with repeated-measures regression analyses and binary logistic regression were used in the analysis. A total of 76 patients completed the 6-month trial. Significantly more patients in the metformin group (N=28, 66.7%) than in placebo group (N=2, 4.8%) resumed their menstruation. Among patients treated with metformin, BMI decreased by a mean of 0.93 and the insulin resistance index by 2.04. In contrast, patients who received placebo had a mean increase in BMI of 0.85. The prolactin, LH, and testosterone levels and LH/FSH ratio decreased significantly in the metformin group at months 2, 4, and 6, but these levels did not change in the placebo group. Metformin was effective in reversing antipsychotic-induced adverse events, including restoration of menstruation, promotion of weight loss, and improvement in insulin resistance in female patients with schizophrenia.

Correlates of poly-tobacco use among youth and young adults: Findings from the Population Assessment of Tobacco and Health study, 2013-2014.

PubMed

Osibogun, Olatokunbo; Taleb, Ziyad Ben; Bahelah, Raed; Salloum, Ramzi G; Maziak, Wasim

2018-06-01

Poly-tobacco use is common among youth and young adults. This study examined sociodemographic, tobacco-related, and substance use characteristics of poly-tobacco use compared to mono-tobacco use among youth and young adults (12-34 years) in the United States. We conducted a descriptive analysis by age-group of 12898 youth (12-17 years), 8843 younger young adults (18-24 years), and 6081 older young adults (24-34 years) from the 2013-2014 Population Assessment of Tobacco and Health study. Multiple logistic regression modeling was conducted to assess the sociodemographic, tobacco-related, and substance use associations with current (past 30 days) tobacco use on a binary scale (poly- versus mono-tobacco use) among tobacco users. Between 2013 and 2014, 3.6% of youth, 21.7% of younger young adults, and 15.8% of older young adults were current poly-tobacco users in the general population. In the regression analyses, among youth tobacco users, heavy drinking was the only factor associated with higher odds of poly-tobacco use. Factors associated with higher odds of poly-tobacco use among younger young adults included being male, having less than high school diploma or GED, residing in the South, having 2 and ≥3 quit attempts, heavy drinking, and marijuana use. Residing in the South, older ages of exposure to tobacco use, and marijuana use were associated with higher odds of poly-tobacco use among older young adults. Regardless of tobacco product type, poly-tobacco use was common among youth and young adults. Interventions designed to address factors associated with poly-tobacco use among youth and young adults are warranted. Published by Elsevier B.V.