Floating Data and the Problem with Illustrating Multiple Regression.
ERIC Educational Resources Information Center
Sachau, Daniel A.
2000-01-01
Discusses how to introduce basic concepts of multiple regression by creating a large-scale, three-dimensional regression model using the classroom walls and floor. Addresses teaching points that should be covered and reveals student reaction to the model. Finds that the greatest benefit of the model is the low fear, walk-through, nonmathematical…
Kuiper, Gerhardus J A J M; Houben, Rik; Wetzels, Rick J H; Verhezen, Paul W M; Oerle, Rene van; Ten Cate, Hugo; Henskens, Yvonne M C; Lancé, Marcus D
2017-11-01
Low platelet counts and hematocrit levels hinder whole blood point-of-care testing of platelet function. Thus far, no reference ranges for MEA (multiple electrode aggregometry) and PFA-100 (platelet function analyzer 100) devices exist for low ranges. Through dilution methods of volunteer whole blood, platelet function at low ranges of platelet count and hematocrit levels was assessed on MEA for four agonists and for PFA-100 in two cartridges. Using (multiple) regression analysis, 95% reference intervals were computed for these low ranges. Low platelet counts affected MEA in a positive correlation (all agonists showed r 2 ≥ 0.75) and PFA-100 in an inverse correlation (closure times were prolonged with lower platelet counts). Lowered hematocrit did not affect MEA testing, except for arachidonic acid activation (ASPI), which showed a weak positive correlation (r 2 = 0.14). Closure time on PFA-100 testing was inversely correlated with hematocrit for both cartridges. Regression analysis revealed different 95% reference intervals in comparison with originally established intervals for both MEA and PFA-100 in low platelet or hematocrit conditions. Multiple regression analysis of ASPI and both tests on the PFA-100 for combined low platelet and hematocrit conditions revealed that only PFA-100 testing should be adjusted for both thrombocytopenia and anemia. 95% reference intervals were calculated using multiple regression analysis. However, coefficients of determination of PFA-100 were poor, and some variance remained unexplained. Thus, in this pilot study using (multiple) regression analysis, we could establish reference intervals of platelet function in anemia and thrombocytopenia conditions on PFA-100 and in thrombocytopenia conditions on MEA.
Riley, Richard D; Ensor, Joie; Jackson, Dan; Burke, Danielle L
2017-01-01
Many meta-analysis models contain multiple parameters, for example due to multiple outcomes, multiple treatments or multiple regression coefficients. In particular, meta-regression models may contain multiple study-level covariates, and one-stage individual participant data meta-analysis models may contain multiple patient-level covariates and interactions. Here, we propose how to derive percentage study weights for such situations, in order to reveal the (otherwise hidden) contribution of each study toward the parameter estimates of interest. We assume that studies are independent, and utilise a decomposition of Fisher's information matrix to decompose the total variance matrix of parameter estimates into study-specific contributions, from which percentage weights are derived. This approach generalises how percentage weights are calculated in a traditional, single parameter meta-analysis model. Application is made to one- and two-stage individual participant data meta-analyses, meta-regression and network (multivariate) meta-analysis of multiple treatments. These reveal percentage study weights toward clinically important estimates, such as summary treatment effects and treatment-covariate interactions, and are especially useful when some studies are potential outliers or at high risk of bias. We also derive percentage study weights toward methodologically interesting measures, such as the magnitude of ecological bias (difference between within-study and across-study associations) and the amount of inconsistency (difference between direct and indirect evidence in a network meta-analysis).
Suzuki, Taku; Iwamoto, Takuji; Shizu, Kanae; Suzuki, Katsuji; Yamada, Harumoto; Sato, Kazuki
2017-05-01
This retrospective study was designed to investigate prognostic factors for postoperative outcomes for cubital tunnel syndrome (CubTS) using multiple logistic regression analysis with a large number of patients. Eighty-three patients with CubTS who underwent surgeries were enrolled. The following potential prognostic factors for disease severity were selected according to previous reports: sex, age, type of surgery, disease duration, body mass index, cervical lesion, presence of diabetes mellitus, Workers' Compensation status, preoperative severity, and preoperative electrodiagnostic testing. Postoperative severity of disease was assessed 2 years after surgery by Messina's criteria which is an outcome measure specifically for CubTS. Bivariate analysis was performed to select candidate prognostic factors for multiple linear regression analyses. Multiple logistic regression analysis was conducted to identify the association between postoperative severity and selected prognostic factors. Both bivariate and multiple linear regression analysis revealed only preoperative severity as an independent risk factor for poor prognosis, while other factors did not show any significant association. Although conflicting results exist regarding prognosis of CubTS, this study supports evidence from previous studies and concludes early surgical intervention portends the most favorable prognosis. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Kiss, I.; Cioată, V. G.; Ratiu, S. A.; Rackov, M.; Penčić, M.
2018-01-01
Multivariate research is important in areas of cast-iron brake shoes manufacturing, because many variables interact with each other simultaneously. This article focuses on expressing the multiple linear regression model related to the hardness assurance by the chemical composition of the phosphorous cast irons destined to the brake shoes, having in view that the regression coefficients will illustrate the unrelated contributions of each independent variable towards predicting the dependent variable. In order to settle the multiple correlations between the hardness of the cast-iron brake shoes, and their chemical compositions several regression equations has been proposed. Is searched a mathematical solution which can determine the optimum chemical composition for the hardness desirable values. Starting from the above-mentioned affirmations two new statistical experiments are effectuated related to the values of Phosphorus [P], Manganese [Mn] and Silicon [Si]. Therefore, the regression equations, which describe the mathematical dependency between the above-mentioned elements and the hardness, are determined. As result, several correlation charts will be revealed.
Rahman, Md. Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D. W.; Labrique, Alain B.; Rashid, Mahbubur; Christian, Parul; West, Keith P.
2017-01-01
Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 − -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset. PMID:29261760
Kabir, Alamgir; Rahman, Md Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D W; Labrique, Alain B; Rashid, Mahbubur; Christian, Parul; West, Keith P
2017-01-01
Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 - -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset.
Metsemakers, W-J; Handojo, K; Reynders, P; Sermon, A; Vanderschot, P; Nijs, S
2015-04-01
Despite modern advances in the treatment of tibial shaft fractures, complications including nonunion, malunion, and infection remain relatively frequent. A better understanding of these injuries and its complications could lead to prevention rather than treatment strategies. A retrospective study was performed to identify risk factors for deep infection and compromised fracture healing after intramedullary nailing (IMN) of tibial shaft fractures. Between January 2000 and January 2012, 480 consecutive patients with 486 tibial shaft fractures were enrolled in the study. Statistical analysis was performed to determine predictors of deep infection and compromised fracture healing. Compromised fracture healing was subdivided in delayed union and nonunion. The following independent variables were selected for analysis: age, sex, smoking, obesity, diabetes, American Society of Anaesthesiologists (ASA) classification, polytrauma, fracture type, open fractures, Gustilo type, primary external fixation (EF), time to nailing (TTN) and reaming. As primary statistical evaluation we performed a univariate analysis, followed by a multiple logistic regression model. Univariate regression analysis revealed similar risk factors for delayed union and nonunion, including fracture type, open fractures and Gustilo type. Factors affecting the occurrence of deep infection in this model were primary EF, a prolonged TTN, open fractures and Gustilo type. Multiple logistic regression analysis revealed polytrauma as the single risk factor for nonunion. With respect to delayed union, no risk factors could be identified. In the same statistical model, deep infection was correlated with primary EF. The purpose of this study was to evaluate risk factors of poor outcome after IMN of tibial shaft fractures. The univariate regression analysis showed that the nature of complications after tibial shaft nailing could be multifactorial. This was not confirmed in a multiple logistic regression model, which only revealed polytrauma and primary EF as risk factors for nonunion and deep infection, respectively. Future strategies should focus on prevention in high-risk populations such as polytrauma patients treated with EF. Copyright © 2014 Elsevier Ltd. All rights reserved.
Viswanathan, M; Pearl, D L; Taboada, E N; Parmley, E J; Mutschall, S K; Jardine, C M
2017-05-01
Using data collected from a cross-sectional study of 25 farms (eight beef, eight swine and nine dairy) in 2010, we assessed clustering of molecular subtypes of C. jejuni based on a Campylobacter-specific 40 gene comparative genomic fingerprinting assay (CGF40) subtypes, using unweighted pair-group method with arithmetic mean (UPGMA) analysis, and multiple correspondence analysis. Exact logistic regression was used to determine which genes differentiate wildlife and livestock subtypes in our study population. A total of 33 bovine livestock (17 beef and 16 dairy), 26 wildlife (20 raccoon (Procyon lotor), five skunk (Mephitis mephitis) and one mouse (Peromyscus spp.) C. jejuni isolates were subtyped using CGF40. Dendrogram analysis, based on UPGMA, showed distinct branches separating bovine livestock and mammalian wildlife isolates. Furthermore, two-dimensional multiple correspondence analysis was highly concordant with dendrogram analysis showing clear differentiation between livestock and wildlife CGF40 subtypes. Based on multilevel logistic regression models with a random intercept for farm of origin, we found that isolates in general, and raccoons more specifically, were significantly more likely to be part of the wildlife branch. Exact logistic regression conducted gene by gene revealed 15 genes that were predictive of whether an isolate was of wildlife or bovine livestock isolate origin. Both multiple correspondence analysis and exact logistic regression revealed that in most cases, the presence of a particular gene (13 of 15) was associated with an isolate being of livestock rather than wildlife origin. In conclusion, the evidence gained from dendrogram analysis, multiple correspondence analysis and exact logistic regression indicates that mammalian wildlife carry CGF40 subtypes of C. jejuni distinct from those carried by bovine livestock. Future studies focused on source attribution of C. jejuni in human infections will help determine whether wildlife transmit Campylobacter jejuni directly to humans. © 2016 Blackwell Verlag GmbH.
Gordon, Evan M.; Stollstorff, Melanie; Vaidya, Chandan J.
2012-01-01
Many researchers have noted that the functional architecture of the human brain is relatively invariant during task performance and the resting state. Indeed, intrinsic connectivity networks (ICNs) revealed by resting-state functional connectivity analyses are spatially similar to regions activated during cognitive tasks. This suggests that patterns of task-related activation in individual subjects may result from the engagement of one or more of these ICNs; however, this has not been tested. We used a novel analysis, spatial multiple regression, to test whether the patterns of activation during an N-back working memory task could be well described by a linear combination of ICNs delineated using Independent Components Analysis at rest. We found that across subjects, the cingulo-opercular Set Maintenance ICN, as well as right and left Frontoparietal Control ICNs, were reliably activated during working memory, while Default Mode and Visual ICNs were reliably deactivated. Further, involvement of Set Maintenance, Frontoparietal Control, and Dorsal Attention ICNs was sensitive to varying working memory load. Finally, the degree of left Frontoparietal Control network activation predicted response speed, while activation in both left Frontoparietal Control and Dorsal Attention networks predicted task accuracy. These results suggest that a close relationship between resting-state networks and task-evoked activation is functionally relevant for behavior, and that spatial multiple regression analysis is a suitable method for revealing that relationship. PMID:21761505
Cruz, Antonio M; Barr, Cameron; Puñales-Pozo, Elsa
2008-01-01
This research's main goals were to build a predictor for a turnaround time (TAT) indicator for estimating its values and use a numerical clustering technique for finding possible causes of undesirable TAT values. The following stages were used: domain understanding, data characterisation and sample reduction and insight characterisation. Building the TAT indicator multiple linear regression predictor and clustering techniques were used for improving corrective maintenance task efficiency in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). Multiple linear regression was used for building a predictive TAT value model. The variables contributing to such model were clinical engineering department response time (CE(rt), 0.415 positive coefficient), stock service response time (Stock(rt), 0.734 positive coefficient), priority level (0.21 positive coefficient) and service time (0.06 positive coefficient). The regression process showed heavy reliance on Stock(rt), CE(rt) and priority, in that order. Clustering techniques revealed the main causes of high TAT values. This examination has provided a means for analysing current technical service quality and effectiveness. In doing so, it has demonstrated a process for identifying areas and methods of improvement and a model against which to analyse these methods' effectiveness.
Ng, Kar Yong; Awang, Norhashidah
2018-01-06
Frequent haze occurrences in Malaysia have made the management of PM 10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM 10 variation and good forecast of PM 10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM 10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants. Three different models were built. They were multiple linear regression (MLR) model with lagged predictor variables (MLR1), MLR model with lagged predictor variables and PM 10 concentrations (MLR2) and regression with time series error (RTSE) model. The findings revealed that humidity, temperature, wind speed, wind direction, carbon monoxide and ozone were the main factors explaining the PM 10 variation in Peninsular Malaysia. Comparison among the three models showed that MLR2 model was on a same level with RTSE model in terms of forecasting accuracy, while MLR1 model was the worst.
An Exploratory Study of Religion and Trust in Ghana
ERIC Educational Resources Information Center
Addai, Isaac; Opoku-Agyeman, Chris; Ghartey, Helen Tekyiwa
2013-01-01
Based on individual-level data from 2008 Afro-barometer survey, this study explores the relationship between religion (religious affiliation and religious importance) and trust (interpersonal and institutional) among Ghanaians. Employing hierarchical multiple regression technique, our analyses reveal a positive relationship between religious…
Perceived Parenting Styles on College Students' Optimism
ERIC Educational Resources Information Center
Baldwin, Debora R.; McIntyre, Anne; Hardaway, Elizabeth
2007-01-01
The purpose of this study was to examine the relationship between perceived parenting styles and levels of optimism in undergraduate college students. Sixty-three participants were administered surveys measuring dispositional optimism and perceived parental Authoritative and Authoritarian styles. Multiple regression analysis revealed that both…
Death Anxiety as a Function of Aging Anxiety
ERIC Educational Resources Information Center
Benton, Jeremy P.; Christopher, Andrew N.; Walter, Mark I.
2007-01-01
To assess how different facets of aging anxiety contributed to the prediction of tangible and existential death anxiety, 167 Americans of various Christian denominations completed a battery of questionnaires. Multiple regression analyses, controlling for demographic variables and previously demonstrated predictors of death anxiety, revealed that…
Long-Distance and Proximal Romantic Relationship Satisfaction: Attachment and Closeness Predictors
ERIC Educational Resources Information Center
Roberts, Amber; Pistole, M. Carole
2009-01-01
Relationship satisfaction was examined in college student long-distance romantic relationships (LDRRs) and geographically proximal romantic relationships (PRRs). LDRR/PRR attachment style proportions and relationship satisfaction were similar. Multiple regression analyses revealed that low attachment avoidance contributed uniquely to high LDRR…
Locomotive syndrome is associated not only with physical capacity but also degree of depression.
Ikemoto, Tatsunori; Inoue, Masayuki; Nakata, Masatoshi; Miyagawa, Hirofumi; Shimo, Kazuhiro; Wakabayashi, Toshiko; Arai, Young-Chang P; Ushida, Takahiro
2016-05-01
Reports of locomotive syndrome (LS) have recently been increasing. Although physical performance measures for LS have been well investigated to date, studies including psychiatric assessment are still scarce. Hence, the aim of this study was to investigate both physical and mental parameters in relation to presence and severity of LS using a 25-question geriatric locomotive function scale (GLFS-25) questionnaire. 150 elderly people aged over 60 years who were members of our physical-fitness center and displayed well-being were enrolled in this study. Firstly, using the previously determined GLFS-25 cutoff value (=16 points), subjects were divided into two groups accordingly: an LS and non-LS group in order to compare each parameter (age, grip strength, timed-up-and-go test (TUG), one-leg standing with eye open, back muscle and leg muscle strength, degree of depression and cognitive impairment) between the groups using the Mann-Whitney U-test followed by multiple logistic regression analysis. Secondly, a multiple linear regression was conducted to determine which variables showed the strongest correlation with severity of LS. We confirmed 110 people for non-LS (73%) and 40 people for LS using the GLFS-25 cutoff value. Comparative analysis between LS and non-LS revealed significant differences in parameters in age, grip strength, TUG, one-leg standing, back muscle strength and degree of depression (p < 0.006, after Bonferroni correction). Multiple logistic regression revealed that functional decline in grip strength, TUG and one-leg standing and degree of depression were significantly associated with LS. On the other hand, we observed that the significant contributors towards the GLFS-25 score were TUG and degree of depression in multiple linear regression analysis. The results indicate that LS is associated with not only the capacity of physical performance but also the degree of depression although most participants fell under the criteria of LS. Copyright © 2016 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.
Feminist identity as a predictor of eating disorder diagnostic status.
Green, Melinda A; Scott, Norman A; Riopel, Cori M; Skaggs, Anna K
2008-06-01
Passive Acceptance (PA) and Active Commitment (AC) subscales of the Feminist Identity Development Scale (FIDS) were examined as predictors of eating disorder diagnostic status as assessed by the Questionnaire for Eating Disorder Diagnoses (Q-EDD). Results of a hierarchical regression analysis revealed PA and AC scores were not statistically significant predictors of ED diagnostic status after controlling for diagnostic subtype. Results of a multiple regression analysis revealed FIDS as a statistically significant predictor of ED diagnostic status when failing to control for ED diagnostic subtype. Discrepancies suggest ED diagnostic subtype may serve as a moderator variable in the relationship between ED diagnostic status and FIDS. (c) 2008 Wiley Periodicals, Inc.
Francoeur, Richard B
2015-01-01
Background The majority of patients with advanced cancer experience symptom pairs or clusters among pain, fatigue, and insomnia. Improved methods are needed to detect and interpret interactions among symptoms or diesease markers to reveal influential pairs or clusters. In prior work, I developed and validated sequential residual centering (SRC), a method that improves the sensitivity of multiple regression to detect interactions among predictors, by conditioning for multicollinearity (shared variation) among interactions and component predictors. Materials and methods Using a hypothetical three-way interaction among pain, fatigue, and sleep to predict depressive affect, I derive and explain SRC multiple regression. Subsequently, I estimate raw and SRC multiple regressions using real data for these symptoms from 268 palliative radiation outpatients. Results Unlike raw regression, SRC reveals that the three-way interaction (pain × fatigue/weakness × sleep problems) is statistically significant. In follow-up analyses, the relationship between pain and depressive affect is aggravated (magnified) within two partial ranges: 1) complete-to-some control over fatigue/weakness when there is complete control over sleep problems (ie, a subset of the pain–fatigue/weakness symptom pair), and 2) no control over fatigue/weakness when there is some-to-no control over sleep problems (ie, a subset of the pain–fatigue/weakness–sleep problems symptom cluster). Otherwise, the relationship weakens (buffering) as control over fatigue/weakness or sleep problems diminishes. Conclusion By reducing the standard error, SRC unmasks a three-way interaction comprising a symptom pair and cluster. Low-to-moderate levels of the moderator variable for fatigue/weakness magnify the relationship between pain and depressive affect. However, when the comoderator variable for sleep problems accompanies fatigue/weakness, only frequent or unrelenting levels of both symptoms magnify the relationship. These findings suggest that a countervailing mechanism involving depressive affect could account for the effectiveness of a cognitive behavioral intervention to reduce the severity of a pain, fatigue, and sleep disturbance cluster in a previous randomized trial. PMID:25565865
Francoeur, Richard B
2015-01-01
The majority of patients with advanced cancer experience symptom pairs or clusters among pain, fatigue, and insomnia. Improved methods are needed to detect and interpret interactions among symptoms or diesease markers to reveal influential pairs or clusters. In prior work, I developed and validated sequential residual centering (SRC), a method that improves the sensitivity of multiple regression to detect interactions among predictors, by conditioning for multicollinearity (shared variation) among interactions and component predictors. Using a hypothetical three-way interaction among pain, fatigue, and sleep to predict depressive affect, I derive and explain SRC multiple regression. Subsequently, I estimate raw and SRC multiple regressions using real data for these symptoms from 268 palliative radiation outpatients. Unlike raw regression, SRC reveals that the three-way interaction (pain × fatigue/weakness × sleep problems) is statistically significant. In follow-up analyses, the relationship between pain and depressive affect is aggravated (magnified) within two partial ranges: 1) complete-to-some control over fatigue/weakness when there is complete control over sleep problems (ie, a subset of the pain-fatigue/weakness symptom pair), and 2) no control over fatigue/weakness when there is some-to-no control over sleep problems (ie, a subset of the pain-fatigue/weakness-sleep problems symptom cluster). Otherwise, the relationship weakens (buffering) as control over fatigue/weakness or sleep problems diminishes. By reducing the standard error, SRC unmasks a three-way interaction comprising a symptom pair and cluster. Low-to-moderate levels of the moderator variable for fatigue/weakness magnify the relationship between pain and depressive affect. However, when the comoderator variable for sleep problems accompanies fatigue/weakness, only frequent or unrelenting levels of both symptoms magnify the relationship. These findings suggest that a countervailing mechanism involving depressive affect could account for the effectiveness of a cognitive behavioral intervention to reduce the severity of a pain, fatigue, and sleep disturbance cluster in a previous randomized trial.
Birthweight Related Factors in Northwestern Iran: Using Quantile Regression Method.
Fallah, Ramazan; Kazemnejad, Anoshirvan; Zayeri, Farid; Shoghli, Alireza
2015-11-18
Birthweight is one of the most important predicting indicators of the health status in adulthood. Having a balanced birthweight is one of the priorities of the health system in most of the industrial and developed countries. This indicator is used to assess the growth and health status of the infants. The aim of this study was to assess the birthweight of the neonates by using quantile regression in Zanjan province. This analytical descriptive study was carried out using pre-registered (March 2010 - March 2012) data of neonates in urban/rural health centers of Zanjan province using multiple-stage cluster sampling. Data were analyzed using multiple linear regressions andquantile regression method and SAS 9.2 statistical software. From 8456 newborn baby, 4146 (49%) were female. The mean age of the mothers was 27.1±5.4 years. The mean birthweight of the neonates was 3104 ± 431 grams. Five hundred and seventy-three patients (6.8%) of the neonates were less than 2500 grams. In all quantiles, gestational age of neonates (p<0.05), weight and educational level of the mothers (p<0.05) showed a linear significant relationship with the i of the neonates. However, sex and birth rank of the neonates, mothers age, place of residence (urban/rural) and career were not significant in all quantiles (p>0.05). This study revealed the results of multiple linear regression and quantile regression were not identical. We strictly recommend the use of quantile regression when an asymmetric response variable or data with outliers is available.
Birthweight Related Factors in Northwestern Iran: Using Quantile Regression Method
Fallah, Ramazan; Kazemnejad, Anoshirvan; Zayeri, Farid; Shoghli, Alireza
2016-01-01
Introduction: Birthweight is one of the most important predicting indicators of the health status in adulthood. Having a balanced birthweight is one of the priorities of the health system in most of the industrial and developed countries. This indicator is used to assess the growth and health status of the infants. The aim of this study was to assess the birthweight of the neonates by using quantile regression in Zanjan province. Methods: This analytical descriptive study was carried out using pre-registered (March 2010 - March 2012) data of neonates in urban/rural health centers of Zanjan province using multiple-stage cluster sampling. Data were analyzed using multiple linear regressions andquantile regression method and SAS 9.2 statistical software. Results: From 8456 newborn baby, 4146 (49%) were female. The mean age of the mothers was 27.1±5.4 years. The mean birthweight of the neonates was 3104 ± 431 grams. Five hundred and seventy-three patients (6.8%) of the neonates were less than 2500 grams. In all quantiles, gestational age of neonates (p<0.05), weight and educational level of the mothers (p<0.05) showed a linear significant relationship with the i of the neonates. However, sex and birth rank of the neonates, mothers age, place of residence (urban/rural) and career were not significant in all quantiles (p>0.05). Conclusion: This study revealed the results of multiple linear regression and quantile regression were not identical. We strictly recommend the use of quantile regression when an asymmetric response variable or data with outliers is available. PMID:26925889
The Effects of Home-School Dissonance on African American Male High School Students
ERIC Educational Resources Information Center
Brown-Wright, Lynda; Tyler, Kenneth Maurice
2010-01-01
The current study examined associations between home-school dissonance and several academic and psychological variables among 80 African American male high school students. Regression analyses revealed that home-school dissonance significantly predicted multiple academic and psychological variables, including amotivation, academic cheating,…
Correlates of Successful Aging: Are They Universal?
ERIC Educational Resources Information Center
Litwin, Howard
2005-01-01
The analysis compared differing correlates of life satisfaction among three diverse population groups in Israel, examining background and health status variables, social environment factors, and activity indicators. Multiple regression analysis revealed that veteran Jewish-Israelis (n = 2,043) had the largest set of predictors, the strongest of…
ERIC Educational Resources Information Center
Hartwig, Elizabeth Kjellstrand; Van Overschelde, James P.
2016-01-01
The authors investigated predictor variables for the Counselor Preparation Comprehensive Examination (CPCE) to examine whether academic variables, demographic variables, and test version were associated with graduate counseling students' CPCE scores. Multiple regression analyses revealed all 3 variables were statistically significant predictors of…
ERIC Educational Resources Information Center
Smokowski, Paul R.; Bacallao, Martica L.
2007-01-01
This investigation examined acculturation risk factors and cultural assets, internalizing behavioral problems, and self-esteem in 323 Latino adolescents living in North Carolina. Multiple regression analyses revealed two risk factors--perceived discrimination and parent-adolescent conflict--as highly significant predictors of adolescent…
Summer School Effects in a Randomized Field Trial
ERIC Educational Resources Information Center
Zvoch, Keith; Stevens, Joseph J.
2013-01-01
This field-based randomized trial examined the effect of assignment to and participation in summer school for two moderately at-risk samples of struggling readers. Application of multiple regression models to difference scores capturing the change in summer reading fluency revealed that kindergarten students randomly assigned to summer school…
Rural Economic Development: What Makes Rural Communities Grow?
ERIC Educational Resources Information Center
Aldrich, Lorna; Kusmin, Lorin
This report identifies local factors that foster rural economic growth. A review of the literature revealed potential indicators of county economic growth, and those indicators were then tested against data for nonmetro counties during the 1980s using multiple regression analysis. The principal variables examined included demographic and labor…
USDA-ARS?s Scientific Manuscript database
Isothermal inactivation studies are commonly used to quantify thermal inactivation kinetics of bacteria. Meta-analyses and comparisons utilizing results from multiple sources have revealed large variations in reported inactivation parameters for Salmonella, even in similar food materials. Different ...
Explaining the Long Reach of Fathers' Prenatal Involvement on Later Paternal Engagement
ERIC Educational Resources Information Center
Cabrera, Natasha J.; Fagan, Jay; Farrie, Danielle
2008-01-01
The present study examined the association between unmarried fathers' prenatal involvement and fathers' engagement later in the child's life. The study sample consisted of 1,686 fathers from the Fragile Families and Child Wellbeing Study. Findings using multiple regressions revealed that fathers' prenatal involvement is significantly and…
Aghamolaei, Teamur; Sadat Tavafian, Sedigheh; Madani, Abdoulhossain
2012-09-01
This study aimed to apply the conceptual framework of the theory of planned behavior (TPB) to explain fish consumption in a sample of people who lived in Bandar Abbass, Iran. We investigated the role of three traditional constructs of TPB that included attitude, social norms, and perceived behavioral control in an effort to characterize the intention to consume fish as well as the behavioral trends that characterize fish consumption. Data were derived from a cross-sectional sample of 321 subjects. Alpha coefficient correlation and linear regression analysis were applied to test the relationships between constructs. The predictors of fish consumption frequency were also evaluated. Multiple regression analysis revealed that attitude, subjective norms, and perceived behavioral control significantly predicted intention to eat fish (R2 = 0.54, F = 128.4, P < 0.001). Multiple regression analysis for the intention to eat fish and perceived behavioral control revealed that both factors significantly predicted fish consumption frequency (R2 = 0.58, F = 223.1, P < 0.001). The results indicated that the models fit well with the data. Attitude, subjective norms, and perceived behavioral control all had significant positive impacts on behavioral intention. Moreover, both intention and perceived behavioral control could be used to predict the frequency of fish consumption.
Song, Lingmin; Zhu, Yuchun; Han, Ping; Chen, Ni; Lin, Dao; Lai, Jianyu; Wei, Qiang
2011-03-01
To reveal the correlation between benign prostatic hyperplasia (BPH) histologic inflammation and serum prostate-specific antigen (sPSA) concentrations, and the possible mechanism. Patients underwent surgery at the Urology Department of West China Hospital of Sichuan University were retrospectively studied. Preoperative sPSA and transrectal ultrasonography were measured. According to the histopathological classification system for chronic prostatic inflammation proposed by the Chronic Prostatitis Collaborative Research Network (CPCRN) and the International Prostatitis Collaborative Network (IPCN), we classified the histologic sections of prostatic biopsy into glandular, periglandular, and stromal inflammation by the anatomical location of inflammatory infiltration. The glandular inflammation was graded according to the inflammatory aggressiveness. The periglandular and stromal inflammation were graded according to the inflammatory density. The correlation between histologic inflammation and sPSA was studied by a multiple regression model in conjunction with age and total prostatic volume. A total of 454 patients with exclusively BPH were analyzed. The periglandular inflammatory infiltration was the most common pattern (95.6%). Single regression analysis revealed that total prostatic volume, the aggressiveness of glandular inflammation, and the intensity of periglandular and stromal inflammation were correlated with sPSA. However, the multiple regression analysis revealed that only the total prostatic volume and the aggressiveness of glandular inflammation were correlated significantly with sPSA (R = .389, 0.289; P = .000). The aggressiveness of glandular inflammatory infiltration in BPH is a significant contributor to elevated sPSA levels. The theory of leakage may be the most reasonable mechanism to reveal the correlation morphologically. We should take inflammation into consideration when interpreting the abnormal elevating of sPSA levels. Copyright © 2011 Elsevier Inc. All rights reserved.
A sampling study on rock properties affecting drilling rate index (DRI)
NASA Astrophysics Data System (ADS)
Yenice, Hayati; Özdoğan, Mehmet V.; Özfırat, M. Kemal
2018-05-01
Drilling rate index (DRI) developed in Norway is a very useful index in determining the drillability of rocks and even in performance prediction of hard rock TBMs and it requires special laboratory test equipment. Drillability is one of the most important subjects in rock excavation. However, determining drillability index from physical and mechanical properties of rocks is very important for practicing engineers such as underground excavation, drilling operations in open pit mining, underground mining and natural stone production. That is why many researchers have studied concerned with drillability to find the correlations between drilling rate index (DRI) and penetration rate, influence of geological properties on drillability prediction in tunneling, correlations between rock properties and drillability. In this study, the relationships between drilling rate index (DRI) and some physico-mechanical properties (Density, Shore hardness, uniaxial compressive strength (UCS, σc), Indirect tensile strength (ITS, σt)) of three different rock groups including magmatic, sedimentary and metamorphic were evaluated using both simple and multiple regression analysis. This study reveals the effects of rock properties on DRI according to different types of rocks. In simple regression, quite high correlations were found between DRI and uniaxial compressive strength (UCS) and also between DRI and indirect tensile strength (ITS) values. Multiple regression analyses revealed even higher correlations when compared to simple regression. Especially, UCS, ITS, Shore hardness (SH) and the interactions between them were found to be very effective on DRI values.
Saleem, Taimur; Ishaque, Sidra; Habib, Nida; Hussain, Syedda Saadia; Jawed, Areeba; Khan, Aamir Ali; Ahmad, Muhammad Imran; Iftikhar, Mian Omer; Mughal, Hamza Pervez; Jehan, Imtiaz
2009-01-01
Background To determine the knowledge, attitudes and practices regarding organ donation in a selected adult population in Pakistan. Methods Convenience sampling was used to generate a sample of 440; 408 interviews were successfully completed and used for analysis. Data collection was carried out via a face to face interview based on a pre-tested questionnaire in selected public areas of Karachi, Pakistan. Data was analyzed using SPSS v.15 and associations were tested using the Pearson's Chi square test. Multiple logistic regression was used to find independent predictors of knowledge status and motivation of organ donation. Results Knowledge about organ donation was significantly associated with education (p = 0.000) and socioeconomic status (p = 0.038). 70/198 (35.3%) people expressed a high motivation to donate. Allowance of organ donation in religion was significantly associated with the motivation to donate (p = 0.000). Multiple logistic regression analysis revealed that higher level of education and higher socioeconomic status were significant (p < 0.05) independent predictors of knowledge status of organ donation. For motivation, multiple logistic regression revealed that higher socioeconomic status, adequate knowledge score and belief that organ donation is allowed in religion were significant (p < 0.05) independent predictors. Television emerged as the major source of information. Only 3.5% had themselves donated an organ; with only one person being an actual kidney donor. Conclusion Better knowledge may ultimately translate into the act of donation. Effective measures should be taken to educate people with relevant information with the involvement of media, doctors and religious scholars. PMID:19534793
Father Influences on Employed Mothers' Work-Family Balance
ERIC Educational Resources Information Center
Fagan, Jay; Press, Julie
2008-01-01
This study employed the ecological systems perspective and gender ideology theory to examine the influence of fathers' paid work-family crossover and family involvement on self-reports of work-family balance by employed mothers with children under the age of 13 (N = 179). Multiple regression analyses revealed that fathers' crossover factors had a…
Peer Influences on the Dating Aggression Process among Brazilian Street Youth: A Brief Report
ERIC Educational Resources Information Center
Antonio, Tiago; Koller, Silvia H.; Hokoda, Audrey
2012-01-01
This study explored risk factors for adolescent dating aggression (ADA) among Brazilian street youth. Forty-three adolescents, between the ages of 13 and 17 years, were recruited at services centers in Porto Alegre, Brazil. Simultaneous multiple regression revealed that ADA was significantly predicted by adolescent dating victimization (ADV), and…
Organizational Response to Conflict: Future Conflict and Work Outcomes
ERIC Educational Resources Information Center
Meyer, Susan
2004-01-01
The purpose of this study was to examine how on organization's response to conflict affected the amount and intensity of future conflict and negative work outcomes. In this cross-sectional study of 3,374 government service workers, bivariate correlations and multiple regressions revealed associations between managers' conflict-handling style (CHS)…
Predictors of Parenting and Infant Outcomes for Impoverished Adolescent Parents
ERIC Educational Resources Information Center
Whitson, Melissa L.; Martinez, Andrew; Ayala, Carmen; Kaufman, Joy S.
2011-01-01
Adolescent mothers and their children are at risk for a myriad of negative outcomes. This study examined risk and protective factors and their impact on a sample (N = 172) of impoverished adolescent mothers. Multiple regression analyses revealed that depressed adolescent mothers report higher levels of parenting stress and that their children are…
ERIC Educational Resources Information Center
Lease, Suzanne H.; Dahlbeck, David T.
2009-01-01
This study investigated the relations of maternal and paternal attachment, parenting styles, and career locus of control to college students' career decision self-efficacy and explored whether these relations differed by student gender. Data analysis using hierarchical multiple regression revealed that attachment was relevant for females' career…
Driving Privileges Facilitate Impaired Driving in Those Youths Who Use Alcohol or Marijuana
ERIC Educational Resources Information Center
Lewis, Todd F.; Scott Olds, R.; Thombs, Dennis L.; Ding, Kele
2009-01-01
The aim of this study was to determine whether possession of a driver's license increases the risk of impaired driving among adolescents who use alcohol or marijuana. An anonymous questionnaire was administered to secondary school students in northeast Ohio across multiple school districts. Logistic regression analyses revealed that after…
Sarcoidosis with Pancreatic Mass, Endobronchial Nodules, and Miliary Opacities in the Lung.
Matsuura, Shun; Mochizuka, Yasutaka; Oishi, Kyohei; Miyashita, Koichi; Naoi, Hyogo; Mochizuki, Eisuke; Mikura, Shinichiro; Tsukui, Masaru; Koshimizu, Naoki; Ohata, Akihiko; Suda, Takahumi
2017-11-15
Sarcoidosis affects multiple organs and rarely has unusual manifestations. A 78-year-old woman was referred to our hospital for coughing symptoms. A chest computed tomography (CT) scan revealed bilateral diffuse miliary patterns and right pleural effusion. Bronchoscopy showed multiple nodules in the carina and the bronchus intermedius. A CT scan of her abdomen revealed hypovascular lesions involving the pancreatic head and body. A transbronchial lung biopsy, bronchial mucosal biopsy, and endoscopic ultrasound-guided fine-needle aspiration of the pancreatic mass demonstrated non-caseating granulomas. We diagnosed the patient with sarcoidosis. She received no treatment for sarcoidosis and has been followed up for one year, during which no pulmonary disease progression had been observed and the pancreatic masses partially regressed.
Ho, S C; Chan, S G; Yip, Y B; Chan, C S Y; Woo, J L F; Sham, A
2008-12-01
This 30-month study investigating bone change and its determinants in 438 perimenopausal Chinese women revealed that the fastest bone loss occurred in women undergoing menopausal transition but maintenance of body weight and physical fitness were beneficial for bone health. Soy protein intake also seemed to exert a protective effect. This 30-month follow-up study aims to investigate change in bone mineral density and its determinants in Hong Kong Chinese perimenopausal women. Four hundred and thirty-eight women aged 45 to 55 years were recruited through random telephone dialing and primary care clinic. Bone mass, body composition, lifestyle measurements were obtained at baseline and at 9-, 18- and 30-month follow-ups. Univariate and stepwise multiple regression analyses were performed with the regression coefficients of BMD/C (derived from baseline and follow-up measurements) as the outcome variables. Menopausal status was classified as pre- or postmenopausal or transitional. Menopausal status was the strongest determinant of bone changes. An annual bone loss of about 0.5% was observed among premenopausal, 2% to 2.5% among transitional, and about 1.5% in postmenopausal women. Multiple regression analyses, revealed that a positive regression slope of body weight was protective for follow-up bone loss at all sites. Number of pregnancy, soy protein intake and walking were protective for total body BMC. Higher baseline LM was also protective for neck of femur BMD. Maintenance of body weight and physical fitness were observed to have a protective effect on for bone loss in Chinese perimenopausal women.
ERIC Educational Resources Information Center
Glenn, Norval D.; Shelton, Beth Ann
1983-01-01
Examined multiple regression results in adjusted percentages for data from a project to assess the impact of formative experiences on adult well being. Differences from some of the adjusted percentages reveal a divorce rate higher for female children of divorce and for individuals from a three-region "divorce belt." (Author/JAC)
Posttraumatic Stress in U.S. Marines: The Role of Unit Cohesion and Combat Exposure
ERIC Educational Resources Information Center
Armistead-Jehle, Patrick; Johnston, Scott L.; Wade, Nathaniel G.; Ecklund, Christofer J.
2011-01-01
Combat exposure is a consistent predictor of posttraumatic stress (PTS). Understanding factors that might buffer the effects of combat exposure is crucial for helping service members weather the stress of war. In a study of U.S. Marines returning from Iraq, hierarchical multiple regression analyses revealed that unit cohesion and combat exposure…
Multi scale habitat relationships of Martes americana in northern Idaho, U.S.A.
Tzeidle N. Wasserman; Samuel A. Cushman; David O. Wallin; Jim Hayden
2012-01-01
We used bivariate scaling and logistic regression to investigate multiple-scale habitat selection by American marten (Martes americana). Bivariate scaling reveals dramatic differences in the apparent nature and strength of relationships between marten occupancy and a number of habitat variables across a range of spatial scales. These differences include reversals in...
Sport Commitment among Competitive Female Gymnasts: A Developmental Perspective
ERIC Educational Resources Information Center
Weiss, Windee M.; Weiss, Maureen R.
2007-01-01
The purpose of this study was to examine age and competitive level differences in the relationship between determinants and level of sport commitment. Gymnasts (N = 304) comprised three age groups (8-11, 11-14.5, and 14.5-18 years) and two competitive levels (Levels 5-6 and 8-10). Multiple regression analyses revealed: (a) perceived costs and…
The effects of texting on driving performance in a driving simulator: the influence of driver age.
Rumschlag, Gordon; Palumbo, Theresa; Martin, Amber; Head, Doreen; George, Rajiv; Commissaris, Randall L
2015-01-01
Distracted driving is a significant contributor to motor vehicle accidents and fatalities, and texting is a particularly significant form of driver distraction that continues to be on the rise. The present study examined the influence of driver age (18-59 years old) and other factors on the disruptive effects of texting on simulated driving behavior. While 'driving' the simulator, subjects were engaged in a series of brief text conversations with a member of the research team. The primary dependent variable was the occurrence of Lane Excursions (defined as any time the center of the vehicle moved outside the directed driving lane, e.g., into the lane for oncoming traffic or onto the shoulder of the road), measured as (1) the percent of subjects that exhibited Lane Excursions, (2) the number of Lane Excursions occurring and (3) the percent of the texting time in Lane Excursions. Multiple Regression analyses were used to assess the influence of several factors on driving performance while texting, including text task duration, texting skill level (subject-reported), texting history (#texts/week), driver gender and driver age. Lane Excursions were not observed in the absence of texting, but 66% of subjects overall exhibited Lane Excursions while texting. Multiple Regression analysis for all subjects (N=50) revealed that text task duration was significantly correlated with the number of Lane Excursions, and texting skill level and driver age were significantly correlated with the percent of subjects exhibiting Lane Excursions. Driver gender was not significantly correlated with Lane Excursions during texting. Multiple Regression analysis of only highly skilled texters (N=27) revealed that driver age was significantly correlated with the number of Lane Excursions, the percent of subjects exhibiting Lane Excursions and the percent of texting time in Lane Excursions. In contrast, Multiple Regression analysis of those drivers who self-identified as not highly skilled texters (N=23) revealed that text task duration was significantly correlated with the number of Lane Excursions. The present studies confirm past reports that texting impairs driving simulator performance. Moreover, the present study demonstrates that for highly skilled texters, the effects of texting on driving are actually worse for older drivers. Given the increasing frequency of texting while driving within virtually all age groups, these data suggest that 'no texting while driving' education and public service messages need to be continued, and they should be expanded to target older drivers as well. Copyright © 2014 Elsevier Ltd. All rights reserved.
Factors affecting match performance in professional Australian football.
Sullivan, Courtney; Bilsborough, Johann C; Cianciosi, Michael; Hocking, Joel; Cordy, Justin T; Coutts, Aaron J
2014-05-01
To determine the physical activity measures and skill-performance characteristics that contribute to coaches' perception of performance and player performance rank in professional Australian Football (AF). Prospective, longitudinal. Physical activity profiles were assessed via microtechnology (GPS and accelerometer) from 40 professional AF players from the same team during 15 Australian Football League games. Skill-performance measure and player-rank scores (Champion Data Rank) were provided by a commercial statistical provider. The physical-performance variables, skill involvements, and individual player performance scores were expressed relative to playing time for each quarter. A stepwise multiple regression was used to examine the contribution of physical activity and skill involvements to coaches' perception of performance and player rank in AF. Stepwise multiple-regression analysis revealed that 42.2% of the variance in coaches' perception of a player's performance could be explained by the skill-performance characteristics (player rank/min, effective kicks/min, pressure points/min, handballs/min, and running bounces/ min), with a small contribution from physical activity measures (accelerations/min) (adjusted R2 = .422, F6,282 = 36.054, P < .001). Multiple regression also revealed that 66.4% of the adjusted variance in player rank could be explained by total disposals/min, effective kicks/min, pressure points/min, kick clangers/min, marks/min, speed (m/min), and peak speed (adjusted R2 = .664, F7,281 = 82.289, P < .001). Increased physical activity throughout a match (speed [m/min] β - 0.097 and peak speed β - 0.116) negatively affects player rank in AF. Skill performance rather than increased physical activity is more important to coaches' perception of performance and player rank in professional AF.
Choi, Ji Young; Oh, Kyung Ja
2013-02-01
The purpose of the present study was to explore the effects of multiple interpersonal traumas on psychiatric diagnosis and behavior problems of sexually abused children in Korea. With 495 children (ages 4-13 years) referred to a public counseling center for sexual abuse in Korea, we found significant differences in the rate of psychiatric diagnoses (r = .23) and severity of behavioral problems (internalizing d = 0.49, externalizing d = 0.40, total d = 0.52) between children who were victims of sexual abuse only (n = 362) and youth who were victims of interpersonal trauma experiences in addition to sexual abuse (n = 133). The effects of multiple interpersonal trauma experiences on single versus multiple diagnoses remained significant in the logistic regression analysis where demographic variables, family environmental factors, sexual abuse characteristics, and postincident factors were considered together, odds ratio (OR) = 0.44, 95% confidence interval (CI) = [0.25, 0.77], p < .01. Similarly, multiple regression analyses revealed a significant effect of multiple interpersonal trauma experiences on severity of behavioral problems above and beyond all aforementioned variables (internalizing β =.12, p = .019, externalizing β = .11, p = .036, total β = .14, p =.008). The results suggested that children with multiple interpersonal traumas are clearly at a greater risk for negative consequences following sexual abuse. Copyright © 2013 International Society for Traumatic Stress Studies.
Identification of molecular markers associated with mite resistance in coconut (Cocos nucifera L.).
Shalini, K V; Manjunatha, S; Lebrun, P; Berger, A; Baudouin, L; Pirany, N; Ranganath, R M; Prasad, D Theertha
2007-01-01
Coconut mite (Aceria guerreronis 'Keifer') has become a major threat to Indian coconut (Coçcos nucifera L.) cultivators and the processing industry. Chemical and biological control measures have proved to be costly, ineffective, and ecologically undesirable. Planting mite-resistant coconut cultivars is the most effective method of preventing yield loss and should form a major component of any integrated pest management stratagem. Coconut genotypes, and mite-resistant and -susceptible accessions were collected from different parts of South India. Thirty-two simple sequence repeat (SSR) and 7 RAPD primers were used for molecular analyses. In single-marker analysis, 9 SSR and 4 RAPD markers associated with mite resistance were identified. In stepwise multiple regression analysis of SSRs, a combination of 6 markers showed 100% association with mite infestation. Stepwise multiple regression analysis for RAPD data revealed that a combination of 3 markers accounted for 83.86% of mite resistance in the selected materials. Combined stepwise multiple regression analysis of RAPD and SSR data showed that a combination of 5 markers explained 100% of the association with mite resistance in coconut. Markers associated with mite resistance are important in coconut breeding programs and will facilitate the selection of mite-resistant plants at an early stage as well as mother plants for breeding programs.
Numakura, Kazuyuki; Tsuchiya, Norihiko; Yuasa, Takeshi; Saito, Mitsuru; Obara, Takashi; Tsuruta, Hiroshi; Narita, Shintaro; Horikawa, Yohei; Satoh, Shigeru; Habuchi, Tomonori
2011-10-01
We report a case of Xp11.2 translocation renal cell carcinoma (RCC) whose lung metastases were effectively treated with sunitinib. A 43-year-old woman presenting with upper abdominal pain was diagnosed with a left renal tumor. Laparoscopic left radical nephrectomy was performed. Histopathological examination of the surgical specimen revealed a clear-cell carcinoma of the left kidney. Two years later, multiple lung metastases were detected and the patient was treated daily with 50 mg sunitinib. A computed tomography scan performed after 2 cycles of sunitinib treatment revealed partial regression of these metastases. The partial regression has been maintained for >3 years. In retrospective evaluation of the primary RCC, tumor cells showed strong nuclear staining for transcription factor E3 (TFE3) protein and TFE3 split-fluorescence in-situ hybridization revealed translocation involving the TFE3 gene. These findings strongly support diagnosis of Xp11.2 translocation RCC.
ERIC Educational Resources Information Center
Jiao, Qun G.; DaRos-Voseles, Denise A.; Collins, Kathleen M. T.; Onwuegbuzie, Anthony J.
2011-01-01
This study examined the extent to which academic procrastination predicted the performance of cooperative groups in graduate-level research methods courses. A total of 28 groups was examined (n = 83 students), ranging in size from 2 to 5 (M = 2.96, SD = 1.10). Multiple regression analyses revealed that neither within-group mean nor within-group…
ERIC Educational Resources Information Center
Kress, Victoria E.; Newgent, Rebecca A.; Whitlock, Janis; Mease, Laura
2015-01-01
The purpose of this study was to identify factors that may protect or insulate people from engaging in nonsuicidal self-injury (NSSI). College students (N = 14,385) from 8 universities participated in a web-based survey. Results of bivariate correlations and multiple regression revealed that spirituality/religiosity, life satisfaction, and life…
NASA Astrophysics Data System (ADS)
Kiss, I.; Alexa, V.; Serban, S.; Rackov, M.; Čavić, M.
2018-01-01
The cast hipereutectoid steel (usually named Adamite) is a roll manufacturing destined material, having mechanical, chemical properties and Carbon [C] content of which stands between steelandiron, along-withitsalloyelements such as Nickel [Ni], Chrome [Cr], Molybdenum [Mo] and/or other alloy elements. Adamite Rolls are basically alloy steel rolls (a kind of high carbon steel) having hardness ranging from 40 to 55 degrees Shore C, with Carbon [C] percentage ranging from 1.35% until to 2% (usually between 1.2˜2.3%), the extra Carbon [C] and the special alloying element giving an extra wear resistance and strength. First of all the Adamite roll’s prominent feature is the small variation in hardness of the working surface, and has a good abrasion resistance and bite performance. This paper reviews key aspects of roll material properties and presents an analysis of the influences of chemical composition upon the mechanical properties (hardness) of the cast hipereutectoid steel rolls (Adamite). Using the multiple regression analysis (the double and triple regression equations), some mathematical correlations between the cast hipereutectoid steel rolls’ chemical composition and the obtained hardness are presented. In this work several results and evidence obtained by actual experiments are presented. Thus, several variation boundaries for the chemical composition of cast hipereutectoid steel rolls, in view the obtaining the proper values of the hardness, are revealed. For the multiple regression equations, correlation coefficients and graphical representations the software Matlab was used.
Role of Alexithymia, Anxiety, and Depression in Predicting Self-Efficacy in Academic Students
2017-01-01
Objective. Little research is available on the predictive factors of self-efficacy in college students. The aim of the present study is to examine the role of alexithymia, anxiety, and depression in predicting self-efficacy in academic students. Design. In a cross-sectional study, a total of 133 students at Babol University of Medical Sciences (Medicine, Dentistry, and Paramedicine) participated in the study between 2014 and 2015. All participants completed the Toronto Alexithymia Scale (TAS-20), College Academic Self-Efficacy Scale (CASES), and 14 items on anxiety and depression derived from the 28 items of the General Health Questionnaire (28-GHQ). Results. Pearson correlation coefficients revealed negative significant relationships between alexithymia and the three subscales with student self-efficacy. There was no significant correlation between anxiety/depression symptoms and student self-efficacy. A backward multiple regression analysis revealed that alexithymia was a negative significant predictor of self-efficacy in academic students (B = −0.512, P < 0.001). The prevalence of alexithymia was 21.8% in students. Multiple backward logistic analysis regression revealed that number of passed semesters, gender, mother's education, father's education, and doctoral level did not accurately predict alexithymia in college students. Conclusion. As alexithymia is prevalent in college students and affects self-efficacy and academic functioning, we suggest it should be routinely evaluated by mental physicians at universities. PMID:28154839
Role of Alexithymia, Anxiety, and Depression in Predicting Self-Efficacy in Academic Students.
Faramarzi, Mahbobeh; Khafri, Soraya
2017-01-01
Objective . Little research is available on the predictive factors of self-efficacy in college students. The aim of the present study is to examine the role of alexithymia, anxiety, and depression in predicting self-efficacy in academic students. Design . In a cross-sectional study, a total of 133 students at Babol University of Medical Sciences (Medicine, Dentistry, and Paramedicine) participated in the study between 2014 and 2015. All participants completed the Toronto Alexithymia Scale (TAS-20), College Academic Self-Efficacy Scale (CASES), and 14 items on anxiety and depression derived from the 28 items of the General Health Questionnaire (28-GHQ). Results . Pearson correlation coefficients revealed negative significant relationships between alexithymia and the three subscales with student self-efficacy. There was no significant correlation between anxiety/depression symptoms and student self-efficacy. A backward multiple regression analysis revealed that alexithymia was a negative significant predictor of self-efficacy in academic students ( B = -0.512, P < 0.001). The prevalence of alexithymia was 21.8% in students. Multiple backward logistic analysis regression revealed that number of passed semesters, gender, mother's education, father's education, and doctoral level did not accurately predict alexithymia in college students. Conclusion . As alexithymia is prevalent in college students and affects self-efficacy and academic functioning, we suggest it should be routinely evaluated by mental physicians at universities.
Functional capacity following univentricular repair--midterm outcome.
Sen, Supratim; Bandyopadhyay, Biswajit; Eriksson, Peter; Chattopadhyay, Amitabha
2012-01-01
Previous studies have seldom compared functional capacity in children following Fontan procedure alongside those with Glenn operation as destination therapy. We hypothesized that Fontan circulation enables better midterm submaximal exercise capacity as compared to Glenn physiology and evaluated this using the 6-minute walk test. Fifty-seven children aged 5-18 years with Glenn (44) or Fontan (13) operations were evaluated with standard 6-minute walk protocols. Baseline SpO(2) was significantly lower in Glenn patients younger than 10 years compared to Fontan counterparts and similar in the two groups in older children. Postexercise SpO(2) fell significantly in Glenn patients compared to the Fontan group. There was no statistically significant difference in baseline, postexercise, or postrecovery heart rates (HRs), or 6-minute walk distances in the two groups. Multiple regression analysis revealed lower resting HR, higher resting SpO(2) , and younger age at latest operation to be significant determinants of longer 6-minute walk distance. Multiple regression analysis also established that younger age at operation, higher resting SpO(2) , Fontan operation, lower resting HR, and lower postexercise HR were significant determinants of higher postexercise SpO(2) . Younger age at operation and exercise, lower resting HR and postexercise HR, higher resting SpO(2) and postexercise SpO(2) , and dominant ventricular morphology being left ventricular or indeterminate/mixed had significant association with better 6-minute work on multiple regression analysis. Lower resting HR had linear association with longer 6-minute walk distances in the Glenn patients. Compared to Glenn physiology, Fontan operation did not have better submaximal exercise capacity assessed by walk distance or work on multiple regression analysis. Lower resting HR, higher resting SpO(2) , and younger age at operation were factors uniformly associated with better submaximal exercise capacity. © 2012 Wiley Periodicals, Inc.
de Vries, Haitze J; Reneman, Michiel F; Groothoff, Johan W; Geertzen, Jan H B; Brouwer, Sandra
2013-03-01
To assess self-reported work ability and work performance of workers who stay at work despite chronic nonspecific musculoskeletal pain (CMP), and to explore which variables were associated with these outcomes. In a cross-sectional study we assessed work ability (Work Ability Index, single item scale 0-10) and work performance (Health and Work Performance Questionnaire, scale 0-10) among 119 workers who continued work while having CMP. Scores of work ability and work performance were categorized into excellent (10), good (9), moderate (8) and poor (0-7). Hierarchical multiple regression and logistic regression analysis was used to analyze the relation of socio-demographic, pain-related, personal- and work-related variables with work ability and work performance. Mean work ability and work performance were 7.1 and 7.7 (poor to moderate). Hierarchical multiple regression analysis revealed that higher work ability scores were associated with lower age, better general health perception, and higher pain self-efficacy beliefs (R(2) = 42 %). Higher work performance was associated with lower age, higher pain self-efficacy beliefs, lower physical work demand category and part-time work (R(2) = 37 %). Logistic regression analysis revealed that work ability ≥8 was significantly explained by age (OR = 0.90), general health perception (OR = 1.04) and pain self-efficacy (OR = 1.15). Work performance ≥8 was explained by pain self-efficacy (OR = 1.11). Many workers with CMP who stay at work report poor to moderate work ability and work performance. Our findings suggest that a subgroup of workers with CMP can stay at work with high work ability and performance, especially when they have high beliefs of pain self-efficacy. Our results further show that not the pain itself, but personal and work-related factors relate to work ability and work performance.
Hossain, Md Golam; Saw, Aik; Alam, Rashidul; Ohtsuki, Fumio; Kamarul, Tunku
2013-09-01
Cephalic index (CI), the ratio of head breadth to head length, is widely used to categorise human populations. The aim of this study was to access the impact of anthropometric measurements on the CI of male Japanese university students. This study included 1,215 male university students from Tokyo and Kyoto, selected using convenient sampling. Multiple regression analysis was used to determine the effect of anthropometric measurements on CI. The variance inflation factor (VIF) showed no evidence of a multicollinearity problem among independent variables. The coefficients of the regression line demonstrated a significant positive relationship between CI and minimum frontal breadth (p < 0.01), bizygomatic breadth (p < 0.01) and head height (p < 0.05), and a negative relationship between CI and morphological facial height (p < 0.01) and head circumference (p < 0.01). Moreover, the coefficient and odds ratio of logistic regression analysis showed a greater likelihood for minimum frontal breadth (p < 0.01) and bizygomatic breadth (p < 0.01) to predict round-headedness, and morphological facial height (p < 0.05) and head circumference (p < 0.01) to predict long-headedness. Stepwise regression analysis revealed bizygomatic breadth, head circumference, minimum frontal breadth, head height and morphological facial height to be the best predictor craniofacial measurements with respect to CI. The results suggest that most of the variables considered in this study appear to influence the CI of adult male Japanese students.
Mckay, Garrett; Huang, Wenxi; Romera-Castillo, Cristina; Crouch, Jenna E; Rosario-Ortiz, Fernando L; Jaffé, Rudolf
2017-05-16
The antioxidant capacity and formation of photochemically produced reactive intermediates (RI) was studied for water samples collected from the Florida Everglades with different spatial (marsh versus estuarine) and temporal (wet versus dry season) characteristics. Measured RI included triplet excited states of dissolved organic matter ( 3 DOM*), singlet oxygen ( 1 O 2 ), and the hydroxyl radical ( • OH). Single and multiple linear regression modeling were performed using a broad range of extrinsic (to predict RI formation rates, R RI ) and intrinsic (to predict RI quantum yields, Φ RI ) parameters. Multiple linear regression models consistently led to better predictions of R RI and Φ RI for our data set but poor prediction of Φ RI for a previously published data set,1 probably because the predictors are intercorrelated (Pearson's r > 0.5). Single linear regression models were built with data compiled from previously published studies (n ≈ 120) in which E2:E3, S, and Φ RI values were measured, which revealed a high degree of similarity between RI-optical property relationships across DOM samples of diverse sources. This study reveals that • OH formation is, in general, decoupled from 3 DOM* and 1 O 2 formation, providing supporting evidence that 3 DOM* is not a • OH precursor. Finally, Φ RI for 1 O 2 and 3 DOM* correlated negatively with antioxidant activity (a surrogate for electron donating capacity) for the collected samples, which is consistent with intramolecular oxidation of DOM moieties by 3 DOM*.
Zhou, Qing-he; Xiao, Wang-pin; Shen, Ying-yan
2014-07-01
The spread of spinal anesthesia is highly unpredictable. In patients with increased abdominal girth and short stature, a greater cephalad spread after a fixed amount of subarachnoidally administered plain bupivacaine is often observed. We hypothesized that there is a strong correlation between abdominal girth/vertebral column length and cephalad spread. Age, weight, height, body mass index, abdominal girth, and vertebral column length were recorded for 114 patients. The L3-L4 interspace was entered, and 3 mL of 0.5% plain bupivacaine was injected into the subarachnoid space. The cephalad spread (loss of temperature sensation and loss of pinprick discrimination) was assessed 30 minutes after intrathecal injection. Linear regression analysis was performed for age, weight, height, body mass index, abdominal girth, vertebral column length, and the spread of spinal anesthesia, and the combined linear contribution of age up to 55 years, weight, height, abdominal girth, and vertebral column length was tested by multiple regression analysis. Linear regression analysis showed that there was a significant univariate correlation among all 6 patient characteristics evaluated and the spread of spinal anesthesia (all P < 0.039) except for age and loss of temperature sensation (P > 0.068). Multiple regression analysis showed that abdominal girth and the vertebral column length were the key determinants for spinal anesthesia spread (both P < 0.0001), whereas age, weight, and height could be omitted without changing the results (all P > 0.059, all 95% confidence limits < 0.372). Multiple regression analysis revealed that the combination of a patient's 5 general characteristics, especially abdominal girth and vertebral column length, had a high predictive value for the spread of spinal anesthesia after a given dose of plain bupivacaine.
Chung, Yuh-Jin; Jung, Woo-Chul
2017-01-01
In the distribution service industry, sales people often experience multiple occupational stressors such as excessive emotional labor, workplace mistreatment, and job insecurity. The present study aimed to explore the associations of these stressors with depressive symptoms among women sales workers at a clothing shopping mall in Korea. A cross sectional study was conducted on 583 women who consist of clothing sales workers and manual workers using a structured questionnaire to assess demographic factors, occupational stressors, and depressive symptoms. Multiple regression analyses were performed to explore the association of these stressors with depressive symptoms. Scores for job stress subscales such as job demand, job control, and job insecurity were higher among sales workers than among manual workers (p < 0.01). The multiple regression analysis revealed the association between occupation and depressive symptoms after controlling for age, educational level, cohabiting status, and occupational stressors (sβ = 0.08, p = 0.04). A significant interaction effect between occupation and social support was also observed in this model (sβ = −0.09, p = 0.02). The multiple regression analysis stratified by occupation showed that job demand, job insecurity, and workplace mistreatment were significantly associated with depressive symptoms in both occupations (p < 0.05), although the strength of statistical associations were slightly different. We found negative associations of social support (sβ = −0.22, p < 0.01) and emotional effort (sβ = −0.17, p < 0.01) with depressive symptoms in another multiple regression model for sales workers. Emotional dissonance (sβ = 0.23, p < 0.01) showed positive association with depressive symptoms in this model. The result of this study indicated that reducing occupational stressors would be effective for women sales workers to prevent depressive symptoms. In particular, promoting social support could be the most effective way to promote women sales workers’ mental health. PMID:29168777
Chung, Yuh-Jin; Jung, Woo-Chul; Kim, Hyunjoo; Cho, Seong-Sik
2017-11-23
In the distribution service industry, sales people often experience multiple occupational stressors such as excessive emotional labor, workplace mistreatment, and job insecurity. The present study aimed to explore the associations of these stressors with depressive symptoms among women sales workers at a clothing shopping mall in Korea. A cross sectional study was conducted on 583 women who consist of clothing sales workers and manual workers using a structured questionnaire to assess demographic factors, occupational stressors, and depressive symptoms. Multiple regression analyses were performed to explore the association of these stressors with depressive symptoms. Scores for job stress subscales such as job demand, job control, and job insecurity were higher among sales workers than among manual workers ( p < 0.01). The multiple regression analysis revealed the association between occupation and depressive symptoms after controlling for age, educational level, cohabiting status, and occupational stressors (sβ = 0.08, p = 0.04). A significant interaction effect between occupation and social support was also observed in this model (sβ = -0.09, p = 0.02). The multiple regression analysis stratified by occupation showed that job demand, job insecurity, and workplace mistreatment were significantly associated with depressive symptoms in both occupations ( p < 0.05), although the strength of statistical associations were slightly different. We found negative associations of social support (sβ = -0.22, p < 0.01) and emotional effort (sβ = -0.17, p < 0.01) with depressive symptoms in another multiple regression model for sales workers. Emotional dissonance (sβ = 0.23, p < 0.01) showed positive association with depressive symptoms in this model. The result of this study indicated that reducing occupational stressors would be effective for women sales workers to prevent depressive symptoms. In particular, promoting social support could be the most effective way to promote women sales workers' mental health.
Pang, Marco Y.C.; Eng, Janice J.
2011-01-01
Introduction Chronic stroke survivors with low bone mineral density (BMD) are particularly prone to fragility fractures. The purpose of this study was to identify the determinants of balance, mobility and falls in this sub-group of stroke patients. Methods Thirty nine chronic stroke survivors with low hip BMD (T-score <-1.0) were studied. Each subject was evaluated for: balance, mobility, leg muscle strength, spasticity, and falls-related self-efficacy. Any falls in the past 12 months were also recorded. Multiple regression analysis was used to identify the determinants of balance and mobility performance whereas logistic regression was used to identify the determinants of falls. Results Multiple regression analysis revealed that after adjusting for basic demographics, falls-related self-efficacy remained independently associated with balance/mobility performance (R2=0.494, P<0.001). Logistic regression showed that falls-related self-efficacy, but not balance and mobility performance, was a significant determinant of falls (odds ratio: 0.18, P=0.04). Conclusions Falls-related self-efficacy, but not mobility and balance performance, was the most important determinant of accidental falls. This psychological factor should not be overlooked in the prevention of fragility fractures among chronic stroke survivors with low hip BMD. PMID:18097709
Bayesian logistic regression in detection of gene-steroid interaction for cancer at PDLIM5 locus.
Wang, Ke-Sheng; Owusu, Daniel; Pan, Yue; Xie, Changchun
2016-06-01
The PDZ and LIM domain 5 (PDLIM5) gene may play a role in cancer, bipolar disorder, major depression, alcohol dependence and schizophrenia; however, little is known about the interaction effect of steroid and PDLIM5 gene on cancer. This study examined 47 single-nucleotide polymorphisms (SNPs) within the PDLIM5 gene in the Marshfield sample with 716 cancer patients (any diagnosed cancer, excluding minor skin cancer) and 2848 noncancer controls. Multiple logistic regression model in PLINK software was used to examine the association of each SNP with cancer. Bayesian logistic regression in PROC GENMOD in SAS statistical software, ver. 9.4 was used to detect gene- steroid interactions influencing cancer. Single marker analysis using PLINK identified 12 SNPs associated with cancer (P< 0.05); especially, SNP rs6532496 revealed the strongest association with cancer (P = 6.84 × 10⁻³); while the next best signal was rs951613 (P = 7.46 × 10⁻³). Classic logistic regression in PROC GENMOD showed that both rs6532496 and rs951613 revealed strong gene-steroid interaction effects (OR=2.18, 95% CI=1.31-3.63 with P = 2.9 × 10⁻³ for rs6532496 and OR=2.07, 95% CI=1.24-3.45 with P = 5.43 × 10⁻³ for rs951613, respectively). Results from Bayesian logistic regression showed stronger interaction effects (OR=2.26, 95% CI=1.2-3.38 for rs6532496 and OR=2.14, 95% CI=1.14-3.2 for rs951613, respectively). All the 12 SNPs associated with cancer revealed significant gene-steroid interaction effects (P < 0.05); whereas 13 SNPs showed gene-steroid interaction effects without main effect on cancer. SNP rs4634230 revealed the strongest gene-steroid interaction effect (OR=2.49, 95% CI=1.5-4.13 with P = 4.0 × 10⁻⁴ based on the classic logistic regression and OR=2.59, 95% CI=1.4-3.97 from Bayesian logistic regression; respectively). This study provides evidence of common genetic variants within the PDLIM5 gene and interactions between PLDIM5 gene polymorphisms and steroid use influencing cancer.
Hahn, Sowon; Buttaccio, Daniel R; Hahn, Jungwon; Lee, Taehun
2015-01-01
The present study demonstrates that levels of extraversion and neuroticism can predict attentional performance during a change detection task. After completing a change detection task built on the flicker paradigm, participants were assessed for personality traits using the Revised Eysenck Personality Questionnaire (EPQ-R). Multiple regression analyses revealed that higher levels of extraversion predict increased change detection accuracies, while higher levels of neuroticism predict decreased change detection accuracies. In addition, neurotic individuals exhibited decreased sensitivity A' and increased fixation dwell times. Hierarchical regression analyses further revealed that eye movement measures mediate the relationship between neuroticism and change detection accuracies. Based on the current results, we propose that neuroticism is associated with decreased attentional control over the visual field, presumably due to decreased attentional disengagement. Extraversion can predict increased attentional performance, but the effect is smaller than the relationship between neuroticism and attention.
Spirituality and Resilience Among Mexican American IPV Survivors.
de la Rosa, Iván A; Barnett-Queen, Timothy; Messick, Madeline; Gurrola, Maria
2016-12-01
Women with abusive partners use a variety of coping strategies. This study examined the correlation between spirituality, resilience, and intimate partner violence using a cross-sectional survey of 54 Mexican American women living along the U.S.-Mexico border. The meaning-making coping model provides the conceptual framework to explore how spirituality is used as a copying strategy. Multiple ordinary least squares (OLS) regression results indicate women who score higher on spirituality also report greater resilient characteristics. Poisson regression analyses revealed that an increase in level of spirituality is associated with lower number of types of abuse experienced. Clinical, programmatic, and research implications are discussed. © The Author(s) 2015.
Eack, Shaun M.; Newhill, Christina E.
2013-01-01
A survey of 118 MSW students was conducted to examine the relationship between social work students’ knowledge about, contact with, and attitudes toward persons with schizophrenia. Hierarchical regression analyses indicated that students’ knowledge about and contact with persons with schizophrenia were significantly related to better attitudes toward this population. Moderated multiple regression analyses revealed a significant interaction between knowledge about and contact with persons with schizophrenia, such that knowledge was only related to positive attitudes among students who had more personal contact with persons with the illness. Implications for social work training in severe mental illness are discussed (99 words). PMID:24353396
A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield
NASA Astrophysics Data System (ADS)
Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan
2018-04-01
In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.
Albuquerque, F S; Peso-Aguiar, M C; Assunção-Albuquerque, M J T; Gálvez, L
2009-08-01
The length-weight relationship and condition factor have been broadly investigated in snails to obtain the index of physical condition of populations and evaluate habitat quality. Herein, our goal was to describe the best predictors that explain Achatina fulica biometrical parameters and well being in a recently introduced population. From November 2001 to November 2002, monthly snail samples were collected in Lauro de Freitas City, Bahia, Brazil. Shell length and total weight were measured in the laboratory and the potential curve and condition factor were calculated. Five environmental variables were considered: temperature range, mean temperature, humidity, precipitation and human density. Multiple regressions were used to generate models including multiple predictors, via model selection approach, and then ranked with AIC criteria. Partial regressions were used to obtain the separated coefficients of determination of climate and human density models. A total of 1.460 individuals were collected, presenting a shell length range between 4.8 to 102.5 mm (mean: 42.18 mm). The relationship between total length and total weight revealed that Achatina fulica presented a negative allometric growth. Simple regression indicated that humidity has a significant influence on A. fulica total length and weight. Temperature range was the main variable that influenced the condition factor. Multiple regressions showed that climatic and human variables explain a small proportion of the variance in shell length and total weight, but may explain up to 55.7% of the condition factor variance. Consequently, we believe that the well being and biometric parameters of A. fulica can be influenced by climatic and human density factors.
The effects of climate change on harp seals (Pagophilus groenlandicus).
Johnston, David W; Bowers, Matthew T; Friedlaender, Ari S; Lavigne, David M
2012-01-01
Harp seals (Pagophilus groenlandicus) have evolved life history strategies to exploit seasonal sea ice as a breeding platform. As such, individuals are prepared to deal with fluctuations in the quantity and quality of ice in their breeding areas. It remains unclear, however, how shifts in climate may affect seal populations. The present study assesses the effects of climate change on harp seals through three linked analyses. First, we tested the effects of short-term climate variability on young-of-the year harp seal mortality using a linear regression of sea ice cover in the Gulf of St. Lawrence against stranding rates of dead harp seals in the region during 1992 to 2010. A similar regression of stranding rates and North Atlantic Oscillation (NAO) index values was also conducted. These analyses revealed negative correlations between both ice cover and NAO conditions and seal mortality, indicating that lighter ice cover and lower NAO values result in higher mortality. A retrospective cross-correlation analysis of NAO conditions and sea ice cover from 1978 to 2011 revealed that NAO-related changes in sea ice may have contributed to the depletion of seals on the east coast of Canada during 1950 to 1972, and to their recovery during 1973 to 2000. This historical retrospective also reveals opposite links between neonatal mortality in harp seals in the Northeast Atlantic and NAO phase. Finally, an assessment of the long-term trends in sea ice cover in the breeding regions of harp seals across the entire North Atlantic during 1979 through 2011 using multiple linear regression models and mixed effects linear regression models revealed that sea ice cover in all harp seal breeding regions has been declining by as much as 6 percent per decade over the time series of available satellite data.
The Effects of Climate Change on Harp Seals (Pagophilus groenlandicus)
Johnston, David W.; Bowers, Matthew T.; Friedlaender, Ari S.; Lavigne, David M.
2012-01-01
Harp seals (Pagophilus groenlandicus) have evolved life history strategies to exploit seasonal sea ice as a breeding platform. As such, individuals are prepared to deal with fluctuations in the quantity and quality of ice in their breeding areas. It remains unclear, however, how shifts in climate may affect seal populations. The present study assesses the effects of climate change on harp seals through three linked analyses. First, we tested the effects of short-term climate variability on young-of-the year harp seal mortality using a linear regression of sea ice cover in the Gulf of St. Lawrence against stranding rates of dead harp seals in the region during 1992 to 2010. A similar regression of stranding rates and North Atlantic Oscillation (NAO) index values was also conducted. These analyses revealed negative correlations between both ice cover and NAO conditions and seal mortality, indicating that lighter ice cover and lower NAO values result in higher mortality. A retrospective cross-correlation analysis of NAO conditions and sea ice cover from 1978 to 2011 revealed that NAO-related changes in sea ice may have contributed to the depletion of seals on the east coast of Canada during 1950 to 1972, and to their recovery during 1973 to 2000. This historical retrospective also reveals opposite links between neonatal mortality in harp seals in the Northeast Atlantic and NAO phase. Finally, an assessment of the long-term trends in sea ice cover in the breeding regions of harp seals across the entire North Atlantic during 1979 through 2011 using multiple linear regression models and mixed effects linear regression models revealed that sea ice cover in all harp seal breeding regions has been declining by as much as 6 percent per decade over the time series of available satellite data. PMID:22238591
Kovačević, Strahinja; Karadžić, Milica; Podunavac-Kuzmanović, Sanja; Jevrić, Lidija
2018-01-01
The present study is based on the quantitative structure-activity relationship (QSAR) analysis of binding affinity toward human prion protein (huPrP C ) of quinacrine, pyridine dicarbonitrile, diphenylthiazole and diphenyloxazole analogs applying different linear and non-linear chemometric regression techniques, including univariate linear regression, multiple linear regression, partial least squares regression and artificial neural networks. The QSAR analysis distinguished molecular lipophilicity as an important factor that contributes to the binding affinity. Principal component analysis was used in order to reveal similarities or dissimilarities among the studied compounds. The analysis of in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) parameters was conducted. The ranking of the studied analogs on the basis of their ADMET parameters was done applying the sum of ranking differences, as a relatively new chemometric method. The main aim of the study was to reveal the most important molecular features whose changes lead to the changes in the binding affinities of the studied compounds. Another point of view on the binding affinity of the most promising analogs was established by application of molecular docking analysis. The results of the molecular docking were proven to be in agreement with the experimental outcome. Copyright © 2017 Elsevier B.V. All rights reserved.
Ibidunni, Ayodotun Stephen; Kehinde, Oladele Joseph; Ibidunni, Oyebisi Mary; Olokundun, Maxwell Ayodele; Olubusayo, Falola Hezekiah; Salau, Odunayo Paul; Borishade, Taiye Tairat; Fred, Peter
2018-06-01
The article presents data on the relationship between financing strategies, entrepreneurial competencies and business growth of technology-based SMEs in Nigeria. Copies of structured questionnaire were administered to 233 SME owners and financial managers. Using descriptive and standard multiple regression statistical analysis, the data revealed that venture capital and business donations significantly influences profit growth of technology-based SMEs. Moreover, the data revealed that technology-`based firms can enhance their access to financing through capacity building in entrepreneurial competencies, such as acquiring the right skills and attitude.
May, Philip A; Tabachnick, Barbara G; Gossage, J Phillip; Kalberg, Wendy O; Marais, Anna-Susan; Robinson, Luther K; Manning, Melanie; Buckley, David; Hoyme, H Eugene
2011-12-01
Previous research in South Africa revealed very high rates of fetal alcohol syndrome (FAS), of 46-89 per 1000 among young children. Maternal and child data from studies in this community summarize the multiple predictors of FAS and partial fetal alcohol syndrome (PFAS). Sequential regression was employed to examine influences on child physical characteristics and dysmorphology from four categories of maternal traits: physical, demographic, childbearing, and drinking. Then, a structural equation model (SEM) was constructed to predict influences on child physical characteristics. Individual sequential regressions revealed that maternal drinking measures were the most powerful predictors of a child's physical anomalies (R² = .30, p < .001), followed by maternal demographics (R² = .24, p < .001), maternal physical characteristics (R²=.15, p < .001), and childbearing variables (R² = .06, p < .001). The SEM utilized both individual variables and the four composite categories of maternal traits to predict a set of child physical characteristics, including a total dysmorphology score. As predicted, drinking behavior is a relatively strong predictor of child physical characteristics (β = 0.61, p < .001), even when all other maternal risk variables are included; higher levels of drinking predict child physical anomalies. Overall, the SEM model explains 62% of the variance in child physical anomalies. As expected, drinking variables explain the most variance. But this highly controlled estimation of multiple effects also reveals a significant contribution played by maternal demographics and, to a lesser degree, maternal physical and childbearing variables. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Ghorbandordinejad, Farhad; Ahmadabad, Roghayyeh Moradian
2016-06-01
This study investigated the relationship between autonomy and English language achievement among third-grade high school students as mediated by foreign language classroom anxiety in a city in the north-west of Iran. A sample of 400 students (187 males, and 213 females) was assessed for their levels of autonomy and foreign language anxiety using the Autonomy Questionnaire and Foreign Language Classroom Anxiety Scale (FLCAS), respectively. Participants' scores on their final English exam were also used as the measurement of their English achievement. The results of Pearson correlation revealed a strong correlation between learners' autonomy and their English achievement (r [Formula: see text] .406, n [Formula: see text] 400, [Formula: see text]). Also, foreign language classroom anxiety was found to be significantly and negatively correlated with English achievement (r [Formula: see text] [Formula: see text].472, n [Formula: see text] 400, [Formula: see text]). Hierarchical multiple regression was used to assess the ability of autonomy to predict language learning achievement, after controlling for the influence of anxiety. In sum, the results of hierarchical multiple regressions revealed that foreign language classroom anxiety significantly mediates the relationship between autonomy and English language achievement. Implications for both teachers and learners, and suggestions for further research are provided.
Rigid and flexible control of eating behavior in a college population.
Timko, C Alix; Perone, Julie
2005-02-01
The objective of this study was to explore the relationship between rigid control (RC) and flexible control (FC) of eating behavior and their relationship to traditional weight, eating, and affective measurements in a large heterogeneous population. Participants were 639 underweight to obese male and female college students. Multiple regression analyses (MRA) revealed that high RC was associated with high Body Mass Index (BMI) and high Disinhibition (DIS), and high FC was associated with low BMI and low DIS in women. In men, high RC was associated with high BMI and high DIS, whereas FC was not related to BMI or DIS. Multiple regression analyses of BMI on RC and FC in the female subsample revealed that the control variables interact in such a way that the relationship between RC and BMI is stronger when FC is lower. In men, there was no interaction between these variables. This study is the first full replication of Westenhoefer's Gezugeltes Essen und Storbarkeit des Ebetaverhaltens: 2. Auflage. Gottingen: Verlag fur Psychologie () findings regarding RC and FC and their relationship to weight (BMI) and Disinhibition (DIS) in women. This is also the only second study to use the expanded, more reliable versions of the RC and FC scales. Overall, high RC in women and men was associated with greater eating and affective pathology.
Bacterial diversity in saliva and oral health-related conditions: the Hisayama Study
NASA Astrophysics Data System (ADS)
Takeshita, Toru; Kageyama, Shinya; Furuta, Michiko; Tsuboi, Hidenori; Takeuchi, Kenji; Shibata, Yukie; Shimazaki, Yoshihiro; Akifusa, Sumio; Ninomiya, Toshiharu; Kiyohara, Yutaka; Yamashita, Yoshihisa
2016-02-01
This population-based study determined the salivary microbiota composition of 2,343 adult residents of Hisayama town, Japan, using 16S rRNA gene next-generation high-throughput sequencing. Of 550 identified species-level operational taxonomic units (OTUs), 72 were common, in ≥75% of all individuals, as well as in ≥75% of the individuals in the lowest quintile of phylogenetic diversity (PD). These “core” OTUs constituted 90.9 ± 6.1% of each microbiome. The relative abundance profiles of 22 of the core OTUs with mean relative abundances ≥1% were stratified into community type I and community type II by partitioning around medoids clustering. Multiple regression analysis revealed that a lower PD was associated with better conditions for oral health, including a lower plaque index, absence of decayed teeth, less gingival bleeding, shallower periodontal pockets and not smoking, and was also associated with tooth loss. By contrast, multiple Poisson regression analysis demonstrated that community type II, as characterized by a higher ratio of the nine dominant core OTUs, including Neisseria flavescens, was implicated in younger age, lower body mass index, fewer teeth with caries experience, and not smoking. Our large-scale data analyses reveal variation in the salivary microbiome among Japanese adults and oral health-related conditions associated with the salivary microbiome.
The Effects of Gender-based Violence on Women's Unwanted Pregnancy and Abortion.
McCloskey, Laura A
2016-06-01
The aim of this research is to understand how gender-based violence across the life-course affects the likelihood of abortion. Women outpatients (n = 309) revealed their exposure to four different forms of gender-based abuse: child sexual abuse (25.7 percent), teenage physical dating violence (40.8 percent), intimate partner violence (43.1 percent), and sexual assault outside an intimate relationship (22 percent). Logistic regressions revealed that no single form of gender-based abuse predicted abortion. The cumulative effect of multiple forms of abuse did increase the odds of having an abortion (OR = 1.39, CI = 1.13-1.69). Child sexual abuse predicted intimate partner violence (OR = 6.71, CI = 3.36-13.41). The cumulative effect of gender-based violence on women's reproductive health warrants further research. Priority should be given to screening for multiple forms of victimization in reproductive healthcare settings.
The Effects of Gender-based Violence on Women’s Unwanted Pregnancy and Abortion
McCloskey, Laura A.
2016-01-01
The aim of this research is to understand how gender-based violence across the life-course affects the likelihood of abortion. Women outpatients (n = 309) revealed their exposure to four different forms of gender-based abuse: child sexual abuse (25.7 percent), teenage physical dating violence (40.8 percent), intimate partner violence (43.1 percent), and sexual assault outside an intimate relationship (22 percent). Logistic regressions revealed that no single form of gender-based abuse predicted abortion. The cumulative effect of multiple forms of abuse did increase the odds of having an abortion (OR = 1.39, CI = 1.13-1.69). Child sexual abuse predicted intimate partner violence (OR = 6.71, CI = 3.36-13.41). The cumulative effect of gender-based violence on women’s reproductive health warrants further research. Priority should be given to screening for multiple forms of victimization in reproductive healthcare settings. PMID:27354842
Seok, Soonhwa; DaCosta, Boaventura
2017-01-01
This study investigated relationships between digital propensity and support needs as well as predictors of digital propensity in the context of support intensity, age, gender, and social maturity. A total of 118 special education teachers rated the support intensity, digital propensity, and social maturity of 352 students with intellectual disability. Leveraging the Digital Propensity Index, Supports Intensity Scale, and the Social Maturity Scale, descriptive statistics, correlations, multiple regressions, and regression analyses were employed. The findings revealed significant relationships between digital propensity and support needs. In addition, significant predictors of digital propensity were found with regard to support intensity, age, gender, and social maturity.
Multiple Correlation versus Multiple Regression.
ERIC Educational Resources Information Center
Huberty, Carl J.
2003-01-01
Describes differences between multiple correlation analysis (MCA) and multiple regression analysis (MRA), showing how these approaches involve different research questions and study designs, different inferential approaches, different analysis strategies, and different reported information. (SLD)
Self-reports of trauma and dissociation: An examination of context effects.
Lemons, Peter; Lynn, Steven Jay
2016-08-01
To examine context effects in moderating the link between self-reported trauma and dissociation in undergraduate samples, we administered these measures either in the same or different experimental contexts. Trauma History Screen/THS (Carlson et al., 2011)-Dissociative Experiences Scale/DES-II (Bernstein & Putnam, 1986) correlations revealed a context effect (greater correlations in same test context), although multiple regression analyses did not confirm this finding. A context effect was supported in DES-Taxon scores using multiple regression for the THS but not the Modified Posttraumatic Stress Scale (MPSS-SR; Falsetti, Resnick, Resick, & Kilpatrick, 1993), an effect confirmed with correlation comparisons. Ethnicity influenced the association between measures of trauma and dissociation. Overall, the relation between measures of trauma and dissociation was small to medium, although high correlations were observed between the DES depersonalization/derealization subscale and the Multiscale Dissociation Inventory (Briere, Weathers, & Runtz, 2005) depersonalization and derealization subscales, supporting the construct validity of these measures. Copyright © 2016 Elsevier Inc. All rights reserved.
Boudou, M; Séjourné, N; Chabrol, H
2007-11-01
This prospective, longitudinal study investigated the contributive role of childbirth pain, perinatal distress and perinatal dissociation to the development of PTSD symptoms following childbirth. One hundred and seventeen women participated at the study. The first day after delivery they completed a questionnaire to evaluate pain, the peritraumatic distress inventory (PDI) and the peritraumatic dissociative experience questionnaire (PDEQ). Six weeks after birth, they completed the impact of event scale-revised (IES-R) to measure posttraumatic stress symptoms and the Edinburgh Postnatal Depression Scale (EPDS) to assess maternal depression. A multiple regression analysis revealed that only both components of perinatal distress, life-threat perception and dysphoric emotions were significant predictors of posttraumatic stress symptoms. In another multiple regression analysis predicting dysphoric emotions, affective dimension of pain was the only significant predictor. Perinatal distress was the best predictor of posttraumatic stress symptoms. Dysphoric emotions were associated with affective dimension of pain, suggesting that women distressed by the childbirth pain would have higher risk to develop posttraumatic stress symptoms.
Eshkoor, Sima Ataollahi; Hamid, Tengku Aizan; Nudin, Siti Sa'adiah Hassan; Mun, Chan Yoke
2013-06-01
This study aimed to identify the effects of sleep quality, physical activity, environmental quality, age, ethnicity, sex differences, marital status, and educational level on the risk of falls in the elderly individuals with dementia. Data were derived from a group of 1210 Malaysian elderly individuals who were noninstitutionalized and demented. The multiple logistic regression model was applied to estimate the risk of falls in respondents. Approximately the prevalence of falls was 17% among the individuals. The results of multiple logistic regression analysis revealed that age (odds ratio [OR] = 1.03), ethnicity (OR = 1.76), sleep quality (OR = 1.46), and environmental quality (OR = 0.62) significantly affected the risk of falls in individuals (P < .05). Furthermore, sex differences, marital status, educational level, and physical activity were not significant predictors of falls in samples (P > .05). It was found that age, ethnic non-Malay, and sleep disruption increased the risk of falls in respondents, but high environmental quality reduced the risk of falls.
Rondon, Ana T; Hilton, Dane C; Jarrett, Matthew A; Ollendick, Thomas H
2018-02-01
We compared clinic-referred youth with ADHD + sluggish cognitive tempo (SCT; n = 34), ADHD Only ( n = 108), and SCT Only ( n = 22) on demographics, co-occurring symptomatology, comorbid diagnoses, and social functioning. In total, 164 youth (age = 6-17 years, M = 9.97) and their parent(s) presented to an outpatient clinic for a psychoeducational assessment. Between-group analyses and regressions were used to examine study variables. SCT groups were older and exhibited more parent-reported internalizing problems, externalizing problems, sleep problems, and social withdrawal on the Child Behavior Checklist. No significant differences emerged between groups on the Teacher Report Form. Regression analyses involving multiple covariates revealed that SCT symptoms were uniquely related to social withdrawal but not general social problems. Based on parent report, SCT symptoms have a unique relationship with internalizing problems, sleep problems, and social withdrawal. Future research should explore correlates of SCT in youth using multiple informants.
ERIC Educational Resources Information Center
Jaccard, James; And Others
1990-01-01
Issues in the detection and interpretation of interaction effects between quantitative variables in multiple regression analysis are discussed. Recent discussions associated with problems of multicollinearity are reviewed in the context of the conditional nature of multiple regression with product terms. (TJH)
Beyond Multiple Regression: Using Commonality Analysis to Better Understand R[superscript 2] Results
ERIC Educational Resources Information Center
Warne, Russell T.
2011-01-01
Multiple regression is one of the most common statistical methods used in quantitative educational research. Despite the versatility and easy interpretability of multiple regression, it has some shortcomings in the detection of suppressor variables and for somewhat arbitrarily assigning values to the structure coefficients of correlated…
Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha
2012-05-01
Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.
Hasslacher, Christoph; Lorenzo Bermejo, Justo
2017-11-01
A lower incidence of cardiovascular events has been reported in type 2 diabetes patients treated with insulin analogs (IAs). Corresponding data on people affected by type 1 diabetes are not available yet. We investigated demographic and clinical data from 509 type 1 diabetics, who were treated in an outpatient clinic from 2006 to 2012. Multiple logistic regression was used to investigate the relationship between the type of insulin treatment and the prevalence of cardiovascular (CV) complications, that is, presence of coronary heart, cerebrovascular and peripheral arterial diseases, adjusting for potential confounders. Results from multiple logistic regression revealed that patients with impaired renal function [estimated glomerular filtration rate (eGFR) < 90 ml/min] show lower CV complication rates when treated with IAs (25%) compared with patients treated with human insulin (HI; 28%) and HI/IA (38%, p = 0.06). CV complication rates in the complete patient collective amounted to 17% (IA), 21% (HI) and 21% (HI/IA, p = 0.08). Examination of CV complications according to the type of IA revealed the lowest complication rates in type 1 diabetics treated with insulin lispro (5.9%) and glargine (16%). However, complication rate differences among insulin treatments did not reach statistical significance. The present cross-sectional study shows a borderline significantly lower CV morbidity in people with type 1 diabetes and impaired renal function when treated with IA compared with HI treatment after adjustment for multiple potential confounders [odds ratio (OR) = 0.78, which translates into a 22% lower complication rate]. Validation of these preliminary findings in confirmatory, prospective studies may have important clinical implications.
Ayaz, Sevin; Ayaz, Ümit Yaşar
2016-01-01
We aimed to present unusual cranial FDG PET/CT findings of a 56-year-old female with multiple myeloma (MM). Plain CT images revealed a lytic lesion in the right parietal bone, filled with an oval-shaped, large, extra-axial, extradural, intracranial mass which measured 75×75×40 mm and had smooth borders. The right parietal lobe was compressed by the mass. The maximum standardized uptake value (SUV max ) of the mass lesion was 8.94 on FDG PET/CT images. Multiple lytic lesions with an increased uptake were also detected in other calvarial bones, in several vertebras and in the proximal left femur. After seven months, a control FDG PET/CT following radiotherapy and chemotherapy revealed almost complete regression of the right parietal extra-axial mass lesion. The number, size and metabolism of lytic lesions in other bones also decreased. FDG PET/CT was useful for an initial evaluation of MM lesions and was effective in monitoring the response of these lesions to therapy.
Effects of psychological distress on blood pressure in adolescents.
Weinrich, S; Weinrich, M; Hardin, S; Gleaton, J; Pesut, D J; Garrison, C
2000-10-01
This cross-sectional survey measured relationships among blood pressure and measures of psychologic distress, family structure, and economic status in a sample of adolescents exposed to Hurricane Hugo. Spielberger's Anger Scale and Derogatis' Brief Symptom Inventory were used. Data analysis revealed 5% of the 1079 adolescents were hypertensive. Multiple regression analyses revealed the following predictors of higher diastolic blood pressure: African-American race, recipient of subsidized lunch, exposure to Hurricane Hugo, and higher anger-in scores in males. The effects of a catastrophic event such as a hurricane on blood pressure and the effects of introjected anger have implications for both health care consumers and providers.
NASA Astrophysics Data System (ADS)
Aligholi, Saeed; Lashkaripour, Gholam Reza; Ghafoori, Mohammad; Azali, Sadegh Tarigh
2017-11-01
Thorough and realistic performance predictions are among the main requisites for estimating excavation costs and time of the tunneling projects. Also, NTNU/SINTEF rock drillability indices, including the Drilling Rate Index™ (DRI), Bit Wear Index™ (BWI), and Cutter Life Index™ (CLI), are among the most effective indices for determining rock drillability. In this study, brittleness value (S20), Sievers' J-Value (SJ), abrasion value (AV), and Abrasion Value Cutter Steel (AVS) tests are conducted to determine these indices for a wide range of Iranian hard igneous rocks. In addition, relationships between such drillability parameters with petrographic features and index properties of the tested rocks are investigated. The results from multiple regression analysis revealed that the multiple regression models prepared using petrographic features provide a better estimation of drillability compared to those prepared using index properties. Also, it was found that the semiautomatic petrography and multiple regression analyses provide a suitable complement to determine drillability properties of igneous rocks. Based on the results of this study, AV has higher correlations with studied mineralogical indices than AVS. The results imply that, in general, rock surface hardness of hard igneous rocks is very high, and the acidic igneous rocks have a lower strength and density and higher S20 than those of basic rocks. Moreover, DRI is higher, while BWI is lower in acidic igneous rocks, suggesting that drill and blast tunneling is more convenient in these rocks than basic rocks.
Burnout, stress and satisfaction among Australian and New Zealand radiation oncology trainees.
Leung, John; Rioseco, Pilar
2017-02-01
To evaluate the incidence of burnout among radiation oncology trainees in Australia and New Zealand and the stress and satisfaction factors related to burnout. A survey of trainees was conducted in mid-2015. There were 42 Likert scale questions on stress, 14 Likert scale questions on satisfaction and the Maslach Burnout Inventory-Human Services Survey assessed burnout. A principal component analysis identified specific stress and satisfaction areas. Categorical variables for the stress and satisfaction factors were computed. Associations between respondent's characteristics and stress and satisfaction subscales were examined by independent sample t-tests and analysis of variance. Effect sizes were calculated using Cohens's d when significant mean differences were observed. This was also done for respondent characteristics and the three burnout subscales. Multiple regression analyses were performed. The response rate was 81.5%. The principal component analysis for stress identified five areas: demands on time, professional development/training, delivery demands, interpersonal demands and administration/organizational issues. There were no significant differences by demographic group or area of interest after P-values were adjusted for the multiple tests conducted. The principal component analysis revealed two satisfaction areas: resources/professional activities and value/delivery of services. There were no significant differences by demographic characteristics or area of interest in the level of satisfaction after P-values were adjusted for the multiple tests conducted. The burnout results revealed 49.5% of respondents scored highly in emotional exhaustion and/or depersonalization and 13.1% had burnout in all three measures. Multiple regression analysis revealed the stress subscales 'demands on time' and 'interpersonal demands' were associated with emotional exhaustion. 'Interpersonal demands' was also associated with depersonalization and correlated negatively with personal accomplishment. The satisfaction of value/delivery of services subscale was associated with higher levels of personal accomplishment. There is a significant level of burnout among radiation oncology trainees in Australia and New Zealand. Further work addressing intervention would be appropriate to reduce levels of burnout. © 2016 The Authors. Journal of Medical Imaging and Radiation Oncology published by John Wiley & Sons Australia, Ltd on behalf of The Royal Australian and New Zealand College of Radiologists.
Reduced opsin gene expression in a cave-dwelling fish
Tobler, Michael; Coleman, Seth W.; Perkins, Brian D.; Rosenthal, Gil G.
2010-01-01
Regressive evolution of structures associated with vision in cave-dwelling organisms is the focus of intense research. Most work has focused on differences between extreme visual phenotypes: sighted, surface animals and their completely blind, cave-dwelling counterparts. We suggest that troglodytic systems, comprising multiple populations that vary along a gradient of visual function, may prove critical in understanding the mechanisms underlying initial regression in visual pathways. Gene expression assays of natural and laboratory-reared populations of the Atlantic molly (Poecilia mexicana) revealed reduced opsin expression in cave-dwelling populations compared with surface-dwelling conspecifics. Our results suggest that the reduction in opsin expression in cave-dwelling populations is not phenotypically plastic but reflects a hardwired system not rescued by exposure to light during retinal ontogeny. Changes in opsin gene expression may consequently represent a first evolutionary step in the regression of eyes in cave organisms. PMID:19740890
Heeren, G Anita; Jemmott, John B; Mandeya, Andrew; Tyler, Joanne C
2009-04-01
Whether certain behavioral beliefs, normative beliefs, and control beliefs predict the intention to use condoms and subsequent condom use was examined among 320 undergraduates at a university in South Africa who completed confidential questionnaires on two occasions separated by 3 months. Participants' mean age was 23.4 years, 47.8% were women, 48.9% were South Africans, and 51.1% were from other sub-Saharan African countries. Multiple regression revealed that condom-use intention was predicted by hedonistic behavioral beliefs, normative beliefs regarding sexual partners and peers, and control beliefs regarding condom-use technical skill and impulse control. Logistic regression revealed that baseline condom-use intention predicted consistent condom use and condom use during most recent intercourse at 3-month follow-up. HIV/STI risk-reduction interventions for undergraduates in South Africa should target their condom-use hedonistic beliefs, normative beliefs regarding partners and peers, and control beliefs regarding technical skill and impulse control.
[Association of mineral and bone disorder with increasing PWV in CKD 1-5 patients].
Shiota, Jun; Watanabe, Mitsuhiro
2007-01-01
The association between pulse wave velocity(PWV) and chronic kidney disease mineral and bone disorder(CKD-MBD) was investigated in CKD 1-5 patients without dialysis. Pulse pressure(PP), PWV, serum Cr, non-HDL-cholesterol, Alb, Ca, Pi, calcitriol, intact-PTH and BAP were measured in sixty patients not receiving a phosphate binder or vitamin D. Using the relationship between age and baPWV in healthy subjects, we determined delta baPWV(measured baPWV-calculated baPWV) as an index for the effect of CKD-related factors. delta baPWV was significantly higher in diabetic patients (p < 0.00001). Simple regression analysis revealed that delta baPWV was positively correlated with PP (p < 0.05) and Log(intact-PTH) (p < 0.01), but negatively correlated with Log(estimated GFR) and Log(calcitriol) (p < 0.01). Multiple regression analysis revealed that delta baPWV was significantly associated with PP and calcitriol, or PP and intact-PTH. These results suggest a relationship between PWV and CKD-MBD.
Suzuki, Hideaki; Tabata, Takahisa; Koizumi, Hiroki; Hohchi, Nobusuke; Takeuchi, Shoko; Kitamura, Takuro; Fujino, Yoshihisa; Ohbuchi, Toyoaki
2014-12-01
This study aimed to create a multiple regression model for predicting hearing outcomes of idiopathic sudden sensorineural hearing loss (ISSNHL). The participants were 205 consecutive patients (205 ears) with ISSNHL (hearing level ≥ 40 dB, interval between onset and treatment ≤ 30 days). They received systemic steroid administration combined with intratympanic steroid injection. Data were examined by simple and multiple regression analyses. Three hearing indices (percentage hearing improvement, hearing gain, and posttreatment hearing level [HLpost]) and 7 prognostic factors (age, days from onset to treatment, initial hearing level, initial hearing level at low frequencies, initial hearing level at high frequencies, presence of vertigo, and contralateral hearing level) were included in the multiple regression analysis as dependent and explanatory variables, respectively. In the simple regression analysis, the percentage hearing improvement, hearing gain, and HLpost showed significant correlation with 2, 5, and 6 of the 7 prognostic factors, respectively. The multiple correlation coefficients were 0.396, 0.503, and 0.714 for the percentage hearing improvement, hearing gain, and HLpost, respectively. Predicted values of HLpost calculated by the multiple regression equation were reliable with 70% probability with a 40-dB-width prediction interval. Prediction of HLpost by the multiple regression model may be useful to estimate the hearing prognosis of ISSNHL. © The Author(s) 2014.
Risk factors for retinal breaks in patients with symptom of floaters.
Singalavanija, Apichart; Amornrattanapan, Chutiwan; Nitiruangjarus, Kanjanee; Tongsai, Sasima
2010-06-01
To identify the risk factors of retinal breaks in patients with the symptom of floaters, and to determine the association between those risk factors and retinal breaks. A retrospective analytic study of 184 patients (55 males and 129 females) that included 220 eyes was conducted. Patient information such as age, symptoms (multiple floaters, flashing), duration of symptom, refractive error, history of cataract surgery, family history of retinal detachment, and complete eye examination were recorded. The patients were divided into two groups, the first group (control group) had symptoms of floaters and no retinal breaks, the second group (retinal breaks group) had symptoms of floaters with retinal breaks. Chi-square test, and the multiple logistic regression were used for statistical analysis. Two hundred twenty eyes, 175 eyes of the control group and 45 eyes of the retinal breaks group were examined and included in this study. The multiple logistic regression analysis revealed that patients with multiple floaters, and floaters and flashing increased the risk of retinal breaks to 5.8 and 4.3 times, respectively, when compared to patients with single floater or floaters alone. Lattice degeneration increased the risk of retinal breaks to 5.9 times when compared to eyes that did not have lattice degeneration. Multiple floaters, flashing and lattice degeneration are risk factors of retinal breaks in patients with symptoms of floaters. Therefore, it is important for the ophthalmologists to be aware of these risk factors and the patients at risk should have follow-up examinations.
[High Risk Sex Behaviors and Associated Factors in Young Men in Chengdu].
2015-11-01
To determine the prevalence of high risk sex behaviors and associated factors in 18-34 years old men in Chengdu. Methods An anonymous questionnaire survey was conducted in 18-34 years old men selected by multi-stage random sampling in Chengdu. Data of 1536 respondents who reported having sex contacts were analyzed. 23.6% of respondents had multiple sex partners in the past 12 months; 11.8% were involved commercial sex; 9.0% had group sex; 4. 7% had anal sex; 15.6% had never used a condom; 37.7% had sex under the influence of alcohol or drugs. Logistic regression analysis revealed that marital status [married, standardized partial regression coefficient (B) = -0.086, P<0.05] , level of education (bachelor or above, B= -0.063, P<0.05), frequency of exposure to pornography (B=0.058, P<0.05), childhood sexual abuse (B= 0.042, P<0.05), first sexual intercourse at an earlier age (B=0.162, P<0.05), frequency of sex under the influence of alcohol or drugs (B=0.054, P<0.05) were significant predictors of having multiple sexual partners. Sexual orientation, age, smoking, alcohol abuse, drug use, anxiety, depression, childhood physical abuse did not appear to be significant factors associated with having multiple sexual partners. Having multiple sexual partners is the main high risk sex behavior of young men in Chengdu. Childhood sexual abuse and early start of sexual intercourse are the major predictors of having multiple sexual partners.
Treuer, T; Feng, Q; Desaiah, D; Altin, M; Wu, S; El-Shafei, A; Serebryakova, E; Gado, M; Faries, D
2014-09-01
The reduced availability of data from non-Western countries limits our ability to understand attention-deficit/hyperactivity disorder (ADHD) treatment outcomes, specifically, adherence and persistence of ADHD in children and adolescents. This analysis assessed predictors of treatment outcomes in a non-Western cohort of patients with ADHD treated with atomoxetine or methylphenidate. Data from a 12-month, prospective, observational study in outpatients aged 6-17 years treated with atomoxetine (N = 234) or methylphenidate (N = 221) were analysed post hoc to determine potential predictors of treatment outcomes. Participating countries included the Russian Federation, China, Taiwan, Egypt, United Arab Emirates and Lebanon. Factors associated with remission were analysed with stepwise multiple logistic regression and classification and regression trees (CART). Cox proportional hazards models with propensity score adjustment assessed differences in atomoxetine persistence among initial-dose cohorts. In patients treated with atomoxetine who had available dosing information (N = 134), Cox proportional hazards revealed lower (< 0.5 mg/kg) initial dose was significantly associated with shorter medication persistence (p < 0.01). multiple logistic regression analysis revealed greater rates of remission for atomoxetine-treated patients were associated with age (older), country (United Arab Emirates) and gender (female) (all p < 0.05). CART analysis confirmed older age and lack of specific phobias were associated with greater remission rates. For methylphenidate, greater baseline weight (highly correlated with the age factor found for atomoxetine) and prior atomoxetine use were associated with greater remission rates. These findings may help clinicians assess factors upon initiation of ADHD treatment to improve course prediction, proper dosing and treatment adherence and persistence. Observational study, therefore no registration. © 2014 John Wiley & Sons Ltd.
Tilburg, Charles E.; Jordan, Linda M.; Carlson, Amy E.; Zeeman, Stephan I.; Yund, Philip O.
2015-01-01
Faecal pollution in stormwater, wastewater and direct run-off can carry zoonotic pathogens to streams, rivers and the ocean, reduce water quality, and affect both recreational and commercial fishing areas of the coastal ocean. Typically, the closure of beaches and commercial fishing areas is governed by the testing for the presence of faecal bacteria, which requires an 18–24 h period for sample incubation. As water quality can change during this testing period, the need for accurate and timely predictions of coastal water quality has become acute. In this study, we: (i) examine the relationship between water quality, precipitation and river discharge at several locations within the Gulf of Maine, and (ii) use multiple linear regression models based on readily obtainable hydrometeorological measurements to predict water quality events at five coastal locations. Analysis of a 12 year dataset revealed that high river discharge and/or precipitation events can lead to reduced water quality; however, the use of only these two parameters to predict water quality can result in a number of errors. Analysis of a higher frequency, 2 year study using multiple linear regression models revealed that precipitation, salinity, river discharge, winds, seasonality and coastal circulation correlate with variations in water quality. Although there has been extensive development of regression models for freshwater, this is one of the first attempts to create a mechanistic model to predict water quality in coastal marine waters. Model performance is similar to that of efforts in other regions, which have incorporated models into water resource managers' decisions, indicating that the use of a mechanistic model in coastal Maine is feasible. PMID:26587258
ERIC Educational Resources Information Center
Shear, Benjamin R.; Zumbo, Bruno D.
2013-01-01
Type I error rates in multiple regression, and hence the chance for false positive research findings, can be drastically inflated when multiple regression models are used to analyze data that contain random measurement error. This article shows the potential for inflated Type I error rates in commonly encountered scenarios and provides new…
Using Robust Standard Errors to Combine Multiple Regression Estimates with Meta-Analysis
ERIC Educational Resources Information Center
Williams, Ryan T.
2012-01-01
Combining multiple regression estimates with meta-analysis has continued to be a difficult task. A variety of methods have been proposed and used to combine multiple regression slope estimates with meta-analysis, however, most of these methods have serious methodological and practical limitations. The purpose of this study was to explore the use…
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...
NASA Astrophysics Data System (ADS)
Alrehaly, Essa D.
Examination of Saudi Arabian educational practices is scarce, but increasingly important, especially in light of the country's pace in worldwide mathematics and science rankings. The purpose of the study is to understand and evaluate parental influence on male children's science education achievements in Saudi Arabia. Parental level of education and participant's choice of science major were used to identify groups for the purpose of data analysis. Data were gathered using five independent variables concerning parental educational practices (attitude, involvement, autonomy support, structure and control) and the dependent variable of science scores in high school. The sample consisted of 338 participants and was arbitrarily drawn from the science-based colleges (medical, engineering, and natural science) at Jazan University in Saudi Arabia. The data were tested using Pearson's analysis, backward multiple regression, one way ANOVA and independent t-test. The findings of the study reveal significant correlations for all five of the variables. Multiple regressions revealed that all five of the parents' educational practices indicators combined together could explain 19% of the variance in science scores and parental attitude toward science and educational involvement combined accounted for more than 18% of the variance. Analysis indicates that no significant difference is attributable to parental involvement and educational level. This finding is important because it indicates that, in Saudi Arabia, results are not consistent with research in Western or other Asian contexts.
The role of enamel thickness and refractive index on human tooth colour.
Oguro, Rena; Nakajima, Masatoshi; Seki, Naoko; Sadr, Alireza; Tagami, Junji; Sumi, Yasunori
2016-08-01
To investigate the role of enamel thickness and refractive index (n) on tooth colour. The colour and enamel thickness of fifteen extracted human central incisors were determined according to CIELab colour scale using spectrophotometer (Crystaleye) and swept-source optical coherence tomography (SS-OCT), respectively. Subsequently, labial enamel was trimmed by approximately 100μm, and the colour and remaining enamel thickness were investigated again. This cycle was repeated until dentin appeared. Enamel blocks were prepared from the same teeth and their n were obtained using SS-OCT. Multiple regression analysis was performed to reveal any effects of enamel thickness and n on colour difference (ΔE00) and differences in colour parameters with CIELCh and CIELab colour scales. Multiple regression analysis revealed that enamel thickness (p=0.02) and n of enamel (p<0.001) were statistically significant predictors of ΔE00 after complete enamel trimming. The n was also a significant predictor of ΔH' (p=0.01). Enamel thickness and n were not statistically significant predictors of ΔL', ΔC', Δa* and Δb*. Enamel affected tooth colour, in which n was a statistically significant predictor for tooth colour change. Understanding the role of enamel in tooth colour could contribute to development of aesthetic restorative materials that mimic the colour of natural tooth with minimal reduction of the existing enamel. Copyright © 2016 Elsevier Ltd. All rights reserved.
Building Regression Models: The Importance of Graphics.
ERIC Educational Resources Information Center
Dunn, Richard
1989-01-01
Points out reasons for using graphical methods to teach simple and multiple regression analysis. Argues that a graphically oriented approach has considerable pedagogic advantages in the exposition of simple and multiple regression. Shows that graphical methods may play a central role in the process of building regression models. (Author/LS)
Testing Different Model Building Procedures Using Multiple Regression.
ERIC Educational Resources Information Center
Thayer, Jerome D.
The stepwise regression method of selecting predictors for computer assisted multiple regression analysis was compared with forward, backward, and best subsets regression, using 16 data sets. The results indicated the stepwise method was preferred because of its practical nature, when the models chosen by different selection methods were similar…
Decreasing Multicollinearity: A Method for Models with Multiplicative Functions.
ERIC Educational Resources Information Center
Smith, Kent W.; Sasaki, M. S.
1979-01-01
A method is proposed for overcoming the problem of multicollinearity in multiple regression equations where multiplicative independent terms are entered. The method is not a ridge regression solution. (JKS)
Female Literacy Rate is a Better Predictor of Birth Rate and Infant Mortality Rate in India.
Saurabh, Suman; Sarkar, Sonali; Pandey, Dhruv K
2013-01-01
Educated women are known to take informed reproductive and healthcare decisions. These result in population stabilization and better infant care reflected by lower birth rates and infant mortality rates (IMRs), respectively. Our objective was to study the relationship of male and female literacy rates with crude birth rates (CBRs) and IMRs of the states and union territories (UTs) of India. The data were analyzed using linear regression. CBR and IMR were taken as the dependent variables; while the overall literacy rates, male, and female literacy rates were the independent variables. CBRs were inversely related to literacy rates (slope parameter = -0.402, P < 0.001). On multiple linear regression with male and female literacy rates, a significant inverse relationship emerged between female literacy rate and CBR (slope = -0.363, P < 0.001), while male literacy rate was not significantly related to CBR (P = 0.674). IMR of the states were also inversely related to their literacy rates (slope = -1.254, P < 0.001). Multiple linear regression revealed a significant inverse relationship between IMR and female literacy (slope = -0.816, P = 0.031), whereas male literacy rate was not significantly related (P = 0.630). Female literacy is relatively highly important for both population stabilization and better infant health.
Mathur, Praveen; Sharma, Sarita; Soni, Bhupendra
2010-01-01
In the present work, an attempt is made to formulate multiple regression equations using all possible regressions method for groundwater quality assessment of Ajmer-Pushkar railway line region in pre- and post-monsoon seasons. Correlation studies revealed the existence of linear relationships (r 0.7) for electrical conductivity (EC), total hardness (TH) and total dissolved solids (TDS) with other water quality parameters. The highest correlation was found between EC and TDS (r = 0.973). EC showed highly significant positive correlation with Na, K, Cl, TDS and total solids (TS). TH showed highest correlation with Ca and Mg. TDS showed significant correlation with Na, K, SO4, PO4 and Cl. The study indicated that most of the contamination present was water soluble or ionic in nature. Mg was present as MgCl2; K mainly as KCl and K2SO4, and Na was present as the salts of Cl, SO4 and PO4. On the other hand, F and NO3 showed no significant correlations. The r2 values and F values (at 95% confidence limit, alpha = 0.05) for the modelled equations indicated high degree of linearity among independent and dependent variables. Also the error % between calculated and experimental values was contained within +/- 15% limit.
Multiple-Instance Regression with Structured Data
NASA Technical Reports Server (NTRS)
Wagstaff, Kiri L.; Lane, Terran; Roper, Alex
2008-01-01
We present a multiple-instance regression algorithm that models internal bag structure to identify the items most relevant to the bag labels. Multiple-instance regression (MIR) operates on a set of bags with real-valued labels, each containing a set of unlabeled items, in which the relevance of each item to its bag label is unknown. The goal is to predict the labels of new bags from their contents. Unlike previous MIR methods, MI-ClusterRegress can operate on bags that are structured in that they contain items drawn from a number of distinct (but unknown) distributions. MI-ClusterRegress simultaneously learns a model of the bag's internal structure, the relevance of each item, and a regression model that accurately predicts labels for new bags. We evaluated this approach on the challenging MIR problem of crop yield prediction from remote sensing data. MI-ClusterRegress provided predictions that were more accurate than those obtained with non-multiple-instance approaches or MIR methods that do not model the bag structure.
Spencer, Monique E; Jain, Alka; Matteini, Amy; Beamer, Brock A; Wang, Nae-Yuh; Leng, Sean X; Punjabi, Naresh M; Walston, Jeremy D; Fedarko, Neal S
2010-08-01
Neopterin, a GTP metabolite expressed by macrophages, is a marker of immune activation. We hypothesize that levels of this serum marker alter with donor age, reflecting increased chronic immune activation in normal aging. In addition to age, we assessed gender, race, body mass index (BMI), and percentage of body fat (%fat) as potential covariates. Serum was obtained from 426 healthy participants whose age ranged from 18 to 87 years. Anthropometric measures included %fat and BMI. Neopterin concentrations were measured by competitive ELISA. The paired associations between neopterin and age, BMI, or %fat were analyzed by Spearman's correlation or by linear regression of log-transformed neopterin, whereas overall associations were modeled by multiple regression of log-transformed neopterin as a function of age, gender, race, BMI, %fat, and interaction terms. Across all participants, neopterin exhibited a positive association with age, BMI, and %fat. Multiple regression modeling of neopterin in women and men as a function of age, BMI, and race revealed that each covariate contributed significantly to neopterin values and that optimal modeling required an interaction term between race and BMI. The covariate %fat was highly correlated with BMI and could be substituted for BMI to yield similar regression coefficients. The association of age and gender with neopterin levels and their modification by race, BMI, or %fat reflect the biology underlying chronic immune activation and perhaps gender differences in disease incidence, morbidity, and mortality.
BLZF1 expression is of prognostic significance in hepatocellular carcinoma
DOE Office of Scientific and Technical Information (OSTI.GOV)
Huang, Run-Yue, E-mail: ry_huang@hotmail.com; Su, Shu-Guang; Wu, Dan-Chun
2015-11-20
BLZF1, a member of b-ZIP family, has been implicated in epigenetic regulation and Wnt/β-catenin signaling. Its expression and clinical significance in human cancers remain largely unknown. In this study, we showed that BLZF1 expression was reduced in hepatocellular carcinoma (HCC) tissues, compared to the paracarcinoma tissues, at both mRNA and protein levels. Results of immunohistochemistry revealed that BLZF1 was presented in both nuclear and cytoplasm. Decreased expression of nuclear and cytosolic BLZF1 in HCC was depicted in 68.2% and 79.2% of the 634 cases. Nuclear BLZF1 expression was significantly associated with tumor multiplicity (P = 0.048) and tumor capsule (P = 0.028), while cytosolicmore » BLZF1 expression was correlated with serum AFP level (P = 0.017), tumor differentiation (P = 0.001) and tumor capsule (P = 0.003). Kaplan–Meier analysis indicated both nuclear and cytosolic BLZF1 expression was associated with poor overall survival. Low nuclear BLZF1 also indicated unfavorable disease-free survival and high tendency of tumor recurrence. Furthermore, multiple Cox regression analysis revealed nuclear BLZF1 as an independent factor for overall survival (Hazard Ratio (HR) = 0.827, 95% confident interval (95%CI): 0.697–0.980, P = 0.029). The prognostic value of BLZF1 was further confirmed by stratified analyses. Collectively, our data suggest BLZF1 is a novel unfavorable biomarker for prognosis of patients with HCC. - Highlights: • BLZF1 expression was much lower in HCC tissues. • Low BLZF1 expression was associated with poor outcomes in a cohort of 634 HCC patients. • Multiple Cox regression analysis indicated nuclear BLZF1 as an independent predictor for overall survival.« less
Forecasting daily patient volumes in the emergency department.
Jones, Spencer S; Thomas, Alun; Evans, R Scott; Welch, Shari J; Haug, Peter J; Snow, Gregory L
2008-02-01
Shifts in the supply of and demand for emergency department (ED) resources make the efficient allocation of ED resources increasingly important. Forecasting is a vital activity that guides decision-making in many areas of economic, industrial, and scientific planning, but has gained little traction in the health care industry. There are few studies that explore the use of forecasting methods to predict patient volumes in the ED. The goals of this study are to explore and evaluate the use of several statistical forecasting methods to predict daily ED patient volumes at three diverse hospital EDs and to compare the accuracy of these methods to the accuracy of a previously proposed forecasting method. Daily patient arrivals at three hospital EDs were collected for the period January 1, 2005, through March 31, 2007. The authors evaluated the use of seasonal autoregressive integrated moving average, time series regression, exponential smoothing, and artificial neural network models to forecast daily patient volumes at each facility. Forecasts were made for horizons ranging from 1 to 30 days in advance. The forecast accuracy achieved by the various forecasting methods was compared to the forecast accuracy achieved when using a benchmark forecasting method already available in the emergency medicine literature. All time series methods considered in this analysis provided improved in-sample model goodness of fit. However, post-sample analysis revealed that time series regression models that augment linear regression models by accounting for serial autocorrelation offered only small improvements in terms of post-sample forecast accuracy, relative to multiple linear regression models, while seasonal autoregressive integrated moving average, exponential smoothing, and artificial neural network forecasting models did not provide consistently accurate forecasts of daily ED volumes. This study confirms the widely held belief that daily demand for ED services is characterized by seasonal and weekly patterns. The authors compared several time series forecasting methods to a benchmark multiple linear regression model. The results suggest that the existing methodology proposed in the literature, multiple linear regression based on calendar variables, is a reasonable approach to forecasting daily patient volumes in the ED. However, the authors conclude that regression-based models that incorporate calendar variables, account for site-specific special-day effects, and allow for residual autocorrelation provide a more appropriate, informative, and consistently accurate approach to forecasting daily ED patient volumes.
Garvey, Jason C; Rankin, Susan R
2015-01-01
This study utilized MANOVA and hierarchical multiple regression to examine the relationships between campus experiences and coming-out decisions among trans- and queer-spectrum undergraduates. Findings revealed higher levels of outness/disclosure for cisgender LGBQ women, and more negative perceptions of campus climate, classroom climate, and curriculum inclusivity and higher use of campus resources for trans-spectrum students. Results also revealed that higher levels of outness significantly related to poorer perceptions of campus responses and campus resources. Implications address the need to foster an encouraging and supportive campus and classroom climate and to improve the relationships with LGBTQ resource centers for trans- and queer-spectrum students.
Predictors of photo naming: Dutch norms for 327 photos.
Shao, Zeshu; Stiegert, Julia
2016-06-01
In the present study, we report naming latencies and norms for 327 photos of objects in Dutch. We provide norms for eight psycholinguistic variables: age of acquisition, familiarity, imageability, image agreement, objective and subjective visual complexity, word frequency, word length in syllables and letters, and name agreement. Furthermore, multiple regression analyses revealed that the significant predictors of photo-naming latencies were name agreement, word frequency, imageability, and image agreement. The naming latencies, norms, and stimuli are provided as supplemental materials.
Examining the relationship between work-family spillover and sleep quality.
Williams, Alysha; Franche, Renée-Louise; Ibrahim, Selahadin; Mustard, Cameron A; Layton, Francine Roussy
2006-01-01
The present study examined the relationship between work-family spillover, job characteristics, and sleep quality in a sample of health care workers (N = 168) recruited from 3 Canadian hospitals. A multiple regression analysis revealed that positive family-to-work spillover is associated with better sleep quality, after controlling for age, physical health, depressive symptomatology, work situation, and number of children. These findings are discussed within a theoretical framework drawing on the concepts of effort and recovery. Copyright 2006 APA.
Frndak, Seth E; Smerbeck, Audrey M; Irwin, Lauren N; Drake, Allison S; Kordovski, Victoria M; Kunker, Katrina A; Khan, Anjum L; Benedict, Ralph H B
2016-10-01
We endeavored to clarify how distinct co-occurring symptoms relate to the presence of negative work events in employed multiple sclerosis (MS) patients. Latent profile analysis (LPA) was utilized to elucidate common disability patterns by isolating patient subpopulations. Samples of 272 employed MS patients and 209 healthy controls (HC) were administered neuroperformance tests of ambulation, hand dexterity, processing speed, and memory. Regression-based norms were created from the HC sample. LPA identified latent profiles using the regression-based z-scores. Finally, multinomial logistic regression tested for negative work event differences among the latent profiles. Four profiles were identified via LPA: a common profile (55%) characterized by slightly below average performance in all domains, a broadly low-performing profile (18%), a poor motor abilities profile with average cognition (17%), and a generally high-functioning profile (9%). Multinomial regression analysis revealed that the uniformly low-performing profile demonstrated a higher likelihood of reported negative work events. Employed MS patients with co-occurring motor, memory and processing speed impairments were most likely to report a negative work event, classifying them as uniquely at risk for job loss.
Tighe, Elizabeth L.; Schatschneider, Christopher
2015-01-01
The purpose of this study was to investigate the joint and unique contributions of morphological awareness and vocabulary knowledge at five reading comprehension levels in Adult Basic Education (ABE) students. We introduce the statistical technique of multiple quantile regression, which enabled us to assess the predictive utility of morphological awareness and vocabulary knowledge at multiple points (quantiles) along the continuous distribution of reading comprehension. To demonstrate the efficacy of our multiple quantile regression analysis, we compared and contrasted our results with a traditional multiple regression analytic approach. Our results indicated that morphological awareness and vocabulary knowledge accounted for a large portion of the variance (82-95%) in reading comprehension skills across all quantiles. Morphological awareness exhibited the greatest unique predictive ability at lower levels of reading comprehension whereas vocabulary knowledge exhibited the greatest unique predictive ability at higher levels of reading comprehension. These results indicate the utility of using multiple quantile regression to assess trajectories of component skills across multiple levels of reading comprehension. The implications of our findings for ABE programs are discussed. PMID:25351773
Inhibitory saccadic dysfunction is associated with cerebellar injury in multiple sclerosis.
Kolbe, Scott C; Kilpatrick, Trevor J; Mitchell, Peter J; White, Owen; Egan, Gary F; Fielding, Joanne
2014-05-01
Cognitive dysfunction is common in patients with multiple sclerosis (MS). Saccadic eye movement paradigms such as antisaccades (AS) can sensitively interrogate cognitive function, in particular, the executive and attentional processes of response selection and inhibition. Although we have previously demonstrated significant deficits in the generation of AS in MS patients, the neuropathological changes underlying these deficits were not elucidated. In this study, 24 patients with relapsing-remitting MS underwent testing using an AS paradigm. Rank correlation and multiple regression analyses were subsequently used to determine whether AS errors in these patients were associated with: (i) neurological and radiological abnormalities, as measured by standard clinical techniques, (ii) cognitive dysfunction, and (iii) regionally specific cerebral white and gray-matter damage. Although AS error rates in MS patients did not correlate with clinical disability (using the Expanded Disability Status Score), T2 lesion load or brain parenchymal fraction, AS error rate did correlate with performance on the Paced Auditory Serial Addition Task and the Symbol Digit Modalities Test, neuropsychological tests commonly used in MS. Further, voxel-wise regression analyses revealed associations between AS errors and reduced fractional anisotropy throughout most of the cerebellum, and increased mean diffusivity in the cerebellar vermis. Region-wise regression analyses confirmed that AS errors also correlated with gray-matter atrophy in the cerebellum right VI subregion. These results support the use of the AS paradigm as a marker for cognitive dysfunction in MS and implicate structural and microstructural changes to the cerebellum as a contributing mechanism for AS deficits in these patients. Copyright © 2013 Wiley Periodicals, Inc.
Yokoi, Masayuki; Tashiro, Takao
2014-01-01
We studied how the separation of dispensing and prescribing of medicines between pharmacies and clinics (the “separation system”) can reduce internal medicine costs. To do so, we obtained publicly available data by searching electronic databases and official web pages of the Japanese government and non-profit public service corporations on the Internet. For Japanese medical institutions, participation in the separation system is optional. Consequently, the expansion rate of the separation system for each of the administrative districts is highly variable. The data were subjected to multiple regression analysis; daily internal medicines were the objective variable and expansion rate of the separation system was the explanatory variable. A multiple regression analysis revealed that the expansion rate of the separation system and the rate of replacing brand name medicine with generic medicine showed a significant negative partial correlation with daily internal medicine costs. Thus, the separation system was as effective in reducing medicine costs as the use of generic medicines. Because of its medical economic efficiency, the separation system should be expanded, especially in Asian countries in which the system is underdeveloped. PMID:24999122
Barnes, J C; Boutwell, Brian B; Miller, J Mitchell; DeShay, Rashaan A; Beaver, Kevin M; White, Norman
2016-01-01
To examine whether differential exposure to pre- and perinatal risk factors explained differences in levels of self-regulation between children of different races (White, Black, Hispanic, Asian, and Other). Multiple regression models based on data from the Early Childhood Longitudinal Study, Birth Cohort (n ≈ 9,850) were used to analyze the impact of pre- and perinatal risk factors on the development of self-regulation at age 2 years. Racial differences in levels of self-regulation were observed. Racial differences were also observed for 9 of the 12 pre-/perinatal risk factors. Multiple regression analyses revealed that a portion of the racial differences in self-regulation was explained by differential exposure to several of the pre-/perinatal risk factors. Specifically, maternal age at childbirth, gestational timing, and the family's socioeconomic status were significantly related to the child's level of self-regulation. These factors accounted for a statistically significant portion of the racial differences observed in self-regulation. The findings indicate racial differences in self-regulation may be, at least partially, explained by racial differences in exposure to pre- and perinatal risk factors.
Yokoi, Masayuki; Tashiro, Takao
2014-04-07
We studied how the separation of dispensing and prescribing of medicines between pharmacies and clinics (the "separation system") can reduce internal medicine costs. To do so, we obtained publicly available data by searching electronic databases and official web pages of the Japanese government and non-profit public service corporations on the Internet. For Japanese medical institutions, participation in the separation system is optional. Consequently, the expansion rate of the separation system for each of the administrative districts is highly variable. The data were subjected to multiple regression analysis; daily internal medicines were the objective variable and expansion rate of the separation system was the explanatory variable. A multiple regression analysis revealed that the expansion rate of the separation system and the rate of replacing brand name medicine with generic medicine showed a significant negative partial correlation with daily internal medicine costs. Thus, the separation system was as effective in reducing medicine costs as the use of generic medicines. Because of its medical economic efficiency, the separation system should be expanded, especially in Asian countries in which the system is underdeveloped.
Golmohammadi, Hassan
2009-11-30
A quantitative structure-property relationship (QSPR) study was performed to develop models those relate the structure of 141 organic compounds to their octanol-water partition coefficients (log P(o/w)). A genetic algorithm was applied as a variable selection tool. Modeling of log P(o/w) of these compounds as a function of theoretically derived descriptors was established by multiple linear regression (MLR), partial least squares (PLS), and artificial neural network (ANN). The best selected descriptors that appear in the models are: atomic charge weighted partial positively charged surface area (PPSA-3), fractional atomic charge weighted partial positive surface area (FPSA-3), minimum atomic partial charge (Qmin), molecular volume (MV), total dipole moment of molecule (mu), maximum antibonding contribution of a molecule orbital in the molecule (MAC), and maximum free valency of a C atom in the molecule (MFV). The result obtained showed the ability of developed artificial neural network to prediction of partition coefficients of organic compounds. Also, the results revealed the superiority of ANN over the MLR and PLS models. Copyright 2009 Wiley Periodicals, Inc.
Cuevas, Kimberly; Calkins, Susan D.; Bell, Martha Ann
2015-01-01
Executive functions (EFs) are linked with optimal cognitive and social-emotional development. Despite behavioral evidence of sex differences in early childhood EF, little is known about potential sex differences in corresponding brain-behavior associations. The present study examined changes in 4-year-olds’ 6–9 Hz EEG power in response to increased executive processing demands (i.e., “Stroop-like” vs. “non-Stroop” day-night tasks). Although there were no sex differences in task performance, an examination of multiple scalp electrode sites revealed that boys exhibited more widespread changes in EEG power as compared to girls. Further, multiple regression analyses controlling for maternal education and non-EF performance indicated that individual differences in boys’ and girls’ EF performance were associated with different frontal neural correlates (i.e., different frontal scalp sites and different measures of EEG power). These data reveal valuable information concerning sex differences in the neural systems underlying executive processing during early childhood. PMID:26681615
ℓ(p)-Norm multikernel learning approach for stock market price forecasting.
Shao, Xigao; Wu, Kun; Liao, Bifeng
2012-01-01
Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ(1)-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ(p)-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ(1)-norm multiple support vector regression model.
Grey, J M; Totsika, V; Hastings, R P
2018-06-01
Little is known about the role of living circumstances to the perception of subjective well-being (SWB) and health of adults with intellectual disability (ID). The aim of the present study was to examine whether living circumstances impact differently on the perception of health and SWB and whether potential differences persist after accounting for other variables (e.g. level of support needs and reporting method). Secondary data analysis was undertaken of a large national survey of adults with an ID in England, aged 16 years and over. Participants were identified as living with family (N = 1528) or living out of home (N = 874). The results of t-test and chi-square revealed that levels of health and SWB were perceived as being higher for people living with family than those living in out-of-home settings. Multiple linear regression analyses fitted to explore factors associated with these reported differences revealed that, when controlling for other variables, living with family was highly associated with reports of better SWB. Multiple logistic regression revealed that whilst the health status of people living with families were perceived as better, this was only true when their support needs were low. Poorest health outcomes were found for people with highest support needs who lived with family. On the whole, the health and well-being of adults living with family were perceived more positively than those living out of home. However, potential health disparities exist for those with high support needs who live with family. Further longitudinal research is needed to explore causes and potential solution to these inequalities. © 2018 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Oguntunde, Philip G.; Lischeid, Gunnar; Dietrich, Ottfried
2018-03-01
This study examines the variations of climate variables and rice yield and quantifies the relationships among them using multiple linear regression, principal component analysis, and support vector machine (SVM) analysis in southwest Nigeria. The climate and yield data used was for a period of 36 years between 1980 and 2015. Similar to the observed decrease ( P < 0.001) in rice yield, pan evaporation, solar radiation, and wind speed declined significantly. Eight principal components exhibited an eigenvalue > 1 and explained 83.1% of the total variance of predictor variables. The SVM regression function using the scores of the first principal component explained about 75% of the variance in rice yield data and linear regression about 64%. SVM regression between annual solar radiation values and yield explained 67% of the variance. Only the first component of the principal component analysis (PCA) exhibited a clear long-term trend and sometimes short-term variance similar to that of rice yield. Short-term fluctuations of the scores of the PC1 are closely coupled to those of rice yield during the 1986-1993 and the 2006-2013 periods thereby revealing the inter-annual sensitivity of rice production to climate variability. Solar radiation stands out as the climate variable of highest influence on rice yield, and the influence was especially strong during monsoon and post-monsoon periods, which correspond to the vegetative, booting, flowering, and grain filling stages in the study area. The outcome is expected to provide more in-depth regional-specific climate-rice linkage for screening of better cultivars that can positively respond to future climate fluctuations as well as providing information that may help optimized planting dates for improved radiation use efficiency in the study area.
Community Air Sensor Network (CAIRSENSE) project ...
Advances in air pollution sensor technology have enabled the development of small and low cost systems to measure outdoor air pollution. The deployment of a large number of sensors across a small geographic area would have potential benefits to supplement traditional monitoring networks with additional geographic and temporal measurement resolution, if the data quality were sufficient. To understand the capability of emerging air sensor technology, the Community Air Sensor Network (CAIRSENSE) project deployed low cost, continuous and commercially-available air pollution sensors at a regulatory air monitoring site and as a local sensor network over a surrounding ~2 km area in Southeastern U.S. Co-location of sensors measuring oxides of nitrogen, ozone, carbon monoxide, sulfur dioxide, and particles revealed highly variable performance, both in terms of comparison to a reference monitor as well as whether multiple identical sensors reproduced the same signal. Multiple ozone, nitrogen dioxide, and carbon monoxide sensors revealed low to very high correlation with a reference monitor, with Pearson sample correlation coefficient (r) ranging from 0.39 to 0.97, -0.25 to 0.76, -0.40 to 0.82, respectively. The only sulfur dioxide sensor tested revealed no correlation (r 0.5), step-wise multiple linear regression was performed to determine if ambient temperature, relative humidity (RH), or age of the sensor in sampling days could be used in a correction algorihm to im
Advanced statistics: linear regression, part II: multiple linear regression.
Marill, Keith A
2004-01-01
The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.
Intimate relationship quality, self-concept and illness acceptance in those with multiple sclerosis.
Wright, Thomas M; Kiropoulos, Litza A
2017-02-01
Lower levels of Intimate Relationship Quality (IRQ) have been found in those with Multiple Sclerosis (MS) compared to the general population. This study examined an MS sample to see whether IRQ was positively associated with self-concept, whether IRQ was positively associated with MS illness acceptance and whether IRQ was predicted by self-concept and illness acceptance. In this cross-sectional study, 115 participants with MS who were in an intimate relationship completed an online survey advertised on MS related websites. The survey assessed demographic variables, MS illness variables and levels of IRQ, self-concept and illness acceptance. Results revealed that IRQ was significantly positively associated with self-concept and with illness acceptance. Multiple hierarchical linear regression analysis revealed that, after controlling for illness duration and level of disability, self-concept significantly predicted IRQ but illness acceptance did not significantly predict IRQ. This study addressed several gaps and methodological flaws in the literature and was the first known to assess predictors of IRQ in those with MS. The results suggest that self-concept could be a potential target for individual and couple psychological interventions to improve IRQ and contribute to improved outcomes for those with MS.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Friddle, Carl J; Koga, Teiichiro; Rubin, Edward M.
2000-03-15
While cardiac hypertrophy has been the subject of intensive investigation, regression of hypertrophy has been significantly less studied, precluding large-scale analysis of the relationship between these processes. In the present study, using pharmacological models of hypertrophy in mice, expression profiling was performed with fragments of more than 3,000 genes to characterize and contrast expression changes during induction and regression of hypertrophy. Administration of angiotensin II and isoproterenol by osmotic minipump produced increases in heart weight (15% and 40% respectively) that returned to pre-induction size following drug withdrawal. From multiple expression analyses of left ventricular RNA isolated at daily time-points duringmore » cardiac hypertrophy and regression, we identified sets of genes whose expression was altered at specific stages of this process. While confirming the participation of 25 genes or pathways previously known to be altered by hypertrophy, a larger set of 30 genes was identified whose expression had not previously been associated with cardiac hypertrophy or regression. Of the 55 genes that showed reproducible changes during the time course of induction and regression, 32 genes were altered only during induction and 8 were altered only during regression. This study identified both known and novel genes whose expression is affected at different stages of cardiac hypertrophy and regression and demonstrates that cardiac remodeling during regression utilizes a set of genes that are distinct from those used during induction of hypertrophy.« less
ERIC Educational Resources Information Center
Anderson, Carolyn J.; Verkuilen, Jay; Peyton, Buddy L.
2010-01-01
Survey items with multiple response categories and multiple-choice test questions are ubiquitous in psychological and educational research. We illustrate the use of log-multiplicative association (LMA) models that are extensions of the well-known multinomial logistic regression model for multiple dependent outcome variables to reanalyze a set of…
NASA Technical Reports Server (NTRS)
Maahs, H. G.
1972-01-01
Eighteen material properties were measured on 45 different, commercially available, artificial graphites. Ablation performance of these same graphites were also measured in a Mach 2 airstream at a stagnation pressure of 5.6 atm. Correlations were developed, where possible, between pairs of the material properties. Multiple regression equations were then formulated relating ablation performance to the various material properties, thus identifying those material properties having the strongest effect on ablation performance. These regression equations reveal that ablation performance in the present test environment depends primarily on maximum grain size, density, ash content, thermal conductivity, and mean pore radius. For optimization of ablation performance, grain size should be small, ash content low, density and thermal conductivity high, and mean pore radius large.
Learning accurate and interpretable models based on regularized random forests regression
2014-01-01
Background Many biology related research works combine data from multiple sources in an effort to understand the underlying problems. It is important to find and interpret the most important information from these sources. Thus it will be beneficial to have an effective algorithm that can simultaneously extract decision rules and select critical features for good interpretation while preserving the prediction performance. Methods In this study, we focus on regression problems for biological data where target outcomes are continuous. In general, models constructed from linear regression approaches are relatively easy to interpret. However, many practical biological applications are nonlinear in essence where we can hardly find a direct linear relationship between input and output. Nonlinear regression techniques can reveal nonlinear relationship of data, but are generally hard for human to interpret. We propose a rule based regression algorithm that uses 1-norm regularized random forests. The proposed approach simultaneously extracts a small number of rules from generated random forests and eliminates unimportant features. Results We tested the approach on some biological data sets. The proposed approach is able to construct a significantly smaller set of regression rules using a subset of attributes while achieving prediction performance comparable to that of random forests regression. Conclusion It demonstrates high potential in aiding prediction and interpretation of nonlinear relationships of the subject being studied. PMID:25350120
Correlates of Adherence among Rural Indian Women Living with HIV/AIDS.
Nyamathi, Adeline; Salem, Benissa; Ernst, E J; Keenan, Colleen; Suresh, P; Sinha, Sanjeev; Ganguly, Kalyan; Ramakrishnan, Padma; Liu, Yihang
2012-01-01
In this prospective, randomized clinical trial, correlates of adherence to antiretroviral therapy (ART) were assessed using a baseline questionnaire among 68 rural women living with AIDS (WLA) in India. Unadjusted analyses revealed positive relationships of ART adherence with Hindu religion, and support from spouses and parents, whereas negative associations were found with depression, poor quality of life, and having ten or more HIV symptoms. Multiple linear regression analysis also revealed that WLA who were Hindu, not depressed, had ART support from spouses and parents, and perceived some benefit from ART were more adherent to ART than their respective counterparts. This study reveals the unique challenges which rural WLA experience and the need to mitigate these challenges early in ART treatment. Further, the findings enable the refinement of an intervention program which will focus on strengthening ART adherence among rural WLA.
Isolating and Examining Sources of Suppression and Multicollinearity in Multiple Linear Regression
ERIC Educational Resources Information Center
Beckstead, Jason W.
2012-01-01
The presence of suppression (and multicollinearity) in multiple regression analysis complicates interpretation of predictor-criterion relationships. The mathematical conditions that produce suppression in regression analysis have received considerable attention in the methodological literature but until now nothing in the way of an analytic…
General Nature of Multicollinearity in Multiple Regression Analysis.
ERIC Educational Resources Information Center
Liu, Richard
1981-01-01
Discusses multiple regression, a very popular statistical technique in the field of education. One of the basic assumptions in regression analysis requires that independent variables in the equation should not be highly correlated. The problem of multicollinearity and some of the solutions to it are discussed. (Author)
ℓ p-Norm Multikernel Learning Approach for Stock Market Price Forecasting
Shao, Xigao; Wu, Kun; Liao, Bifeng
2012-01-01
Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ 1-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ p-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ 1-norm multiple support vector regression model. PMID:23365561
Sample size determination for logistic regression on a logit-normal distribution.
Kim, Seongho; Heath, Elisabeth; Heilbrun, Lance
2017-06-01
Although the sample size for simple logistic regression can be readily determined using currently available methods, the sample size calculation for multiple logistic regression requires some additional information, such as the coefficient of determination ([Formula: see text]) of a covariate of interest with other covariates, which is often unavailable in practice. The response variable of logistic regression follows a logit-normal distribution which can be generated from a logistic transformation of a normal distribution. Using this property of logistic regression, we propose new methods of determining the sample size for simple and multiple logistic regressions using a normal transformation of outcome measures. Simulation studies and a motivating example show several advantages of the proposed methods over the existing methods: (i) no need for [Formula: see text] for multiple logistic regression, (ii) available interim or group-sequential designs, and (iii) much smaller required sample size.
Richardson, Miles
2017-04-01
In ergonomics there is often a need to identify and predict the separate effects of multiple factors on performance. A cost-effective fractional factorial approach to understanding the relationship between task characteristics and task performance is presented. The method has been shown to provide sufficient independent variability to reveal and predict the effects of task characteristics on performance in two domains. The five steps outlined are: selection of performance measure, task characteristic identification, task design for user trials, data collection, regression model development and task characteristic analysis. The approach can be used for furthering knowledge of task performance, theoretical understanding, experimental control and prediction of task performance. Practitioner Summary: A cost-effective method to identify and predict the separate effects of multiple factors on performance is presented. The five steps allow a better understanding of task factors during the design process.
Himle, Joseph A; Weaver, Addie; Bybee, Deborah; O'Donnell, Lisa; Vlnka, Sarah; Laviolette, Wayne; Steinberger, Edward; Golenberg, Zipora; Levine, Debra Siegel
2014-07-01
The literature has consistently demonstrated that social anxiety disorder has substantial negative impacts on occupational functioning. However, to date, no empirical work has focused on understanding the specific nature of vocational problems among persons with social anxiety disorder. This study examined the association between perceived barriers to employment, employment skills, and job aspirations and social anxiety among adults seeking vocational rehabilitation services. Data from intake assessments (June 2010-December 2011) of 265 low-income, unemployed adults who initiated vocational rehabilitation services in urban Michigan were examined to assess perceived barriers to employment, employment skills, job aspirations, and demographic characteristics among participants who did or did not screen positive for social anxiety disorder. Bivariate and multiple logistic regression analyses were performed. After adjustment for other factors, the multiple logistic regression analysis revealed that perceiving more employment barriers involving experience and skills, reporting fewer skills related to occupations requiring social skills, and having less education were significantly associated with social anxiety disorder. Participants who screened positive for social anxiety disorder were significantly less likely to aspire to social jobs. Employment-related characteristics that were likely to have an impact on occupational functioning were significantly different between persons with and without social anxiety problems. Identifying these differences in employment barriers, skills, and job aspirations revealed important information for designing psychosocial interventions for treatment of social anxiety disorder. The findings underscored the need for vocational services professionals to assess and address social anxiety among their clients.
SU-F-R-20: Image Texture Features Correlate with Time to Local Failure in Lung SBRT Patients
DOE Office of Scientific and Technical Information (OSTI.GOV)
Andrews, M; Abazeed, M; Woody, N
Purpose: To explore possible correlation between CT image-based texture and histogram features and time-to-local-failure in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT).Methods and Materials: From an IRB-approved lung SBRT registry for patients treated between 2009–2013 we selected 48 (20 male, 28 female) patients with local failure. Median patient age was 72.3±10.3 years. Mean time to local failure was 15 ± 7.1 months. Physician-contoured gross tumor volumes (GTV) on the planning CT images were processed and 3D gray-level co-occurrence matrix (GLCM) based texture and histogram features were calculated in Matlab. Data were exported tomore » R and a multiple linear regression model was used to examine the relationship between texture features and time-to-local-failure. Results: Multiple linear regression revealed that entropy (p=0.0233, multiple R2=0.60) from GLCM-based texture analysis and the standard deviation (p=0.0194, multiple R2=0.60) from the histogram-based features were statistically significantly correlated with the time-to-local-failure. Conclusion: Image-based texture analysis can be used to predict certain aspects of treatment outcomes of NSCLC patients treated with SBRT. We found entropy and standard deviation calculated for the GTV on the CT images displayed a statistically significant correlation with and time-to-local-failure in lung SBRT patients.« less
Secular trends in Cherokee cranial morphology: Eastern vs Western bands.
Sutphin, Rebecca; Ross, Ann H; Jantz, Richard L
2014-01-01
The research objective was to examine if secular trends can be identified for cranial data commissioned by Boas in 1892, specifically for cranial breadth and cranial length of the Eastern and Western band Cherokee who experienced environmental hardships. Multiple regression analysis was used to test the degree of relationship between each of the cranial measures: cranial length, cranial breadth and cephalic index, along with predictor variables (year-of-birth, location, sex, admixture); the model revealed a significant difference for all craniometric variables. Additional regression analysis was performed with smoothing Loess plots to observe cranial length and cranial breadth change over time (year-of-birth) separately for Eastern and Western Cherokee band females and males born between 1783-1874. This revealed the Western and Eastern bands show a decrease in cranial length over time. Eastern band individuals maintain a relatively constant head breadth, while Western Band individuals show a sharp decline beginning around 1860. These findings support negative secular trend occurring for both Cherokee bands where the environment made a detrimental impact; this is especially marked with the Western Cherokee band.
Tighe, Elizabeth L; Schatschneider, Christopher
2016-07-01
The purpose of this study was to investigate the joint and unique contributions of morphological awareness and vocabulary knowledge at five reading comprehension levels in adult basic education (ABE) students. We introduce the statistical technique of multiple quantile regression, which enabled us to assess the predictive utility of morphological awareness and vocabulary knowledge at multiple points (quantiles) along the continuous distribution of reading comprehension. To demonstrate the efficacy of our multiple quantile regression analysis, we compared and contrasted our results with a traditional multiple regression analytic approach. Our results indicated that morphological awareness and vocabulary knowledge accounted for a large portion of the variance (82%-95%) in reading comprehension skills across all quantiles. Morphological awareness exhibited the greatest unique predictive ability at lower levels of reading comprehension whereas vocabulary knowledge exhibited the greatest unique predictive ability at higher levels of reading comprehension. These results indicate the utility of using multiple quantile regression to assess trajectories of component skills across multiple levels of reading comprehension. The implications of our findings for ABE programs are discussed. © Hammill Institute on Disabilities 2014.
Stepwise versus Hierarchical Regression: Pros and Cons
ERIC Educational Resources Information Center
Lewis, Mitzi
2007-01-01
Multiple regression is commonly used in social and behavioral data analysis. In multiple regression contexts, researchers are very often interested in determining the "best" predictors in the analysis. This focus may stem from a need to identify those predictors that are supportive of theory. Alternatively, the researcher may simply be interested…
NASA Astrophysics Data System (ADS)
Nagano, Hirohiko; Iwata, Hiroki
2017-03-01
Alaska wildfires may play an important role in nitrogen (N) dry deposition in Alaskan boreal forests. Here we used annual N dry deposition data measured by CASTNET at Denali National Park (DEN417) during 1999-2013, to evaluate the relationships between wildfire extent and N dry deposition in Alaska. We established six potential factors for multiple regression analysis, including burned area within 100 km of DEN417 (BA100km) and in other distant parts of Alaska (BAAK), the sum of indexes of North Atlantic Oscillation and Arctic Oscillation (OI), number of days with negative OI (OIday), precipitation (PRCP), and number of days with PRCP (PRCPday). Multiple regression analysis was conducted for both time scales, annual (using only annual values of factors) and six-month (using annual values of BAAK and BA100km, and fire and non-fire seasons' values of other four factors) time scales. Together, BAAK, BA100km, and OIday, along with PRCPday in the case of the six-month scale, explained more than 92% of the interannual variation in N dry deposition. The influence of BA100km on N dry deposition was ten-fold greater than from BAAK; the qualitative contribution was almost zero, however, due to the small BA100km. BAAK was the leading explanatory factor, with a 15 ± 14% contribution. We further calculated N dry deposition during 1950-2013 using the obtained regression equation and long-term records for the factors. The N dry deposition calculated for 1950-2013 revealed that an increased occurrence of wildfires during the 2000s led to the maximum N dry deposition exhibited during this decade. As a result, the effect of BAAK on N dry deposition remains sufficiently large, even when large possible uncertainties (>40%) in the measurement of N dry deposition are taken into account for the multiple regression analysis.
Female Literacy Rate is a Better Predictor of Birth Rate and Infant Mortality Rate in India
Saurabh, Suman; Sarkar, Sonali; Pandey, Dhruv K.
2013-01-01
Background: Educated women are known to take informed reproductive and healthcare decisions. These result in population stabilization and better infant care reflected by lower birth rates and infant mortality rates (IMRs), respectively. Materials and Methods: Our objective was to study the relationship of male and female literacy rates with crude birth rates (CBRs) and IMRs of the states and union territories (UTs) of India. The data were analyzed using linear regression. CBR and IMR were taken as the dependent variables; while the overall literacy rates, male, and female literacy rates were the independent variables. Results: CBRs were inversely related to literacy rates (slope parameter = −0.402, P < 0.001). On multiple linear regression with male and female literacy rates, a significant inverse relationship emerged between female literacy rate and CBR (slope = −0.363, P < 0.001), while male literacy rate was not significantly related to CBR (P = 0.674). IMR of the states were also inversely related to their literacy rates (slope = −1.254, P < 0.001). Multiple linear regression revealed a significant inverse relationship between IMR and female literacy (slope = −0.816, P = 0.031), whereas male literacy rate was not significantly related (P = 0.630). Conclusion: Female literacy is relatively highly important for both population stabilization and better infant health. PMID:26664840
Navarta-Sánchez, María Victoria; Senosiain García, Juana M; Riverol, Mario; Ursúa Sesma, María Eugenia; Díaz de Cerio Ayesa, Sara; Anaut Bravo, Sagrario; Caparrós Civera, Neus; Portillo, Mari Carmen
2016-08-01
The influence that social conditions and personal attitudes may have on the quality of life (QoL) of Parkinson's disease (PD) patients and informal caregivers does not receive enough attention in health care, as a result of it not being clearly identified, especially in informal caregivers. The aim of this study was to provide a comprehensive analysis of psychosocial adjustment and QoL determinants in PD patients and informal caregivers. Ninety-one PD patients and 83 caregivers participated in the study. Multiple regression analyses were performed including benefit finding, coping, disease severity and socio-demographic factors, in order to determine how these aspects influence the psychosocial adjustment and QoL in PD patients and caregivers. Regression models showed that severity of PD was the main predictor of psychosocial adjustment and QoL in patients. Nevertheless, multiple regression analyses also revealed that coping was a significant predictor of psychosocial adjustment in patients and caregivers. Furthermore, psychosocial adjustment was significantly related to QoL in patients and caregivers. Also, coping and benefit finding were predictors of QoL in caregivers but not in patients. Multidisciplinary interventions aimed at improving PD patients' QoL may have more effective outcomes if education about coping skills, and how these can help towards a positive psychosocial adjustment to illness, were included, and targeted not only at patients, but also at informal caregivers.
Rębacz-Maron, Ewa; Parafiniuk, Mirosław
2014-01-01
The aim of this paper was to examine the extent to which socioeconomic factors, anthropological data and somatic indices influenced the results of spirometric measurements (FEV1 and FVC) in Tanzanian youth. The population studied were young black Bantu men aged 12.8-24.0 years. Analysis was performed for the whole data set (n = 255), as well as separately for two age groups: under 17.5 years (n = 168) and 17.5 + (n = 87). A backward stepwise multiple regression analysis was performed for FEV1 and FVC as dependent variables on socioeconomic and anthropometric data. Multiple regression analysis for the whole group revealed that the socioeconomic and anthropometric data under analysis accounted for 38% of the variation in FEV1. In addition the analysis demonstrated that 34% of the variation in FVC could be accounted for by the variables used in the regression. A significant impact in explaining the variability of FVC was exhibited by the thorax mobility, financial situation of the participants and Pignet-Verwaecka Index. Analysis of the data indicates the significant role of selected socio-economic factors on the development of the biological specimens investigated. There were no perceptible pathologies, and the results can be treated as a credible interpretation of the influence exerted by the environment in which the teenagers under study grew up.
Machado-Carvalhais, Helenaura P; Ramos-Jorge, Maria L; Auad, Sheyla M; Martins, Laura H P M; Paiva, Saul M; Pordeus, Isabela A
2008-10-01
The aims of this cross-sectional study were to determine the prevalence of occupational accidents with exposure to biological material among undergraduate students of dentistry and to estimate potential risk factors associated with exposure to blood. Data were collected through a self-administered questionnaire (86.4 percent return rate), which was completed by a sample of 286 undergraduate dental students (mean age 22.4 +/-2.4 years). The students were enrolled in the clinical component of the curriculum, which corresponds to the final six semesters of study. Descriptive, bivariate, simple logistic regression and multiple logistic regression (Forward Stepwise Procedure) analyses were performed. The level of statistical significance was set at 5 percent. Percutaneous and mucous exposures to potentially infectious biological material were reported by 102 individuals (35.6 percent); 26.8 percent reported the occurrence of multiple episodes of exposure. The logistic regression analyses revealed that the incomplete use of individual protection equipment (OR=3.7; 95 percent CI 1.5-9.3), disciplines where surgical procedures are carried out (OR=16.3; 95 percent CI 7.1-37.2), and handling sharp instruments (OR=4.4; 95 percent CI 2.1-9.1), more specifically, hollow-bore needles (OR=6.8; 95 percent CI 2.1-19.0), were independently associated with exposure to blood. Policies of reviewing the procedures during clinical practice are recommended in order to reduce occupational exposure.
Villarrasa-Sapiña, Israel; Álvarez-Pitti, Julio; Cabeza-Ruiz, Ruth; Redón, Pau; Lurbe, Empar; García-Massó, Xavier
2018-02-01
Excess body weight during childhood causes reduced motor functionality and problems in postural control, a negative influence which has been reported in the literature. Nevertheless, no information regarding the effect of body composition on the postural control of overweight and obese children is available. The objective of this study was therefore to establish these relationships. A cross-sectional design was used to establish relationships between body composition and postural control variables obtained in bipedal eyes-open and eyes-closed conditions in twenty-two children. Centre of pressure signals were analysed in the temporal and frequency domains. Pearson correlations were applied to establish relationships between variables. Principal component analysis was applied to the body composition variables to avoid potential multicollinearity in the regression models. These principal components were used to perform a multiple linear regression analysis, from which regression models were obtained to predict postural control. Height and leg mass were the body composition variables that showed the highest correlation with postural control. Multiple regression models were also obtained and several of these models showed a higher correlation coefficient in predicting postural control than simple correlations. These models revealed that leg and trunk mass were good predictors of postural control. More equations were found in the eyes-open than eyes-closed condition. Body weight and height are negatively correlated with postural control. However, leg and trunk mass are better postural control predictors than arm or body mass. Finally, body composition variables are more useful in predicting postural control when the eyes are open. Copyright © 2017 Elsevier Ltd. All rights reserved.
Jeong, Jin-Seok; Lee, Seung-Youp; Chang, Moontaek
2016-06-01
The aim of this study was to evaluate alterations of papilla dimensions after orthodontic closure of the diastema between maxillary central incisors. Sixty patients who had a visible diastema between maxillary central incisors that had been closed by orthodontic approximation were selected for this study. Various papilla dimensions were assessed on clinical photographs and study models before the orthodontic treatment and at the follow-up examination after closure of the diastema. Influences of the variables assessed before orthodontic treatment on the alterations of papilla height (PH) and papilla base thickness (PBT) were evaluated by univariate regression analysis. To analyze potential influences of the 3-dimensional papilla dimensions before orthodontic treatment on the alterations of PH and PBT, a multiple regression model was formulated including the 3-dimensional papilla dimensions as predictor variables. On average, PH decreased by 0.80 mm and PBT increased after orthodontic closure of the diastema (P<0.01). Univariate regression analysis revealed that the PH (P=0.002) and PBT (P=0.047) before orthodontic treatment influenced the alteration of PH. With respect to the alteration of PBT, the diastema width (P=0.045) and PBT (P=0.000) were found to be influential factors. PBT before the orthodontic treatment significantly influenced the alteration of PBT in the multiple regression model. PH decreased but PBT increased after orthodontic closure of the diastema. The papilla dimensions before orthodontic treatment influenced the alterations of PH and PBT after closure of the diastema. The PBT increased more when the diastema width before the orthodontic treatment was larger.
Bomfim, Rafael Aiello; Crosato, Edgard; Mazzilli, Luiz Eugênio Nigro; Frias, Antonio Carlos
2015-01-01
This study evaluates the prevalence and risk factors of non-carious cervical lesions (NCCLs) in a Brazilian population of workers exposed and non-exposed to acid mists and chemical products. One hundred workers (46 exposed and 54 non-exposed) were evaluated in a Centro de Referência em Saúde do Trabalhador - CEREST (Worker's Health Reference Center). The workers responded to questionnaires regarding their personal information and about alcohol consumption and tobacco use. A clinical examination was conducted to evaluate the presence of NCCLs, according to WHO parameters. Statistical analyses were performed by unconditional logistic regression and multiple linear regression, with the critical level of p < 0.05. NCCLs were significantly associated with age groups (18-34, 35-44, 45-68 years). The unconditional logistic regression showed that the presence of NCCLs was better explained by age group (OR = 4.04; CI 95% 1.77-9.22) and occupational exposure to acid mists and chemical products (OR = 3.84; CI 95% 1.10-13.49), whereas the linear multiple regression revealed that NCCLs were better explained by years of smoking (p = 0.01) and age group (p = 0.04). The prevalence of NCCLs in the study population was particularly high (76.84%), and the risk factors for NCCLs were age, exposure to acid mists and smoking habit. Controlling risk factors through preventive and educative measures, allied to the use of personal protective equipment to prevent the occupational exposure to acid mists, may contribute to minimizing the prevalence of NCCLs.
Ito, Yukiko; Hattori, Reiko; Mase, Hiroki; Watanabe, Masako; Shiotani, Itaru
2008-12-01
Pollen information is indispensable for allergic individuals and clinicians. This study aimed to develop forecasting models for the total annual count of airborne pollen grains based on data monitored over the last 20 years at the Mie Chuo Medical Center, Tsu, Mie, Japan. Airborne pollen grains were collected using a Durham sampler. Total annual pollen count and pollen count from October to December (OD pollen count) of the previous year were transformed to logarithms. Regression analysis of the total pollen count was performed using variables such as the OD pollen count and the maximum temperature for mid-July of the previous year. Time series analysis revealed an alternate rhythm of the series of total pollen count. The alternate rhythm consisted of a cyclic alternation of an "on" year (high pollen count) and an "off" year (low pollen count). This rhythm was used as a dummy variable in regression equations. Of the three models involving the OD pollen count, a multiple regression equation that included the alternate rhythm variable and the interaction of this rhythm with OD pollen count showed a high coefficient of determination (0.844). Of the three models involving the maximum temperature for mid-July, those including the alternate rhythm variable and the interaction of this rhythm with maximum temperature had the highest coefficient of determination (0.925). An alternate pollen dispersal rhythm represented by a dummy variable in the multiple regression analysis plays a key role in improving forecasting models for the total annual sugi pollen count.
Pang, M Y C; Eng, J J
2008-07-01
Chronic stroke survivors with low hip bone density are particularly prone to fractures. This study shows that fear of falling is independently associated with falls in this population. Thus, fear of falling should not be overlooked in the prevention of fragility fractures in these patients. Chronic stroke survivors with low bone mineral density (BMD) are particularly prone to fragility fractures. The purpose of this study was to identify the determinants of balance, mobility and falls in this sub-group of stroke patients. Thirty-nine chronic stroke survivors with low hip BMD (T-score <-1.0) were studied. Each subject was evaluated for the following: balance, mobility, leg muscle strength, spasticity, and fall-related self-efficacy. Any falls in the past 12 months were also recorded. Multiple regression analysis was used to identify the determinants of balance and mobility performance, whereas logistic regression was used to identify the determinants of falls. Multiple regression analysis revealed that after adjusting for basic demographics, fall-related self-efficacy remained independently associated with balance/mobility performance (R2 = 0.494, P < 0.001). Logistic regression showed that fall-related self-efficacy, but not balance and mobility performance, was a significant determinant of falls (odds ratio: 0.18, P = 0.04). Fall-related self-efficacy, but not mobility and balance performance, was the most important determinant of accidental falls. This psychological factor should not be overlooked in the prevention of fragility fractures among chronic stroke survivors with low hip BMD.
Tokunaga, Makoto; Watanabe, Susumu; Sonoda, Shigeru
2017-09-01
Multiple linear regression analysis is often used to predict the outcome of stroke rehabilitation. However, the predictive accuracy may not be satisfactory. The objective of this study was to elucidate the predictive accuracy of a method of calculating motor Functional Independence Measure (mFIM) at discharge from mFIM effectiveness predicted by multiple regression analysis. The subjects were 505 patients with stroke who were hospitalized in a convalescent rehabilitation hospital. The formula "mFIM at discharge = mFIM effectiveness × (91 points - mFIM at admission) + mFIM at admission" was used. By including the predicted mFIM effectiveness obtained through multiple regression analysis in this formula, we obtained the predicted mFIM at discharge (A). We also used multiple regression analysis to directly predict mFIM at discharge (B). The correlation between the predicted and the measured values of mFIM at discharge was compared between A and B. The correlation coefficients were .916 for A and .878 for B. Calculating mFIM at discharge from mFIM effectiveness predicted by multiple regression analysis had a higher degree of predictive accuracy of mFIM at discharge than that directly predicted. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Khazaei, Ardeshir; Sarmasti, Negin; Seyf, Jaber Yousefi
2016-03-01
Quantitative structure activity relationship were used to study a series of curcumin-related compounds with inhibitory effect on prostate cancer PC-3 cells, pancreas cancer Panc-1 cells, and colon cancer HT-29 cells. Sphere exclusion method was used to split data set in two categories of train and test set. Multiple linear regression, principal component regression and partial least squares were used as the regression methods. In other hand, to investigate the effect of feature selection methods, stepwise, Genetic algorithm, and simulated annealing were used. In two cases (PC-3 cells and Panc-1 cells), the best models were generated by a combination of multiple linear regression and stepwise (PC-3 cells: r2 = 0.86, q2 = 0.82, pred_r2 = 0.93, and r2m (test) = 0.43, Panc-1 cells: r2 = 0.85, q2 = 0.80, pred_r2 = 0.71, and r2m (test) = 0.68). For the HT-29 cells, principal component regression with stepwise (r2 = 0.69, q2 = 0.62, pred_r2 = 0.54, and r2m (test) = 0.41) is the best method. The QSAR study reveals descriptors which have crucial role in the inhibitory property of curcumin-like compounds. 6ChainCount, T_C_C_1, and T_O_O_7 are the most important descriptors that have the greatest effect. With a specific end goal to design and optimization of novel efficient curcumin-related compounds it is useful to introduce heteroatoms such as nitrogen, oxygen, and sulfur atoms in the chemical structure (reduce the contribution of T_C_C_1 descriptor) and increase the contribution of 6ChainCount and T_O_O_7 descriptors. Models can be useful in the better design of some novel curcumin-related compounds that can be used in the treatment of prostate, pancreas, and colon cancers.
Use of Empirical Estimates of Shrinkage in Multiple Regression: A Caution.
ERIC Educational Resources Information Center
Kromrey, Jeffrey D.; Hines, Constance V.
1995-01-01
The accuracy of four empirical techniques to estimate shrinkage in multiple regression was studied through Monte Carlo simulation. None of the techniques provided unbiased estimates of the population squared multiple correlation coefficient, but the normalized jackknife and bootstrap techniques demonstrated marginally acceptable performance with…
Enhance-Synergism and Suppression Effects in Multiple Regression
ERIC Educational Resources Information Center
Lipovetsky, Stan; Conklin, W. Michael
2004-01-01
Relations between pairwise correlations and the coefficient of multiple determination in regression analysis are considered. The conditions for the occurrence of enhance-synergism and suppression effects when multiple determination becomes bigger than the total of squared correlations of the dependent variable with the regressors are discussed. It…
Vungkhanching, Martha; Tonsing, Kareen N
2016-08-11
This study investigated social workers' role clarity as members of an interdisciplinary team in traumatic and acquired brain injury treatment settings. A total of 37 social workers from 7 Western countries completed an anonymous online survey questionnaire. The majority of participants have more than 10 years of experience working in brain injury treatment settings (59.5%), and about 54% have been in their current employment for more than 10 years. Findings revealed that there were significant positive correlations between perceived respect, team collaboration, and perceived value of self for team with role clarity. Multiple regression analysis revealed that perceived value of self for team was a significant predictor of role clarity (p < .05).
Curtis, Ross E; Kim, Seyoung; Woolford, John L; Xu, Wenjie; Xing, Eric P
2013-03-21
Association analysis using genome-wide expression quantitative trait locus (eQTL) data investigates the effect that genetic variation has on cellular pathways and leads to the discovery of candidate regulators. Traditional analysis of eQTL data via pairwise statistical significance tests or linear regression does not leverage the availability of the structural information of the transcriptome, such as presence of gene networks that reveal correlation and potentially regulatory relationships among the study genes. We employ a new eQTL mapping algorithm, GFlasso, which we have previously developed for sparse structured regression, to reanalyze a genome-wide yeast dataset. GFlasso fully takes into account the dependencies among expression traits to suppress false positives and to enhance the signal/noise ratio. Thus, GFlasso leverages the gene-interaction network to discover the pleiotropic effects of genetic loci that perturb the expression level of multiple (rather than individual) genes, which enables us to gain more power in detecting previously neglected signals that are marginally weak but pleiotropically significant. While eQTL hotspots in yeast have been reported previously as genomic regions controlling multiple genes, our analysis reveals additional novel eQTL hotspots and, more interestingly, uncovers groups of multiple contributing eQTL hotspots that affect the expression level of functional gene modules. To our knowledge, our study is the first to report this type of gene regulation stemming from multiple eQTL hotspots. Additionally, we report the results from in-depth bioinformatics analysis for three groups of these eQTL hotspots: ribosome biogenesis, telomere silencing, and retrotransposon biology. We suggest candidate regulators for the functional gene modules that map to each group of hotspots. Not only do we find that many of these candidate regulators contain mutations in the promoter and coding regions of the genes, in the case of the Ribi group, we provide experimental evidence suggesting that the identified candidates do regulate the target genes predicted by GFlasso. Thus, this structured association analysis of a yeast eQTL dataset via GFlasso, coupled with extensive bioinformatics analysis, discovers a novel regulation pattern between multiple eQTL hotspots and functional gene modules. Furthermore, this analysis demonstrates the potential of GFlasso as a powerful computational tool for eQTL studies that exploit the rich structural information among expression traits due to correlation, regulation, or other forms of biological dependencies.
An Effect Size for Regression Predictors in Meta-Analysis
ERIC Educational Resources Information Center
Aloe, Ariel M.; Becker, Betsy Jane
2012-01-01
A new effect size representing the predictive power of an independent variable from a multiple regression model is presented. The index, denoted as r[subscript sp], is the semipartial correlation of the predictor with the outcome of interest. This effect size can be computed when multiple predictor variables are included in the regression model…
Regression Analysis: Legal Applications in Institutional Research
ERIC Educational Resources Information Center
Frizell, Julie A.; Shippen, Benjamin S., Jr.; Luna, Andrew L.
2008-01-01
This article reviews multiple regression analysis, describes how its results should be interpreted, and instructs institutional researchers on how to conduct such analyses using an example focused on faculty pay equity between men and women. The use of multiple regression analysis will be presented as a method with which to compare salaries of…
RAWS II: A MULTIPLE REGRESSION ANALYSIS PROGRAM,
This memorandum gives instructions for the use and operation of a revised version of RAWS, a multiple regression analysis program. The program...of preprocessed data, the directed retention of variable, listing of the matrix of the normal equations and its inverse, and the bypassing of the regression analysis to provide the input variable statistics only. (Author)
Incremental Net Effects in Multiple Regression
ERIC Educational Resources Information Center
Lipovetsky, Stan; Conklin, Michael
2005-01-01
A regular problem in regression analysis is estimating the comparative importance of the predictors in the model. This work considers the 'net effects', or shares of the predictors in the coefficient of the multiple determination, which is a widely used characteristic of the quality of a regression model. Estimation of the net effects can be a…
2017-03-23
PUBLIC RELEASE; DISTRIBUTION UNLIMITED Using Multiple and Logistic Regression to Estimate the Median Will- Cost and Probability of Cost and... Cost and Probability of Cost and Schedule Overrun for Program Managers Ryan C. Trudelle Follow this and additional works at: https://scholar.afit.edu...afit.edu. Recommended Citation Trudelle, Ryan C., "Using Multiple and Logistic Regression to Estimate the Median Will- Cost and Probability of Cost and
The relationship between negative expressivity, anger, and PTSD symptom clusters.
Claycomb, Meredith; Roley, Michelle E; Contractor, Ateka A; Armour, Cherie; Dranger, Paula; Wang, Li; Elhai, Jon D
2016-09-30
More investigation is needed to understand how specific posttraumatic stress disorder (PTSD) symptom clusters relate to the internal experience of anger and overt negative behaviors in response to anger (negative expressivity). We investigated whether anger mediated relations between PTSD symptom clusters and negative expressivity. Multiple regression revealed lower PTSD intrusion symptoms associated with higher levels of negative expressivity. Anger mediated this relationship. Higher avoidance symptoms related to higher negative expressivity. Clinical implications, limitations, and strengths are discussed. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Chi, ShaoHui; Wang, Zuhao; Liu, Xiufeng; Zhu, Lei
2017-11-01
This study investigated the associations among students' attitudes towards science, students' perceived difficulty of learning science, gender, parents' occupations and their scientific competencies. A sample of 1591 (720 males and 871 females) ninth-grade students from 29 junior high schools in Shanghai completed a scientific competency test and a Likert scale questionnaire. Multiple regression analysis revealed that students' general interest of science, their parents' occupations and perceived difficulty of science significantly associated with their scientific competencies. However, there was no gender gap in terms of scientific competencies.
Tools to Support Interpreting Multiple Regression in the Face of Multicollinearity
Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K.
2012-01-01
While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses. PMID:22457655
Tools to support interpreting multiple regression in the face of multicollinearity.
Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K
2012-01-01
While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses.
Sex differences in estimating multiple intelligences in self and others: a replication in Russia.
Furnham, Adrian; Shagabutdinova, Ksenia
2012-01-01
This was a crosscultural study that focused on sex differences in self- and other-estimates of multiple intelligences (including 10 that were specified by Gardner, 1999 and three by Sternberg, 1988) as well as in an overall general intelligence estimate. It was one of a programmatic series of studies done in over 30 countries that has demonstrated the female "humility" and male "hubris" effect in self-estimated and other-estimated intelligence. Two hundred and thirty Russian university students estimated their own and their parents' overall intelligence and "multiple intelligences." Results revealed no sex difference in estimates of overall intelligence for both self and parents, but men rated themselves higher on spatial intelligence. This contradicted many previous findings in the area which have shown that men rate their own overall intelligence and mathematical intelligence significantly higher than do women. Regressions indicated that estimates of verbal, logical, and spatial intelligences were the best predictors of estimates of overall intelligence, which is a consistent finding over many studies. Regressions also showed that participants' openness to experience and self-respect were good predictors of intelligence estimates. A comparison with a British sample showed that Russians gave higher mother estimates, and were less likely to believe that IQ tests measure intelligence. Results were discussed in relation to the influence of gender role stereotypes on lay conception of intelligence across cultures.
Multidimensional Predictors of Fatigue among Octogenarians and Centenarians
Cho, Jinmyoung; Martin, Peter; Margrett, Jennifer; MacDonald, Maurice; Johnson, Mary Ann; Poon, Leonard W.
2012-01-01
Background Fatigue is a common and frequently observed complaint among older adults. However, knowledge about the nature and correlates of fatigue in old age is very limited. Objective: This study examined the relationship of functional indicators, psychological and situational factors and fatigue for 210 octogenarians and centenarians from the Georgia Centenarian Study. Methods Three indicators of functional capacity (self-rated health, instrumental activities of daily living, physical activities of daily living), two indicators of psychological well-being (positive and negative affect), two indicators of situational factors (social network and social support), and a multidimensional fatigue scale were used. Blocked multiple regression analyses were computed to examine significant factors related to fatigue. In addition, multi-group analysis in structural equation modeling was used to investigate residential differences (i.e., long-term care facilities vs. private homes) in the relationship between significant factors and fatigue. Results Blocked multiple regression analyses indicated that two indicators of functional capacity, self-rated health and instrumental activities of daily living, both positive and negative affect, and social support were significant predictors of fatigue among oldest-old adults. The multiple group analysis in structural equation modeling revealed a significant difference among oldest-old adults based on residential status. Conclusion The results suggest that we should not consider fatigue as merely an unpleasant physical symptom, but rather adopt a perspective that different factors such as psychosocial aspects can influence fatigue in advanced later life. PMID:22094445
Kawada, Tomoyuki; Yamada, Natsuki
2012-01-01
Job satisfaction is an important factor in the occupational lives of workers. In this study, the relationship between one-dimensional scale of job satisfaction and psychological wellbeing was evaluated. A total of 1,742 workers (1,191 men and 551 women) participated. 100-point scale evaluating job satisfaction (0 [extremely dissatisfied] to 100 [extremely satisfied]) and the General Health Questionnaire, 12-item version (GHQ-12) evaluating psychological wellbeing were used. A multiple regression analysis was then used, controlling for gender and age. The change in the GHQ-12 and job satisfaction scores after a two-year interval was also evaluated. The mean age for the subjects was 42.2 years for the men and 36.2 years for the women. The GHQ-12 and job satisfaction scores were significantly correlated in each generation. The partial correlation coefficients between the changes in the two variables, controlling for age, were -0.395 for men and -0.435 for women (p< 0.001). A multiple regression analysis revealed that the 100-point job satisfaction score was associated with the GHQ-12 results (p< 0.001). The adjusted multiple correlation coefficient was 0.275. The 100-point scale, which is a simple and easy tool for evaluating job satisfaction, was significantly associated with psychological wellbeing as judged using the GHQ-12.
Multidimensional predictors of fatigue among octogenarians and centenarians.
Cho, Jinmyoung; Martin, Peter; Margrett, Jennifer; MacDonald, Maurice; Johnson, Mary Ann; Poon, Leonard W; Jazwinski, S M; Green, R C; Gearing, M; Woodard, J L; Tenover, J S; Siegler, I C; Rott, C; Rodgers, W L; Hausman, D; Arnold, J; Davey, A
2012-01-01
Fatigue is a common and frequently observed complaint among older adults. However, knowledge about the nature and correlates of fatigue in old age is very limited. This study examined the relationship of functional indicators, psychological and situational factors and fatigue for 210 octogenarians and centenarians from the Georgia Centenarian Study. Three indicators of functional capacity (self-rated health, instrumental activities of daily living, physical activities of daily living), two indicators of psychological well-being (positive and negative affect), two indicators of situational factors (social network and social support), and a multidimensional fatigue scale were used. Blocked multiple regression analyses were computed to examine significant factors related to fatigue. In addition, multi-group analysis in structural equation modeling was used to investigate residential differences (i.e., long-term care facilities vs. private homes) in the relationship between significant factors and fatigue. Blocked multiple regression analyses indicated that two indicators of functional capacity, self-rated health and instrumental activities of daily living, both positive and negative affect, and social support were significant predictors of fatigue among oldest-old adults. The multiple group analysis in structural equation modeling revealed a significant difference among oldest-old adults based on residential status. The results suggest that we should not consider fatigue as merely an unpleasant physical symptom, but rather adopt a perspective that different factors such as psychosocial aspects can influence fatigue in advanced later life. Copyright © 2011 S. Karger AG, Basel.
NASA Astrophysics Data System (ADS)
Zahari, Siti Meriam; Ramli, Norazan Mohamed; Moktar, Balkiah; Zainol, Mohammad Said
2014-09-01
In the presence of multicollinearity and multiple outliers, statistical inference of linear regression model using ordinary least squares (OLS) estimators would be severely affected and produces misleading results. To overcome this, many approaches have been investigated. These include robust methods which were reported to be less sensitive to the presence of outliers. In addition, ridge regression technique was employed to tackle multicollinearity problem. In order to mitigate both problems, a combination of ridge regression and robust methods was discussed in this study. The superiority of this approach was examined when simultaneous presence of multicollinearity and multiple outliers occurred in multiple linear regression. This study aimed to look at the performance of several well-known robust estimators; M, MM, RIDGE and robust ridge regression estimators, namely Weighted Ridge M-estimator (WRM), Weighted Ridge MM (WRMM), Ridge MM (RMM), in such a situation. Results of the study showed that in the presence of simultaneous multicollinearity and multiple outliers (in both x and y-direction), the RMM and RIDGE are more or less similar in terms of superiority over the other estimators, regardless of the number of observation, level of collinearity and percentage of outliers used. However, when outliers occurred in only single direction (y-direction), the WRMM estimator is the most superior among the robust ridge regression estimators, by producing the least variance. In conclusion, the robust ridge regression is the best alternative as compared to robust and conventional least squares estimators when dealing with simultaneous presence of multicollinearity and outliers.
[Portal vein thrombosis and Prevotella melanigenica revealing an appendicular abscess].
Paneri, G; Prince-Zucchelli, M A; Masseboeuf, H; Timpone, G
2002-04-06
The misleading aspects of appendicitis are multiple. We report an observation, original not only from a clinical and bacteriological point of view but also because of the presence of a portal vein thrombosis. A 48 year-old man was hospitalized for prolonged fever. Examination revealed a thrombosis of the portal vein. Several hemocultures were positive for Prevotella melaninogenica. There was no abnormality in blood crasis and/or thrombophilia. Since the digestive and endoscopic control was negative, as well as the scanographic and sonographic exploration of the appendix area, exploratory laparotomy was performed and revealed an abscess on the appendix, which was responsible for the clinical, biological and radiological images. Appendectomy led to complete, immediate and permanent regression of the fever. The discovery of a Prevotella-type germ disputes the pathogenicity of such an anaerobic germ, at distance from a site where it is normally saprophyte.
An improved multiple linear regression and data analysis computer program package
NASA Technical Reports Server (NTRS)
Sidik, S. M.
1972-01-01
NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.
Upper extremity disorders in heavy industry workers in Greece.
Tsouvaltzidou, Thomaella; Alexopoulos, Evangelos; Fragkakis, Ioannis; Jelastopulu, Eleni
2017-06-18
To investigate the disability due to musculoskeletal disorders of the upper extremities in heavy industry workers. The population under study consisted of 802 employees, both white- and blue-collar, working in a shipyard industry in Athens, Greece. Data were collected through the distribution of questionnaires and the recording of individual and job-related characteristics during the period 2006-2009. The questionnaires used were the Quick Disabilities of the Arm, Shoulder and Hand (QD) Outcome Measure, the Work Ability Index (WAI) and the Short-Form-36 (SF-36) Health Survey. The QD was divided into three parameters - movement restrictions in everyday activities, work and sports/music activities - and the SF-36 into two items, physical and emotional. Multiple linear regression analysis was performed by means of the SPSS v.22 for Windows Statistical Package. The answers given by the participants for the QD did not reveal great discomfort regarding the execution of manual tasks, with the majority of the participants scoring under 5%, meaning no disability. After conducting multiple linear regression, age revealed a positive association with the parameter of restrictions in everyday activities (b = 0.64, P = 0.000). Basic education showed a statistically significant association regarding restrictions during leisure activities, with b = 2.140 ( P = 0.029) for compulsory education graduates. WAI's final score displayed negative charging in the regression analysis of all three parameters, with b = -0.142 ( P = 0.0), b = -0.099 ( P = 0.055) and b = -0.376 ( P = 0.001) respectively, while the physical and emotional components of SF-36 associated with movement restrictions only in daily activities and work. The participants' specialty made no statistically significant associations with any of the three parameters of the QD. Increased musculoskeletal disorders of the upper extremity are associated with older age, lower basic education and physical and mental/emotional health and reduced working ability.
ERIC Educational Resources Information Center
Baylor, Carolyn; Yorkston, Kathryn; Bamer, Alyssa; Britton, Deanna; Amtmann, Dagmar
2010-01-01
Purpose: To explore variables associated with self-reported communicative participation in a sample (n = 498) of community-dwelling adults with multiple sclerosis (MS). Method: A battery of questionnaires was administered online or on paper per participant preference. Data were analyzed using multiple linear backward stepwise regression. The…
Kang, Seung-Gul; Lee, Yu Jin; Kim, Seog Ju; Lim, Weonjeong; Lee, Heon-Jeong; Park, Young-Min; Cho, In Hee; Cho, Seong-Jin; Hong, Jin Pyo
2014-02-01
The current study aims to determine the associations of insufficient sleep with suicide attempts and self-injury in a large, school-based Korean adolescent sample. A sample of 4553 middle- and high-school students (grades 7-10) was recruited in this study. Finally, 4145 students completed self-report questionnaires including items on sleep duration (weekday/weekend), self-injury, suicide attempts during the past year, the Suicidal Ideation Questionnaire (SIQ), and the Beck Depression Inventory (BDI). A multiple linear regression model showed that higher SIQ scores were associated with longer weekend catch-up sleep duration (p=0.009), higher BDI score (p<0.001), and longer time spent in a private educational institute (p=0.025). The multiple logistic regression analysis revealed that longer weekend catch-up sleep duration (p=0.011), higher BDI score (p<0.001), longer time spent in a private educational institute (p=0.046), and poorer academic record (p=0.029) were associated with suicide attempt and self-injury during the past year. The present results suggest that weekend catch-up sleep duration--which is an indicator of insufficient weekday sleep--might be associated with suicide attempts and self-injury in Korean adolescents. © 2014.
Takaesu, Yoshikazu; Kishimoto, Taishiro; Murakoshi, Akiko; Takahashi, Nobutada; Inoue, Yuichi
2016-02-28
The purpose of the study was to identify factors associated with discontinuation of aripiprazole after switching from other antipsychotics in patients with schizophrenia in real world clinical settings. From January 2011 to December 2012, a prospective, 48-week open-label study was undertaken. Thirty-eight subjects on antipsychotic monotherapy were switched to aripiprazole. Patients who discontinued aripiprazole were compared to those who continued with regards to demographic characteristics as well as treatment factors. Multiple regression analysis was conducted to identify predictors for aripiprazole discontinuation. Thirteen out of 38 patients (34.2%) discontinued aripiprazole during the follow up period. Nine patients (23.7%) discontinued aripiprazole due to worsening of psychotic symptoms. Multiple logistic regression analysis revealed that only the duration of previous antipsychotic treatment was associated with aripiprazole discontinuation after switching to aripiprazole. The receiver operating curve (ROC) analysis identified that the cut-off length for duration of illness to predict aripiprazole discontinuation was 10.5 years. Longer duration of illness was associated with aripiprazole discontinuation. Greater caution may be required when treating such patients with aripiprazole. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Social determinants of cataract surgery utilization in south India. The Operations Research Group.
Brilliant, G E; Lepkowski, J M; Zurita, B; Thulasiraj, R D
1991-04-01
A field trial was conducted to compare the effects of eight health education and economic incentive interventions on the awareness and acceptance of cataract surgery. Cataract screening and follow-up surgery were offered to more than 19,000 residents age 40 years and older in a probability sample of 90 villages in south India. Eight months after intervention, an evaluation was conducted to identify those in need of surgery who had been operated on. Two principal measures of program effectiveness are examined: awareness of cataract surgery and acceptance of the surgery. The type of intervention had a negligible effect on awareness of cataract surgery. A multiple logistic regression analysis revealed that individuals who were aware of surgery tended to be male, literate, and more affluent than those who were unaware of that option. Interventions that covered the complete costs of surgery had higher surgery acceptance rates. One health education strategy, house-to-house visits by a subject with aphakia, increased acceptance of the procedure more than others. In a multiple logistic regression analysis of acceptance rates, persons accepting surgery tended to be male; other factors were not important in explaining variation in acceptance rates.
Neutropenia is independently associated with sub-therapeutic serum concentration of vancomycin.
Choi, Min Hyuk; Choe, Yeon Hwa; Lee, Sang-Guk; Jeong, Seok Hoon; Kim, Jeong-Ho
2017-02-01
We aimed to identify the impact of the presence of neutropenia on serum vancomycin concentration (SVC). A retrospective study was conducted from January 2005 to December 2015. The study population was comprised of adult patients who were performed serum concentration of vancomycin. Patients with renal failure or using non-conventional dosages of vancomycin were excluded. A total of 1307 adult patients were included in this study, of whom 163 (12.4%) were neutropenic. Patients with neutropenia presented significantly lower SVCs than non-neutropenic patients (P<0.0001). Multiple linear regressions showed significant association between neutropenia and trough SVC (beta coefficients, -2.351; P=0.004). Multiple logistic regression analysis also revealed a significant association between sub-therapeutic vancomycin concentrations (trough SVC values<10mg/l) and neutropenia (odds ratio, 1.75, P=0.029) CONCLUSIONS: The presence of neutropenia is significantly associated with low SVC, even after adjusting for other variables. Therefore, neutropenic patients had a higher risk of sub-therapeutic SVC compared with non-neutropenic patients. We recommended that vancomycin therapy should be monitored with TDM-guided optimization of dosage and intervals, especially in neutropenic patients. Copyright © 2016 Elsevier B.V. All rights reserved.
Park, Ji Nam; Han, Mi Ah; Park, Jong; Ryu, So Yeon
2016-04-14
The aim of this study was to analyze the association between general working conditions and depressive symptoms among Korean employees. The target population of the study was native employees nationwide who were at least 15 years old, and 50,032 such individuals were enrolled in the study. Depressive symptoms was assessed using the WHO-5 wellbeing index. Associations between general characteristics, job-related characteristics, work environment, and depressive symptoms were tested using chi-square tests, t-tests, and multiple logistic regression analysis. The prevalence of depressive symptoms was 39% (40.7% in males and 36.5% in females). Multiple regression analysis revealed that male subjects, older subjects, subjects with higher education status, subjects with lower monthly income, current smokers, and frequent drinkers were more likely to have depressive symptoms. In addition, longer weekly work hours, occupation type (skilled, unskilled, operative, or economic sector), shift work, working to tight deadlines, exposure to stress at work, and hazard exposure were associated with depressive symptoms. This representative study will be a guide to help manage depression among Korean employees. We expect that further research will identify additional causal relationships between general or specific working conditions and depression.
Ueda-Consolvo, Tomoko; Hayashi, Atsushi; Ozaki, Mayumi; Nakamura, Tomoko; Yagou, Takaaki; Abe, Shinya
2017-07-01
To assess the correlation between endothelial dysfunction and frequency of antivascular endothelial growth factor (anti-VEGF) treatment for neovascular age-related macular degeneration (nAMD). We examined 64 consecutive patients with nAMD who were evaluated for endothelial function by use of peripheral arterial tonometry (EndoPAT 2000; Itamar Medical, Caesarea, Israel) at Toyama University Hospital from January 2015. We tallied the number of anti-VEGF treatments between January 2014 and December 2015 and determined the correlation between the number of anti-VEGF injections and endothelial function expressed as the reactive hyperemia index (RHI). Multiple regression analysis was also performed to identify the independent predictors of a larger number of injections. The mean number of anti-VEGF injections was 8.2 ± 3.3. The mean lnRHI was 0.47 ± 0.17. The lnRHI correlated with the number of anti-VEGF injections (r = -0.56; P = 0.030). The multiple regression analysis revealed that endothelial function, neovascular subtypes, and treatment regimens were associated with the number of injections. Endothelial dysfunction may affect the efficacy of anti-VEGF therapy. Neovascular subtypes may also predict a larger number of injections.
The Geometry of Enhancement in Multiple Regression
ERIC Educational Resources Information Center
Waller, Niels G.
2011-01-01
In linear multiple regression, "enhancement" is said to occur when R[superscript 2] = b[prime]r greater than r[prime]r, where b is a p x 1 vector of standardized regression coefficients and r is a p x 1 vector of correlations between a criterion y and a set of standardized regressors, x. When p = 1 then b [is congruent to] r and…
Single versus multiple sets of resistance exercise: a meta-regression.
Krieger, James W
2009-09-01
There has been considerable debate over the optimal number of sets per exercise to improve musculoskeletal strength during a resistance exercise program. The purpose of this study was to use hierarchical, random-effects meta-regression to compare the effects of single and multiple sets per exercise on dynamic strength. English-language studies comparing single with multiple sets per exercise, while controlling for other variables, were considered eligible for inclusion. The analysis comprised 92 effect sizes (ESs) nested within 30 treatment groups and 14 studies. Multiple sets were associated with a larger ES than a single set (difference = 0.26 +/- 0.05; confidence interval [CI]: 0.15, 0.37; p < 0.0001). In a dose-response model, 2 to 3 sets per exercise were associated with a significantly greater ES than 1 set (difference = 0.25 +/- 0.06; CI: 0.14, 0.37; p = 0.0001). There was no significant difference between 1 set per exercise and 4 to 6 sets per exercise (difference = 0.35 +/- 0.25; CI: -0.05, 0.74; p = 0.17) or between 2 to 3 sets per exercise and 4 to 6 sets per exercise (difference = 0.09 +/- 0.20; CI: -0.31, 0.50; p = 0.64). There were no interactions between set volume and training program duration, subject training status, or whether the upper or lower body was trained. Sensitivity analysis revealed no highly influential studies, and no evidence of publication bias was observed. In conclusion, 2 to 3 sets per exercise are associated with 46% greater strength gains than 1 set, in both trained and untrained subjects.
NASA Astrophysics Data System (ADS)
Li, B.; Huang, F.; Chang, S.; Qi, H.; Zhai, H.
2018-04-01
Indentifying the spatio-temporal patterns of ecosystem services supply and demand and the driving forces is of great significance to the regional ecological security and sustainable socio-economic development. Due to long term and high-intensity development, the ecological environment in central and southern Liaoning urban agglomerations has been greatly destroyed thereafter has restricted sustainable development in this region. Based on Landsat ETM and OLI images, land use of this urban agglomeration in 2005, 2010 and 2015 was extracted. The integrative index of multiple-ecosystem services (IMES) was used to quantify the supply (IMESs), demand (IMESd) and balance (IMESb) of multiple-ecosystem services, The spatial patterns of ecosystem services and its dynamics for the period of 2005-2015 were revealed. The multiple regression and stepwise regression analysis were used to explore relationships between ecosystem services and socioeconomic factors. The results showed that the IMESs of the region increased by 2.93 %, whereas IMESd dropped 38 %. The undersupplied area was reduced to 2. The IMESs and IMESb were mainly negatively correlated with gross domestic product (GDP), population density, foreign investment and industrial output, while GDP per capita and the number of teachers had significant positive impacts on ecosystem services supply. The positive correlation between IMESd and GDP, population density and foreign investment were found. The ecosystem services models were established. Supply and balance of multiple-ecosystem services were positively correlated with population density, but the demand was the opposite. The results can provide some reference value for the coordinately economic and ecological development in the study area.
A comparison of two microscale laboratory reporting methods in a secondary chemistry classroom
NASA Astrophysics Data System (ADS)
Martinez, Lance Michael
This study attempted to determine if there was a difference between the laboratory achievement of students who used a modified reporting method and those who used traditional laboratory reporting. The study also determined the relationships between laboratory performance scores and the independent variables score on the Group Assessment of Logical Thinking (GALT) test, chronological age in months, gender, and ethnicity for each of the treatment groups. The study was conducted using 113 high school students who were enrolled in first-year general chemistry classes at Pueblo South High School in Colorado. The research design used was the quasi-experimental Nonequivalent Control Group Design. The statistical treatment consisted of the Multiple Regression Analysis and the Analysis of Covariance. Based on the GALT, students in the two groups were generally in the concrete and transitional stages of the Piagetian cognitive levels. The findings of the study revealed that the traditional and the modified methods of laboratory reporting did not have any effect on the laboratory performance outcome of the subjects. However, the students who used the traditional method of reporting showed a higher laboratory performance score when evaluation was conducted using the New Standards rubric recommended by the state. Multiple Regression Analysis revealed that there was a significant relationship between the criterion variable student laboratory performance outcome of individuals who employed traditional laboratory reporting methods and the composite set of predictor variables. On the contrary, there was no significant relationship between the criterion variable student laboratory performance outcome of individuals who employed modified laboratory reporting methods and the composite set of predictor variables.
Patel, Manthan H; Kumar, Jayanth V; Moss, Mark E
2013-05-01
The authors conducted an analysis of data from the National Health and Nutrition Examination Survey (NHANES) to understand the association between diabetes and tooth loss in the United States. The authors analyzed the oral examination and self-reported diabetes data obtained from the NHANES 2003-2004 cycle and included 2,508 participants representing a civilian, noninstitutionalized U.S. population 50 years and older. The authors calculated the prevalence of edentulism and the number of missing teeth among dentate people, and they used multiple regression analyses to assess the association between diabetes and tooth loss. The prevalence of edentulism was 28 percent and 14 percent among people with and without diabetes, respectively. The multiple logistic regression analysis revealed that people with diabetes were more likely to be edentulous than were those without diabetes (adjusted odds ratio = 2.25; 95 percent confidence interval, 1.19-4.21). Among dentate adults, those with diabetes had a higher number of missing teeth than did adults without diabetes (mean [standard error {SE}] = 9.8 [0.67]), mean [SE] = 6.7 [0.29]); P < .01). These study results revealed that adults with diabetes are at higher risk of experiencing tooth loss and edentulism than are adults without diabetes. One of every five cases of edentulism in the United States is linked to diabetes. Practical Implications. Although the association between diabetes and periodontal disease is well established, health care professionals also need to recognize the risk of tooth loss and its effect on quality of life among people with diabetes.
Investigation of relationship between social capital and quality of life in female headed families
Rimaz, Shahnaz; Dastoorpoor, Maryam; Vesali, Samira; Saiepour, Narges; Nedjat, Saharnaz; Sadeghi, Masoumeh; Merghati Khoei, Effat
2015-01-01
Background: Although most studies on female-headed families focus on women's access to social support, the associations between social capital and quality of life in these families are unclear in many societies (such as Iran). This study aimed to determine the associations between social capital and quality of life in Iranian female headed families. Methods: This cross-sectional study was performed on 152 female-headed households supported by Tehran Municipality, district 9 from April 2011 to July 2012. Convenience sampling was employed. Data were collected using demographic questionnaire, the Iranian version of World Health Organization Quality of Life, and the Word Bank Social Capital. Descriptive and multiple regression methods were used to analyze the data. Results: The mean±SD age of participants was 50.8±13.8 years. Findings revealed that in quality of life, the domains of environment health and social relation received the lowest (9.87 ± 2.41) and the highest (12.61 ±3.43) scores respectively; and with respect to social capital, membership in groups and social trust had the least (19.61 ± 17.11) and the most (51.04 ± 17.37) scores, respectively. The multiple regression model revealed a significant positive association between total score of the quality of life and the total score for the social capital (p< 0.001). Conclusion: Findings suggest that quality of life of female-headed families and social capital domains are strongly related. This means that by improving the social capital, women’s life can also be improved. PMID:26793661
Inverse Association between Air Pressure and Rheumatoid Arthritis Synovitis
Furu, Moritoshi; Nakabo, Shuichiro; Ohmura, Koichiro; Nakashima, Ran; Imura, Yoshitaka; Yukawa, Naoichiro; Yoshifuji, Hajime; Matsuda, Fumihiko; Ito, Hiromu; Fujii, Takao; Mimori, Tsuneyo
2014-01-01
Rheumatoid arthritis (RA) is a bone destructive autoimmune disease. Many patients with RA recognize fluctuations of their joint synovitis according to changes of air pressure, but the correlations between them have never been addressed in large-scale association studies. To address this point we recruited large-scale assessments of RA activity in a Japanese population, and performed an association analysis. Here, a total of 23,064 assessments of RA activity from 2,131 patients were obtained from the KURAMA (Kyoto University Rheumatoid Arthritis Management Alliance) database. Detailed correlations between air pressure and joint swelling or tenderness were analyzed separately for each of the 326 patients with more than 20 assessments to regulate intra-patient correlations. Association studies were also performed for seven consecutive days to identify the strongest correlations. Standardized multiple linear regression analysis was performed to evaluate independent influences from other meteorological factors. As a result, components of composite measures for RA disease activity revealed suggestive negative associations with air pressure. The 326 patients displayed significant negative mean correlations between air pressure and swellings or the sum of swellings and tenderness (p = 0.00068 and 0.00011, respectively). Among the seven consecutive days, the most significant mean negative correlations were observed for air pressure three days before evaluations of RA synovitis (p = 1.7×10−7, 0.00027, and 8.3×10−8, for swellings, tenderness and the sum of them, respectively). Standardized multiple linear regression analysis revealed these associations were independent from humidity and temperature. Our findings suggest that air pressure is inversely associated with synovitis in patients with RA. PMID:24454853
2016-01-01
Purpose The aim of this study was to evaluate alterations of papilla dimensions after orthodontic closure of the diastema between maxillary central incisors. Methods Sixty patients who had a visible diastema between maxillary central incisors that had been closed by orthodontic approximation were selected for this study. Various papilla dimensions were assessed on clinical photographs and study models before the orthodontic treatment and at the follow-up examination after closure of the diastema. Influences of the variables assessed before orthodontic treatment on the alterations of papilla height (PH) and papilla base thickness (PBT) were evaluated by univariate regression analysis. To analyze potential influences of the 3-dimensional papilla dimensions before orthodontic treatment on the alterations of PH and PBT, a multiple regression model was formulated including the 3-dimensional papilla dimensions as predictor variables. Results On average, PH decreased by 0.80 mm and PBT increased after orthodontic closure of the diastema (P<0.01). Univariate regression analysis revealed that the PH (P=0.002) and PBT (P=0.047) before orthodontic treatment influenced the alteration of PH. With respect to the alteration of PBT, the diastema width (P=0.045) and PBT (P=0.000) were found to be influential factors. PBT before the orthodontic treatment significantly influenced the alteration of PBT in the multiple regression model. Conclusions PH decreased but PBT increased after orthodontic closure of the diastema. The papilla dimensions before orthodontic treatment influenced the alterations of PH and PBT after closure of the diastema. The PBT increased more when the diastema width before the orthodontic treatment was larger. PMID:27382507
Inami, Satoshi; Moridaira, Hiroshi; Takeuchi, Daisaku; Shiba, Yo; Nohara, Yutaka; Taneichi, Hiroshi
2016-11-01
Adult spinal deformity (ASD) classification showing that ideal pelvic incidence minus lumbar lordosis (PI-LL) value is within 10° has been received widely. But no study has focused on the optimum level of PI-LL value that reflects wide variety in PI among patients. This study was conducted to determine the optimum PI-LL value specific to an individual's PI in postoperative ASD patients. 48 postoperative ASD patients were recruited. Spino-pelvic parameters and Oswestry Disability Index (ODI) were measured at the final follow-up. Factors associated with good clinical results were determined by stepwise multiple regression model using the ODI. The patients with ODI under the 75th percentile cutoff were designated into the "good" health related quality of life (HRQOL) group. In this group, the relationship between the PI-LL and PI was assessed by regression analysis. Multiple regression analysis revealed PI-LL as significant parameters associated with ODI. Thirty-six patients with an ODI <22 points (75th percentile cutoff) were categorized into a good HRQOL group, and linear regression models demonstrated the following equation: PI-LL = 0.41PI-11.12 (r = 0.45, P = 0.0059). On the basis of this equation, in the patients with a PI = 50°, the PI-LL is 9°. Whereas in those with a PI = 30°, the optimum PI-LL is calculated to be as low as 1°. In those with a PI = 80°, PI-LL is estimated at 22°. Consequently, an optimum PI-LL is inconsistent in that it depends on the individual PI.
Koper, Olga Martyna; Kamińska, Joanna; Milewska, Anna; Sawicki, Karol; Mariak, Zenon; Kemona, Halina; Matowicka-Karna, Joanna
2018-05-18
The influence of isoform A of reticulon-4 (Nogo-A), also known as neurite outgrowth inhibitor, on primary brain tumor development was reported. Therefore the aim was the evaluation of Nogo-A concentrations in cerebrospinal fluid (CSF) and serum of brain tumor patients compared with non-tumoral individuals. All serum results, except for two cases, obtained both in brain tumors and non-tumoral individuals, were below the lower limit of ELISA detection. Cerebrospinal fluid Nogo-A concentrations were significantly lower in primary brain tumor patients compared to non-tumoral individuals. The univariate linear regression analysis found that if white blood cell count increases by 1 × 10 3 /μL, the mean cerebrospinal fluid Nogo-A concentration value decreases 1.12 times. In the model of multiple linear regression analysis predictor variables influencing cerebrospinal fluid Nogo-A concentrations included: diagnosis, sex, and sodium level. The mean cerebrospinal fluid Nogo-A concentration value was 1.9 times higher for women in comparison to men. In the astrocytic brain tumor group higher sodium level occurs with lower cerebrospinal fluid Nogo-A concentrations. We found the opposite situation in non-tumoral individuals. Univariate linear regression analysis revealed, that cerebrospinal fluid Nogo-A concentrations change in relation to white blood cell count. In the created model of multiple linear regression analysis we found, that within predictor variables influencing CSF Nogo-A concentrations were diagnosis, sex, and sodium level. Results may be relevant to the search for cerebrospinal fluid biomarkers and potential therapeutic targets in primary brain tumor patients. Nogo-A concentrations were tested by means of enzyme-linked immunosorbent assay (ELISA).
Advanced statistics: linear regression, part I: simple linear regression.
Marill, Keith A
2004-01-01
Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.
Loch, T P; Scribner, K; Tempelman, R; Whelan, G; Faisal, M
2012-01-01
Herein, we describe the prevalence of bacterial infections in Chinook salmon, Oncorhynchus tshawytscha (Walbaum), returning to spawn in two tributaries within the Lake Michigan watershed. Ten bacterial genera, including Renibacterium, Aeromonas, Carnobacterium, Serratia, Proteus, Pseudomonas, Hafnia, Salmonella, Shewanella and Morganella, were detected in the kidneys of Chinook salmon (n = 480) using culture, serological and molecular analyses. Among these, Aeromonas salmonicida was detected at a prevalence of ∼15%. Analyses revealed significant interactions between location/time of collection and gender for these infections, whereby overall infection prevalence increased greatly later in the spawning run and was significantly higher in females. Renibacterium salmoninarum was detected in fish kidneys at an overall prevalence of >25%. Logistic regression analyses revealed that R. salmoninarum prevalence differed significantly by location/time of collection and gender, with a higher likelihood of infection later in the spawning season and in females vs. males. Chi-square analyses quantifying non-independence of infection by multiple pathogens revealed a significant association between R. salmoninarum and motile aeromonad infections. Additionally, greater numbers of fish were found to be co-infected by multiple bacterial species than would be expected by chance alone. The findings of this study suggest a potential synergism between bacteria infecting spawning Chinook salmon. © 2011 Blackwell Publishing Ltd.
Saleh, F; Renno, W; Klepacek, I; Ibrahim, G; Dashti, H; Asfar, S; Behbehani, A; Al-Sayer, H; Dashti, A; Kerry, Crotty
2005-01-01
To develop an effective pharmaceutical treatment for a disease, we need to fully understand the biological behavior of that disease, especially when dealing with cancer. The current available treatment for cancer may help in lessening the burden of the disease or, on certain occasions, in increasing the survival of the patient. However, a total eradication of cancer remains the researchers' hope. Some of the discoveries in the field of medicine relied on observations of natural events. Among these events is the spontaneous regression of cancer. It has been argued that such regression could be immunologically-mediated, but no direct evidence has been shown to support such an argument. We, hereby, provide compelling evidence that spontaneous cancer regression in humans is immunologically-mediated, hoping that the results from this study would stimulate the pharmaceutical industry to focus more on cancer vaccine immunotherapy. Our results showed that patients with >3 primary melanomas (very rare group among cancer patients) develop significant histopathological spontaneous regression of further melanomas that they could acquire during their life (P=0.0080) as compared to patients with single primary melanoma where the phenomenon of spontaneous regression is absent or minimal. It seems that such regression resulted from the repeated exposure to the tumor which mimics a self-immunization process. Analysis of the regressing tumors revealed heavy infiltration by T lymphocytes as compared to non-regressing tumors (P<0.0001), the predominant of which were T cytotoxic rather than T helper. Mature dendritic cells were also found in significant number (P<0.0001) in the regressing tumors as compared to the non regressing ones, which demonstrate an active involvement of the different arms of the immune system in the multiple primary melanoma patients in the process of tumor regression. Also, MHC expression was significantly higher in the regressing versus the non-regressing tumors (P <0.0001), which reflects a proper tumor antigen expression. Associated with tumor regression was also loss of the melanoma common tumor antigen Melan A/ MART-1 in the multiple primary melanoma patients as compared to the single primary ones (P=0.0041). Furthermore, loss of Melan A/ MART-1 in the regressing tumors significantly correlated with the presence of Melan A/ MART-1-specific CTLs in the peripheral blood of these patients (P=0.03), which adds to the evidence that the phenomenon of regression seen in these patients was immunologically-mediated and tumor-specific. Such correlation was also seen in another rare group of melanoma patients, namely those with occult primary melanoma. The lesson that we could learn from nature in this study is that inducing cancer regression using the different arms of the immune system is possible. Also, developing a novel cancer vaccine is not out of reach.
Brown-Wright, Lynda; Tyler, Kenneth M; Graves, Scott L; Thomas, Deneia; Stevens-Watkins, Danelle; Mulder, Shambra
2013-01-01
The current study examined the association among home-school dissonance, amotivation, and classroom disruptive behavior among 309 high school juniors and seniors at two urban high schools in the Southern region of the country. Students completed two subscales of the Patterns of Learning Activities Scales (PALS) and one subscale of the Academic Motivation Scale (AMS). ANCOVA analyses revealed significant differences in classroom disruptive behaviors for the gender independent variable. Controlling for gender in the multiple hierarchical regression analyses, it was revealed that home-school dissonance significantly predicted both amotivation and classroom disruptive behavior. In addition, a Sobel mediation analysis showed that amotivation was a significant mediator of the association between home-school dissonance and classroom disruptive behavior. Findings and limitations are discussed.
Brown-Wright, Lynda; Tyler, Kenneth M.; Graves, Scott L.; Thomas, Deneia; Stevens-Watkins, Danelle; Mulder, Shambra
2015-01-01
The current study examined the association among home–school dissonance, amotivation, and classroom disruptive behavior among 309 high school juniors and seniors at two urban high schools in the Southern region of the country. Students completed two subscales of the Patterns of Learning Activities Scales (PALS) and one subscale of the Academic Motivation Scale (AMS). ANCOVA analyses revealed significant differences in classroom disruptive behaviors for the gender independent variable. Controlling for gender in the multiple hierarchical regression analyses, it was revealed that home–school dissonance significantly predicted both amotivation and classroom disruptive behavior. In addition, a Sobel mediation analysis showed that amotivation was a significant mediator of the association between home–school dissonance and classroom disruptive behavior. Findings and limitations are discussed. PMID:27081213
Shinozuka, Jun; Awaguni, Hitoshi; Tanaka, Shin-Ichiro; Makino, Shigeru; Maruyama, Rikken; Inaba, Tohru; Imashuku, Shinsaku
2016-07-01
Pulmonary nodules associated with Epstein-Barr virus (EBV)-related atypical infectious mononucleosis have rarely been described. A 12-year-old Japanese boy, upon admission, revealed multiple small round nodules (a total of 7 nodules in 4 to 8 mm size) in the lungs on computed tomography. The hemorrhagic pharyngeal tonsils with hot signals on 18F-fluorodeoxyglucose-positron emission tomography-computed tomography were biopsied revealing the presence of EBV-encoded small nuclear RNA (EBER)-positive cells; however, no lymphoma was noted. The patient was diagnosed as having atypical EBV-infectious mononucleosis associated with primary EBV infection. Pulmonary nodules markedly reduced in numbers and sizes spontaneously over a 2-year period. Differential diagnosis of pulmonary nodules in childhood should include atypical EBV infection.
Tang, Feng-Cheng; Li, Ren-Hau; Huang, Shu-Ling
2016-01-01
Background and Objectives Prolonged fatigue is common among employees, but the relationship between prolonged fatigue and job-related psychosocial factors is seldom studied. This study aimed (1) to assess the individual relations of physical condition, psychological condition, and job-related psychosocial factors to prolonged fatigue among employees, and (2) to clarify the associations between job-related psychosocial factors and prolonged fatigue using hierarchical regression when demographic characteristics, physical condition, and psychological condition were controlled. Methods A cross-sectional study was employed. A questionnaire was used to obtain information pertaining to demographic characteristics, physical condition (perceived physical health and exercise routine), psychological condition (perceived mental health and psychological distress), job-related psychosocial factors (job demand, job control, and workplace social support), and prolonged fatigue. Results A total of 3,109 employees were recruited. Using multiple regression with controlled demographic characteristics, psychological condition explained 52.0% of the variance in prolonged fatigue. Physical condition and job-related psychosocial factors had an adjusted R2 of 0.370 and 0.251, respectively. Hierarchical multiple regression revealed that, among job-related psychosocial factors, job demand and job control showed significant associations with fatigue. Conclusion Our findings highlight the role of job demand and job control, in addition to the role of perceived physical health, perceived mental health, and psychological distress, in workers’ prolonged fatigue. However, more research is required to verify the causation among all the variables. PMID:26930064
NASA Astrophysics Data System (ADS)
Nishidate, Izumi; Wiswadarma, Aditya; Hase, Yota; Tanaka, Noriyuki; Maeda, Takaaki; Niizeki, Kyuichi; Aizu, Yoshihisa
2011-08-01
In order to visualize melanin and blood concentrations and oxygen saturation in human skin tissue, a simple imaging technique based on multispectral diffuse reflectance images acquired at six wavelengths (500, 520, 540, 560, 580 and 600nm) was developed. The technique utilizes multiple regression analysis aided by Monte Carlo simulation for diffuse reflectance spectra. Using the absorbance spectrum as a response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as predictor variables, multiple regression analysis provides regression coefficients. Concentrations of melanin and total blood are then determined from the regression coefficients using conversion vectors that are deduced numerically in advance, while oxygen saturation is obtained directly from the regression coefficients. Experiments with a tissue-like agar gel phantom validated the method. In vivo experiments with human skin of the human hand during upper limb occlusion and of the inner forearm exposed to UV irradiation demonstrated the ability of the method to evaluate physiological reactions of human skin tissue.
ERIC Educational Resources Information Center
Quinino, Roberto C.; Reis, Edna A.; Bessegato, Lupercio F.
2013-01-01
This article proposes the use of the coefficient of determination as a statistic for hypothesis testing in multiple linear regression based on distributions acquired by beta sampling. (Contains 3 figures.)
Does substance misuse moderate the relationship between criminal thinking and recidivism?
Caudy, Michael S.; Folk, Johanna B.; Stuewig, Jeffrey B.; Wooditch, Alese; Martinez, Andres; Maass, Stephanie; Tangney, June P.; Taxman, Faye S.
2014-01-01
Purpose Some differential intervention frameworks contend that substance use is less robustly related to recidivism outcomes than other criminogenic needs such as criminal thinking. The current study tested the hypothesis that substance use disorder severity moderates the relationship between criminal thinking and recidivism. Methods The study utilized two independent criminal justice samples. Study 1 included 226 drug-involved probationers. Study 2 included 337 jail inmates with varying levels of substance use disorder severity. Logistic regression was employed to test the main and interactive effects of criminal thinking and substance use on multiple dichotomous indicators of recidivism. Results Bivariate analyses revealed a significant correlation between criminal thinking and recidivism in the jail sample (r = .18, p < .05) but no significant relationship in the probation sample. Logistic regressions revealed that SUD symptoms moderated the relationship between criminal thinking and recidivism in the jail-based sample (B = −.58, p < .05). A significant moderation effect was not observed in the probation sample. Conclusions Study findings indicate that substance use disorder symptoms moderate the strength of the association between criminal thinking and recidivism. These findings demonstrate the need for further research into the interaction between various dynamic risk factors. PMID:25598559
Heyman, Gene M; Dunn, Brian J; Mignone, Jason
2014-01-01
Years-of-school is negatively correlated with illicit drug use. However, educational attainment is positively correlated with IQ and negatively correlated with impulsivity, two traits that are also correlated with drug use. Thus, the negative correlation between education and drug use may reflect the correlates of schooling, not schooling itself. To help disentangle these relations we obtained measures of working memory, simple memory, IQ, disposition (impulsivity and psychiatric status), years-of-school and frequency of illicit and licit drug use in methadone clinic and community drug users. We found strong zero-order correlations between all measures, including IQ, impulsivity, years-of-school, psychiatric symptoms, and drug use. However, multiple regression analyses revealed a different picture. The significant predictors of illicit drug use were gender, involvement in a methadone clinic, and years-of-school. That is, psychiatric symptoms, impulsivity, cognition, and IQ no longer predicted illicit drug use in the multiple regression analyses. Moreover, high risk subjects (low IQ and/or high impulsivity) who spent 14 or more years in school used stimulants and opiates less than did low risk subjects who had spent <14 years in school. Smoking and drinking had a different correlational structure. IQ and years-of-school predicted whether someone ever became a smoker, whereas impulsivity predicted the frequency of drinking bouts, but years-of-school did not. Many subjects reported no use of one or more drugs, resulting in a large number of "zeroes" in the data sets. Cragg's Double-Hurdle regression method proved the best approach for dealing with this problem. To our knowledge, this is the first report to show that years-of-school predicts lower levels of illicit drug use after controlling for IQ and impulsivity. This paper also highlights the advantages of Double-Hurdle regression methods for analyzing the correlates of drug use in community samples.
Santoro, Antonio; Piccirilli, Manolo; Brunetto, Giacoma Maria Floriana; Delfini, Roberto; Cantore, Giampaolo
2007-11-01
The authors present their experience with the 17th pediatric intramedullary cavernoma reported in English literature. The patient firstly underwent surgery for a left frontal cavernoma when he was 2 years old. Also the child's mother was operated for a C2-C3 intramedullary cavernoma. He grew up normally and the radiological follow-up was negative for other brainstem cavernous malformations. When he was 11 years old he complained a worsening tetraparesis. A cerebral and spinal magnetic resonance (MR) imaging revealed the presence of a C1 intramedullary cavernoma and a pontine cavernoma. He underwent surgery for the cervical lesion, which was completely removed. The postoperative course was regular with a total recovery from the neurological deficit. The boy underwent a radiological follow-up, monitoring the pontine lesion, which spontaneously regressed when he was 19 years old. The rarity of the pediatric intramedullary cavernoma, the familial occurrence, and the spontaneous regression of the pontine cavernoma make this case very peculiar.
Pakula, Basia; Marshall, Brandon D L; Shoveller, Jean A; Chesney, Margaret A; Coates, Thomas J; Koblin, Beryl; Mayer, Kenneth; Mimiaga, Matthew; Operario, Don
2016-08-01
This study examines gradients in depressive symptoms by socioeconomic position (SEP; i.e., income, education, employment) in a sample of men who have sex with men (MSM). Data were used from EXPLORE, a randomized, controlled behavioral HIV prevention trial for HIV-uninfected MSM in six U.S. cities (n = 4,277). Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression scale (short form). Multiple linear regressions were fitted with interaction terms to assess additive and multiplicative relationships between SEP and depressive symptoms. Depressive symptoms were more prevalent among MSM with lower income, lower educational attainment, and those in the unemployed/other employment category. Income, education, and employment made significant contributions in additive models after adjustment. The employment-income interaction was statistically significant, indicating a multiplicative effect. This study revealed gradients in depressive symptoms across SEP of MSM, pointing to income and employment status and, to a lesser extent, education as key factors for understanding heterogeneity of depressive symptoms.
Kato, Tsukasa
2016-04-30
Psychological inflexibility is a core concept in Acceptance and Commitment Therapy. The primary aim of this study was to examine psychological inflexibility and depressive symptoms among Asian English speakers. A total of 900 adults in India, the Philippines, and Singapore completed some measures related to psychological inflexibility and depressive symptoms through a Web-based survey. Multiple regression analyses revealed that higher psychological inflexibility was significantly associated with higher levels of depressive symptoms in all the samples, after controlling for the effects of gender, marital status, and interpersonal stress. In addition, the effect sizes of the changes in the R(2) values when only psychological flexibility scores were entered in the regression model were large for all the samples. Moreover, overall, the beta-weight of the psychological flexibility scores obtained by the Philippine sample was the lowest of all three samples. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Effect of pencil grasp on the speed and legibility of handwriting in children.
Schwellnus, Heidi; Carnahan, Heather; Kushki, Azadeh; Polatajko, Helene; Missiuna, Cheryl; Chau, Tom
2012-01-01
Pencil grasps other than the dynamic tripod may be functional for handwriting. This study examined the impact of grasp on handwriting speed and legibility. We videotaped 120 typically developing fourth-grade students while they performed a writing task. We categorized the grasps they used and evaluated their writing for speed and legibility using a handwriting assessment. Using linear regression analysis, we examined the relationship between grasp and handwriting. We documented six categories of pencil grasp: four mature grasp patterns, one immature grasp pattern, and one alternating grasp pattern. Multiple linear regression results revealed no significant effect for mature grasp on either legibility or speed. Pencil grasp patterns did not influence handwriting speed or legibility in this sample of typically developing children. This finding adds to the mounting body of evidence that alternative grasps may be acceptable for fast and legible handwriting. Copyright © 2012 by the American Occupational Therapy Association, Inc.
Linear and nonlinear models for predicting fish bioconcentration factors for pesticides.
Yuan, Jintao; Xie, Chun; Zhang, Ting; Sun, Jinfang; Yuan, Xuejie; Yu, Shuling; Zhang, Yingbiao; Cao, Yunyuan; Yu, Xingchen; Yang, Xuan; Yao, Wu
2016-08-01
This work is devoted to the applications of the multiple linear regression (MLR), multilayer perceptron neural network (MLP NN) and projection pursuit regression (PPR) to quantitative structure-property relationship analysis of bioconcentration factors (BCFs) of pesticides tested on Bluegill (Lepomis macrochirus). Molecular descriptors of a total of 107 pesticides were calculated with the DRAGON Software and selected by inverse enhanced replacement method. Based on the selected DRAGON descriptors, a linear model was built by MLR, nonlinear models were developed using MLP NN and PPR. The robustness of the obtained models was assessed by cross-validation and external validation using test set. Outliers were also examined and deleted to improve predictive power. Comparative results revealed that PPR achieved the most accurate predictions. This study offers useful models and information for BCF prediction, risk assessment, and pesticide formulation. Copyright © 2016 Elsevier Ltd. All rights reserved.
Prediction of performance on the RCMP physical ability requirement evaluation.
Stanish, H I; Wood, T M; Campagna, P
1999-08-01
The Royal Canadian Mounted Police use the Physical Ability Requirement Evaluation (PARE) for screening applicants. The purposes of this investigation were to identify those field tests of physical fitness that were associated with PARE performance and determine which most accurately classified successful and unsuccessful PARE performers. The participants were 27 female and 21 male volunteers. Testing included measures of aerobic power, anaerobic power, agility, muscular strength, muscular endurance, and body composition. Multiple regression analysis revealed a three-variable model for males (70-lb bench press, standing long jump, and agility) explaining 79% of the variability in PARE time, whereas a one-variable model (agility) explained 43% of the variability for females. Analysis of the classification accuracy of the males' data was prohibited because 91% of the males passed the PARE. Classification accuracy of the females' data, using logistic regression, produced a two-variable model (agility, 1.5-mile endurance run) with 93% overall classification accuracy.
The M Word: Multicollinearity in Multiple Regression.
ERIC Educational Resources Information Center
Morrow-Howell, Nancy
1994-01-01
Notes that existence of substantial correlation between two or more independent variables creates problems of multicollinearity in multiple regression. Discusses multicollinearity problem in social work research in which independent variables are usually intercorrelated. Clarifies problems created by multicollinearity, explains detection of…
Ling, Ru; Liu, Jiawang
2011-12-01
To construct prediction model for health workforce and hospital beds in county hospitals of Hunan by multiple linear regression. We surveyed 16 counties in Hunan with stratified random sampling according to uniform questionnaires,and multiple linear regression analysis with 20 quotas selected by literature view was done. Independent variables in the multiple linear regression model on medical personnels in county hospitals included the counties' urban residents' income, crude death rate, medical beds, business occupancy, professional equipment value, the number of devices valued above 10 000 yuan, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, and utilization rate of hospital beds. Independent variables in the multiple linear regression model on county hospital beds included the the population of aged 65 and above in the counties, disposable income of urban residents, medical personnel of medical institutions in county area, business occupancy, the total value of professional equipment, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, utilization rate of hospital beds, and length of hospitalization. The prediction model shows good explanatory and fitting, and may be used for short- and mid-term forecasting.
Flourishing: exploring predictors of mental health within the college environment.
Fink, John E
2014-01-01
To explore the predictive factors of student mental health within the college environment. Students enrolled at 7 unique universities during years 2008 (n=1,161) and 2009 (n=1,459). Participants completed survey measures of mental health, consequences of alcohol use, and engagement in the college environment. In addition to replicating previous findings related to Keyes' Mental Health Continuum, multiple regression analysis revealed several predictors of college student mental health, including supportive college environments, students' sense of belonging, professional confidence, and civic engagement. However, multiple measures of engaged learning were not found to predict mental health. Results suggest that supportive college environments foster student flourishing. Implications for promoting mental health across campus are discussed. Future research should build on exploratory findings and test confirmatory models to better understand relationships between the college environment and student flourishing.
NASA Astrophysics Data System (ADS)
McCammon, Susan; Golden, Jeannie; Wuensch, Karl L.
This study investigated the extent to which thinking skills and mathematical competency would predict the course performance of freshman and sophomore science majors enrolled in physics courses. Multiple-regression equations revealed that algebra and critical thinking skills were the best overall predictors across several physics courses. Although arithmetic skills, math anxiety, and primary mental abilities scores also correlated with performance, they were redundant with the algebra and critical thinking. The most surprising finding of the study was the differential validity by sex; predictor variables were successful in predicting course performance for women but not for men.
Internet use and loneliness in older adults.
Sum, Shima; Mathews, R Mark; Hughes, Ian; Campbell, Andrew
2008-04-01
Use of the Internet by seniors as a communication technology may lead to changes in older adult social relationships. This study used an online questionnaire to survey 222 Australians over 55 years of age on Internet use. Respondents primarily used the Internet for communication, seeking information, and commercial purposes. The results showed negative correlations between loneliness and well-being. Multiple regression analyses revealed that greater use of the Internet as a communication tool was associated with a lower level of social loneliness. In contrast, greater use of the Internet to find new people was associated with a higher level of emotional loneliness.
Neurocognition and community outcome in schizophrenia: long-term predictive validity.
Fujii, Daryl E; Wylie, A Michael
2003-02-01
The present study examined the predictive validity of neuropsychological measures to functional outcome in 26 schizophrenic patients 15-plus year post-testing. Outcome measures included score on the Resource Associated Functional Level Scale (RAFLS), number of state hospital admissions, and total duration of state hospital inpatient stay. Results of several stepwise multiple regressions revealed that verbal memory significantly predicted RAFLS score, accounting for nearly half of the variance. Trails B significantly predicted duration of state hospital inpatient status. Discussion focused on the utility of these measures for clinicians and system planners. Copyright 2002 Elsevier Science B.V.
Okello, J; Nakimuli-Mpungu, E; Klasen, F; Voss, C; Musisi, S; Broekaert, E; Derluyn, I
2015-07-15
We have previously shown that depression symptoms are associated with multiple risk behaviors and that parental attachments are protective against depression symptoms in post-war adolescents. Accumulating literature indicates that low levels of attachment may sensitize individuals to increased multiple risk behaviors when depression symptoms exist. This investigation examined the interactive effects of attachment and depression symptoms on multiple risk behavior. We conducted hierarchical logistic regression analyses to examine the impact of attachment and depression symptoms on multiple risk behavior in our post-war sample of 551 adolescents in Gulu district. Analyses revealed interactive effects for only maternal attachment-by-depression interaction. Interestingly, high levels of maternal attachment exacerbated the relationship between depression symptoms and multiple risk behaviors while low levels of maternal attachment attenuated this relationship. It is possible that this analysis could be biased by a common underlying factor that influences self-reporting and therefore is correlated with each of self-reported attachment security, depressive symptoms, and multiple risk behaviors. These findings suggest that maternal attachment serves as a protective factor at low levels while serving as an additional risk factor at high levels. Findings support and expand current knowledge about the roles that attachment and depression symptoms play in the development of multiple risk behaviors and suggest a more complex etiology for post-war adolescents. Copyright © 2015 Elsevier B.V. All rights reserved.
Prediction of reported consumption of selected fat-containing foods.
Tuorila, H; Pangborn, R M
1988-10-01
A total of 100 American females (mean age = 20.8 years) completed a questionnaire, in which their beliefs, evaluations, liking and consumption (frequency, consumption compared to others, intention to consume) of milk, cheese, ice cream, chocolate and "high-fat foods" were measured. For the design and analysis, the basic frame of reference was the Fishbein-Ajzen model of reasoned action, but the final analyses were carried out with stepwise multiple regression analysis. In addition to the components of the Fishbein-Ajzen model, beliefs and evaluations were used as independent variables. On the average, subjects reported liking all the products but not "high-fat foods", and thought that milk and cheese were "good for you" whereas the remaining items were "bad for you". Principal component analysis for beliefs revealed factors related to pleasantness/benefit aspects, to health and weight concern and to the "functionality" of the foods. In stepwise multiple regression analyses, liking was the predominant predictor of reported consumption for all the foods, but various belief factors, particularly those related to concern with weight, also significantly predicted consumption. Social factors played only a minor role. The multiple R's of the predictive functions varied from 0.49 to 0.74. The fact that all four foods studied elicited individual sets of beliefs and belief structures, and that none of them was rated similar to the generic "high-fat foods", emphasizes that consumers attach meaning to integrated food entities rather than to ingredients.
Andruszkow, Hagen; Hildebrand, Frank; Lefering, Rolf; Pape, Hans-Christoph; Hoffmann, Reinhard; Schweigkofler, Uwe
2014-10-01
Helicopter emergency medical service (HEMS) has been established in the preclinical treatment of multiple traumatised patients despite an ongoing controversy towards the potential benefit. Celebrating the 20th anniversary of TraumaRegister DGU(®) of the German Trauma Society (DGU) the presented study intended to provide an overview of HEMS rescue in Germany over the last 10 years analysing the potential beneficial impact of a nationwide helicopter rescue in multiple traumatised patients. We analysed TraumaRegister DGU(®) including multiple traumatised patients (ISS ≥ 16) between 2002 and 2012. In-hospital mortality was defined as main outcome. An adjusted, multivariate regression with 13 confounders was performed to evaluate the potential survival benefit. 42,788 patients were included in the present study. 14,275 (33.4%) patients were rescued by HEMS and 28,513 (66.6%) by GEMS. Overall, 66.8% (n=28,569) patients were transported to a level I trauma centre and 28.2% (n=12,052) to a level II trauma centre. Patients rescued by HEMS sustained a higher injury severity compared to GEMS (ISS HEMS: 29.5 ± 12.6 vs. 27.5 ± 11.8). Helicopter rescue teams performed more on-scene interventions, and mission times were increased in HEMS rescue (HEMS: 77.2 ± 28.7 min. vs. GEMS: 60.9 ± 26.9 min.). Linear regression analysis revealed that the frequency of HEMS rescue has decreased significantly between 2002 and 2012. In case of transportation to level I trauma centres a decrease of 1.7% per year was noted (p<0.001) while a decline of 1.6% per year (p<0.001) was measured for level II trauma centre admissions. According to multivariate logistic regression HEMS was proven a positive independent survival predictor between 2002 and 2012 (OR 0.863; 95%-CI 0.800-0.930; Nagelkerkes-R(2) 0.539) with only little differences between each year. This study was able to prove an independent survival benefit of HEMS in multiple traumatised patients during the last 10 years. Despite this fact, a constant decline of HEMS rescue missions was found in multiple trauma patients due to unknown reasons. We concluded that HEMS should be used more often in case of trauma in order to guarantee the proven benefit for multiple traumatised patients. Copyright © 2014 Elsevier Ltd. All rights reserved.
As a fast and effective technique, the multiple linear regression (MLR) method has been widely used in modeling and prediction of beach bacteria concentrations. Among previous works on this subject, however, several issues were insufficiently or inconsistently addressed. Those is...
MULTIPLE REGRESSION MODELS FOR HINDCASTING AND FORECASTING MIDSUMMER HYPOXIA IN THE GULF OF MEXICO
A new suite of multiple regression models were developed that describe the relationship between the area of bottom water hypoxia along the northern Gulf of Mexico and Mississippi-Atchafalaya River nitrate concentration, total phosphorus (TP) concentration, and discharge. Variabil...
Khalil, Mohamed H.; Shebl, Mostafa K.; Kosba, Mohamed A.; El-Sabrout, Karim; Zaki, Nesma
2016-01-01
Aim: This research was conducted to determine the most affecting parameters on hatchability of indigenous and improved local chickens’ eggs. Materials and Methods: Five parameters were studied (fertility, early and late embryonic mortalities, shape index, egg weight, and egg weight loss) on four strains, namely Fayoumi, Alexandria, Matrouh, and Montazah. Multiple linear regression was performed on the studied parameters to determine the most influencing one on hatchability. Results: The results showed significant differences in commercial and scientific hatchability among strains. Alexandria strain has the highest significant commercial hatchability (80.70%). Regarding the studied strains, highly significant differences in hatching chick weight among strains were observed. Using multiple linear regression analysis, fertility made the greatest percent contribution (71.31%) to hatchability, and the lowest percent contributions were made by shape index and egg weight loss. Conclusion: A prediction of hatchability using multiple regression analysis could be a good tool to improve hatchability percentage in chickens. PMID:27651666
Mean centering, multicollinearity, and moderators in multiple regression: The reconciliation redux.
Iacobucci, Dawn; Schneider, Matthew J; Popovich, Deidre L; Bakamitsos, Georgios A
2017-02-01
In this article, we attempt to clarify our statements regarding the effects of mean centering. In a multiple regression with predictors A, B, and A × B (where A × B serves as an interaction term), mean centering A and B prior to computing the product term can clarify the regression coefficients (which is good) and the overall model fit R 2 will remain undisturbed (which is also good).
2013-01-01
application of the Hammett equation with the constants rph in the chemistry of organophosphorus compounds, Russ. Chem. Rev. 38 (1969) 795–811. [13...of oximes and OP compounds and the ability of oximes to reactivate OP- inhibited AChE. Multiple linear regression equations were analyzed using...phosphonate pairs, 21 oxime/ phosphoramidate pairs and 12 oxime/phosphate pairs. The best linear regression equation resulting from multiple regression anal
He, Dan; Kuhn, David; Parida, Laxmi
2016-06-15
Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait prediction is usually represented as linear regression models. In many cases, for the same set of samples and markers, multiple traits are observed. Some of these traits might be correlated with each other. Therefore, modeling all the multiple traits together may improve the prediction accuracy. In this work, we view the multitrait prediction problem from a machine learning angle: as either a multitask learning problem or a multiple output regression problem, depending on whether different traits share the same genotype matrix or not. We then adapted multitask learning algorithms and multiple output regression algorithms to solve the multitrait prediction problem. We proposed a few strategies to improve the least square error of the prediction from these algorithms. Our experiments show that modeling multiple traits together could improve the prediction accuracy for correlated traits. The programs we used are either public or directly from the referred authors, such as MALSAR (http://www.public.asu.edu/~jye02/Software/MALSAR/) package. The Avocado data set has not been published yet and is available upon request. dhe@us.ibm.com. © The Author 2016. Published by Oxford University Press.
Simple and multiple linear regression: sample size considerations.
Hanley, James A
2016-11-01
The suggested "two subjects per variable" (2SPV) rule of thumb in the Austin and Steyerberg article is a chance to bring out some long-established and quite intuitive sample size considerations for both simple and multiple linear regression. This article distinguishes two of the major uses of regression models that imply very different sample size considerations, neither served well by the 2SPV rule. The first is etiological research, which contrasts mean Y levels at differing "exposure" (X) values and thus tends to focus on a single regression coefficient, possibly adjusted for confounders. The second research genre guides clinical practice. It addresses Y levels for individuals with different covariate patterns or "profiles." It focuses on the profile-specific (mean) Y levels themselves, estimating them via linear compounds of regression coefficients and covariates. By drawing on long-established closed-form variance formulae that lie beneath the standard errors in multiple regression, and by rearranging them for heuristic purposes, one arrives at quite intuitive sample size considerations for both research genres. Copyright © 2016 Elsevier Inc. All rights reserved.
Multiple imputation for cure rate quantile regression with censored data.
Wu, Yuanshan; Yin, Guosheng
2017-03-01
The main challenge in the context of cure rate analysis is that one never knows whether censored subjects are cured or uncured, or whether they are susceptible or insusceptible to the event of interest. Considering the susceptible indicator as missing data, we propose a multiple imputation approach to cure rate quantile regression for censored data with a survival fraction. We develop an iterative algorithm to estimate the conditionally uncured probability for each subject. By utilizing this estimated probability and Bernoulli sample imputation, we can classify each subject as cured or uncured, and then employ the locally weighted method to estimate the quantile regression coefficients with only the uncured subjects. Repeating the imputation procedure multiple times and taking an average over the resultant estimators, we obtain consistent estimators for the quantile regression coefficients. Our approach relaxes the usual global linearity assumption, so that we can apply quantile regression to any particular quantile of interest. We establish asymptotic properties for the proposed estimators, including both consistency and asymptotic normality. We conduct simulation studies to assess the finite-sample performance of the proposed multiple imputation method and apply it to a lung cancer study as an illustration. © 2016, The International Biometric Society.
Undergraduate Student Motivation in Modularized Developmental Mathematics Courses
ERIC Educational Resources Information Center
Pachlhofer, Keith A.
2017-01-01
This study used the Motivated Strategies for Learning Questionnaire in modularized courses at three institutions across the nation (N = 189), and multiple regression was completed to investigate five categories of student motivation that predicted academic success and course completion. The overall multiple regression analysis was significant and…
MULGRES: a computer program for stepwise multiple regression analysis
A. Jeff Martin
1971-01-01
MULGRES is a computer program source deck that is designed for multiple regression analysis employing the technique of stepwise deletion in the search for most significant variables. The features of the program, along with inputs and outputs, are briefly described, with a note on machine compatibility.
Categorical Variables in Multiple Regression: Some Cautions.
ERIC Educational Resources Information Center
O'Grady, Kevin E.; Medoff, Deborah R.
1988-01-01
Limitations of dummy coding and nonsense coding as methods of coding categorical variables for use as predictors in multiple regression analysis are discussed. The combination of these approaches often yields estimates and tests of significance that are not intended by researchers for inclusion in their models. (SLD)
Peer influences on the dating aggression process among Brazilian street youth: A brief report
Antônio, Tiago; Koller, Silvia H.; Hokoda, Audrey
2011-01-01
This study explored risk factors for adolescent dating aggression (ADA) among Brazilian street youth. Forty-three adolescents, between the ages of 13-17 years, were recruited at services centers in Porto Alegre, Brazil. Simultaneous multiple regression revealed that ADA was significantly predicted by adolescent dating victimization, and that this relationship was moderated by peer involvement in dating aggression. Results also revealed that peer involvement in dating aggression did not significantly predict ADA. These findings suggested that having peers who are involved in dating aggression exacerbates the effects of dating victimization on ADA among Brazilian street youth. However, adolescent dating victimization might be a stronger risk factor for dating aggression in this population, because when controlling for the effects of victimization in dating conflicts peer abuse towards romantic partners did not uniquely contribute to ADA. PMID:22203638
Fear of Death in a Sample of Physicians
Wood, Keith; Robinson, Paul J.
1984-01-01
Recently, reliable and valid methods of assessing fear of death have been developed. In this study, three well established questionnaires (the Threat Index, the Death Anxiety Scale and the Collett-Lester Fear of Death Scale) were used to assess and compare fear of death in a group of physicians (n = 30) with a group of non-physicians (n = 30). T-tests and hierarchical multiple regression analyses revealed no significant differences between physicians' and non-physicians' fear of death as measured by the Threat Index and Templer's Death Anxiety Scale. The Collett-Lester Fear of Death Scale revealed that physicians were less fearful of death. More specifically, physicians demonstrated less fear on the Collett-Lester subscales, `fear of dying of self' and `fear of dying of others', than did non-physicians. These findings and those of earlier, contradictory research, are discussed. PMID:21279021
Multiple Imputation of a Randomly Censored Covariate Improves Logistic Regression Analysis.
Atem, Folefac D; Qian, Jing; Maye, Jacqueline E; Johnson, Keith A; Betensky, Rebecca A
2016-01-01
Randomly censored covariates arise frequently in epidemiologic studies. The most commonly used methods, including complete case and single imputation or substitution, suffer from inefficiency and bias. They make strong parametric assumptions or they consider limit of detection censoring only. We employ multiple imputation, in conjunction with semi-parametric modeling of the censored covariate, to overcome these shortcomings and to facilitate robust estimation. We develop a multiple imputation approach for randomly censored covariates within the framework of a logistic regression model. We use the non-parametric estimate of the covariate distribution or the semiparametric Cox model estimate in the presence of additional covariates in the model. We evaluate this procedure in simulations, and compare its operating characteristics to those from the complete case analysis and a survival regression approach. We apply the procedures to an Alzheimer's study of the association between amyloid positivity and maternal age of onset of dementia. Multiple imputation achieves lower standard errors and higher power than the complete case approach under heavy and moderate censoring and is comparable under light censoring. The survival regression approach achieves the highest power among all procedures, but does not produce interpretable estimates of association. Multiple imputation offers a favorable alternative to complete case analysis and ad hoc substitution methods in the presence of randomly censored covariates within the framework of logistic regression.
Advanced Statistics for Exotic Animal Practitioners.
Hodsoll, John; Hellier, Jennifer M; Ryan, Elizabeth G
2017-09-01
Correlation and regression assess the association between 2 or more variables. This article reviews the core knowledge needed to understand these analyses, moving from visual analysis in scatter plots through correlation, simple and multiple linear regression, and logistic regression. Correlation estimates the strength and direction of a relationship between 2 variables. Regression can be considered more general and quantifies the numerical relationships between an outcome and 1 or multiple variables in terms of a best-fit line, allowing predictions to be made. Each technique is discussed with examples and the statistical assumptions underlying their correct application. Copyright © 2017 Elsevier Inc. All rights reserved.
Park, Kyung-Ae; Park, Yeon-Hwan; Suh, Min-Hee; Choi-Kwon, Smi
2015-09-01
Differing lifestyle, nutritional, and genetic factors may lead to a differing stiffness index (SI) determined by quantitative ultrasound in elderly men and women. The purpose of this study was to determine SI and the gender-specific factors associated with low SI in a Korean elderly cohort. This was a cross-sectional descriptive study identifying the gender-specific factors related to SI in 252 men and women aged 65 years and greater from local senior centers in Seoul, Korea between January and February 2009. The mean SI of elderly men was significantly higher than that of the women's. A multiple regression analysis reveals that age, nutritional status, and physical activity were predictive factors of lower SI in men, whereas age, alcohol consumption, educational level, and genetic polymorphism were predictive factors for elderly women. Low SI was common in both elderly men and women. We found gender differences in factors linked to low SI. In multiple regression analysis, nutritional status and physical activity were more important factors in men, whereas alcohol consumption, educational level, and genetic polymorphism were significant factors predicting low SI in women. Gender-specific modifiable risk factors associated with low SI should be considered when developing osteoporosis prevention programs for the elderly. Copyright © 2015. Published by Elsevier B.V.
Nursing home cost and ownership type: evidence of interaction effects.
Arling, G; Nordquist, R H; Capitman, J A
1987-06-01
Due to steadily increasing public expenditures for nursing home care, much research has focused on factors that influence nursing home costs, especially for Medicaid patients. Nursing home cost function studies have typically used a number of predictor variables in a multiple regression analysis to determine the effect of these variables on operating cost. Although several authors have suggested that nursing home ownership types have different goal orientations, not necessarily based on economic factors, little attention has been paid to this issue in empirical research. In this study, data from 150 Virginia nursing homes were used in multiple regression analysis to examine factors accounting for nursing home operating costs. The context of the study was the Virginia Medicaid reimbursement system, which has intermediate care and skilled nursing facility (ICF and SNF) facility-specific per diem rates, set according to facility cost histories. The analysis revealed interaction effects between ownership and other predictor variables (e.g., percentage Medicaid residents, case mix, and region), with predictor variables having different effects on cost depending on ownership type. Conclusions are drawn about the goal orientations and behavior of chain-operated, individual for-profit, and public and nonprofit facilities. The implications of these findings for long-term care reimbursement policies are discussed.
Takao, Tetsuya; Tsujimura, Akira; Okuda, Hidenobu; Yamamoto, Keisuke; Fukuhara, Shinichiro; Matsuoka, Yasuhiro; Miyagawa, Yasushi; Nonomura, Norio; Okuyama, Akihiko
2011-06-01
The aim of this study was to investigate the relation between lower urinary tract symptoms (LUTS), erectile dysfunction (ED) and depression in Japanese patients with late-onset hypogonadism (LOH) symptoms. The study comprised 87 Japanese patients with LOH symptoms (>27 points on the Aging Males Symptoms Scale). Thirty-four patients were diagnosed as having depression and the remaining 53 patients were diagnosed as not having depression by the Mini International Neuropsychiatric Interview. We compared the International Index of Erectile Function (IIEF) 5, International Prostate Symptom Score (IPSS), IPSS quality-of-life (QOL) index, King's Health Questionnaire (KHQ), endocrinological data, and free uroflow study between depression and non-depression patients and performed multiple logistic regression analysis. IIEF5 scores of depression patients were significantly lower than those of non-depression patients. In KHQ, only the category of general health perceptions was significantly higher in depression patients than non-depression patients. However, IPSS, QOL index, and endocrinological and uroflowmetric data showed no significant difference between the groups. Multiple logistic regression analysis revealed moderate and severe ED to be risk factors for depression. However, LUTS are not related to depression. Moderate and severe ED is correlated with depression, whereas LUTS are not related to depression in Japanese LOH patients.
Akiyama, Tomoyuki; Akiyama, Mari; Hayashi, Yumiko; Shibata, Takashi; Hanaoka, Yoshiyuki; Toda, Soichiro; Imai, Katsumi; Hamano, Shin-Ichiro; Okanishi, Tohru; Yoshinaga, Harumi; Kobayashi, Katsuhiro
2017-03-01
We quantified pyridoxal 5'-phosphate (PLP), pyridoxal (PL), and 4-pyridoxic acid (PA) in the cerebrospinal fluid (CSF) of children and to investigate the effect of age, sex, epilepsy, and anti-epileptic drug (AED) therapy on these vitamers. CSF samples prospectively collected from 116 pediatric patients were analyzed. PLP, PL, and PA were measured using high-performance liquid chromatography with fluorescence detection, using pre-column derivatization by semicarbazide. Effects of age, sex, epilepsy, and AEDs on these vitamers and the PLP/PL ratio were evaluated using multiple linear regression models. The PLP, PL, and PA concentrations were correlated negatively with age and the PLP/PL ratio was correlated positively with age. Multiple regression analysis revealed that the presence of epilepsy was associated with lower PLP concentrations and PLP/PL ratios but sex and AED therapy had no influence on these values. The observed ranges of these vitamers in epileptic and non-epileptic patients were demonstrated. We showed the age dependence of PLP and PL in CSF from pediatric patients. Epileptic patients had lower PLP concentrations and PLP/PL ratios than non-epileptic patients, but it is unknown whether this is the cause, or a result, of epilepsy. Copyright © 2016 Elsevier B.V. All rights reserved.
Souza-Oliveira, Ana Carolina; Cunha, Thúlio Marquez; Passos, Liliane Barbosa da Silva; Lopes, Gustavo Camargo; Gomes, Fabiola Alves; Röder, Denise Von Dolinger de Brito
2016-01-01
Ventilator-associated pneumonia is the most prevalent nosocomial infection in intensive care units and is associated with high mortality rates (14-70%). This study evaluated factors influencing mortality of patients with Ventilator-associated pneumonia (VAP), including bacterial resistance, prescription errors, and de-escalation of antibiotic therapy. This retrospective study included 120 cases of Ventilator-associated pneumonia admitted to the adult adult intensive care unit of the Federal University of Uberlândia. The chi-square test was used to compare qualitative variables. Student's t-test was used for quantitative variables and multiple logistic regression analysis to identify independent predictors of mortality. De-escalation of antibiotic therapy and resistant bacteria did not influence mortality. Mortality was 4 times and 3 times higher, respectively, in patients who received an inappropriate antibiotic loading dose and in patients whose antibiotic dose was not adjusted for renal function. Multiple logistic regression analysis revealed the incorrect adjustment for renal function was the only independent factor associated with increased mortality. Prescription errors influenced mortality of patients with Ventilator-associated pneumonia, underscoring the challenge of proper Ventilator-associated pneumonia treatment, which requires continuous reevaluation to ensure that clinical response to therapy meets expectations. Copyright © 2016. Published by Elsevier Editora Ltda.
Self-identity and the theory of planned behaviour: between- and within-participants analyses.
Hagger, Martin S; Chatzisarantis, Nikos L D
2006-12-01
Two studies addressed the hypothesis that a minority of people are more oriented towards their self-identity when forming intentions to act than the traditional antecedents of intentional action; attitudes, subjective norms and perceived behavioural control (PBC). In Study 1, participants (N=241) completed measures of an augmented version of theory of planned behaviour (TPB) that included self-identity for 30 behaviours. Using within-participants multiple regression analyses, the sample was classified into self-identity-oriented (SI-oriented) and TPB-oriented groups. Between-participants multiple regression analyses revealed that self-identity was a significantly stronger predictor of intentions and accounted for significantly more incremental variance in intentions in the SI-oriented sample compared with the TPB-oriented sample across the 30 behaviours. In Study 2, participants (N=250) completed the same TPB and self-identity measures used in Study 1 as well as measures of generalized self-concept and social physique anxiety for dieting behaviour. Results indicated that self-identity was significantly associated with the generalized self-related measures, and self-concept and social physique anxiety moderated the self-identity-intention relationship. This investigation provides some preliminary evidence to support the effect of individual differences in self-identity on the formation of intentions to act.
Li, Siyue; Zhang, Quanfa
2011-06-15
Water samples were collected for determination of dissolved trace metals in 56 sampling sites throughout the upper Han River, China. Multivariate statistical analyses including correlation analysis, stepwise multiple linear regression models, and principal component and factor analysis (PCA/FA) were employed to examine the land use influences on trace metals, and a receptor model of factor analysis-multiple linear regression (FA-MLR) was used for source identification/apportionment of anthropogenic heavy metals in the surface water of the River. Our results revealed that land use was an important factor in water metals in the snow melt flow period and land use in the riparian zone was not a better predictor of metals than land use away from the river. Urbanization in a watershed and vegetation along river networks could better explain metals, and agriculture, regardless of its relative location, however slightly explained metal variables in the upper Han River. FA-MLR analysis identified five source types of metals, and mining, fossil fuel combustion, and vehicle exhaust were the dominant pollutions in the surface waters. The results demonstrated great impacts of human activities on metal concentrations in the subtropical river of China. Copyright © 2011 Elsevier B.V. All rights reserved.
Association between the Type of Workplace and Lung Function in Copper Miners
Gruszczyński, Leszek; Wojakowska, Anna; Ścieszka, Marek; Turczyn, Barbara; Schmidt, Edward
2016-01-01
The aim of the analysis was to retrospectively assess changes in lung function in copper miners depending on the type of workplace. In the groups of 225 operators, 188 welders, and 475 representatives of other jobs, spirometry was performed at the start of employment and subsequently after 10, 20, and 25 years of work. Spirometry Longitudinal Data Analysis software was used to estimate changes in group means for FEV1 and FVC. Multiple linear regression analysis was used to assess an association between workplace and lung function. Lung function assessed on the basis of calculation of longitudinal FEV1 (FVC) decline was similar in all studied groups. However, multiple linear regression model used in cross-sectional analysis revealed an association between workplace and lung function. In the group of welders, FEF75 was lower in comparison to operators and other miners as early as after 10 years of work. Simultaneously, in smoking welders, the FEV1/FVC ratio was lower than in nonsmokers (p < 0,05). The interactions between type of workplace and smoking (p < 0,05) in their effect on FVC, FEV1, PEF, and FEF50 were shown. Among underground working copper miners, the group of smoking welders is especially threatened by impairment of lung ventilatory function. PMID:27274987
Khodaverdi, Zeinab; Bahram, Abbas; Khalaji, Hassan; Kazemnejad, Anoshirvan
2013-10-01
The main purpose of this study was to determine which correlate, perceived motor competence or motor skill competence, best predicts girls' physical activity behavior. A sample of 352 girls (mean age=8.7, SD=0.3 yr) participated in this study. To assess motor skill competence and perceived motor competence, each child completed the Test of Gross Motor Development-2 and Physical Ability sub-scale of Marsh's Self-Description Questionnaire. Children's physical activity was assessed by the Physical Activity Questionnaire for Older Children. Multiple linear regression model was used to determine whether perceived motor competence or motor skill competence best predicts moderate-to-vigorous self-report physical activity. Multiple regression analysis indicated that motor skill competence and perceived motor competence predicted 21% variance in physical activity (R(2)=0.21, F=48.9, P=0.001), and motor skill competence (R(2)=0.15, ᵝ=0.33, P= 0.001) resulted in more variance than perceived motor competence (R(2)=0.06, ᵝ=0.25, P=0.001) in physical activity. Results revealed motor skill competence had more influence in comparison with perceived motor competence on physical activity level. We suggest interventional programs based on motor skill competence and perceived motor competence should be administered or implemented to promote physical activity in young girls.
Searching for a neurologic injury's Wechsler Adult Intelligence Scale-Third Edition profile.
Gonçalves, Marta A; Moura, Octávio; Castro-Caldas, Alexandre; Simões, Mário R
2017-01-01
This study aimed to investigate the presence of a Wechsler Adult Intelligence Scale-Third Edition (WAIS-III) cognitive profile in a Portuguese neurologic injured sample. The Portuguese WAIS-III was administered to 81 mixed neurologic patients and 81 healthy matched controls selected from the Portuguese standardization sample. Although the mixed neurologic injury group performed significantly lower than the healthy controls for the majority of the WAIS-III scores (i.e., composite measures, discrepancies, and subtests), the mean scores were within the normal range and, therefore, at risk of being unobserved in a clinical evaluation. ROC curves analysis showed poor to acceptable diagnostic accuracy for the WAIS-III composite measures and subtests (Working Memory Index and Digit Span revealed the highest accuracy for discriminating between participants, respectively). Multiple regression analysis showed that both literacy and the presence of brain injury were significant predictors for all of the composite measures. In addition, multiple regression analysis also showed that literacy, age of injury onset, and years of survival predicted all seven composite measures for the mixed neurologic injured group. Despite the failure to find a WAIS-III cognitive profile for mixed neurologic patients, the results showed a significant influence of brain lesion and literacy in the performance of the WAIS-III.
Examining the Relationship of Textbooks and Labs on Student Achievement in Eighth-Grade Science
NASA Astrophysics Data System (ADS)
Sugalan, Anacita Noromor
One of the most important objectives of teachers, parents, school administrators, and students is to improve student scores on standardized tests such as the State of Texas Assessment for Academic Readiness (STAAR) in eighth-grade science. This quasi experimental study examined the science achievement scores between schools that use textbooks and labs when delivering instruction. This study utilized a quantitative approach using archival data and survey design. Analysis of covariance (ANCOVA) and multiple regression were used to analyze the data while controlling STAAR eighth-grade reading scores to reveal significant differences between classes. The sample and population for this study were predominantly eighth-grade Hispanic students in South Texas. Analysis of covariance showed that classes that used high labs got higher science scores and that the reading scores were significantly related to science scores. Multiple regression findings indicated that textbooks and labs were significant predictors of student achievement on the STAAR eighth- grade science class result in South Texas for Spring 2015. The findings of this study may serve as a catalyst for improving student achievement in science through changes in textbook adoption and doing labs in science. The result suggests the need to research further to investigate other contributing factors of student achievement.
Nursing home cost and ownership type: evidence of interaction effects.
Arling, G; Nordquist, R H; Capitman, J A
1987-01-01
Due to steadily increasing public expenditures for nursing home care, much research has focused on factors that influence nursing home costs, especially for Medicaid patients. Nursing home cost function studies have typically used a number of predictor variables in a multiple regression analysis to determine the effect of these variables on operating cost. Although several authors have suggested that nursing home ownership types have different goal orientations, not necessarily based on economic factors, little attention has been paid to this issue in empirical research. In this study, data from 150 Virginia nursing homes were used in multiple regression analysis to examine factors accounting for nursing home operating costs. The context of the study was the Virginia Medicaid reimbursement system, which has intermediate care and skilled nursing facility (ICF and SNF) facility-specific per diem rates, set according to facility cost histories. The analysis revealed interaction effects between ownership and other predictor variables (e.g., percentage Medicaid residents, case mix, and region), with predictor variables having different effects on cost depending on ownership type. Conclusions are drawn about the goal orientations and behavior of chain-operated, individual for-profit, and public and nonprofit facilities. The implications of these findings for long-term care reimbursement policies are discussed. PMID:3301746
Siddall, James; Huebner, E Scott; Jiang, Xu
2013-01-01
This study examined the cross-sectional and prospective relationships between three sources of school-related social support (parent involvement, peer support for learning, and teacher-student relationships) and early adolescents' global life satisfaction. The participants were 597 middle school students from 1 large school in the southeastern United States who completed measures of school social climate and life satisfaction on 2 occasions, 5 months apart. The results revealed that school-related experiences in terms of social support for learning contributed substantial amounts of variance to individual differences in adolescents' satisfaction with their lives as a whole. Cross-sectional multiple regression analyses of the differential contributions of the sources of support demonstrated that family and peer support for learning contributed statistically significant, unique variance to global life satisfaction reports. Prospective multiple regression analyses demonstrated that only family support for learning continued to contribute statistically significant, unique variance to the global life satisfaction reports at Time 2. The results suggest that school-related experiences, especially family-school interactions, spill over into adolescents' overall evaluations of their lives at a time when direct parental involvement in schooling and adolescents' global life satisfaction are generally declining. Recommendations for future research and educational policies and practices are discussed. © 2013 American Orthopsychiatric Association.
Oosono, Yasufumi; Yokoyama, Kazuhito; Itoh, Hiroaki; Enomoto, Miyuki; Ishiwata, Miki
2018-04-01
Even if patients with terminal cancer hope to spend the rest of their lives at home, they are often unable to leave the hospital early due to their family caregivers' anxiety. This study aimed to investigate in Japan the discrepancies between the supports needed by and actually provided by palliative care unit nurses (PCUNs) to the family caregivers for discharge of patients with terminal cancer. In this cross-sectional study, self-administered questionnaires including 6-point Likert-type scales assessing the reasons for difficulties in transition to home-based care were distributed to 1227 PCUNs. Using paired t tests, the differences between the scores on perceived importance and actual supports to family caregivers were examined. The supports actually provided were classified by factor analysis. The relationships between the PCUNs' characteristics and mean scores on the supports in each category were examined using multiple regression analysis. A total of 1023 (83.4%) completed questionnaires were returned. Scores on the actually provided supports for discharge to family caregivers were consistently and significantly lower than the corresponding scores on perceived importance for all 57 items ( P < .001). Factor analysis revealed that the supports actually provided to the family caregivers had a 4-factor structure. Multiple regression analyses revealed that gaining experience in palliative care, receiving necessary training, cooperating with palliative care staff, and cooperating with local service providers were significantly associated with higher levels of actual supply of supports to family caregivers. Our findings suggest that PCUNs need to be encouraged to provide further support to family caregivers for the discharge of patients with terminal cancer.
Alavi, Seyyed Salman; Mohammadi, Mohammad Reza; Souri, Hamid; Mohammadi Kalhori, Soroush; Jannatifard, Fereshteh; Sepahbodi, Ghazal
2017-01-01
The aim of this study was to evaluate the effect of variables such as personality traits, driving behavior and mental illness on road traffic accidents among the drivers with accidents and those without road crash. In this cohort study, 800 bus and truck drivers were recruited. Participants were selected among drivers who referred to Imam Sajjad Hospital (Tehran, Iran) during 2013-2015. The Manchester driving behavior questionnaire (MDBQ), big five personality test (NEO personality inventory) and semi-structured interview (schizophrenia and affective disorders scale) were used. After two years, we surveyed all accidents due to human factors that involved the recruited drivers. The data were analyzed using the SPSS software by performing the descriptive statistics, t-test, and multiple logistic regression analysis methods. P values less than 0.05 were considered statistically significant. In terms of controlling the effective and demographic variables, the findings revealed significant differences between the two groups of drivers that were and were not involved in road accidents. In addition, it was found that depression and anxiety could increase the odds ratio (OR) of road accidents by 2.4- and 2.7-folds, respectively (P=0.04, P=0.004). It is noteworthy to mention that neuroticism alone can increase the odds of road accidents by 1.1-fold (P=0.009), but other personality factors did not have a significant effect on the equation. The results revealed that some mental disorders affect the incidence of road collisions. Considering the importance and sensitivity of driving behavior, it is necessary to evaluate multiple psychological factors influencing drivers before and after receiving or renewing their driver's license.
Alavi, Seyyed Salman; Mohammadi, Mohammad Reza; Souri, Hamid; Mohammadi Kalhori, Soroush; Jannatifard, Fereshteh; Sepahbodi, Ghazal
2017-01-01
Background: The aim of this study was to evaluate the effect of variables such as personality traits, driving behavior and mental illness on road traffic accidents among the drivers with accidents and those without road crash. Methods: In this cohort study, 800 bus and truck drivers were recruited. Participants were selected among drivers who referred to Imam Sajjad Hospital (Tehran, Iran) during 2013-2015. The Manchester driving behavior questionnaire (MDBQ), big five personality test (NEO personality inventory) and semi-structured interview (schizophrenia and affective disorders scale) were used. After two years, we surveyed all accidents due to human factors that involved the recruited drivers. The data were analyzed using the SPSS software by performing the descriptive statistics, t-test, and multiple logistic regression analysis methods. P values less than 0.05 were considered statistically significant. Results: In terms of controlling the effective and demographic variables, the findings revealed significant differences between the two groups of drivers that were and were not involved in road accidents. In addition, it was found that depression and anxiety could increase the odds ratio (OR) of road accidents by 2.4- and 2.7-folds, respectively (P=0.04, P=0.004). It is noteworthy to mention that neuroticism alone can increase the odds of road accidents by 1.1-fold (P=0.009), but other personality factors did not have a significant effect on the equation. Conclusion: The results revealed that some mental disorders affect the incidence of road collisions. Considering the importance and sensitivity of driving behavior, it is necessary to evaluate multiple psychological factors influencing drivers before and after receiving or renewing their driver’s license. PMID:28293047
Shea, Jennifer; Wadden, Danny; Gulliver, Wayne; Randell, Edward; Vasdev, Sudesh; Sun, Guang
2013-01-01
Background Magnesium plays a role in glucose and insulin homeostasis and evidence suggests that magnesium intake is associated with insulin resistance (IR). However, data is inconsistent and most studies have not adequately controlled for critical confounding factors. Objective The study investigated the association between magnesium intake and IR in normal-weight (NW), overweight (OW) and obese (OB) along with pre- and post- menopausal women. Design A total of 2295 subjects (590 men and 1705 women) were recruited from the CODING study. Dietary magnesium intake was computed from the Willett Food Frequency Questionnaire (FFQ). Adiposity (NW, OW and OB) was classified by body fat percentage (%BF) measured by Dual-energy X-ray absorptiometry according to the Bray criteria. Multiple regression analyses were used to test adiposity-specific associations of dietary magnesium intake on insulin resistance adjusting for caloric intake, physical activity, medication use and menopausal status. Results Subjects with the highest intakes of dietary magnesium had the lowest levels of circulating insulin, HOMA-IR, and HOMA-ß and subjects with the lowest intake of dietary magnesium had the highest levels of these measures, suggesting a dose effect. Multiple regression analysis revealed a strong inverse association between dietary magnesium with IR. In addition, adiposity and menopausal status were found to be critical factors revealing that the association between dietary magnesium and IR was stronger in OW and OB along with Pre-menopausal women. Conclusion The results of this study indicate that higher dietary magnesium intake is strongly associated with the attenuation of insulin resistance and is more beneficial for overweight and obese individuals in the general population and pre-menopausal women. Moreover, the inverse correlation between insulin resistance and dietary magnesium intake is stronger when adjusting for %BF than BMI. PMID:23472169
Prediction of Maximal Oxygen Uptake by Six-Minute Walk Test and Body Mass Index in Healthy Boys.
Jalili, Majid; Nazem, Farzad; Sazvar, Akbar; Ranjbar, Kamal
2018-05-14
To develop an equation to predict maximal oxygen uptake (VO2max) based on the 6-minute walk test (6MWT) and body composition in healthy boys. Direct VO2max, 6-minute walk distance, and anthropometric characteristics were measured in 349 healthy boys (12.49 ± 2.72 years). Multiple regression analysis was used to generate VO2max prediction equations. Cross-validation of the VO2max prediction equations was assessed with predicted residual sum of squares statistics. Pearson correlation was used to assess the correlation between measured and predicted VO2max. Objectively measured VO2max had a significant correlation with demographic and 6MWT characteristics (R = 0.11-0.723, P < .01). Multiple regression analysis revealed the following VO2max prediction equation: VO2max (mL/kg/min) = 12.701 + (0.06 × 6-minute walk distance m ) - (0.732 × body mass index kg/m2 ) (R 2 = 0.79, standard error of the estimate [SEE] = 2.91 mL/kg/min, %SEE = 6.9%). There was strong correlation between measured and predicted VO2max (r = 0.875, P < .001). Cross-validation revealed minimal shrinkage (R 2 p = 0.78 and predicted residual sum of squares SEE = 2.99 mL/kg/min). This study provides a relatively accurate and convenient VO2max prediction equation based on the 6MWT and body mass index in healthy boys. This model can be used for evaluation of cardiorespiratory fitness of boys in different settings. Copyright © 2018 Elsevier Inc. All rights reserved.
Ikeya, Yoshimori; Fukuyama, Naoto; Mori, Hidezo
2015-03-01
N-3 fatty acids, including eicosapentaenoic acid (EPA), prevent ischemic stroke. The preventive effect has been attributed to an antithrombic effect induced by elevated EPA and reduced arachidonic acid (AA) levels. However, the relationship between intracranial hemorrhage and N-3 fatty acids has not yet been elucidated. In this cross-sectional study, we compared common clinical and lifestyle parameters between 70 patients with intracranial hemorrhages and 66 control subjects. The parameters included blood chemistry data, smoking, alcohol intake, fish consumption, and the incidences of underlying diseases. The comparisons were performed using the Mann-Whitney U test followed by multiple logistic regression analysis. Nonparametric tests revealed that the 70 patients with intracerebral hemorrhages exhibited significantly higher diastolic blood pressures and alcohol intakes and lower body mass indices, high-density lipoprotein (HDL) cholesterol levels, EPA concentrations, EPA/AA ratios, and vegetable consumption compared with the 66 control subjects. A multiple logistic regression analysis revealed that higher diastolic blood pressure and alcohol intake and lower body mass index, HDL cholesterol, EPA/AA ratio, and vegetable consumption were relative risk factors for intracerebral hemorrhage. High HDL cholesterol was a common risk factor in both of the sex-segregated subgroups and the <65-year-old subgroup. However, neither EPA nor the EPA/AA ratio was a risk factor in these subgroups. Eicosapentaenoic acid was relative risk factor only in the ≥65-year-old subgroup. Rather than higher EPA levels, lower EPA concentrations and EPA/AA ratios were found to be risk factors for intracerebral hemorrhage in addition to previously known risk factors such as blood pressure, alcohol consumption, and lifestyle. Copyright © 2015 Elsevier Inc. All rights reserved.
Olfactory function in chemical workers exposed to acrylate and methacrylate vapors.
Schwartz, B S; Doty, R L; Monroe, C; Frye, R; Barker, S
1989-01-01
An investigation of the olfactory function of 731 workers at a chemical facility which manufacturers acrylates and methacrylates was undertaken using a standardized quantitative test. In a cross-sectional analysis of the data, no associations of chemical exposure with olfactory test scores were observed. A nested case-control study designed to evaluate the cumulative effects of exposure on olfactory function, however, revealed elevated crude exposure odds ratios (95% confidence interval) of 2.0 (1.1, 3.8) for all workers and 6.0 (1.7, 21.5) for workers who never smoked cigarettes. Logistic regression analysis, adjusting for multiple confounders, revealed exposure odds ratios of 2.8 (1.1, 7.0) and 13.5 (2.1, 87.6) in these same groups, respectively, and a dose-response relationship between olfactory dysfunction and cumulative exposure scores--semi-quantitative indices of lifetime exposure to the acrylates. The data also revealed decreasing exposure odds ratios with increasing duration since last exposure to these chemicals, suggesting that the effects may be reversible. PMID:2784947
Use of Thematic Mapper for water quality assessment
NASA Technical Reports Server (NTRS)
Horn, E. M.; Morrissey, L. A.
1984-01-01
The evaluation of simulated TM data obtained on an ER-2 aircraft at twenty-five predesignated sample sites for mapping water quality factors such as conductivity, pH, suspended solids, turbidity, temperature, and depth, is discussed. Using a multiple regression for the seven TM bands, an equation is developed for the suspended solids. TM bands 1, 2, 3, 4, and 6 are used with logarithm conductivity in a multiple regression. The assessment of regression equations for a high coefficient of determination (R-squared) and statistical significance is considered. Confidence intervals about the mean regression point are calculated in order to assess the robustness of the regressions used for mapping conductivity, turbidity, and suspended solids, and by regressing random subsamples of sites and comparing the resultant range of R-squared, cross validation is conducted.
Due to the complexity of the processes contributing to beach bacteria concentrations, many researchers rely on statistical modeling, among which multiple linear regression (MLR) modeling is most widely used. Despite its ease of use and interpretation, there may be time dependence...
Data from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network are used to estimate organic mass to organic carbon (OM/OC) ratios across the United States by extending previously published multiple regression techniques. Our new methodology addresses com...
Analysis and Interpretation of Findings Using Multiple Regression Techniques
ERIC Educational Resources Information Center
Hoyt, William T.; Leierer, Stephen; Millington, Michael J.
2006-01-01
Multiple regression and correlation (MRC) methods form a flexible family of statistical techniques that can address a wide variety of different types of research questions of interest to rehabilitation professionals. In this article, we review basic concepts and terms, with an emphasis on interpretation of findings relevant to research questions…
Tracking the Gender Pay Gap: A Case Study
ERIC Educational Resources Information Center
Travis, Cheryl B.; Gross, Louis J.; Johnson, Bruce A.
2009-01-01
This article provides a short introduction to standard considerations in the formal study of wages and illustrates the use of multiple regression and resampling simulation approaches in a case study of faculty salaries at one university. Multiple regression is especially beneficial where it provides information on strength of association, specific…
Estimating air drying times of lumber with multiple regression
William T. Simpson
2004-01-01
In this study, the applicability of a multiple regression equation for estimating air drying times of red oak, sugar maple, and ponderosa pine lumber was evaluated. The equation allows prediction of estimated air drying times from historic weather records of temperature and relative humidity at any desired location.
Using Robust Variance Estimation to Combine Multiple Regression Estimates with Meta-Analysis
ERIC Educational Resources Information Center
Williams, Ryan
2013-01-01
The purpose of this study was to explore the use of robust variance estimation for combining commonly specified multiple regression models and for combining sample-dependent focal slope estimates from diversely specified models. The proposed estimator obviates traditionally required information about the covariance structure of the dependent…
Multiple Regression: A Leisurely Primer.
ERIC Educational Resources Information Center
Daniel, Larry G.; Onwuegbuzie, Anthony J.
Multiple regression is a useful statistical technique when the researcher is considering situations in which variables of interest are theorized to be multiply caused. It may also be useful in those situations in which the researchers is interested in studies of predictability of phenomena of interest. This paper provides an introduction to…
Using Monte Carlo Techniques to Demonstrate the Meaning and Implications of Multicollinearity
ERIC Educational Resources Information Center
Vaughan, Timothy S.; Berry, Kelly E.
2005-01-01
This article presents an in-class Monte Carlo demonstration, designed to demonstrate to students the implications of multicollinearity in a multiple regression study. In the demonstration, students already familiar with multiple regression concepts are presented with a scenario in which the "true" relationship between the response and…
ERIC Educational Resources Information Center
Bates, Reid A.; Holton, Elwood F., III; Burnett, Michael F.
1999-01-01
A case study of learning transfer demonstrates the possible effect of influential observation on linear regression analysis. A diagnostic method that tests for violation of assumptions, multicollinearity, and individual and multiple influential observations helps determine which observation to delete to eliminate bias. (SK)
Angore, Banchalem Nega; Tufa, Efrata Girma; Bisetegen, Fithamlak Solomon
2018-04-19
Reducing maternal mortality and improving maternal health care through increased utilization of postnatal care utilization is a global and local priority. However studies that have been carried out in Ethiopia regarding determinants are limited. So This study aims to assess the magnitude of postnatal care utilization and its determinants in Debre Birhan Town, North Ethiopia. A community-based cross-sectional study was conducted from March 1 to April 25, 2015, in Debre Birhan Town. Data were collected through face-to-face interviews using structured pre-tested questionnaires. The data were entered and cleaned in Epi Info version 3.5 and analyzed using SPSS version 20. Bivariate and multiple logistic regression analyses were used. Variable with p value less than or equal to 0.2 at bivariate analysis were entered into multiple logistic regression. Significance was declared at 0.05 in multiple logistic regressions and considered to be an independent factor. From the total respondents, we found that 327 (83.3%) mothers utilized the postnatal care services. Single mothers were less likely to utilize postnatal care services than those mothers who are married and live together [adjusted odds ratio (AOR) = 0.06, 95% CI (0.01, 0.45)]. This study revealed that respondent's knowledge about postnatal care services is an important predictor of postnatal care utilization [AOR = 0.03, 95% CI (0.00, 0.44)] and mothers who delivered in a health care facility were more likely to receive PNC than mothers who did not deliver in a health care facility [AOR = 0.65, 95% CI (0.58, 0.94)]. The postnatal care utilization rate in Debre Birhan town was 83.3%. Marital status, maternal knowledge, and place of delivery were predictors of postnatal care service utilization. So specific attention should be directed towards the improvement of women's education since the perception of the need for PNC services were positively correlated with the mother's education.
Stroke secondary to multiple spontaneous cholesterol emboli.
Pascual, M; Baumgartner, J M; Bounameaux, H
1991-01-01
We describe one male, 49-year-old diabetic patient in whom regressive stroke with aphasia and right-sided hemiparesia was related to multiple small emboli in the left paraventricular cortex. Simultaneous presence of several cholesterol emboli in the left eye ground and detection of an atheromatous plaque at the homolateral carotid bifurcation let assume that the cerebral emboli originated from that plaque and also consisted of cholesterol crystals. The patient was discharged on low-dose aspirin (100 mg/day) after neurologic improvement. Follow-up at one year revealed clinical stability, recurrence of the cholesterol emboli at the eye ground examination and no change of the carotid plaque. Cholesterol embolization with renal failure, hypertension and peripheral arterial occlusions causing skin ulcerations is classical in case of atheromatous aortic disease but stroke has rarely been reported in this syndrome. However, more frequent use of invasive procedures (arteriography, transluminal angioplasty, vascular surgery) or thrombolytic treatment might increase its incidence in the near future.
Relationships Among Substance Use, Multiple Sexual Partners, and Condomless Sex.
Zhao, Yunchuan Lucy; Kim, Heejung; Peltzer, Jill
2017-04-01
Male and female students manifest different behaviors in condomless sex. This cross-sectional, exploratory, correlational study examined the differences in risk factors for condomless sex between male and female high school students, using secondary data from 4,968 sexually active males and females participating in the 2011 National Youth Risk Behavior Survey. Results in descriptive statistics and multivariate binary logistic regressions revealed that condomless sex was reported as 39.70% in general. A greater proportion of females engaged in condomless sex (23.26%) than did males (16.44%). Physical abuse by sex partners was a common reason for failure to use condoms regardless of gender. Lower condom use was found in (1) those experiencing forced sex by a partner in males, (2) female smokers, and (3) female with multiple sex partners. Thus, sexual health education should address the different risk factors and consider gender characteristics to reduce condomless sex.
Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Markopoulos, John; Igglessi-Markopoulou, Olga
2006-08-01
A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.
Nie, Z Q; Ou, Y Q; Zhuang, J; Qu, Y J; Mai, J Z; Chen, J M; Liu, X Q
2016-05-01
Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions.
Wavelet regression model in forecasting crude oil price
NASA Astrophysics Data System (ADS)
Hamid, Mohd Helmie; Shabri, Ani
2017-05-01
This study presents the performance of wavelet multiple linear regression (WMLR) technique in daily crude oil forecasting. WMLR model was developed by integrating the discrete wavelet transform (DWT) and multiple linear regression (MLR) model. The original time series was decomposed to sub-time series with different scales by wavelet theory. Correlation analysis was conducted to assist in the selection of optimal decomposed components as inputs for the WMLR model. The daily WTI crude oil price series has been used in this study to test the prediction capability of the proposed model. The forecasting performance of WMLR model were also compared with regular multiple linear regression (MLR), Autoregressive Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) using root mean square errors (RMSE) and mean absolute errors (MAE). Based on the experimental results, it appears that the WMLR model performs better than the other forecasting technique tested in this study.
Multiple regression for physiological data analysis: the problem of multicollinearity.
Slinker, B K; Glantz, S A
1985-07-01
Multiple linear regression, in which several predictor variables are related to a response variable, is a powerful statistical tool for gaining quantitative insight into complex in vivo physiological systems. For these insights to be correct, all predictor variables must be uncorrelated. However, in many physiological experiments the predictor variables cannot be precisely controlled and thus change in parallel (i.e., they are highly correlated). There is a redundancy of information about the response, a situation called multicollinearity, that leads to numerical problems in estimating the parameters in regression equations; the parameters are often of incorrect magnitude or sign or have large standard errors. Although multicollinearity can be avoided with good experimental design, not all interesting physiological questions can be studied without encountering multicollinearity. In these cases various ad hoc procedures have been proposed to mitigate multicollinearity. Although many of these procedures are controversial, they can be helpful in applying multiple linear regression to some physiological problems.
ERIC Educational Resources Information Center
Li, Spencer D.
2011-01-01
Mediation analysis in child and adolescent development research is possible using large secondary data sets. This article provides an overview of two statistical methods commonly used to test mediated effects in secondary analysis: multiple regression and structural equation modeling (SEM). Two empirical studies are presented to illustrate the…
A Simple and Convenient Method of Multiple Linear Regression to Calculate Iodine Molecular Constants
ERIC Educational Resources Information Center
Cooper, Paul D.
2010-01-01
A new procedure using a student-friendly least-squares multiple linear-regression technique utilizing a function within Microsoft Excel is described that enables students to calculate molecular constants from the vibronic spectrum of iodine. This method is advantageous pedagogically as it calculates molecular constants for ground and excited…
Conjoint Analysis: A Study of the Effects of Using Person Variables.
ERIC Educational Resources Information Center
Fraas, John W.; Newman, Isadore
Three statistical techniques--conjoint analysis, a multiple linear regression model, and a multiple linear regression model with a surrogate person variable--were used to estimate the relative importance of five university attributes for students in the process of selecting a college. The five attributes include: availability and variety of…
An Exploratory Study of Face-to-Face and Cyberbullying in Sixth Grade Students
ERIC Educational Resources Information Center
Accordino, Denise B.; Accordino, Michael P.
2011-01-01
In a pilot study, sixth grade students (N = 124) completed a questionnaire assessing students' experience with bullying and cyberbullying, demographic information, quality of parent-child relationship, and ways they have dealt with bullying/cyberbullying in the past. Two multiple regression analyses were conducted. The multiple regression analysis…
ERIC Educational Resources Information Center
Campbell, S. Duke; Greenberg, Barry
The development of a predictive equation capable of explaining a significant percentage of enrollment variability at Florida International University is described. A model utilizing trend analysis and a multiple regression approach to enrollment forecasting was adapted to investigate enrollment dynamics at the university. Four independent…
ERIC Educational Resources Information Center
Fraas, John W.; Newman, Isadore
1996-01-01
In a conjoint-analysis consumer-preference study, researchers must determine whether the product factor estimates, which measure consumer preferences, should be calculated and interpreted for each respondent or collectively. Multiple regression models can determine whether to aggregate data by examining factor-respondent interaction effects. This…
Double Cross-Validation in Multiple Regression: A Method of Estimating the Stability of Results.
ERIC Educational Resources Information Center
Rowell, R. Kevin
In multiple regression analysis, where resulting predictive equation effectiveness is subject to shrinkage, it is especially important to evaluate result replicability. Double cross-validation is an empirical method by which an estimate of invariance or stability can be obtained from research data. A procedure for double cross-validation is…
Paschalidou, Anastasia K; Karakitsios, Spyridon; Kleanthous, Savvas; Kassomenos, Pavlos A
2011-02-01
In the present work, two types of artificial neural network (NN) models using the multilayer perceptron (MLP) and the radial basis function (RBF) techniques, as well as a model based on principal component regression analysis (PCRA), are employed to forecast hourly PM(10) concentrations in four urban areas (Larnaca, Limassol, Nicosia and Paphos) in Cyprus. The model development is based on a variety of meteorological and pollutant parameters corresponding to the 2-year period between July 2006 and June 2008, and the model evaluation is achieved through the use of a series of well-established evaluation instruments and methodologies. The evaluation reveals that the MLP NN models display the best forecasting performance with R (2) values ranging between 0.65 and 0.76, whereas the RBF NNs and the PCRA models reveal a rather weak performance with R (2) values between 0.37-0.43 and 0.33-0.38, respectively. The derived MLP models are also used to forecast Saharan dust episodes with remarkable success (probability of detection ranging between 0.68 and 0.71). On the whole, the analysis shows that the models introduced here could provide local authorities with reliable and precise predictions and alarms about air quality if used on an operational basis.
Explaining match outcome in elite Australian Rules football using team performance indicators.
Robertson, Sam; Back, Nicole; Bartlett, Jonathan D
2016-01-01
The relationships between team performance indicators and match outcome have been examined in many team sports, however are limited in Australian Rules football. Using data from the 2013 and 2014 Australian Football League (AFL) regular seasons, this study assessed the ability of commonly reported discrete team performance indicators presented in their relative form (standardised against their opposition for a given match) to explain match outcome (Win/Loss). Logistic regression and decision tree (chi-squared automatic interaction detection (CHAID)) analyses both revealed relative differences between opposing teams for "kicks" and "goal conversion" as the most influential in explaining match outcome, with two models achieving 88.3% and 89.8% classification accuracies, respectively. Models incorporating a smaller performance indicator set displayed a slightly reduced ability to explain match outcome (81.0% and 81.5% for logistic regression and CHAID, respectively). However, both were fit to 2014 data with reduced error in comparison to the full models. Despite performance similarities across the two analysis approaches, the CHAID model revealed multiple winning performance indicator profiles, thereby increasing its comparative feasibility for use in the field. Coaches and analysts may find these results useful in informing strategy and game plan development in Australian Rules football, with the development of team-specific models recommended in future.
MBS Measurement Tool for Swallow Impairment—MBSImp: Establishing a Standard
Martin-Harris, Bonnie; Brodsky, Martin B.; Michel, Yvonne; Castell, Donald O.; Schleicher, Melanie; Sandidge, John; Maxwell, Rebekah; Blair, Julie
2014-01-01
The aim of this study was to test reliability, content, construct, and external validity of a new modified barium swallowing study (MBSS) tool (MBSImp) that is used to quantify swallowing impairment. Multiple regression, confirmatory factor, and correlation analyses were used to analyze 300 in- and outpatients with heterogeneous medical and surgical diagnoses who were sequentially referred for MBS exams at a university medical center and private tertiary care community hospital. Main outcome measures were the MBSImp and index scores of aspiration, health status, and quality of life. Inter- and intrarater concordance were 80% or greater for blinded scoring of MBSSs. Regression analysis revealed contributions of eight of nine swallow types to impressions of overall swallowing impairment (p ≤ 0.05). Factor analysis revealed 13 significant components (loadings ≥ 0.5) that formed two impairment groupings (oral and pharyngeal). Significant correlations were found between Oral and Pharyngeal Impairment scores and Penetration-Aspiration Scale scores, and indexes of intake status, nutrition, health status, and quality of life. The MBSImp demonstrated clinical practicality, favorable inter- and intrarater reliability following standardized training, content, and external validity. This study reflects potential for establishment of a new standard for quantification and comparison of oropharyngeal swallowing impairment across patient diagnoses as measured on MBSS. PMID:18855050
Davies-Venn, Evelyn; Nelson, Peggy; Souza, Pamela
2015-01-01
Some listeners with hearing loss show poor speech recognition scores in spite of using amplification that optimizes audibility. Beyond audibility, studies have suggested that suprathreshold abilities such as spectral and temporal processing may explain differences in amplified speech recognition scores. A variety of different methods has been used to measure spectral processing. However, the relationship between spectral processing and speech recognition is still inconclusive. This study evaluated the relationship between spectral processing and speech recognition in listeners with normal hearing and with hearing loss. Narrowband spectral resolution was assessed using auditory filter bandwidths estimated from simultaneous notched-noise masking. Broadband spectral processing was measured using the spectral ripple discrimination (SRD) task and the spectral ripple depth detection (SMD) task. Three different measures were used to assess unamplified and amplified speech recognition in quiet and noise. Stepwise multiple linear regression revealed that SMD at 2.0 cycles per octave (cpo) significantly predicted speech scores for amplified and unamplified speech in quiet and noise. Commonality analyses revealed that SMD at 2.0 cpo combined with SRD and equivalent rectangular bandwidth measures to explain most of the variance captured by the regression model. Results suggest that SMD and SRD may be promising clinical tools for diagnostic evaluation and predicting amplification outcomes. PMID:26233047
Davies-Venn, Evelyn; Nelson, Peggy; Souza, Pamela
2015-07-01
Some listeners with hearing loss show poor speech recognition scores in spite of using amplification that optimizes audibility. Beyond audibility, studies have suggested that suprathreshold abilities such as spectral and temporal processing may explain differences in amplified speech recognition scores. A variety of different methods has been used to measure spectral processing. However, the relationship between spectral processing and speech recognition is still inconclusive. This study evaluated the relationship between spectral processing and speech recognition in listeners with normal hearing and with hearing loss. Narrowband spectral resolution was assessed using auditory filter bandwidths estimated from simultaneous notched-noise masking. Broadband spectral processing was measured using the spectral ripple discrimination (SRD) task and the spectral ripple depth detection (SMD) task. Three different measures were used to assess unamplified and amplified speech recognition in quiet and noise. Stepwise multiple linear regression revealed that SMD at 2.0 cycles per octave (cpo) significantly predicted speech scores for amplified and unamplified speech in quiet and noise. Commonality analyses revealed that SMD at 2.0 cpo combined with SRD and equivalent rectangular bandwidth measures to explain most of the variance captured by the regression model. Results suggest that SMD and SRD may be promising clinical tools for diagnostic evaluation and predicting amplification outcomes.
Petty, J L; Bacarese-Hamilton, M; Davies, L E; Oliver, C
2014-01-01
Several behavioural correlates of self-injury, aggression and destructive behaviour have been identified in children and young adults with intellectual disabilities. This cross-sectional study aimed to further explore these correlates in very young children with developmental delay. Parents of 56 children (40 male) under the age of five years (mean age 2 years 10 months) completed a questionnaire about their child's behaviour and the presence of behavioural correlates, including repetitive, over-active or impulsive behaviour and more severe developmental delay. Parents reported very high prevalence of self-injurious, aggressive and destructive behaviour: 51%, 64% and 51%, respectively. A binary logistic regression revealed that a higher score on a measure of overactive and impulsive behaviour significantly predicted the presence of destructive behaviour. A multiple linear regression revealed that both repetitive behaviour and number of health problems approached significance as independent predictors of severe self-injurious behaviour. Despite the very small sample, several factors emerged as potential predictors of self-injurious, aggressive and destructive behaviour. These findings support the need for further investigation in a larger sample. Confirmation in this age group could help guide the development of targeted early intervention for these behaviours by identifying behavioural risk markers. Copyright © 2013 Elsevier Ltd. All rights reserved.
Sümer, Zeynep Hatipoğlu
2015-12-01
The purpose of this study is to examine the role of gender, religiosity, sexual activity, and sexual knowledge in predicting attitudes toward controversial aspects of sexuality among Turkish university students. Participants were 162 female and 135 male undergraduate students who were recruited on a volunteer basis from an urban state university in Turkey. The SKAT-A Attitude Scale along with background information form, sexual activities inventory, and sexual knowledge scale were administered to the participants. Simultaneous multiple regression analyses revealed that religiosity, particularly attendance to religious services was the most significant predictor in explaining university students' attitudes toward masturbation, abortion, homosexuality, pornography, and sexual coercion.
Lorente Prieto, Laura; Salanova Soria, Marisa; Martínez Martínez, Isabel; Schaufeli, Wilmar
2008-08-01
Our purpose was to extend the Job Demand-Resources Model (Schaufeli & Bakker, 2004) by including personal resources, job demands and job resources to predict burnout (exhaustion, cynicism, depersonalization) and work engagement (vigour and dedication). The sample comprised 274 teachers from 23 secondary schools of the Valencian Community (Spain). Hierarchical multiple regression analyses have revealed: (1) the predictor effect of quantitative overload on exhaustion and dedication at T2, (2) role conflict on cynicism and (3) role ambiguity on dedication. Lastly, the mediating role of burnout and engagement at T2. Practical implications and directions of future research are discussed.
Jung, Juergen
2013-01-01
We explore the determinants of inspection outcomes across 1.6 million Occupational Safety and Health Agency (OSHA) audits from 1990 through 2010. We find that discretion in enforcement differs in state and federally conducted inspections. State agencies are more sensitive to local economic conditions, finding fewer standard violations and fewer serious violations as unemployment increases. Larger companies receive greater lenience in multiple dimensions. Inspector issued fines and final fines, after negotiated reductions, are both smaller during Republican presidencies. Quantile regression analysis reveals that Presidential and Congressional party affiliations have their greatest impact on the largest negotiated reductions in fines. PMID:24659856
Mathad, Monali D; Rajesh, S K; Pradhan, Balaram
2017-12-06
The present study aimed to explore the correlates and predictors of spiritual well-being among nursing students. One hundred and forty-five BSc nursing students were recruited from three nursing colleges in Bangalore, Karnataka, India. Data were collected using SHALOM, FMI, SCS-SF and SWLS questionnaires and analysed by the Pearson correlation test and multiple regression analysis. The results of our study revealed a significant correlation between variables, and a considerable amount of variance was explained by self-compassion, mindfulness and satisfaction with life on personal, communal, environmental and transcendental domains of spiritual well-being.
Organizational Commitment and Nurses' Characteristics as Predictors of Job Involvement.
Alammar, Kamila; Alamrani, Mashael; Alqahtani, Sara; Ahmad, Muayyad
2016-01-01
To predict nurses' job involvement on the basis of their organizational commitment and personal characteristics at a large tertiary hospital in Saudi Arabia. Data were collected in 2015 from a convenience sample of 558 nurses working at a large tertiary hospital in Riyadh, Saudi Arabia. A cross-sectional correlational design was used in this study. Data were collected using a structured questionnaire. All commitment scales had significant relationships. Multiple linear regression analysis revealed that the model predicted a sizeable proportion of variance in nurses' job involvement (p < 0.001). High organizational commitment enhances job involvement, which may lead to more organizational stability and effectiveness.
Factors associated with active commuting to work among women.
Bopp, Melissa; Child, Stephanie; Campbell, Matthew
2014-01-01
Active commuting (AC), the act of walking or biking to work, has notable health benefits though rates of AC remain low among women. This study used a social-ecological framework to examine the factors associated with AC among women. A convenience sample of employed, working women (n = 709) completed an online survey about their mode of travel to work. Individual, interpersonal, institutional, community, and environmental influences were assessed. Basic descriptive statistics and frequencies described the sample. Simple logistic regression models examined associations with the independent variables with AC participation and multiple logistic regression analysis determined the relative influence of social ecological factors on AC participation. The sample was primarily middle-aged (44.09±11.38 years) and non-Hispanic White (92%). Univariate analyses revealed several individual, interpersonal, institutional, community and environmental factors significantly associated with AC. The multivariable logistic regression analysis results indicated that significant factors associated with AC included number of children, income, perceived behavioral control, coworker AC, coworker AC normative beliefs, employer and community supports for AC, and traffic. The results of this study contribute to the limited body of knowledge on AC participation for women and may help to inform gender-tailored interventions to enhance AC behavior and improve health.
Contributions of sociodemographic factors to criminal behavior
Mundia, Lawrence; Matzin, Rohani; Mahalle, Salwa; Hamid, Malai Hayati; Osman, Ratna Suriani
2016-01-01
We explored the extent to which prisoner sociodemographic variables (age, education, marital status, employment, and whether their parents were married or not) influenced offending in 64 randomly selected Brunei inmates, comprising both sexes. A quantitative field survey design ideal for the type of participants used in a prison context was employed to investigate the problem. Hierarchical multiple regression analysis with backward elimination identified prisoner marital status and age groups as significantly related to offending. Furthermore, hierarchical multinomial logistic regression analysis with backward elimination indicated that prisoners’ age, primary level education, marital status, employment status, and parental marital status as significantly related to stealing offenses with high odds ratios. All 29 nonrecidivists were false negatives and predicted to reoffend upon release. Similarly, all 33 recidivists were projected to reoffend after release. Hierarchical binary logistic regression analysis revealed age groups (24–29 years and 30–35 years), employed prisoner, and primary level education as variables with high likelihood trends for reoffending. The results suggested that prisoner interventions (educational, counseling, and psychotherapy) in Brunei should treat not only antisocial personality, psychopathy, and mental health problems but also sociodemographic factors. The study generated offending patterns, trends, and norms that may inform subsequent investigations on Brunei prisoners. PMID:27382342
Body Fat Percentage Prediction Using Intelligent Hybrid Approaches
Shao, Yuehjen E.
2014-01-01
Excess of body fat often leads to obesity. Obesity is typically associated with serious medical diseases, such as cancer, heart disease, and diabetes. Accordingly, knowing the body fat is an extremely important issue since it affects everyone's health. Although there are several ways to measure the body fat percentage (BFP), the accurate methods are often associated with hassle and/or high costs. Traditional single-stage approaches may use certain body measurements or explanatory variables to predict the BFP. Diverging from existing approaches, this study proposes new intelligent hybrid approaches to obtain fewer explanatory variables, and the proposed forecasting models are able to effectively predict the BFP. The proposed hybrid models consist of multiple regression (MR), artificial neural network (ANN), multivariate adaptive regression splines (MARS), and support vector regression (SVR) techniques. The first stage of the modeling includes the use of MR and MARS to obtain fewer but more important sets of explanatory variables. In the second stage, the remaining important variables are served as inputs for the other forecasting methods. A real dataset was used to demonstrate the development of the proposed hybrid models. The prediction results revealed that the proposed hybrid schemes outperformed the typical, single-stage forecasting models. PMID:24723804
Shatat, Ibrahim F; Abdallah, Rany T; Sas, David J; Hailpern, Susan M
2012-07-01
Despite being associated with multiple disease processes and cardiovascular outcomes, uric acid (UA) reference ranges for adolescents are lacking. We sought to describe the distribution of UA and its relationship to demographic, clinical, socioeconomic, and dietary factors among U.S. adolescents. A nationally representative subsample of 1,912 adolescents aged 13-18 years in NHANES 2005-2008 representing 19,888,299 adolescents was used for this study. Percentiles of the distribution of UA were estimated using quantile regression. Linear regression models examined the association of UA and demographic, socioeconomic, and dietary factors. Mean UA level was 5.14 ± 1.45 mg/dl. Mean UA increased with increasing age and was higher in non-Hispanic white race, male sex, higher body mass index (BMI) Z-score, and with higher systolic blood pressure. In fully adjusted linear regression models, sex, age, race, and BMI were independent determinants of higher UA. This study defines serum UA reference ranges for adolescents. Also, it reveals some intriguing relationships between UA and demographic and clinical characteristics that warrant further studies to examine the pathophysiological role of UA in different disease processes.
Ridge: a computer program for calculating ridge regression estimates
Donald E. Hilt; Donald W. Seegrist
1977-01-01
Least-squares coefficients for multiple-regression models may be unstable when the independent variables are highly correlated. Ridge regression is a biased estimation procedure that produces stable estimates of the coefficients. Ridge regression is discussed, and a computer program for calculating the ridge coefficients is presented.
Zhu, Xiang; Stephens, Matthew
2017-01-01
Bayesian methods for large-scale multiple regression provide attractive approaches to the analysis of genome-wide association studies (GWAS). For example, they can estimate heritability of complex traits, allowing for both polygenic and sparse models; and by incorporating external genomic data into the priors, they can increase power and yield new biological insights. However, these methods require access to individual genotypes and phenotypes, which are often not easily available. Here we provide a framework for performing these analyses without individual-level data. Specifically, we introduce a “Regression with Summary Statistics” (RSS) likelihood, which relates the multiple regression coefficients to univariate regression results that are often easily available. The RSS likelihood requires estimates of correlations among covariates (SNPs), which also can be obtained from public databases. We perform Bayesian multiple regression analysis by combining the RSS likelihood with previously proposed prior distributions, sampling posteriors by Markov chain Monte Carlo. In a wide range of simulations RSS performs similarly to analyses using the individual data, both for estimating heritability and detecting associations. We apply RSS to a GWAS of human height that contains 253,288 individuals typed at 1.06 million SNPs, for which analyses of individual-level data are practically impossible. Estimates of heritability (52%) are consistent with, but more precise, than previous results using subsets of these data. We also identify many previously unreported loci that show evidence for association with height in our analyses. Software is available at https://github.com/stephenslab/rss. PMID:29399241
NASA Astrophysics Data System (ADS)
Taştan Kırık, Özgecan
2013-12-01
This study explores the science teaching efficacy beliefs of pr-service elementary teachers and the relationship between efficacy beliefs and multiple factors such as antecedent factors (participation in extracurricular activities and number of science and science teaching methods courses taken), conceptual understanding, classroom management beliefs and science teaching attitudes. Science education majors ( n = 71) and elementary education majors ( n = 262) were compared with respect to these variables. Finally, the predictors of two constructs of science teaching efficacy beliefs, personal science teaching efficacy (PSTE) and science teaching outcome expectancy (STOE), were examined by multiple linear regression analysis. According to the results, participation in extracurricular activities has a significant but low correlation with science concept knowledge, science teaching attitudes, PSTE and STOE. In addition, there is a small but significant correlation between science concept knowledge and outcome expectancy, which leads the idea that preservice elementary teachers' conceptual understanding in science contributes to their science teaching self-efficacy. This study reveals a moderate correlation between science teaching attitudes and STOE and a high correlation between science teaching attitudes and PSTE. Additionally, although the correlation coefficient is low, the number of methodology courses was found to be one of the correlates of science teaching attitudes. Furthermore, students of both majors generally had positive self-efficacy beliefs on both the STOE and PSTE. Specifically, science education majors had higher science teaching self-efficacy than elementary education majors. Regression results showed that science teaching attitude is the major factor in predicting both PSTE and STOE for both groups.
Singh, Jagmahender; Pathak, R K; Chavali, Krishnadutt H
2011-03-20
Skeletal height estimation from regression analysis of eight sternal lengths in the subjects of Chandigarh zone of Northwest India is the topic of discussion in this study. Analysis of eight sternal lengths (length of manubrium, length of mesosternum, combined length of manubrium and mesosternum, total sternal length and first four intercostals lengths of mesosternum) measured from 252 male and 91 female sternums obtained at postmortems revealed that mean cadaver stature and sternal lengths were more in North Indians and males than the South Indians and females. Except intercostal lengths, all the sternal lengths were positively correlated with stature of the deceased in both sexes (P < 0.001). The multiple regression analysis of sternal lengths was found more useful than the linear regression for stature estimation. Using multivariate regression analysis, the combined length of manubrium and mesosternum in both sexes and the length of manubrium along with 2nd and 3rd intercostal lengths of mesosternum in males were selected as best estimators of stature. Nonetheless, the stature of males can be predicted with SEE of 6.66 (R(2) = 0.16, r = 0.318) from combination of MBL+BL_3+LM+BL_2, and in females from MBL only, it can be estimated with SEE of 6.65 (R(2) = 0.10, r = 0.318), whereas from the multiple regression analysis of pooled data, stature can be known with SEE of 6.97 (R(2) = 0.387, r = 575) from the combination of MBL+LM+BL_2+TSL+BL_3. The R(2) and F-ratio were found to be statistically significant for almost all the variables in both the sexes, except 4th intercostal length in males and 2nd to 4th intercostal lengths in females. The 'major' sternal lengths were more useful than the 'minor' ones for stature estimation The universal regression analysis used by Kanchan et al. [39] when applied to sternal lengths, gave satisfactory estimates of stature for males only but female stature was comparatively better estimated from simple linear regressions. But they are not proposed for the subjects of known sex, as they underestimate the male and overestimate female stature. However, intercostal lengths were found to be the poor estimators of stature (P < 0.05). And also sternal lengths exhibit weaker correlation coefficients and higher standard errors of estimate. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
Oligoclonal bands predict multiple sclerosis in children with optic neuritis.
Heussinger, Nicole; Kontopantelis, Evangelos; Gburek-Augustat, Janina; Jenke, Andreas; Vollrath, Gesa; Korinthenberg, Rudolf; Hofstetter, Peter; Meyer, Sascha; Brecht, Isabel; Kornek, Barbara; Herkenrath, Peter; Schimmel, Mareike; Wenner, Kirsten; Häusler, Martin; Lutz, Soeren; Karenfort, Michael; Blaschek, Astrid; Smitka, Martin; Karch, Stephanie; Piepkorn, Martin; Rostasy, Kevin; Lücke, Thomas; Weber, Peter; Trollmann, Regina; Klepper, Jörg; Häussler, Martin; Hofmann, Regina; Weissert, Robert; Merkenschlager, Andreas; Buttmann, Mathias
2015-06-01
We retrospectively evaluated predictors of conversion to multiple sclerosis (MS) in 357 children with isolated optic neuritis (ON) as a first demyelinating event who had a median follow-up of 4.0 years. Multiple Cox proportional-hazards regressions revealed abnormal cranial magnet resonance imaging (cMRI; hazard ratio [HR] = 5.94, 95% confidence interval [CI] = 3.39-10.39, p < 0.001), presence of cerebrospinal fluid immunoglobulin G oligoclonal bands (OCB; HR = 3.69, 95% CI = 2.32-5.86, p < 0.001), and age (HR = 1.08 per year of age, 95% CI = 1.02-1.13, p = 0.003) as independent predictors of conversion, whereas sex and laterality (unilateral vs bilateral) had no influence. Combined cMRI and OCB positivity indicated a 26.84-fold higher HR for developing MS compared to double negativity (95% CI = 12.26-58.74, p < 0.001). Accordingly, cerebrospinal fluid analysis may supplement cMRI to determine the risk of MS in children with isolated ON. © 2015 American Neurological Association.
Chambers, Brian; Chambers, Jayne; Churilov, Leonid; Cameron, Heather; Macdonell, Richard
2014-09-01
We evaluated internal jugular vein and vertebral vein volume flow using ultrasound, in patients with clinically isolated syndrome or mild multiple sclerosis and controls, to determine whether volume flow was different between the two groups. In patients and controls, internal jugular vein volume flow increased from superior to inferior segments, consistent with recruitment from collateral veins. Internal jugular vein and vertebral vein volume flow were greater on the right in supine and sitting positions. Internal jugular vein volume flow was higher in the supine posture. Vertebral vein volume flow was higher in the sitting posture. Regression analyses of cube root transformed volume flow data, adjusted for supine/sitting, right/left and internal jugular vein/vertebral vein, revealed no significant difference in volume flow in patients compared to controls. Our findings further refute the concept of venous obstruction as a causal factor in the pathogenesis of multiple sclerosis. Control volume flow data may provide useful normative reference values. © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.
Fueglistaler, Philipp; Amsler, Felix; Schüepp, Marcel; Fueglistaler-Montali, Ida; Attenberger, Corinna; Pargger, Hans; Jacob, Augustinus Ludwig; Gross, Thomas
2010-08-01
Prospective data regarding the prognostic value of the Sequential Organ Failure Assessment (SOFA) score in comparison with the Simplified Acute Physiology Score (SAPS II) and trauma scores on the outcome of multiple-trauma patients are lacking. Single-center evaluation (n = 237, Injury Severity Score [ISS] >16; mean ISS = 29). Uni- and multivariate analysis of SAPS II, SOFA, revised trauma, polytrauma, and trauma and ISS scores (TRISS) was performed. The 30-day mortality was 22.8% (n = 54). SOFA day 1 was significantly higher in nonsurvivors compared with survivors (P < .001) and correlated well with the length of intensive care unit stay (r = .50, P < .001). Logistic regression revealed SAPS II to have the best predictive value of 30-day mortality (area under the receiver operating characteristic = .86 +/- .03). The SOFA score significantly added prognostic information with regard to mortality to both SAPS II and TRISS. The combination of critically ill and trauma scores may increase the accuracy of mortality prediction in multiple-trauma patients. 2010 Elsevier Inc. All rights reserved.
Neuropsychological and structural brain lesions in multiple sclerosis: a regional analysis.
Swirsky-Sacchetti, T; Mitchell, D R; Seward, J; Gonzales, C; Lublin, F; Knobler, R; Field, H L
1992-07-01
Quantified lesion scores derived from MRI correlate significantly with neuropsychological testing in patients with multiple sclerosis (MS). Variables used to reflect disease severity include total lesion area (TLA), ventricular-brain ratio, and size of the corpus callosum. We used these general measures of cerebral lesion involvement as well as specific ratings of lesion involvement by frontal, temporal, and parieto-occipital regions to quantify the topographic distribution of lesions and consequent effects upon cognitive function. Lesions were heavily distributed in the parieto-occipital regions bilaterally. Neuropsychological tests were highly related to all generalized measures of cerebral involvement, with TLA being the best predictor of neuropsychological deficit. Mean TLA for the cognitively impaired group was 28.30 cm2 versus 7.41 cm2 for the cognitively intact group (p less than 0.0001). Multiple regression analyses revealed that left frontal lobe involvement best predicted impaired abstract problem solving, memory, and word fluency. Left parieto-occipital lesion involvement best predicted deficits in verbal learning and complex visual-integrative skills. Analysis of regional cerebral lesion load may assist in understanding the particular pattern and course of cognitive deficits in MS.
Recent Northern Hemisphere snow cover extent trends and implications for the snow-albedo feedback
NASA Astrophysics Data System (ADS)
Déry, Stephen J.; Brown, Ross D.
2007-11-01
Monotonic trend analysis of Northern Hemisphere snow cover extent (SCE) over the period 1972-2006 with the Mann-Kendall test reveals significant declines in SCE during spring over North America and Eurasia, with lesser declines during winter and some increases in fall SCE. The weekly mean trend attains -1.28, -0.78, and -0.48 × 106 km2 (35 years)-1 over the Northern Hemisphere, North America, and Eurasia, respectively. The standardized SCE time series vary and trend coherently over Eurasia and North America, with evidence of a poleward amplification of decreasing SCE trends during spring. Multiple linear regression analyses reveal a significant dependence of the retreat of the spring continental SCE on latitude and elevation. The poleward amplification is consistent with an enhanced snow-albedo feedback over northern latitudes that acts to reinforce an initial anomaly in the cryospheric system.
Sawada, Kazuhiko; Saito, Shigeyoshi; Horiuchi-Hirose, Miwa; Mori, Yuki; Yoshioka, Yoshichika; Murase, Kenya
2013-09-01
Cerebellar abnormalities in 4-week-old rats with a single whole body X-irradiation at a dose of 0.5, 1.0, or 1.5 Gy on embryonic day (ED) 15 were examined by magnetic resonance imaging (MRI) volumetry. A 3D T2 W-MRI anatomical sequence with high-spatial resolution at 11.7-tesla was acquired from the fixed rat heads. By MRI volumetry, whole cerebellar volumes decreased dose-dependently. Multiple linear regression analysis revealed that the cortical volume (standardized β=0.901; P<0.001) was a major explanatory variable for the whole cerebellar volume, whereas both volumes of the white matter and deep cerebellar nuclei also decreased depending on the X-irradiation dose. The present MRI volumetric analysis revealed a dose-related cerebellar cortical hypoplasia by prenatal exposure to X-irradiation on E15. © 2013 The Authors. Congenital Anomalies © 2013 Japanese Teratology Society.
Quijada-Morín, Natalia; Williams, Pascale; Rivas-Gonzalo, Julián C; Doco, Thierry; Escribano-Bailón, M Teresa
2014-07-01
The influence of the proanthocyanidic, polysaccharide and oligosaccharide composition on astringency perception of Tempranillo wines has been evaluated. Statistical analyses revealed the existence of relationships between chemical composition and perceived astringency. Proanthocyanidic subunit distribution had the strongest contribution to the multiple linear regression (MLR) model. Polysaccharide families showed clear opposition to astringency perception according to principal component analysis (PCA) results, being stronger for mannoproteins and rhamnogalacturonan-II (RG-II), but only Polysaccharides Rich in Arabinose and Galactose (PRAGs) were considered in the final fitted MLR model, which explained 96.8% of the variability observed in the data. Oligosaccharides did not show a clear opposition, revealing that structure and size of carbohydrates are important for astringency perception. Mannose and galactose residues in the oligosaccharide fraction are positively related to astringency perception, probably because its presence is consequence of the degradation of polysaccharides. Copyright © 2014 Elsevier Ltd. All rights reserved.
Poliosis circumscripta unmasking a scalp melanoma.
Yeo, L; Husain, E; Rajpara, S
2015-12-01
A 28-year-old man presented with a 1-year history of a localized patch of grey hair and an underlying darkly pigmented lesion on his right occipital area. Clinical appearance revealed poliosis overlying an asymmetrical plaque with variable degrees of brown pigmentation and white discolouration. Owing to the suspicious nature of the lesion, excision with a 2 mm margin was performed. Histology revealed an invasive melanoma with extensive regression and prominent involvement of multiple hair follicles. Scalp melanoma with associated poliosis is extremely rare, and has only been reported once in the literature to date. There have been two reports in the opthalmology literature regarding eyelash poliosis associated with orbital melanoma. The pathogenesis of poliosis still remains unclear. This is the second reported case of poliosis circmscripta unmasking a scalp melanoma, and highlights the importance of being vigilant when examining patients with poliosis of the scalp. © 2014 British Association of Dermatologists.
The physical, behavioral, and psychosocial consequences of Internet use in college students.
Clark, Deborah J; Frith, Karen H; Demi, Alice S
2004-01-01
The purposes of this study were to identify the physical, behavioral, and psychosocial consequences of Internet use in undergraduate college students; and to evaluate whether time, social norms, and adopter category predict the consequences of Internet use. Rogers' model for studying consequences of innovation was adapted for this study. A descriptive, correlational design was used. Convenience sampling yielded 293 undergraduate students who answered the online survey. Consequences of Internet use were assessed with the researcher-developed instrument, the Internet Consequences Scale (ICONS). Mean scores on the behavioral and psychosocial subscales of the ICONS indicated positive consequences of Internet use, while the physical consequences subscale revealed negative consequences. Multiple regression analyses revealed a small, but significant, amount of variance in consequences of Internet use that could be explained by time, social norms, and adopter category, thus supporting the adapted model for the study of consequences of Internet use in college students.
Early, Jody; Armstrong, Shelley Nicole; Burke, Sloane; Thompson, Doris Lee
2011-01-01
This study examined female college students' knowledge, attitudes, and breast cancer screening and determined significant predictors of breast self-examination, clinical breast examination, and mammography among this population. A convenience sample of 1,074 college women from 3 universities participated in the research. Respondents completed an online version of the Toronto Breast Self-examination Instrument as well as questions developed by the authors. Descriptive statistics showed gaps in college women's knowledge of breast health and negative attitudes toward screening that were relative to age. Multiple linear and logistic regression analyses revealed that knowledge, attitudes, and copay were significant predictors of screening, whereas family history and ethnicity were not. This study supported previous smaller-sample studies that showed college women to be a priority population for breast health education and revealed new significant factors that should be addressed in health education for this group.
Desire thinking as a predictor of gambling.
Fernie, Bruce A; Caselli, Gabriele; Giustina, Lucia; Donato, Gilda; Marcotriggiani, Antonella; Spada, Marcantonio M
2014-04-01
Desire thinking is a voluntary cognitive process involving verbal and imaginal elaboration of a desired target. A desired target can relate to an object, an internal state or an activity, such as gambling. This study investigated the role of desire thinking in gambling in a cohort of participants recruited from community and clinical settings. Ninety five individuals completed a battery of self-report measures consisting of the Hospital Anxiety and Depression Scale (HADS), the Gambling Craving Scale (GCS), the Desire Thinking Questionnaire (DTQ) and the South Oaks Gambling Screen (SOGS). Correlation analyses revealed that gender, educational level, recruitment source, anxiety and depression, craving and desire thinking were correlated with gambling. A hierarchical multiple regression analysis revealed that both recruitment source and desire thinking were the only independent predictors of gambling when controlling for all other study variables, including craving. These findings are discussed in the light of metacognitive therapy (MCT). Copyright © 2014 Elsevier Ltd. All rights reserved.
Socioscientific Argumentation: The effects of content knowledge and morality
NASA Astrophysics Data System (ADS)
Sadler, Troy D.; Donnelly, Lisa A.
2006-10-01
Broad support exists within the science education community for the incorporation of socioscientific issues (SSI) and argumentation in the science curriculum. This study investigates how content knowledge and morality contribute to the quality of SSI argumentation among high school students. We employed a mixed-methods approach: 56 participants completed tests of content knowledge and moral reasoning as well as interviews, related to SSI topics, which were scored based on a rubric for argumentation quality. Multiple regression analyses revealed no statistically significant relationships among content knowledge, moral reasoning, and argumentation quality. Qualitative analyses of the interview transcripts supported the quantitative results in that participants very infrequently revealed patterns of content knowledge application. However, most of the participants did perceive the SSI as moral problems. We propose a “Threshold Model of Knowledge Transfer” to account for the relationship between content knowledge and argumentation quality. Implications for science education are discussed.
ERIC Educational Resources Information Center
Porter, Kristin E.; Reardon, Sean F.; Unlu, Fatih; Bloom, Howard S.; Robinson-Cimpian, Joseph P.
2014-01-01
A valuable extension of the single-rating regression discontinuity design (RDD) is a multiple-rating RDD (MRRDD). To date, four main methods have been used to estimate average treatment effects at the multiple treatment frontiers of an MRRDD: the "surface" method, the "frontier" method, the "binding-score" method, and…
ERIC Educational Resources Information Center
Hafner, Lawrence E.
A study developed a multiple regression prediction equation for each of six selected achievement variables in a popular standardized test of achievement. Subjects, 42 fourth-grade pupils randomly selected across several classes in a large elementary school in a north Florida city, were administered several standardized tests to determine predictor…
ERIC Educational Resources Information Center
Muller, Veronica; Brooks, Jessica; Tu, Wei-Mo; Moser, Erin; Lo, Chu-Ling; Chan, Fong
2015-01-01
Purpose: The main objective of this study was to determine the extent to which physical and cognitive-affective factors are associated with fibromyalgia (FM) fatigue. Method: A quantitative descriptive design using correlation techniques and multiple regression analysis. The participants consisted of 302 members of the National Fibromyalgia &…
ERIC Educational Resources Information Center
Choi, Kilchan
2011-01-01
This report explores a new latent variable regression 4-level hierarchical model for monitoring school performance over time using multisite multiple-cohorts longitudinal data. This kind of data set has a 4-level hierarchical structure: time-series observation nested within students who are nested within different cohorts of students. These…
ERIC Educational Resources Information Center
Richter, Tobias
2006-01-01
Most reading time studies using naturalistic texts yield data sets characterized by a multilevel structure: Sentences (sentence level) are nested within persons (person level). In contrast to analysis of variance and multiple regression techniques, hierarchical linear models take the multilevel structure of reading time data into account. They…
Some Applied Research Concerns Using Multiple Linear Regression Analysis.
ERIC Educational Resources Information Center
Newman, Isadore; Fraas, John W.
The intention of this paper is to provide an overall reference on how a researcher can apply multiple linear regression in order to utilize the advantages that it has to offer. The advantages and some concerns expressed about the technique are examined. A number of practical ways by which researchers can deal with such concerns as…
A Spreadsheet Tool for Learning the Multiple Regression F-Test, T-Tests, and Multicollinearity
ERIC Educational Resources Information Center
Martin, David
2008-01-01
This note presents a spreadsheet tool that allows teachers the opportunity to guide students towards answering on their own questions related to the multiple regression F-test, the t-tests, and multicollinearity. The note demonstrates approaches for using the spreadsheet that might be appropriate for three different levels of statistics classes,…
ERIC Educational Resources Information Center
Anderson, Joan L.
2006-01-01
Data from graduate student applications at a large Western university were used to determine which factors were the best predictors of success in graduate school, as defined by cumulative graduate grade point average. Two statistical models were employed and compared: artificial neural networking and simultaneous multiple regression. Both models…
ERIC Educational Resources Information Center
Preacher, Kristopher J.; Curran, Patrick J.; Bauer, Daniel J.
2006-01-01
Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests and plotting the…
Regression Models for the Analysis of Longitudinal Gaussian Data from Multiple Sources
O’Brien, Liam M.; Fitzmaurice, Garrett M.
2006-01-01
We present a regression model for the joint analysis of longitudinal multiple source Gaussian data. Longitudinal multiple source data arise when repeated measurements are taken from two or more sources, and each source provides a measure of the same underlying variable and on the same scale. This type of data generally produces a relatively large number of observations per subject; thus estimation of an unstructured covariance matrix often may not be possible. We consider two methods by which parsimonious models for the covariance can be obtained for longitudinal multiple source data. The methods are illustrated with an example of multiple informant data arising from a longitudinal interventional trial in psychiatry. PMID:15726666
Interpretation of commonly used statistical regression models.
Kasza, Jessica; Wolfe, Rory
2014-01-01
A review of some regression models commonly used in respiratory health applications is provided in this article. Simple linear regression, multiple linear regression, logistic regression and ordinal logistic regression are considered. The focus of this article is on the interpretation of the regression coefficients of each model, which are illustrated through the application of these models to a respiratory health research study. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.
Applied Multiple Linear Regression: A General Research Strategy
ERIC Educational Resources Information Center
Smith, Brandon B.
1969-01-01
Illustrates some of the basic concepts and procedures for using regression analysis in experimental design, analysis of variance, analysis of covariance, and curvilinear regression. Applications to evaluation of instruction and vocational education programs are illustrated. (GR)
Gambling disorder-related illegal acts: Regression model of associated factors
Gorsane, Mohamed Ali; Reynaud, Michel; Vénisse, Jean-Luc; Legauffre, Cindy; Valleur, Marc; Magalon, David; Fatséas, Mélina; Chéreau-Boudet, Isabelle; Guilleux, Alice; JEU Group; Challet-Bouju, Gaëlle; Grall-Bronnec, Marie
2017-01-01
Background and aims Gambling disorder-related illegal acts (GDRIA) are often crucial events for gamblers and/or their entourage. This study was designed to determine the predictive factors of GDRIA. Methods Participants were 372 gamblers reporting at least three DSM-IV-TR (American Psychiatric Association, 2000) criteria. They were assessed on the basis of sociodemographic characteristics, gambling-related characteristics, their personality profile, and psychiatric comorbidities. A multiple logistic regression was performed to identify the relevant predictors of GDRIA and their relative contribution to the prediction of the presence of GDRIA. Results Multivariate analysis revealed a higher South Oaks Gambling Scale score, comorbid addictive disorders, and a lower level of income as GDRIA predictors. Discussion and conclusion An original finding of this study was that the comorbid addictive disorder effect might be mediated by a disinhibiting effect of stimulant substances on GDRIA. Further studies are necessary to replicate these results, especially in a longitudinal design, and to explore specific therapeutic interventions. PMID:28198636
Gambling disorder-related illegal acts: Regression model of associated factors.
Gorsane, Mohamed Ali; Reynaud, Michel; Vénisse, Jean-Luc; Legauffre, Cindy; Valleur, Marc; Magalon, David; Fatséas, Mélina; Chéreau-Boudet, Isabelle; Guilleux, Alice; Challet-Bouju, Gaëlle; Grall-Bronnec, Marie
2017-03-01
Background and aims Gambling disorder-related illegal acts (GDRIA) are often crucial events for gamblers and/or their entourage. This study was designed to determine the predictive factors of GDRIA. Methods Participants were 372 gamblers reporting at least three DSM-IV-TR (American Psychiatric Association, 2000) criteria. They were assessed on the basis of sociodemographic characteristics, gambling-related characteristics, their personality profile, and psychiatric comorbidities. A multiple logistic regression was performed to identify the relevant predictors of GDRIA and their relative contribution to the prediction of the presence of GDRIA. Results Multivariate analysis revealed a higher South Oaks Gambling Scale score, comorbid addictive disorders, and a lower level of income as GDRIA predictors. Discussion and conclusion An original finding of this study was that the comorbid addictive disorder effect might be mediated by a disinhibiting effect of stimulant substances on GDRIA. Further studies are necessary to replicate these results, especially in a longitudinal design, and to explore specific therapeutic interventions.
Wang, Xing-Chen; Li, Ai-Hua; Dizy, Marta; Ullah, Niamat; Sun, Wei-Xuan; Tao, Yong-Sheng
2017-08-01
To improve the aroma profile of Ecolly dry white wine, the simultaneous and sequential inoculations of selected Rhodotorula mucilaginosa and Saccharomyces cerevisiae were performed in wine making of this work. The two yeasts were mixed in various ratios for making the mixed inoculum. The amount of volatiles and aroma characteristics were determined the following year. Mixed fermentation improved both the varietal and fermentative aroma compound composition, especially that of (Z)-3-hexene-1-ol, nerol oxide, certain acetates and ethyls group compounds. Citrus, sweet fruit, acid fruit, berry, and floral aroma traits were enhanced by mixed fermentation; however, an animal note was introduced upon using higher amounts of R. mucilaginosa. Aroma traits were regressed with volatiles as observed by the partial least-square regression method. Analysis of correlation coefficients revealed that the aroma traits were the multiple interactions of volatile compounds, with the fermentative volatiles having more impact on aroma than varietal compounds. Copyright © 2017 Elsevier Ltd. All rights reserved.
Population heterogeneity in the salience of multiple risk factors for adolescent delinquency.
Lanza, Stephanie T; Cooper, Brittany R; Bray, Bethany C
2014-03-01
To present mixture regression analysis as an alternative to more standard regression analysis for predicting adolescent delinquency. We demonstrate how mixture regression analysis allows for the identification of population subgroups defined by the salience of multiple risk factors. We identified population subgroups (i.e., latent classes) of individuals based on their coefficients in a regression model predicting adolescent delinquency from eight previously established risk indices drawn from the community, school, family, peer, and individual levels. The study included N = 37,763 10th-grade adolescents who participated in the Communities That Care Youth Survey. Standard, zero-inflated, and mixture Poisson and negative binomial regression models were considered. Standard and mixture negative binomial regression models were selected as optimal. The five-class regression model was interpreted based on the class-specific regression coefficients, indicating that risk factors had varying salience across classes of adolescents. Standard regression showed that all risk factors were significantly associated with delinquency. Mixture regression provided more nuanced information, suggesting a unique set of risk factors that were salient for different subgroups of adolescents. Implications for the design of subgroup-specific interventions are discussed. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Jones, William I.
This study examined the understanding of nature of science among participants in their final year of a 4-year undergraduate teacher education program at a Midwest liberal arts university. The Logic Model Process was used as an integrative framework to focus the collection, organization, analysis, and interpretation of the data for the purpose of (1) describing participant understanding of NOS and (2) to identify participant characteristics and teacher education program features related to those understandings. The Views of Nature of Science Questionnaire form C (VNOS-C) was used to survey participant understanding of 7 target aspects of Nature of Science (NOS). A rubric was developed from a review of the literature to categorize and score participant understanding of the target aspects of NOS. Participants' high school and college transcripts, planning guides for their respective teacher education program majors, and science content and science teaching methods course syllabi were examined to identify and categorize participant characteristics and teacher education program features. The R software (R Project for Statistical Computing, 2010) was used to conduct an exploratory analysis to determine correlations of the antecedent and transaction predictor variables with participants' scores on the 7 target aspects of NOS. Fourteen participant characteristics and teacher education program features were moderately and significantly ( p < .01) correlated with participant scores on the target aspects of NOS. The 6 antecedent predictor variables were entered into multiple regression analyses to determine the best-fit model of antecedent predictor variables for each target NOS aspect. The transaction predictor variables were entered into separate multiple regression analyses to determine the best-fit model of transaction predictor variables for each target NOS aspect. Variables from the best-fit antecedent and best-fit transaction models for each target aspect of NOS were then combined. A regression analysis for each of the combined models was conducted to determine the relative effect of these variables on the target aspects of NOS. Findings from the multiple regression analyses revealed that each of the fourteen predictor variables was present in the best-fit model for at least 1 of the 7 target aspects of NOS. However, not all of the predictor variables were statistically significant (p < .007) in the models and their effect (beta) varied. Participants in the teacher education program who had higher ACT Math scores, completed more high school science credits, and were enrolled either in the Middle Childhood with a science concentration program major or in the Adolescent/Young Adult Science Education program major were more likely to have an informed understanding on each of the 7 target aspects of NOS. Analyses of the planning guides and the course syllabi in each teacher education program major revealed differences between the program majors that may account for the results.
ERIC Educational Resources Information Center
Porter, Kristin E.; Reardon, Sean F.; Unlu, Fatih; Bloom, Howard S.; Cimpian, Joseph R.
2017-01-01
A valuable extension of the single-rating regression discontinuity design (RDD) is a multiple-rating RDD (MRRDD). To date, four main methods have been used to estimate average treatment effects at the multiple treatment frontiers of an MRRDD: the "surface" method, the "frontier" method, the "binding-score" method, and…
ERIC Educational Resources Information Center
Woolley, Kristin K.
Many researchers are unfamiliar with suppressor variables and how they operate in multiple regression analyses. This paper describes the role suppressor variables play in a multiple regression model and provides practical examples that explain how they can change research results. A variable that when added as another predictor increases the total…
ERIC Educational Resources Information Center
Martz, Erin
2004-01-01
Because the onset of a spinal cord injury may involve a brush with death and because serious injury and disability can act as a reminder of death, death anxiety was examined as a predictor of posttraumatic stress levels among individuals with disabilities. This cross-sectional study used multiple regression and multivariate multiple regression to…
McClelland, Gary H; Irwin, Julie R; Disatnik, David; Sivan, Liron
2017-02-01
Multicollinearity is irrelevant to the search for moderator variables, contrary to the implications of Iacobucci, Schneider, Popovich, and Bakamitsos (Behavior Research Methods, 2016, this issue). Multicollinearity is like the red herring in a mystery novel that distracts the statistical detective from the pursuit of a true moderator relationship. We show multicollinearity is completely irrelevant for tests of moderator variables. Furthermore, readers of Iacobucci et al. might be confused by a number of their errors. We note those errors, but more positively, we describe a variety of methods researchers might use to test and interpret their moderated multiple regression models, including two-stage testing, mean-centering, spotlighting, orthogonalizing, and floodlighting without regard to putative issues of multicollinearity. We cite a number of recent studies in the psychological literature in which the researchers used these methods appropriately to test, to interpret, and to report their moderated multiple regression models. We conclude with a set of recommendations for the analysis and reporting of moderated multiple regression that should help researchers better understand their models and facilitate generalizations across studies.
Luck, Tobias; Pabst, Alexander; Rodriguez, Francisca S; Schroeter, Matthias L; Witte, Veronica; Hinz, Andreas; Mehnert, Anja; Engel, Christoph; Loeffler, Markus; Thiery, Joachim; Villringer, Arno; Riedel-Heller, Steffi G
2018-05-01
To provide new age-, sex-, and education-specific reference values for an extended version of the well-established Consortium to Establish a Registry for Alzheimer's Disease Neuropsychological Assessment Battery (CERAD-NAB) that additionally includes the Trail Making Test and the Verbal Fluency Test-S-Words. Norms were calculated based on the cognitive performances of n = 1,888 dementia-free participants (60-79 years) from the population-based German LIFE-Adult-Study. Multiple regressions were used to examine the association of the CERAD-NAB scores with age, sex, and education. In order to calculate the norms, quantile and censored quantile regression analyses were performed estimating marginal means of the test scores at 2.28, 6.68, 10, 15.87, 25, 50, 75, and 90 percentiles for age-, sex-, and education-specific subgroups. Multiple regression analyses revealed that younger age was significantly associated with better cognitive performance in 15 CERAD-NAB measures and higher education with better cognitive performance in all 17 measures. Women performed significantly better than men in 12 measures and men than women in four measures. The determined norms indicate ceiling effects for the cognitive performances in the Boston Naming, Word List Recognition, Constructional Praxis Copying, and Constructional Praxis Recall tests. The new norms for the extended CERAD-NAB will be useful for evaluating dementia-free German-speaking adults in a broad variety of relevant cognitive domains. The extended CERAD-NAB follows more closely the criteria for the new DSM-5 Mild and Major Neurocognitive Disorder. Additionally, it could be further developed to include a test for social cognition. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Eyvazlou, Meysam; Zarei, Esmaeil; Rahimi, Azin; Abazari, Malek
2016-01-01
Concerns about health problems due to the increasing use of mobile phones are growing. Excessive use of mobile phones can affect the quality of sleep as one of the important issues in the health literature and general health of people. Therefore, this study investigated the relationship between the excessive use of mobile phones and general health and quality of sleep on 450 Occupational Health and Safety (OH&S) students in five universities of medical sciences in the North East of Iran in 2014. To achieve this objective, special questionnaires that included Cell Phone Overuse Scale, Pittsburgh's Sleep Quality Index (PSQI) and General Health Questionnaire (GHQ) were used, respectively. In addition to descriptive statistical methods, independent t-test, Pearson correlation, analysis of variance (ANOVA) and multiple regression tests were performed. The results revealed that half of the students had a poor level of sleep quality and most of them were considered unhealthy. The Pearson correlation co-efficient indicated a significant association between the excessive use of mobile phones and the total score of general health and the quality of sleep. In addition, the results of the multiple regression showed that the excessive use of mobile phones has a significant relationship between each of the four subscales of general health and the quality of sleep. Furthermore, the results of the multivariate regression indicated that the quality of sleep has a simultaneous effect on each of the four scales of the general health. Overall, a simultaneous study of the effects of the mobile phones on the quality of sleep and the general health could be considered as a trigger to employ some intervention programs to improve their general health status, quality of sleep and consequently educational performance.
Fafouti, M; Paparrigopoulos, T; Zervas, Y; Rabavilas, A; Malamos, N; Liappas, I; Tzavara, C
2010-01-01
A significant proportion of breast cancer patients experience psychiatric morbidity. The present study compared the psychopathological profile (depression, anxiety and general psychopathology) of Greek women with breast cancer with a group of healthy controls. Patients (n=109) were recruited from a specialized oncology breast cancer department and healthy controls (n=71) from a breast outpatient clinic. General psychopathology was assessed by the SCL-90-R. The Montgomery-Asberg Depression Rating Scale (MADRS) and the Spielberger State-Trait Anxiety Inventory (STAI) were used for assessing depression and anxiety. Demographics and clinical characteristics were also recorded. Data were modeled using multiple regression analysis. The mean age was 54.7±18.1 years for the control group and 51.2±9.5 years for the patient group (p=0.288). Mean scores on SCL-90-R, MADRS and STAI were significantly higher in the cancer group compared to controls (p<0.05). Multiple regression analysis revealed that breast cancer was independently and positively associated with all psychological measures (p<0.05). Regression coefficients ranged from 0.19 (SCL-90-R, psychotism) to 0.33 (MADRS). Lower anger/aggressiveness and anxiety were found in highly educated women; divorced/widowed women scored higher on obsessionality and MADRS compared to married women. Psychiatric treatment was associated with higher scores on somatization, depression, phobic anxiety and general psychopathology. Anxiety, depression, and overall psychopathology are more frequent in breast cancer patients compared to controls. Disease makes a larger independent contribution to all psychopathological measures than any other investigated variable. Therefore, breast cancer patients should be closely followed up in order to identify and timely treat any mental health problems that may arise.
Mukerjee, Shaibal; Smith, Luther A; Johnson, Mary M; Neas, Lucas M; Stallings, Casson A
2009-08-01
Passive ambient air sampling for nitrogen dioxide (NO(2)) and volatile organic compounds (VOCs) was conducted at 25 school and two compliance sites in Detroit and Dearborn, Michigan, USA during the summer of 2005. Geographic Information System (GIS) data were calculated at each of 116 schools. The 25 selected schools were monitored to assess and model intra-urban gradients of air pollutants to evaluate impact of traffic and urban emissions on pollutant levels. Schools were chosen to be statistically representative of urban land use variables such as distance to major roadways, traffic intensity around the schools, distance to nearest point sources, population density, and distance to nearest border crossing. Two approaches were used to investigate spatial variability. First, Kruskal-Wallis analyses and pairwise comparisons on data from the schools examined coarse spatial differences based on city section and distance from heavily trafficked roads. Secondly, spatial variation on a finer scale and as a response to multiple factors was evaluated through land use regression (LUR) models via multiple linear regression. For weeklong exposures, VOCs did not exhibit spatial variability by city section or distance from major roads; NO(2) was significantly elevated in a section dominated by traffic and industrial influence versus a residential section. Somewhat in contrast to coarse spatial analyses, LUR results revealed spatial gradients in NO(2) and selected VOCs across the area. The process used to select spatially representative sites for air sampling and the results of coarse and fine spatial variability of air pollutants provide insights that may guide future air quality studies in assessing intra-urban gradients.
Schoeler, Tabea; Theobald, Delphine; Pingault, Jean-Baptiste; Farrington, David P; Coid, Jeremy W; Bhattacharyya, Sagnik
2018-04-02
Evidence regarding the association between cannabis use and depression remain conflicting, especially as studies have not typically adopted a longitudinal design with a follow-up period that was long enough to adequately cover the risk period for onset of depression. Males from the Cambridge Study in Delinquent Development (CSDD) (N = 285) were assessed seven times from age 8 to 48 years to prospectively investigate the association between cannabis use and risk of major depressive disorder (MDD). A combination of multiple analyses (logistic regression, Cox regression, fixed-effects analysis) was employed to explore the strength and direction of effect within different developmental stages. Multiple regression analyses revealed that early-onset cannabis use (before age 18) but not late-onset cannabis use (after age 27) was associated with a higher risk and shorter time until a subsequent MDD diagnosis. This effect was present in high-frequency [(odds ratio (OR) 8.83, 95% confidence interval (CI) 1.29-70.79]; [hazard ratio (HR) 8.69, 95% CI 2.07-36.52)] and low-frequency early-onset users (OR 2.41, 95% CI 1.22-4.76; HR 2.09, 95% CI 1.16-3.74). Effect of increased frequency of cannabis use on increased risk of subsequent MDD was observed only for use during adolescence (age 14-18) but not at later life stages, while controlling for observed and non-unobserved time-invariant factors. Conversely, MDD in adulthood (age 18-32) was linked to a reduction in subsequent cannabis use (age 32-48). The present findings provide evidence implicating frequent cannabis use during adolescence as a risk factor for later life depression. Future studies should further examine causality of effects in larger samples.
Fu, Chang; Li, Zhen; Mao, Zongfu
2018-01-30
Participation in social activities is one of important factors for older adults' health. The present study aims to examine the cross-sectional association between social activities and cognitive function among Chinese elderly. A total of 8966 individuals aged 60 and older from the 2015 China Health and Retirement Longitudinal Study were obtained for this study. Telephone interviews of cognitive status, episodic memory, and visuospatial abilities were assessed by questionnaire. We used the sum of all three of the above measures to represent the respondent's cognitive status as a whole. Types and frequencies of participation in social groups were used to measure social activities. Multiple linear regression analysis was used to explore the relationship between social activities and cognitive function. After adjustment for demographics, smoking, drinking, depression, hypertension, diabetes, basic activities of daily living, instrumental activities of daily living, and self-rated health, multiple linear regression analysis revealed that interaction with friends, participating in hobby groups, and sports groups were associated with better cognitive function among both men and women ( p < 0.05); doing volunteer work was associated with better cognitive function among women but not among men ( p < 0.05). These findings suggest that there is a cross-sectional association between participation in social activities and cognitive function among Chinese elderly. Longitudinal studies are needed to examine the effects of social activities on cognitive function.
Fu, Chang; Li, Zhen; Mao, Zongfu
2018-01-01
Participation in social activities is one of important factors for older adults’ health. The present study aims to examine the cross-sectional association between social activities and cognitive function among Chinese elderly. A total of 8966 individuals aged 60 and older from the 2015 China Health and Retirement Longitudinal Study were obtained for this study. Telephone interviews of cognitive status, episodic memory, and visuospatial abilities were assessed by questionnaire. We used the sum of all three of the above measures to represent the respondent’s cognitive status as a whole. Types and frequencies of participation in social groups were used to measure social activities. Multiple linear regression analysis was used to explore the relationship between social activities and cognitive function. After adjustment for demographics, smoking, drinking, depression, hypertension, diabetes, basic activities of daily living, instrumental activities of daily living, and self-rated health, multiple linear regression analysis revealed that interaction with friends, participating in hobby groups, and sports groups were associated with better cognitive function among both men and women (p < 0.05); doing volunteer work was associated with better cognitive function among women but not among men (p < 0.05). These findings suggest that there is a cross-sectional association between participation in social activities and cognitive function among Chinese elderly. Longitudinal studies are needed to examine the effects of social activities on cognitive function. PMID:29385773
Ishii, K; Murakoshi, T; Hayashi, S; Saito, M; Sago, H; Takahashi, Y; Sumie, M; Nakata, M; Matsushita, M; Shinno, T; Naruse, H; Torii, Y
2011-01-01
The aim of this study was to evaluate the use of ultrasound assessment to predict risk of mortality in expectantly managed monochorionic twin fetuses with selective intrauterine growth restriction (sIUGR). This was a retrospective study of 101 monochorionic twin pregnancies diagnosed with sIUGR before 26 weeks of gestation. All patients were under expectant management during the observation period. At the initial evaluation, the presence or absence of each of the following abnormalities was documented: oligohydramnios; stuck twin phenomenon; severe IUGR < 3(rd) centile of estimated fetal weight; abnormal Doppler in the umbilical artery; and polyhydramnios in the larger twin. The relationships between these ultrasound findings and mortality of sIUGR fetuses were evaluated using multiple logistic regression analysis. Of 101 sIUGR twins, 22 (21.8%) fetuses suffered intrauterine demise and nine (8.9%) suffered neonatal death; 70 (69.3%) survived the neonatal period. Multiple logistic regression analysis revealed that the stuck twin phenomenon (odds ratio (OR): 14.5; 95% CI: 2.2-93.2; P = 0.006) and constantly absent diastolic flow in the umbilical artery (OR: 29.4; 95% CI: 3.3-264.0; P = 0.003) were significant risk factors for mortality. Not only abnormal Doppler flow in the umbilical artery but also severe oligohydramnios should be recognized as important indicators for mortality in monochorionic twins with sIUGR.
Dobashi, Kosuke; Nagamine, Masanori; Shigemura, Jun; Tsunoda, Tomoya; Shimizu, Kunio; Yoshino, Aihide; Nomura, Soichiro
2014-01-01
Disaster relief workers are potentially exposed to severe stressors on the job, resulting in a variety of psychological responses. This study aims to clarify the psychological effects of disaster relief activities on Japan Ground Self-Defense Force (JGSDF) personnel following the 2011 Great East Japan Earthquake. A self-report questionnaire was administered to 606 JGSDF personnel one month after completing the disaster relief mission. Posttraumatic stress responses and general psychological distress were assessed using the Impact of Event Scale-Revised (IES-R) and the K10 scales. Associations between outcome variables and independent variables (age, gender, military rank, length of deployment, and exposure to dead bodies) were measured with univariate analyses and subsequent multiple logistic regression analyses. The mean (± SD) IES-R score was 6.2 (± 8.1), and the mean K10 score was 12.8 (± 4.4). In the univariate analyses, exposure to dead bodies and age were identified as significant factors for IES-R and K10 scores, (p < 0.01). However, the multiple logistic regression analyses did not reveal any significant factors although body handlers' exposure approached significance for IES-R. The subjects reported very low psychological responses despite the severe nature of their disaster relief activities. Several factors may account for the low levels of psychological distress and posttraumatic symptoms observed in this study.
Biomechanical, anthropometric, and psychological determinants of barbell back squat strength.
Vigotsky, Andrew D; Bryanton, Megan A; Nuckols, Greg; Beardsley, Chris; Contreras, Bret; Evans, Jessica; Schoenfeld, Brad J
2018-02-27
Previous investigations of strength have only focused on biomechanical or psychological determinants, while ignoring the potential interplay and relative contributions of these variables. The purpose of this study was to investigate the relative contributions of biomechanical, anthropometric, and psychological variables to the prediction of maximum parallel barbell back squat strength. Twenty-one college-aged participants (male = 14; female = 7; age = 23 ± 3 years) reported to the laboratory for two visits. The first visit consisted of anthropometric, psychometric, and parallel barbell back squat one-repetition maximum (1RM) testing. On the second visit, participants performed isometric dynamometry testing for the knee, hip, and spinal extensors in a sticking point position-specific manner. Multiple linear regression and correlations were used to investigate the combined and individual relationships between biomechanical, anthropometric, and psychological variables and squat 1RM. Multiple regression revealed only one statistically predictive determinant: fat free mass normalized to height (standardized estimate ± SE = 0.6 ± 0.3; t(16) = 2.28; p = 0.037). Correlation coefficients for individual variables and squat 1RM ranged from r = -0.79-0.83, with biomechanical, anthropometric, experiential, and sex predictors showing the strongest relationships, and psychological variables displaying the weakest relationships. These data suggest that back squat strength in a heterogeneous population is multifactorial and more related to physical rather than psychological variables.
Psychological impact of sports activity in spinal cord injury patients.
Gioia, M C; Cerasa, A; Di Lucente, L; Brunelli, S; Castellano, V; Traballesi, M
2006-12-01
To investigate whether sports activity is associated with better psychological profiles in patients with spinal cord injury (SCI) and to evaluate the effect of demographic factors on psychological benefits. The State-Trait Anxiety Inventory, Form X2 (STAI-X2), the Eysenck Personality Questionnaire for extraversion (EPQ-R (E)) and the questionnaire for depression (QD) were administered in a cross-sectional study of 137 males with spinal cord injury including 52 tetraplegics and 85 paraplegics. The subjects were divided into two groups according to sports activity participation (high frequency vs no sports participation). Moreover, multiple regression analysis was adopted to investigate the influence of demographic variables, such as age, educational level, occupational status and marital status, on psychological variables. Analysis of variance revealed significant differences among the groups for anxiety (STAI-X2), extraversion (EPQ-R (E)) and depression (QD). In particular, SCI patients who did not practice sports showed higher anxiety and depression scores and lower extraversion scores than sports participants. In addition, with respect to the paraplegics, the tetraplegic group showed the lowest depression scores. Following multiple regression analysis, only the sports activity factor remained as an independent factor of anxiety scores. These findings demonstrate that sports activity is associated with better psychological status in SCI patients, irrespective of tetraplegia and paraplegia, and that psychological benefits are not emphasized by demographic factors.
Khodaverdi, Zeinab; Bahram, Abbas; Khalaji, Hassan; Kazemnejad, Anoshirvan
2013-01-01
Abstract Background The main purpose of this study was to determine which correlate, perceived motor competence or motor skill competence, best predicts girls’ physical activity behavior. Methods A sample of 352 girls (mean age=8.7, SD=0.3 yr) participated in this study. To assess motor skill competence and perceived motor competence, each child completed the Test of Gross Motor Development-2 and Physical Ability sub-scale of Marsh’s Self-Description Questionnaire. Children’s physical activity was assessed by the Physical Activity Questionnaire for Older Children. Multiple linear regression model was used to determine whether perceived motor competence or motor skill competence best predicts moderate-to-vigorous self-report physical activity. Results Multiple regression analysis indicated that motor skill competence and perceived motor competence predicted 21% variance in physical activity (R2=0.21, F=48.9, P=0.001), and motor skill competence (R2=0.15, ᵝ=0.33, P= 0.001) resulted in more variance than perceived motor competence (R2=0.06, ᵝ=0.25, P=0.001) in physical activity. Conclusion Results revealed motor skill competence had more influence in comparison with perceived motor competence on physical activity level. We suggest interventional programs based on motor skill competence and perceived motor competence should be administered or implemented to promote physical activity in young girls. PMID:26060623
Kang, Kun-Tai; Chiu, Shuenn-Nan; Weng, Wen-Chin; Lee, Pei-Lin; Hsu, Wei-Chung
2017-03-01
To compare office blood pressure (BP) and 24-hour ambulatory BP (ABP) monitoring to facilitate the diagnosis and management of hypertension in children with obstructive sleep apnea (OSA). Children aged 4-16 years with OSA-related symptoms were recruited from a tertiary referral medical center. All children underwent overnight polysomnography, office BP, and 24-hour ABP studies. Multiple linear regression analyses were applied to elucidate the association between the apnea-hypopnea index and BP. Correlation and consistency between office BP and 24-hour ABP were measured by Pearson correlation, intraclass correlation, and Bland-Altman analyses. In the 163 children enrolled (mean age, 8.2 ± 3.3 years; 67% male). The prevalence of systolic hypertension at night was significantly higher in children with moderate-to-severe OSA than in those with primary snoring (44.9% vs 16.1%, P = .006). Pearson correlation and intraclass correlation analyses revealed associations between office BP and 24-hour BP, and Bland-Altman analysis indicated an agreement between office and 24-hour BP measurements. However, multiple linear regression analyses demonstrated that 24-hour BP (nighttime systolic BP and mean arterial pressure), unlike office BP, was independently associated with the apnea-hypopnea index, after adjustment for adiposity variables. Twenty-four-hour ABP is more strongly correlated with OSA in children, compared with office BP. Copyright © 2016 Elsevier Inc. All rights reserved.
Kelso, Gwendolyn A; Cohen, Mardge H; Weber, Kathleen M; Dale, Sannisha K; Cruise, Ruth C; Brody, Leslie R
2014-07-01
Critical consciousness, the awareness of social oppression, is important to investigate as a buffer against HIV disease progression in HIV-infected African American women in the context of experiences with discrimination. Critical consciousness comprises several dimensions, including social group identification, discontent with distribution of social power, rejection of social system legitimacy, and a collective action orientation. The current study investigated self-reported critical consciousness as a moderator of perceived gender and racial discrimination on HIV viral load and CD4+ cell count in 67 African American HIV-infected women. Higher critical consciousness was found to be related to higher likelihood of having CD4+ counts over 350 and lower likelihood of detectable viral load when perceived racial discrimination was high, as revealed by multiple logistic regressions that controlled for highly active antiretroviral therapy (HAART) adherence. Multiple linear regressions showed that at higher levels of perceived gender and racial discrimination, women endorsing high critical consciousness had a larger positive difference between nadir CD4+ (lowest pre-HAART) and current CD4+ count than women endorsing low critical consciousness. These findings suggest that raising awareness of social oppression to promote joining with others to enact social change may be an important intervention strategy to improve HIV outcomes in African American HIV-infected women who report experiencing high levels of gender and racial discrimination.
Suzuki, Seitaro; Yoshino, Koichi; Takayanagi, Atsushi; Ishizuka, Yoichi; Satou, Ryouichi; Kamijo, Hideyuki; Sugihara, Naoki
2016-06-10
This cross-sectional study was conducted to examine tooth loss and associated factors among professional drivers and white-collar workers. The participants were recruited by applying screening procedures to a pool of Japanese registrants in an online database. The participants were asked to complete a self-reported questionnaire. A total of 592 professional drivers and 328 white-collar workers (male, aged 30 to 69 years) were analyzed. A multiple logistic regression analysis was performed to identify differences between professional drivers and white-collar workers. The results showed that professional drivers had fewer teeth than white-collar workers (odds ratio [OR], 1.74; 95% confidence interval [95% CI], 1.150-2.625). Moreover, a second multiple logistic regression analysis revealed that several factors were associated with the number of teeth among professional drivers: diabetes mellitus (OR, 2.68; 95% CI, 1.388-5.173), duration of brushing teeth (OR, 1.66; 95% CI, 1.066-2.572), frequency of eating breakfast (OR, 2.23; 95% CI, 1.416-3.513), frequency of eating out (OR, 1.70; 95% CI, 1.086-2.671) and smoking status (OR, 2.88; 95% CI, 1.388-5.964). These findings suggest that the lifestyles of professional drivers could be related to not only their general health status, but also tooth loss.
Principals' instructional management skills and middle school science teacher job satisfaction
NASA Astrophysics Data System (ADS)
Gibbs-Harper, Nzinga A.
The purpose of this research study was to determine if a relationship exists between teachers' perceptions of principals' instructional leadership behaviors and middle school teacher job satisfaction. Additionally, this study sought to assess whether principal's instructional leadership skills were predictors of middle school teachers' satisfaction with work itself. This study drew from 13 middle schools in an urban Mississippi school district. Participants included teachers who taught science. Each teacher was given the Principal Instructional Management Rating Scale (PIMRS; Hallinger, 2011) and the Teacher Job Satisfaction Questionnaire (TJSQ; Lester, 1987) to answer the research questions. The study was guided by two research questions: (a) Is there a relationship between the independent variables Defining the School's Mission, Managing the Instructional Program, and Developing the School Learning Climate Program and the dependent variable Work Itself?; (b) Are Defining the School's Mission, Managing the Instructional Program, and Developing the School Learning Climate Program predictors of Work Itself? The Pearson's correlation and multiple regression analysis were utilized to examine the relationship between the three dimensions of principals' instructional leadership and teacher satisfaction with work itself. The data revealed that there was a strong, positive correlation between all three dimensions of principals' instructional leadership and teacher satisfaction with work itself. However, the multiple regression analysis determined that teachers' perceptions of principals' instructional management skills is a slight predictor of Defining the School's Mission only.
Kelso, Gwendolyn A.; Cohen, Mardge H.; Weber, Kathleen M.; Dale, Sannisha K.; Cruise, Ruth C.; Brody, Leslie R.
2014-01-01
Critical consciousness, the awareness of social oppression, is important to investigate as a buffer against HIV disease progression in HIV-infected African American women in the context of experiences with discrimination. Critical consciousness comprises several dimensions, including social group identification, discontent with distribution of social power, rejection of social system legitimacy, and a collective action orientation. The current study investigated self-reported critical consciousness as a moderator of perceived gender and racial discrimination on HIV viral load and CD4+ cell count in 67 African American HIV-infected women. Higher critical consciousness was found to be related to higher likelihood of having CD4+ counts over 350 and lower likelihood of detectable viral load when perceived racial discrimination was high, as revealed by multiple logistic regressions that controlled for highly active antiretroviral therapy (HAART) adherence. Multiple linear regressions showed that at higher levels of perceived gender and racial discrimination, women endorsing high critical consciousness had a larger positive difference between nadir CD4+ (lowest pre-HAART) and current CD4+ count than women endorsing low critical consciousness. These findings suggest that raising awareness of social oppression to promote joining with others to enact social change may be an important intervention strategy to improve HIV outcomes in African American HIV-infected women who report experiencing high levels of gender and racial discrimination. PMID:24077930
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.
Liu, Qi; Wu, Youcong; Yuan, Youhua; Bai, Li; Niu, Kun
2011-12-01
To research the relationship between the virulence factors of Saccharomyces albicans (S. albicans) and the random amplified polymorphic DNA (RAPD) bands of them, and establish the regression model by multiple regression analysis. Extracellular phospholipase, secreted proteinase, ability to generate germ tubes and adhere to oral mucosal cells of 92 strains of S. albicans were measured in vitro; RAPD-polymerase chain reaction (RAPD-PCR) was used to get their bands. Multiple regression for virulence factors of S. albicans and RAPD-PCR bands was established. The extracellular phospholipase activity was associated with 4 RAPD bands: 350, 450, 650 and 1 300 bp (P < 0.05); secreted proteinase activity of S. albicans was associated with 2 bands: 350 and 1 200 bp (P < 0.05); the ability of germ tube produce was associated with 2 bands: 400 and 550 bp (P < 0.05). Some RAPD bands will reflect the virulence factors of S. albicans indirectly. These bands would contain some important messages for regulation of S. albicans virulence factors.
Simultaneous multiple non-crossing quantile regression estimation using kernel constraints
Liu, Yufeng; Wu, Yichao
2011-01-01
Quantile regression (QR) is a very useful statistical tool for learning the relationship between the response variable and covariates. For many applications, one often needs to estimate multiple conditional quantile functions of the response variable given covariates. Although one can estimate multiple quantiles separately, it is of great interest to estimate them simultaneously. One advantage of simultaneous estimation is that multiple quantiles can share strength among them to gain better estimation accuracy than individually estimated quantile functions. Another important advantage of joint estimation is the feasibility of incorporating simultaneous non-crossing constraints of QR functions. In this paper, we propose a new kernel-based multiple QR estimation technique, namely simultaneous non-crossing quantile regression (SNQR). We use kernel representations for QR functions and apply constraints on the kernel coefficients to avoid crossing. Both unregularised and regularised SNQR techniques are considered. Asymptotic properties such as asymptotic normality of linear SNQR and oracle properties of the sparse linear SNQR are developed. Our numerical results demonstrate the competitive performance of our SNQR over the original individual QR estimation. PMID:22190842
Green, Kimberly T.; Beckham, Jean C.; Youssef, Nagy; Elbogen, Eric B.
2013-01-01
Objective The present study sought to investigate the longitudinal effects of psychological resilience against alcohol misuse adjusting for socio-demographic factors, trauma-related variables, and self-reported history of alcohol abuse. Methodology Data were from National Post-Deployment Adjustment Study (NPDAS) participants who completed both a baseline and one-year follow-up survey (N=1090). Survey questionnaires measured combat exposure, probable posttraumatic stress disorder (PTSD), psychological resilience, and alcohol misuse, all of which were measured at two discrete time periods (baseline and one-year follow-up). Baseline resilience and change in resilience (increased or decreased) were utilized as independent variables in separate models evaluating alcohol misuse at the one-year follow-up. Results Multiple linear regression analyses controlled for age, gender, level of educational attainment, combat exposure, PTSD symptom severity, and self-reported alcohol abuse. Accounting for these covariates, findings revealed that lower baseline resilience, younger age, male gender, and self-reported alcohol abuse were related to alcohol misuse at the one-year follow-up. A separate regression analysis, adjusting for the same covariates, revealed a relationship between change in resilience (from baseline to the one-year follow-up) and alcohol misuse at the one-year follow-up. The regression model evaluating these variables in a subset of the sample in which all the participants had been deployed to Iraq and/or Afghanistan was consistent with findings involving the overall era sample. Finally, logistic regression analyses of the one-year follow-up data yielded similar results to the baseline and resilience change models. Conclusions These findings suggest that increased psychological resilience is inversely related to alcohol misuse and is protective against alcohol misuse over time. Additionally, it supports the conceptualization of resilience as a process which evolves over time. Moreover, our results underscore the importance of assessing resilience as part of alcohol use screening for preventing alcohol misuse in Iraq and Afghanistan era military veterans. PMID:24090625
Lakatos, Peter Laszlo; Fekete, Sandor; Horanyi, Margit; Fischer, Simon; Abonyi, Margit E
2006-01-01
An association between chronic hepatitis C virus (HCV) infection and essential mixed cryoglobulinaemia and non-Hodgkin lymphoma (NHL) has been suggested. However, a causative role of HCV in these conditions has not been established. The authors report a case of a 50 year-old woman with chronic hepatitis C (CHC) who has been followed up since 1998 due to a high viral load, genotype 1b and moderately elevated liver function tests (LFTs). Laboratory data and liver biopsy revealed moderate activity (grade: 5/18, stage: 1/6). In April 1999, one-year interferon therapy was started. HCV-RNA became negative with normalization of LFTs. However, the patient relapsed during treatment. In September 2002, the patient was admitted for chronic back pain. A CT examination demonstrated degenerative changes. In March 2003, multiple myeloma was diagnosed (IgG-kappa, bone ma-rrow biopsy: 50% plasma cell infiltration). MRI revealed a compression fracture of the 5th lumbar vertebral body and an abdominal mass in the right lower quadrant, infiltrating the canalis spinalis. Treatment with vincristine, adriamycin and dexamethasone (VAD) was started and bisphosphonate was administered regularly. In January 2004, after six cycles of VAD therapy, the multiple myeloma regressed. Thalidomide, as a second line trea-tment of refractory multiple myeloma (MM) was initiated, and followed by peginterferon-α2b and ribavirin against the HCV infection in June. In June 2005, LFTs returned to normal, while HCV-RNA was negative, demonstrating an end of treatment response. Although a pathogenic role of HCV infection in malignant lymphoproliferative disorders has not been established, NHL and possibly MM may develop in CHC patients, supporting a role of a complex follow-up in these patients. PMID:16610042
Computational Identification of Genomic Features That Influence 3D Chromatin Domain Formation.
Mourad, Raphaël; Cuvier, Olivier
2016-05-01
Recent advances in long-range Hi-C contact mapping have revealed the importance of the 3D structure of chromosomes in gene expression. A current challenge is to identify the key molecular drivers of this 3D structure. Several genomic features, such as architectural proteins and functional elements, were shown to be enriched at topological domain borders using classical enrichment tests. Here we propose multiple logistic regression to identify those genomic features that positively or negatively influence domain border establishment or maintenance. The model is flexible, and can account for statistical interactions among multiple genomic features. Using both simulated and real data, we show that our model outperforms enrichment test and non-parametric models, such as random forests, for the identification of genomic features that influence domain borders. Using Drosophila Hi-C data at a very high resolution of 1 kb, our model suggests that, among architectural proteins, BEAF-32 and CP190 are the main positive drivers of 3D domain borders. In humans, our model identifies well-known architectural proteins CTCF and cohesin, as well as ZNF143 and Polycomb group proteins as positive drivers of domain borders. The model also reveals the existence of several negative drivers that counteract the presence of domain borders including P300, RXRA, BCL11A and ELK1.
Computational Identification of Genomic Features That Influence 3D Chromatin Domain Formation
Mourad, Raphaël; Cuvier, Olivier
2016-01-01
Recent advances in long-range Hi-C contact mapping have revealed the importance of the 3D structure of chromosomes in gene expression. A current challenge is to identify the key molecular drivers of this 3D structure. Several genomic features, such as architectural proteins and functional elements, were shown to be enriched at topological domain borders using classical enrichment tests. Here we propose multiple logistic regression to identify those genomic features that positively or negatively influence domain border establishment or maintenance. The model is flexible, and can account for statistical interactions among multiple genomic features. Using both simulated and real data, we show that our model outperforms enrichment test and non-parametric models, such as random forests, for the identification of genomic features that influence domain borders. Using Drosophila Hi-C data at a very high resolution of 1 kb, our model suggests that, among architectural proteins, BEAF-32 and CP190 are the main positive drivers of 3D domain borders. In humans, our model identifies well-known architectural proteins CTCF and cohesin, as well as ZNF143 and Polycomb group proteins as positive drivers of domain borders. The model also reveals the existence of several negative drivers that counteract the presence of domain borders including P300, RXRA, BCL11A and ELK1. PMID:27203237
Monitoring heavy metal Cr in soil based on hyperspectral data using regression analysis
NASA Astrophysics Data System (ADS)
Zhang, Ningyu; Xu, Fuyun; Zhuang, Shidong; He, Changwei
2016-10-01
Heavy metal pollution in soils is one of the most critical problems in the global ecology and environment safety nowadays. Hyperspectral remote sensing and its application is capable of high speed, low cost, less risk and less damage, and provides a good method for detecting heavy metals in soil. This paper proposed a new idea of applying regression analysis of stepwise multiple regression between the spectral data and monitoring the amount of heavy metal Cr by sample points in soil for environmental protection. In the measurement, a FieldSpec HandHeld spectroradiometer is used to collect reflectance spectra of sample points over the wavelength range of 325-1075 nm. Then the spectral data measured by the spectroradiometer is preprocessed to reduced the influence of the external factors, and the preprocessed methods include first-order differential equation, second-order differential equation and continuum removal method. The algorithms of stepwise multiple regression are established accordingly, and the accuracy of each equation is tested. The results showed that the accuracy of first-order differential equation works best, which makes it feasible to predict the content of heavy metal Cr by using stepwise multiple regression.
Forecasting USAF JP-8 Fuel Needs
2009-03-01
versus complex ones. When we consider long -term forecasts, 5-years in this case, multiple regression outperforms ANN modeling within the specified...with more simple and easy-to-implement methods, versus complex ones. When we consider long -term 5-year forecasts, our multiple regression model...effort. The insight and experience was certainly appreciated. Special thanks to my Turkish peers for their continuous support and help during this long
ERIC Educational Resources Information Center
Le, Huy; Marcus, Justin
2012-01-01
This study used Monte Carlo simulation to examine the properties of the overall odds ratio (OOR), which was recently introduced as an index for overall effect size in multiple logistic regression. It was found that the OOR was relatively independent of study base rate and performed better than most commonly used R-square analogs in indexing model…
ERIC Educational Resources Information Center
Pecorella, Patricia A.; Bowers, David G.
Multiple regression in a double cross-validated design was used to predict two performance measures (total variable expense and absence rate) by multi-month period in five industrial firms. The regressions do cross-validate, and produce multiple coefficients which display both concurrent and predictive effects, peaking 18 months to two years…
USDA-ARS?s Scientific Manuscript database
A technique of using multiple calibration sets in partial least squares regression (PLS) was proposed to improve the quantitative determination of ammonia from open-path Fourier transform infrared spectra. The spectra were measured near animal farms, and the path-integrated concentration of ammonia...
Lorenzo-Seva, Urbano; Ferrando, Pere J
2011-03-01
We provide an SPSS program that implements currently recommended techniques and recent developments for selecting variables in multiple linear regression analysis via the relative importance of predictors. The approach consists of: (1) optimally splitting the data for cross-validation, (2) selecting the final set of predictors to be retained in the equation regression, and (3) assessing the behavior of the chosen model using standard indices and procedures. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from brm.psychonomic-journals.org/content/supplemental.
Standardized Regression Coefficients as Indices of Effect Sizes in Meta-Analysis
ERIC Educational Resources Information Center
Kim, Rae Seon
2011-01-01
When conducting a meta-analysis, it is common to find many collected studies that report regression analyses, because multiple regression analysis is widely used in many fields. Meta-analysis uses effect sizes drawn from individual studies as a means of synthesizing a collection of results. However, indices of effect size from regression analyses…
Learning to be cruel?: exploring the onset and frequency of animal cruelty.
Hensley, Christopher; Tallichet, Suzanne E
2005-02-01
Few studies have examined how animal cruelty is learned within a specific social context among incarcerated individuals. Using data from 261 inmates, this study specifically addressed how demographic characteristics and childhood experiences with animal abuse may have affected the recurrence and onset of childhood and adolescent cruelty as a learned behavior. Multiple regression analyses revealed that inmates who experienced animal cruelty at a younger age were more likely to demonstrate recurrent animal cruelty themselves. In addition, respondents who observed a friend abuse animals were more likely to hurt or kill animals more frequently. Finally, inmates who were younger when they first witnessed animal cruelty also hurt or killed animals at a younger age.
Han, Beth; Remsburg, Robin E
2005-01-01
Using data from the 1996 and 2000 National Home and Hospice Care Surveys (N = 2,455), we examined length of use in home care among patients with Medicare-only payment source before and during the Medicare interim payment system (IPS). Logistic regression analyses revealed that patients were 2.9 times more likely to be discharged within 60 days during IPS than before IPS. The impact of Medicare IPS on length of use in home care among patients with Medicare only was stronger than what the existing literature indicates, which combines Medicare patients with multiple payment sources and patients with Medicare-only together.
The role of attitudes and culture in family caregiving for older adults.
Anngela-Cole, Linda; Hilton, Jeanne M
2009-01-01
This study evaluated cultural differences in attitudes toward caregiving and the stress levels of family caregivers. Participants included 98 Japanese American and 86 Caucasian American family caregivers caring for frail elders. Analyses using MANOVA and multiple regression analyses revealed that the Caucasian caregivers had more positive attitudes and provided more hours of care than the Japanese caregivers but that both groups had elevated levels of caregiver stress. The stress that family caregivers currently experience could lead to a future generation of care recipients who enter old age in worse condition than their predecessors. Professionals need to work together to develop culturally appropriate, evidence-based interventions to address this issue.
The interactive effects of proactive personality and work-family interference on well-being.
Cunningham, Christopher J L; De La Rosa, Gabriel M
2008-07-01
Proactive personality was expected to moderate the relationship between controllable work and nonwork stressors (e.g., time-based work-family interference) and job/life satisfaction. Moderated multiple regression analyses of survey data from a sample of professionals (N=133) revealed a significant interaction between time-based family interfering-with work and proactive personality predicting life satisfaction and several main effects offering partial support for the hypothesized relationships (alpha<.05). No other interactions between proactive personality and other forms of work-family interference were observed. The benefits of proactive personality may only emerge when personal control over occupational stressors can be exercised. Copyright (c) 2008 APA, all rights reserved.
Does the perception that God controls health outcomes matter for health behaviors?
Karvinen, Kristina H; Carr, Lucas J
2014-04-01
The purpose of this study was to examine the associations between God Locus of Health Control, health behaviors, and beliefs utilizing a cross-sectional online survey (N = 549). Results indicated that God Locus of Health Control was correlated with alcohol use, physical activity, perceived risk of chronic disease, and beliefs that poor health behaviors contribute to chronic disease (all p values < .05). Multiple regression analyses including covariates and other locus of control variables revealed that God Locus of Health Control was only an independent correlate of the belief that physical inactivity contributed to chronic disease. Insights from this study may be important for future faith-based health behavior change interventions.
Biegel, D E; Milligan, S E; Putnam, P L; Song, L Y
1994-10-01
This study uses a stress-coping-support framework to examine the predictors of caregiver burden with a sample of 103 lower social class family caregivers of persons with chronic mental illness. Results of multiple regression analyses show that the greater the frequency of client behavioral symptoms and the lower the amount of perceived support from family members, the higher the level of overall caregiver burden. Examination of the predictors of specific types of burden-family disruption, stigma, strain, and dependency-reveal that different constellations of variables predict different types of burden. The need for mental health agencies to address caregiver and client concerns is addressed. Implications are presented for practice and future research.
Lee, Tiane L.; Fiske, Susan T.; Glick, Peter; Chen, Zhixia
2013-01-01
Gender-based structural power and heterosexual dependency produce ambivalent gender ideologies, with hostility and benevolence separately shaping close-relationship ideals. The relative importance of romanticized benevolent versus more overtly power-based hostile sexism, however, may be culturally dependent. Testing this, northeast US (N=311) and central Chinese (N=290) undergraduates rated prescriptions and proscriptions (ideals) for partners and completed Ambivalent Sexism and Ambivalence toward Men Inventories (ideologies). Multiple regressions analyses conducted on group-specific relationship ideals revealed that benevolent ideologies predicted partner ideals, in both countries, especially for US culture’s romance-oriented relationships. Hostile attitudes predicted men’s ideals, both American and Chinese, suggesting both societies’ dominant-partner advantage. PMID:23914004
Linking strain anisotropy and plasticity in copper metallization
DOE Office of Scientific and Technical Information (OSTI.GOV)
Murray, Conal E., E-mail: conal@us.ibm.com; Jordan-Sweet, Jean; Priyadarshini, Deepika
2015-05-04
The elastic anisotropy of copper leads to significant variation in the x-ray elastic constants (XEC), which link diffraction-based strain measurements to stress. An accurate depiction of the mechanical response in copper thin films requires a determination of an appropriate grain interaction model that lies between Voigt and Reuss limits. It is shown that the associated XEC weighting fraction, x*, between these limits provides a metric by which strain anisotropy can be quantified. Experimental values of x*, as determined by a linear regression scheme of diffraction data collected from multiple reflections, reveal the degree of strain anisotropy and its dependence onmore » plastic deformation induced during in-situ and ex-situ thermal treatments.« less
Hahm, Hyeouk Chris; Augsberger, Astraea; Feranil, Mario; Jang, Jisun; Tagerman, Michelle
2017-01-01
We examined the association between forced sex history and mental health, sexual health, and substance use among Asian American women (n = 720); 14.3% of our sample (n = 103) reported forced sex experiences. Multiple logistic regression analyses revealed that participants with forced sex histories were 2-8 times more likely to have higher rates of mental health problems, HIV risk behavior, and substance use. Qualitative analysis was used to supplement the quantitative results and give depth to our findings. Our results suggest that interventions for Asian American women who experienced forced sex should integrate mental health, substance use, and sexual health treatments. PMID:27230614
NASA Technical Reports Server (NTRS)
Yorchak, J. P.; Hartley, C. S.; Hinman, E.
1985-01-01
The use of aptitude tests and questionnaries to evaluate an individuals aptitude for teleoperation is studied. The Raven Progressive Matrices Test and Differential Aptitude Tests, and a 16-item questionnaire for assessing the subject's interests, academic background, and previous experience are described. The Proto-Flight Manipulator Arm, cameras, console, hand controller, and task board utilized by the 17 engineers are examined. The correlation between aptitude scores and questionnaire responses, and operator performance is investigated. Multiple regression data reveal that the eight predictor variables are not individually significant for evaluating operator performance; however, the complete test battery is applicable for predicting 49 percent of subject variance on the criterion task.
Length of training, hostility and the martial arts: a comparison with other sporting groups.
Daniels, K; Thornton, E
1992-01-01
Previous research has indicated that training in the martial arts leads to a reduction in levels of hostility. However, such research has only compared hostility within martial arts groups. The present research compares two martial arts groups and two other sporting groups on levels of assaultive, verbal and indirect hostility. Moderated multiple regression analyses revealed a significant interaction between length of training in the respondent's stated sport and whether that sport was a martial art in predicting assaultive and verbal hostility. The form of the interaction suggests that participation in the martial arts is associated, over time, with decreased feelings of assaultive and verbal hostility. PMID:1422642
Nakamura, Ryo; Nakano, Kumiko; Tamura, Hiroyasu; Mizunuma, Masaki; Fushiki, Tohru; Hirata, Dai
2017-08-01
Many factors contribute to palatability. In order to evaluate the palatability of Japanese alcohol sake paired with certain dishes by integrating multiple factors, here we applied an evaluation method previously reported for palatability of cheese by multiple regression analysis based on 3 subdomain factors (rewarding, cultural, and informational). We asked 94 Japanese participants/subjects to evaluate the palatability of sake (1st evaluation/E1 for the first cup, 2nd/E2 and 3rd/E3 for the palatability with aftertaste/afterglow of certain dishes) and to respond to a questionnaire related to 3 subdomains. In E1, 3 factors were extracted by a factor analysis, and the subsequent multiple regression analyses indicated that the palatability of sake was interpreted by mainly the rewarding. Further, the results of attribution-dissections in E1 indicated that 2 factors (rewarding and informational) contributed to the palatability. Finally, our results indicated that the palatability of sake was influenced by the dish eaten just before drinking.
Correlation and simple linear regression.
Eberly, Lynn E
2007-01-01
This chapter highlights important steps in using correlation and simple linear regression to address scientific questions about the association of two continuous variables with each other. These steps include estimation and inference, assessing model fit, the connection between regression and ANOVA, and study design. Examples in microbiology are used throughout. This chapter provides a framework that is helpful in understanding more complex statistical techniques, such as multiple linear regression, linear mixed effects models, logistic regression, and proportional hazards regression.
Wu, Jia-sheng; Shi, Rong; Zhong, Jie; Lu, Xiong; Ma, Bing-liang; Wang, Tian-ming; Zan, Bin; Ma, Yue-ming; Cheng, Neng-neng; Qiu, Fu-rong
2013-01-01
In Chinese medicine, Xiexin decoction (XXD) has been used for the clinical treatment of diabetes for at least 1700 years. The present study was conducted to investigate the effective ingredients of XXD and their molecular mechanisms of antidiabetic nephropathy in rats. Rats with diabetes induced by high-fat diet and streptozotocin were treated with XXD extract for 12 weeks. XXD significantly improved the glucolipid metabolism disorder, attenuated albuminuria and renal pathological changes, reduced renal advanced glycation end-products, inhibited receptor for advanced glycation end-product and inflammation factors expression, suppressed renal nuclear factor-κB pathway activity, and downregulated renal transforming growth factor-β1. The concentrations of multiple components in plasma from XXD were determined by liquid chromatography and tandem mass spectrometry. Pharmacokinetic/pharmacodynamic analysis using partial least square regression revealed that 8 ingredients of XXD were responsible for renal protective effects via actions on multiple molecular targets. Our study suggests that the renal protective role of XXD with multiple effective ingredients involves inhibition of inflammation through downregulation of the nuclear factor-κB pathway, reducing renal advanced glycation end-products and receptor for advanced glycation end-product in diabetic rats. PMID:23935673
Valente, Andrea; Bürki, Audrey; Laganaro, Marina
2014-01-01
A major effort in cognitive neuroscience of language is to define the temporal and spatial characteristics of the core cognitive processes involved in word production. One approach consists in studying the effects of linguistic and pre-linguistic variables in picture naming tasks. So far, studies have analyzed event-related potentials (ERPs) during word production by examining one or two variables with factorial designs. Here we extended this approach by investigating simultaneously the effects of multiple theoretical relevant predictors in a picture naming task. High density EEG was recorded on 31 participants during overt naming of 100 pictures. ERPs were extracted on a trial by trial basis from picture onset to 100 ms before the onset of articulation. Mixed-effects regression models were conducted to examine which variables affected production latencies and the duration of periods of stable electrophysiological patterns (topographic maps). Results revealed an effect of a pre-linguistic variable, visual complexity, on an early period of stable electric field at scalp, from 140 to 180 ms after picture presentation, a result consistent with the proposal that this time period is associated with visual object recognition processes. Three other variables, word Age of Acquisition, Name Agreement, and Image Agreement influenced response latencies and modulated ERPs from ~380 ms to the end of the analyzed period. These results demonstrate that a topographic analysis fitted into the single trial ERPs and covering the entire processing period allows one to associate the cost generated by psycholinguistic variables to the duration of specific stable electrophysiological processes and to pinpoint the precise time-course of multiple word production predictors at once.
VoxelStats: A MATLAB Package for Multi-Modal Voxel-Wise Brain Image Analysis.
Mathotaarachchi, Sulantha; Wang, Seqian; Shin, Monica; Pascoal, Tharick A; Benedet, Andrea L; Kang, Min Su; Beaudry, Thomas; Fonov, Vladimir S; Gauthier, Serge; Labbe, Aurélie; Rosa-Neto, Pedro
2016-01-01
In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab(®) and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the estimation of advanced regional association metrics at the voxel level.
Increased risk of kidney damage among Chinese adults with simple renal cyst.
Kong, Xianglei; Ma, Xiaojing; Zhang, Chengyin; Su, Hong; Gong, Xiaojie; Xu, Dongmei
2018-05-04
The presence of simple renal cyst (SRC) has been related to hypertension, the early and long-term allograft function, and aortic disease, but the relationship with kidney damage was still controversial. Accordingly, we conducted a large sample cross-sectional study to explore the association of SRC with indicators of kidney damage among Chinese adults. A total of 42,369 adults (aged 45.8 ± 13.67 years, 70.6% males) who visited the Health Checkup Clinic were consecutively enrolled. SRC was assessed by ultrasonography according to Bosniak category. Multiple regression models were applied to explore the relationships between SRC and indicators of kidney damage [proteinuria (dipstick urine protein ≥ 1+) and decreased estimated glomerular filtration rate (DeGFR) < 60 ml/min/1.73 m 2 ]. Among all participants in the study, the prevalence of SRC was 10.5%. As a categorical outcome, participants with more 1 cyst and with 1 cyst had higher percentage of proteinuria [53 (5.3%) and 93 (2.7%) vs. 596 (1.6%), p < 0.001] and DeGFR [57 (5.7%) and 85 (2.5%) vs. 278 (0.7%), p < 0.001] compared with participants with no cyst. SRC significantly correlated with proteinuria [OR 1.59 (95% CI 1.30-1.95)] and DeGFR [OR 1.97 (95% CI 1.56-2.47)] after adjusting for potential confounders. Furthermore, the results also demonstrated that maximum diameter (per 1 cm increase), bilateral location, and multiple cysts significantly correlated with DeGFR in the multiple logistic regression analysis. The study revealed that SRC significantly correlated with kidney damage and special attention should be paid among Chinese adults with SRC.
Mägi, Reedik; Suleimanov, Yury V; Clarke, Geraldine M; Kaakinen, Marika; Fischer, Krista; Prokopenko, Inga; Morris, Andrew P
2017-01-11
Genome-wide association studies (GWAS) of single nucleotide polymorphisms (SNPs) have been successful in identifying loci contributing genetic effects to a wide range of complex human diseases and quantitative traits. The traditional approach to GWAS analysis is to consider each phenotype separately, despite the fact that many diseases and quantitative traits are correlated with each other, and often measured in the same sample of individuals. Multivariate analyses of correlated phenotypes have been demonstrated, by simulation, to increase power to detect association with SNPs, and thus may enable improved detection of novel loci contributing to diseases and quantitative traits. We have developed the SCOPA software to enable GWAS analysis of multiple correlated phenotypes. The software implements "reverse regression" methodology, which treats the genotype of an individual at a SNP as the outcome and the phenotypes as predictors in a general linear model. SCOPA can be applied to quantitative traits and categorical phenotypes, and can accommodate imputed genotypes under a dosage model. The accompanying META-SCOPA software enables meta-analysis of association summary statistics from SCOPA across GWAS. Application of SCOPA to two GWAS of high-and low-density lipoprotein cholesterol, triglycerides and body mass index, and subsequent meta-analysis with META-SCOPA, highlighted stronger association signals than univariate phenotype analysis at established lipid and obesity loci. The META-SCOPA meta-analysis also revealed a novel signal of association at genome-wide significance for triglycerides mapping to GPC5 (lead SNP rs71427535, p = 1.1x10 -8 ), which has not been reported in previous large-scale GWAS of lipid traits. The SCOPA and META-SCOPA software enable discovery and dissection of multiple phenotype association signals through implementation of a powerful reverse regression approach.
Estimation of PM2.5 and PM10 using ground-based AOD measurements during KORUS-AQ campaign
NASA Astrophysics Data System (ADS)
Koo, J. H.; Kim, J.; Kim, S.; Go, S.; Lee, S.; Lee, H.; Mok, J.; Hong, J.; Lee, J.; Eck, T. F.; Holben, B. N.
2017-12-01
During the KORUS-AQ campaign (2 May - 12 June, 2016), aerosol optical depth (AOD) was obtained at multiple channels using various ground-based instruments at Yonsei University, Seoul: AERONET sunphotometer, SKYNET skyradiometer, Brewer spectrophotometer, and multi-filter rotating shadowband radiometer (MFRSR). At the same location, planetary boundary layer (PBL) height and vertical profile of backscattering coefficients also can be obtained based on the celiometer measurements. Using celiometer products and various AODs, we try to estimate the amount of particular matter (PM2.5 and PM10) and validate with in-situ surface PM2.5 and PM10 measurements from AIRKOREA network. Direct comparison between PM2.5 and AOD reveals that the ultraviolet(UV) channel AOD has better correlations, due to the higher sensitivity of short wavelength to the fine-mode particle. In contrast, PM10 shows the highest correlation with the near-infrared(NIR) AOD. Next, we extract the boundary-layer portion of AOD using either PBL height or vertical profile of backscattering coefficients to compare with PM2.5 and PM10. Both results enhance the correlation, but consideration of weighting factor calculated from backscattering coefficients shows larger contribution to the correlation increase. Finally, we performed the multiple linear regression to estimate PM2.5 and PM10 using AODs. Consideration of meteorology (temperature, wind speed, and relative humidity) can enhance the correlation and also O3 and NO2 consideration highly contributes to the high correlation. This finding implies the importance to consider the ambient condition of secondary aerosol formation related to the PM2.5 variation. Multiple regression model finally finds the correlation 0.7-0.8, and diminishes the wavelength-dependent correlation patterns.
Kohn, Yair Y; Symonds, Jane E; Kleffmann, Torsten; Nakagawa, Shinichi; Lagisz, Malgorzata; Lokman, P Mark
2015-12-01
In order to develop biomarkers that may help predict the egg quality of captive hapuku (Polyprion oxygeneios) and provide potential avenues for its manipulation, the present study (1) sequenced the proteome of early-stage embryos using isobaric tag for relative and absolute quantification analysis, and (2) aimed to establish the predictive value of the abundance of identified proteins with regard to egg quality through regression analysis. Egg quality was determined for eight different egg batches by blastomere symmetry scores. In total, 121 proteins were identified and assigned to one of nine major groups according to their function/pathway. A mixed-effects model analysis revealed a decrease in relative protein abundance that correlated with (decreasing) egg quality in one major group (heat-shock proteins). No differences were found in the other protein groups. Linear regression analysis, performed for each identified protein separately, revealed seven proteins that showed a significant decrease in relative abundance with reduced blastomere symmetry: two correlates that have been named in other studies (vitellogenin, heat-shock protein-70) and a further five new candidate proteins (78 kDa glucose-regulated protein, elongation factor-2, GTP-binding nuclear protein Ran, iduronate 2-sulfatase and 6-phosphogluconate dehydrogenase). Notwithstanding issues associated with multiple statistical testing, we conclude that these proteins, and especially iduronate 2-sulfatase and the generic heat-shock protein group, could serve as biomarkers of egg quality in hapuku.
Mokarami, Hamidreza; Stallones, Lorann; Nazifi, Morteza; Taghavi, Sayed Mohammad
2016-10-17
The role of psychosocial and physical work factors in predicting health related quality of life (HRQOL) has not been investigated among Iranian industrial workers. The present study is designed to assess these relationships among Iranian workers from steel and cosmetic factories. A cross-sectional study was conducted among 280 workers from two factories. Psychosocial and physical work factors and HRQOL were measured by the Persian translations of the following questionnaires: Job Content Questionnaire (JCQ) and the World Health Organization Quality of Life-Brief (WHOQOL-Brief). An instrument was developed to assess socio-demographic, health, and other work-related factors. The data were analyzed using independent t-tests, Pearson product moment correlation and hierarchical multiple regression. Results revealed that the respondents generally had poor HRQOLs especially in the environmental domain. The steel factory workers who were exposed to higher levels of occupational risk factors suffered from poorer HRQOL compared to the cosmetic factory workers. The results of hierarchical regression for all participants revealed that social support, sleep quality, work schedule, smoking and exercise were significant predictors of all domains of HRQOL. To improve the worker's HRQOL, intervention programs should focus on promoting social support, sleep quality, exercise and smoking habits. Moreover, reducing hazardous work environments should be considered an important intervention to promote HRQOL.
Factor analysis and multiple regression between topography and precipitation on Jeju Island, Korea
NASA Astrophysics Data System (ADS)
Um, Myoung-Jin; Yun, Hyeseon; Jeong, Chang-Sam; Heo, Jun-Haeng
2011-11-01
SummaryIn this study, new factors that influence precipitation were extracted from geographic variables using factor analysis, which allow for an accurate estimation of orographic precipitation. Correlation analysis was also used to examine the relationship between nine topographic variables from digital elevation models (DEMs) and the precipitation in Jeju Island. In addition, a spatial analysis was performed in order to verify the validity of the regression model. From the results of the correlation analysis, it was found that all of the topographic variables had a positive correlation with the precipitation. The relations between the variables also changed in accordance with a change in the precipitation duration. However, upon examining the correlation matrix, no significant relationship between the latitude and the aspect was found. According to the factor analysis, eight topographic variables (latitude being the exception) were found to have a direct influence on the precipitation. Three factors were then extracted from the eight topographic variables. By directly comparing the multiple regression model with the factors (model 1) to the multiple regression model with the topographic variables (model 3), it was found that model 1 did not violate the limits of statistical significance and multicollinearity. As such, model 1 was considered to be appropriate for estimating the precipitation when taking into account the topography. In the study of model 1, the multiple regression model using factor analysis was found to be the best method for estimating the orographic precipitation on Jeju Island.
Weather Impact on Airport Arrival Meter Fix Throughput
NASA Technical Reports Server (NTRS)
Wang, Yao
2017-01-01
Time-based flow management provides arrival aircraft schedules based on arrival airport conditions, airport capacity, required spacing, and weather conditions. In order to meet a scheduled time at which arrival aircraft can cross an airport arrival meter fix prior to entering the airport terminal airspace, air traffic controllers make regulations on air traffic. Severe weather may create an airport arrival bottleneck if one or more of airport arrival meter fixes are partially or completely blocked by the weather and the arrival demand has not been reduced accordingly. Under these conditions, aircraft are frequently being put in holding patterns until they can be rerouted. A model that predicts the weather impacted meter fix throughput may help air traffic controllers direct arrival flows into the airport more efficiently, minimizing arrival meter fix congestion. This paper presents an analysis of air traffic flows across arrival meter fixes at the Newark Liberty International Airport (EWR). Several scenarios of weather impacted EWR arrival fix flows are described. Furthermore, multiple linear regression and regression tree ensemble learning approaches for translating multiple sector Weather Impacted Traffic Indexes (WITI) to EWR arrival meter fix throughputs are examined. These weather translation models are developed and validated using the EWR arrival flight and weather data for the period of April-September in 2014. This study also compares the performance of the regression tree ensemble with traditional multiple linear regression models for estimating the weather impacted throughputs at each of the EWR arrival meter fixes. For all meter fixes investigated, the results from the regression tree ensemble weather translation models show a stronger correlation between model outputs and observed meter fix throughputs than that produced from multiple linear regression method.
Akkus, Zeki; Camdeviren, Handan; Celik, Fatma; Gur, Ali; Nas, Kemal
2005-09-01
To determine the risk factors of osteoporosis using a multiple binary logistic regression method and to assess the risk variables for osteoporosis, which is a major and growing health problem in many countries. We presented a case-control study, consisting of 126 postmenopausal healthy women as control group and 225 postmenopausal osteoporotic women as the case group. The study was carried out in the Department of Physical Medicine and Rehabilitation, Dicle University, Diyarbakir, Turkey between 1999-2002. The data from the 351 participants were collected using a standard questionnaire that contains 43 variables. A multiple logistic regression model was then used to evaluate the data and to find the best regression model. We classified 80.1% (281/351) of the participants using the regression model. Furthermore, the specificity value of the model was 67% (84/126) of the control group while the sensitivity value was 88% (197/225) of the case group. We found the distribution of residual values standardized for final model to be exponential using the Kolmogorow-Smirnow test (p=0.193). The receiver operating characteristic curve was found successful to predict patients with risk for osteoporosis. This study suggests that low levels of dietary calcium intake, physical activity, education, and longer duration of menopause are independent predictors of the risk of low bone density in our population. Adequate dietary calcium intake in combination with maintaining a daily physical activity, increasing educational level, decreasing birth rate, and duration of breast-feeding may contribute to healthy bones and play a role in practical prevention of osteoporosis in Southeast Anatolia. In addition, the findings of the present study indicate that the use of multivariate statistical method as a multiple logistic regression in osteoporosis, which maybe influenced by many variables, is better than univariate statistical evaluation.
Nguyen, Quynh C.; Osypuk, Theresa L.; Schmidt, Nicole M.; Glymour, M. Maria; Tchetgen Tchetgen, Eric J.
2015-01-01
Despite the recent flourishing of mediation analysis techniques, many modern approaches are difficult to implement or applicable to only a restricted range of regression models. This report provides practical guidance for implementing a new technique utilizing inverse odds ratio weighting (IORW) to estimate natural direct and indirect effects for mediation analyses. IORW takes advantage of the odds ratio's invariance property and condenses information on the odds ratio for the relationship between the exposure (treatment) and multiple mediators, conditional on covariates, by regressing exposure on mediators and covariates. The inverse of the covariate-adjusted exposure-mediator odds ratio association is used to weight the primary analytical regression of the outcome on treatment. The treatment coefficient in such a weighted regression estimates the natural direct effect of treatment on the outcome, and indirect effects are identified by subtracting direct effects from total effects. Weighting renders treatment and mediators independent, thereby deactivating indirect pathways of the mediators. This new mediation technique accommodates multiple discrete or continuous mediators. IORW is easily implemented and is appropriate for any standard regression model, including quantile regression and survival analysis. An empirical example is given using data from the Moving to Opportunity (1994–2002) experiment, testing whether neighborhood context mediated the effects of a housing voucher program on obesity. Relevant Stata code (StataCorp LP, College Station, Texas) is provided. PMID:25693776
Henry, Stephen G.; Jerant, Anthony; Iosif, Ana-Maria; Feldman, Mitchell D.; Cipri, Camille; Kravitz, Richard L.
2015-01-01
Objective To identify factors associated with participant consent to record visits; to estimate effects of recording on patient-clinician interactions Methods Secondary analysis of data from a randomized trial studying communication about depression; participants were asked for optional consent to audio record study visits. Multiple logistic regression was used to model likelihood of patient and clinician consent. Multivariable regression and propensity score analyses were used to estimate effects of audio recording on 6 dependent variables: discussion of depressive symptoms, preventive health, and depression diagnosis; depression treatment recommendations; visit length; visit difficulty. Results Of 867 visits involving 135 primary care clinicians, 39% were recorded. For clinicians, only working in academic settings (P=0.003) and having worked longer at their current practice (P=0.02) were associated with increased likelihood of consent. For patients, white race (P=0.002) and diabetes (P=0.03) were associated with increased likelihood of consent. Neither multivariable regression nor propensity score analyses revealed any significant effects of recording on the variables examined. Conclusion Few clinician or patient characteristics were significantly associated with consent. Audio recording had no significant effect on any dependent variables. Practice Implications Benefits of recording clinic visits likely outweigh the risks of bias in this setting. PMID:25837372
Iterative integral parameter identification of a respiratory mechanics model.
Schranz, Christoph; Docherty, Paul D; Chiew, Yeong Shiong; Möller, Knut; Chase, J Geoffrey
2012-07-18
Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual's model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS) patients. The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.
Qu, Mingkai; Wang, Yan; Huang, Biao; Zhao, Yongcun
2018-06-01
The traditional source apportionment models, such as absolute principal component scores-multiple linear regression (APCS-MLR), are usually susceptible to outliers, which may be widely present in the regional geochemical dataset. Furthermore, the models are merely built on variable space instead of geographical space and thus cannot effectively capture the local spatial characteristics of each source contributions. To overcome the limitations, a new receptor model, robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR), was proposed based on the traditional APCS-MLR model. Then, the new method was applied to the source apportionment of soil metal elements in a region of Wuhan City, China as a case study. Evaluations revealed that: (i) RAPCS-RGWR model had better performance than APCS-MLR model in the identification of the major sources of soil metal elements, and (ii) source contributions estimated by RAPCS-RGWR model were more close to the true soil metal concentrations than that estimated by APCS-MLR model. It is shown that the proposed RAPCS-RGWR model is a more effective source apportionment method than APCS-MLR (i.e., non-robust and global model) in dealing with the regional geochemical dataset. Copyright © 2018 Elsevier B.V. All rights reserved.
Picco, Louisa; Pang, Shirlene; Lau, Ying Wen; Jeyagurunathan, Anitha; Satghare, Pratika; Abdin, Edimansyah; Vaingankar, Janhavi Ajit; Lim, Susan; Poh, Chee Lien; Chong, Siow Ann; Subramaniam, Mythily
2016-12-30
This study aimed to: (i) determine the prevalence, socio-demographic and clinical correlates of internalized stigma and (ii) explore the association between internalized stigma and quality of life, general functioning, hope and self-esteem, among a multi-ethnic Asian population of patients with mental disorders. This cross-sectional, survey recruited adult patients (n=280) who were seeking treatment at outpatient and affiliated clinics of the only tertiary psychiatric hospital in Singapore. Internalized stigma was measured using the Internalized Stigma of Mental Illness scale. 43.6% experienced moderate to high internalized stigma. After making adjustments in multiple logistic regression analysis, results revealed there were no significant socio-demographic or clinical correlates relating to internalized stigma. Individual logistic regression models found a negative relationship between quality of life, self-esteem, general functioning and internalized stigma whereby lower scores were associated with higher internalized stigma. In the final regression model, which included all psychosocial variables together, self-esteem was the only variable significantly and negatively associated with internalized stigma. The results of this study contribute to our understanding of the role internalized stigma plays in patients with mental illness, and the impact it can have on psychosocial aspects of their lives. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.
Regional flow duration curves: Geostatistical techniques versus multivariate regression
Pugliese, Alessio; Farmer, William H.; Castellarin, Attilio; Archfield, Stacey A.; Vogel, Richard M.
2016-01-01
A period-of-record flow duration curve (FDC) represents the relationship between the magnitude and frequency of daily streamflows. Prediction of FDCs is of great importance for locations characterized by sparse or missing streamflow observations. We present a detailed comparison of two methods which are capable of predicting an FDC at ungauged basins: (1) an adaptation of the geostatistical method, Top-kriging, employing a linear weighted average of dimensionless empirical FDCs, standardised with a reference streamflow value; and (2) regional multiple linear regression of streamflow quantiles, perhaps the most common method for the prediction of FDCs at ungauged sites. In particular, Top-kriging relies on a metric for expressing the similarity between catchments computed as the negative deviation of the FDC from a reference streamflow value, which we termed total negative deviation (TND). Comparisons of these two methods are made in 182 largely unregulated river catchments in the southeastern U.S. using a three-fold cross-validation algorithm. Our results reveal that the two methods perform similarly throughout flow-regimes, with average Nash-Sutcliffe Efficiencies 0.566 and 0.662, (0.883 and 0.829 on log-transformed quantiles) for the geostatistical and the linear regression models, respectively. The differences between the reproduction of FDC's occurred mostly for low flows with exceedance probability (i.e. duration) above 0.98.
Liu, Chao-Yu; Huang, Wei-Lieh; Kao, Wei-Chih; Gau, Susan Shur-Fen
2017-12-01
Childhood attention-deficit/hyperactivity disorder (ADHD) and comorbid oppositional defiant disorder/conduct disorder (ODD/CD) are associated with negative school outcomes. The study aimed to examine the impact of ADHD and ODD/CD on various school functions. 395 youths with ADHD (244 with ADHD + ODD/CD and 151 with ADHD only) and 156 controls received semi-structured psychiatric interviews. School functions were assessed and compared between each group with a multiple-level model. The results showed that youths with ADHD had poorer performance across different domains of school functioning. Youths with ADHD + ODD/CD had more behavioral problems but similar academic performance than those with ADHD only. The multiple linear regression models revealed that ADHD impaired academic performance while ODD/CD aggravated behavioral problems. Our findings imply that comorbid ODD/CD may specifically contribute to social difficulties in youths with ADHD. Measures of early detection and intervention for ODD/CD should be conducted to prevent adverse outcomes.
JEFFERSON, ANGELA L.; BARAKAT, LAMIA P.; GIOVANNETTI, TANIA; PAUL, ROBERT H.; GLOSSER, GUILA
2009-01-01
This study examined the contribution of object perception and spatial localization to functional dependence among Alzheimer's disease (AD) patients. Forty patients with probable AD completed measures assessing verbal recognition memory, working memory, object perception, spatial localization, semantic knowledge, and global cognition. Primary caregivers completed a measure of activities of daily living (ADLs) that included instrumental and basic self-care subscales (i.e., IADLs and BADLs, respectively). Stepwise multiple regressions revealed that global cognition accounted for significant portions of variance among the ADL total, IADL, and BADL scores. However, when global cognition was removed from the model, object perception was the only significant cognitive predictor of the ADL total and IADL subscale scores, accounting for 18.5% and 19.3% of the variance, respectively. When considering multiple cognitive components simultaneously, object perception and the integrity of the inferotemporal cortex is important in the completion of functional abilities in general and IADLs in particular among AD patients. PMID:16822730
Oppong Asante, Kwaku; Meyer-Weitz, Anna
2015-02-01
Homeless youth are regarded as an extremely high risk group, susceptible to suicidal ideation substance abuse, and high rates of mental illness. While there exists a substantial body of knowledge regarding resilience of homeless youth, few studies has examined the relationship between perceived resilience and health risk behaviours. The present study describes the findings from a quantitative examination of street-related demographics, resilience, suicidal ideation, substance abuse, sexual risk behaviours and violent related behaviours among 227 homeless youth. The findings revealed that perceived resilience was negatively related to suicidal ideation, substance abuse and violence. Suicidal ideation was positively related to both substance abuse and violence, whilst violence and substance abuse were positively correlated. Multiple regressions showed that perceived resilience served as a protective factor for suicidal ideation and having multiple sexual lifetime partners, suggesting that youth with lower level of perceived resilience were more likely to engage in various health risks behaviours. Copyright © 2014 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.
Self-esteem is associated with perceived stress in multiple sclerosis patients.
N Ifantopoulou, Parthena; K Artemiadis, Artemios; Triantafyllou, Nikolaos; Chrousos, George; Papanastasiou, Ioannis; Darviri, Christina
2015-07-01
Previous studies have showed that perceived stress (PS) in patients with multiple sclerosis (MS) constitutes an important factor for disease onset, relapse, symptomatology and psychological adjustment. The aim of this pilot cross-sectional study was to examine the role of self-esteem in PS, after controlling for sociodemographical characteristics, depression and personality in MS patients. Sixty-six relapsing-remitting MS patients (66.67% females, mean age of 40 ± 11.1 years old, mean duration of disease 133.6 ± 128.8 months) were studied. Perceived stress, self-esteem, depression and personality type were assessed using self-administered questionnaires. Hierarchical multivariate regression modelling was used. Higher education and depression and lower self-esteem were independently and significantly associated with increased PS, accounting for 40.5% of its variance. Univariate analyses revealed that low extroversion and openness and higher neurotism were associated with higher PS, although no significant after adjusting for other factors. Although our findings need further confirmation, psychological interventions targetting self-esteem are strongly encouraged.
Relationship among several measurements of slipperiness obtained in a laboratory environment.
Chang, Wen-Ruey; Chang, Chien-Chi
2018-04-01
Multiple sensing mechanisms could be used in forming responses to avoid slips, but previous studies, correlating only two parameters, revealed a limited picture of this complex system. In this study, the participants walked as fast as possible without a slip under 15 conditions of different degrees of slipperiness. The relationships among various response parameters, including perceived slipperiness rating, utilized coefficient of friction (UCOF), slipmeter measurement and kinematic parameters, were evaluated. The results showed that the UCOF, perceived rating and heel angle had higher adjusted R 2 values as dependent variables in the multiple linear regressions with the remaining variables in the final pool as independent variables. Although each variable in the final data pool could reflect some measurement of slipperiness, these three variables are more inclusive than others in representing the other variables and were bigger predictors of other variables, so they could be better candidates for measurements of slipperiness. Copyright © 2017 Elsevier Ltd. All rights reserved.
A Statistical Multimodel Ensemble Approach to Improving Long-Range Forecasting in Pakistan
2012-03-01
Impact of global warming on monsoon variability in Pakistan. J. Anim. Pl. Sci., 21, no. 1, 107–110. Gillies, S., T. Murphree, and D. Meyer, 2012...are generated by multiple regression models that relate globally distributed oceanic and atmospheric predictors to local predictands. The...generated by multiple regression models that relate globally distributed oceanic and atmospheric predictors to local predictands. The predictands are
Suppression Situations in Multiple Linear Regression
ERIC Educational Resources Information Center
Shieh, Gwowen
2006-01-01
This article proposes alternative expressions for the two most prevailing definitions of suppression without resorting to the standardized regression modeling. The formulation provides a simple basis for the examination of their relationship. For the two-predictor regression, the author demonstrates that the previous results in the literature are…
NASA Astrophysics Data System (ADS)
Yoshida, Kenichiro; Nishidate, Izumi; Ojima, Nobutoshi; Iwata, Kayoko
2014-01-01
To quantitatively evaluate skin chromophores over a wide region of curved skin surface, we propose an approach that suppresses the effect of the shading-derived error in the reflectance on the estimation of chromophore concentrations, without sacrificing the accuracy of that estimation. In our method, we use multiple regression analysis, assuming the absorbance spectrum as the response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as the predictor variables. The concentrations of melanin and total hemoglobin are determined from the multiple regression coefficients using compensation formulae (CF) based on the diffuse reflectance spectra derived from a Monte Carlo simulation. To suppress the shading-derived error, we investigated three different combinations of multiple regression coefficients for the CF. In vivo measurements with the forearm skin demonstrated that the proposed approach can reduce the estimation errors that are due to shading-derived errors in the reflectance. With the best combination of multiple regression coefficients, we estimated that the ratio of the error to the chromophore concentrations is about 10%. The proposed method does not require any measurements or assumptions about the shape of the subjects; this is an advantage over other studies related to the reduction of shading-derived errors.
Byun, Bo-Ram; Kim, Yong-Il; Yamaguchi, Tetsutaro; Maki, Koutaro; Son, Woo-Sung
2015-01-01
This study was aimed to examine the correlation between skeletal maturation status and parameters from the odontoid process/body of the second vertebra and the bodies of third and fourth cervical vertebrae and simultaneously build multiple regression models to be able to estimate skeletal maturation status in Korean girls. Hand-wrist radiographs and cone beam computed tomography (CBCT) images were obtained from 74 Korean girls (6-18 years of age). CBCT-generated cervical vertebral maturation (CVM) was used to demarcate the odontoid process and the body of the second cervical vertebra, based on the dentocentral synchondrosis. Correlation coefficient analysis and multiple linear regression analysis were used for each parameter of the cervical vertebrae (P < 0.05). Forty-seven of 64 parameters from CBCT-generated CVM (independent variables) exhibited statistically significant correlations (P < 0.05). The multiple regression model with the greatest R (2) had six parameters (PH2/W2, UW2/W2, (OH+AH2)/LW2, UW3/LW3, D3, and H4/W4) as independent variables with a variance inflation factor (VIF) of <2. CBCT-generated CVM was able to include parameters from the second cervical vertebral body and odontoid process, respectively, for the multiple regression models. This suggests that quantitative analysis might be used to estimate skeletal maturation status.
ERIC Educational Resources Information Center
Crawford, John R.; Garthwaite, Paul H.; Denham, Annie K.; Chelune, Gordon J.
2012-01-01
Regression equations have many useful roles in psychological assessment. Moreover, there is a large reservoir of published data that could be used to build regression equations; these equations could then be employed to test a wide variety of hypotheses concerning the functioning of individual cases. This resource is currently underused because…
Liu, Kuo; He, Liu; Tang, Xun; Wang, Jinwei; Li, Na; Wu, Yiqun; Marshall, Roger; Li, Jingrong; Zhang, Zongxin; Liu, Jianjiang; Xu, Haitao; Yu, Liping; Hu, Yonghua
2014-01-10
Chinese menopausal women comprise a large population and the women in it experience menopausal symptoms in many different ways. Their health related quality of life (HRQOL) is not particularly well studied. Our study intends to evaluate the influence of menopause on HRQOL and explore other risk factors for HRQOL in rural China. An interview study was conducted from June to August 2010 in Beijing based on cross-sectional design. 1,351 women aged 40-59 were included in the study. HRQOL was measured using the EuroQol Group's 5-domain (EQ5D) questionnaire. Comparison of HRQOL measures (EQ5D index and EQ5D-VAS scores) was done between different menopausal groups. Logistic regression and multiple regression analysis were performed to adjust potential confounders and explore other risk factors for health problems and HRQOL measures. Postmenopausal women who had menopause for 2-5 years (+1b stage) were more likely to suffer mobility problems (OR = 1.835, p = 0.008) after multiple adjustment. Menopause was also related to impaired EQ5D index and EQ5D-VAS scores after adjustment for age. Among menopausal groups categorized by menopausal duration, a consistent decrement in EQ5D index and EQ5D-VAS scores, that is, worsening HRQOL, was observed (p < 0.05). Multiple regression analysis revealed low education level and physical activity were associated with EQ5D index (β = -0.080, p = 0.003, and β = 0.056, p = 0.040, respectively). Cigarette smoking and chronic disease were associated with EQ5D index (β = -0.135, p < 0.001 and β = -0.104, p < 0.001, respectively) and EQ5D-VAS (β = -0.057, P = 0.034 and β = -0.214, p < 0.001, respectively). Reduction in physical function was found within the first five years after menopause. Worsening EQ5D index and EQ5D-VAS scores were related to menopause. Education level, physical activity, cigarette smoking, and chronic disease history were associated with HRQOL in middle aged Chinese rural women.
Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.
Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao
2016-04-01
To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.
Raj, Retheep; Sivanandan, K S
2017-01-01
Estimation of elbow dynamics has been the object of numerous investigations. In this work a solution is proposed for estimating elbow movement velocity and elbow joint angle from Surface Electromyography (SEMG) signals. Here the Surface Electromyography signals are acquired from the biceps brachii muscle of human hand. Two time-domain parameters, Integrated EMG (IEMG) and Zero Crossing (ZC), are extracted from the Surface Electromyography signal. The relationship between the time domain parameters, IEMG and ZC with elbow angular displacement and elbow angular velocity during extension and flexion of the elbow are studied. A multiple input-multiple output model is derived for identifying the kinematics of elbow. A Nonlinear Auto Regressive with eXogenous inputs (NARX) structure based multiple layer perceptron neural network (MLPNN) model is proposed for the estimation of elbow joint angle and elbow angular velocity. The proposed NARX MLPNN model is trained using Levenberg-marquardt based algorithm. The proposed model is estimating the elbow joint angle and elbow movement angular velocity with appreciable accuracy. The model is validated using regression coefficient value (R). The average regression coefficient value (R) obtained for elbow angular displacement prediction is 0.9641 and for the elbow anglular velocity prediction is 0.9347. The Nonlinear Auto Regressive with eXogenous inputs (NARX) structure based multiple layer perceptron neural networks (MLPNN) model can be used for the estimation of angular displacement and movement angular velocity of the elbow with good accuracy.
Factors influencing undergraduates' self-evaluation of numerical competence
NASA Astrophysics Data System (ADS)
Tariq, Vicki N.; Durrani, Naureen
2012-04-01
This empirical study explores factors influencing undergraduates' self-evaluation of their numerical competence, using data from an online survey completed by 566 undergraduates from a diversity of academic disciplines, across all four faculties at a post-1992 UK university. Analysis of the data, which included correlation and multiple regression analyses, revealed that undergraduates exhibiting greater confidence in their mathematical and numeracy skills, as evidenced by their higher self-evaluation scores and their higher scores on the confidence sub-scale contributing to the measurement of attitude, possess more cohesive, rather than fragmented, conceptions of mathematics, and display more positive attitudes towards mathematics/numeracy. They also exhibit lower levels of mathematics anxiety. Students exhibiting greater confidence also tended to be those who were relatively young (i.e. 18-29 years), whose degree programmes provided them with opportunities to practise and further develop their numeracy skills, and who possessed higher pre-university mathematics qualifications. The multiple regression analysis revealed two positive predictors (overall attitude towards mathematics/numeracy and possession of a higher pre-university mathematics qualification) and five negative predictors (mathematics anxiety, lack of opportunity to practise/develop numeracy skills, being a more mature student, being enrolled in Health and Social Care compared with Science and Technology, and possessing no formal mathematics/numeracy qualification compared with a General Certificate of Secondary Education or equivalent qualification) accounted for approximately 64% of the variation in students' perceptions of their numerical competence. Although the results initially suggested that male students were significantly more confident than females, one compounding variable was almost certainly the students' highest pre-university mathematics or numeracy qualification, since a higher percentage of males (24%) compared to females (15%) possessed an Advanced Subsidiary or A2 qualification (or equivalent) in mathematics. Of particular concern is the fact that undergraduates based in Health and Social Care expressed significantly less confidence in their numeracy skills than students from any of the other three faculties.
Shrooti, Shah; Mangala, Shrestha; Nirmala, Pokharel; Devkumari, Shrestha; Dharanidhar, Baral
2016-04-01
Being a mother is considered by many women as their most important role in life. Women's perceptions of their abilities to manage the demands of parenting and the parenting skills they posses are reflected by perceived maternal role competence. The present study was carried out to assess the perceived maternal role competence and its associated factors among mothers. A descriptive cross-sectional research study was carried out on 290 mothers of infant in four immunization clinics of Dharan, Nepal. Data were collected using a standardized predesigned, pretested questionnaire (Parent sense of competence scale, Rosenberg's self esteem scale, Maternity social support scale). The data were analyzed using descriptive and inferential statistics and multiple regression analysis at 0.05 level of significance. The mean score of the perceived maternal role competence obtained by mothers was 64.34±7.90 and those of knowledge/skill and valuing/comfort subscale were 31±6.01 and 33±3.75, respectively. There was a significant association between perceived maternal role competence and factors as the age of the mother (P<0.001), educational status (P=0.015), occupation (P=0.001) and readiness for pregnancy (P=0.022). The study findings revealed a positive correlation between perceived maternal role competence and age at marriage (r=0.132, P=0.024), per capita income (r=0.118, P=0.045), self esteem (r=0.379, P<0.001), social support (r=0.272, P<0.001), and number of support persons (r=0.119, P=0.043). The results of the step wise multiple regression analysis revealed that the major predictor of perceived maternal role competence was self esteem. The factors associated with perceived maternal role competence were age, education, occupation, per capita income, self esteem, social support, and the number of support persons.
Tsuchimine, Shoko; Yasui-Furukori, Norio; Kaneda, Ayako; Kaneko, Sunao
2013-01-01
Background The functional polymorphism Val158Met in the catechol-O-methyltransferase (COMT) gene has been associated with differences in prefrontal cognitive functions in patients with schizophrenia and healthy individuals. Several studies have indicated that the Met allele is associated with better performance on measures of cognitive function. We investigated whether the COMT Val158Met genotype was associated with cognitive function in 149 healthy controls and 118 patients with schizophrenia. Methods Cognitive function, including verbal memory, working memory, motor speed, attention, executive function and verbal fluency, was assessed by the Brief Assessment of Cognition in Schizophrenia (BACS-J). We employed a one-way analysis of variance (ANOVA) and a multiple regression analysis to determine the associations between the COMT Val158Met genotype and the BACS-J measurements. Results The one-way ANOVA revealed a significant difference in the scores on the Tower of London, a measure of executive function, between the different Val158Met genotypes in the healthy controls (p = 0.023), and a post-hoc analysis showed significant differences between the scores on the Tower of London in the val/val genotype group (18.6 ± 2.4) compared to the other two groups (17.6 ± 2.7 for val/met and 17.1 ± 3.2 for met/met; p = 0.027 and p = 0.024, respectively). Multiple regression analyses revealed that executive function was significantly correlated with the Val158Met genotype (p = 0.003). However, no evidence was found for an effect of the COMT on any cognitive domains of the BACS-J in the patients with schizophrenia. Conclusion These data support the hypothesis that the COMT Val158Met genotype maintains an optimal level of dopamine activity. Further studies should be performed that include a larger sample size and include patients on and off medication, as these patients would help to confirm our findings. PMID:24282499
Influence of Day Length and Physical Activity on Sleep Patterns in Older Icelandic Men and Women
Brychta, Robert J.; Arnardottir, Nanna Yr; Johannsson, Erlingur; Wright, Elizabeth C.; Eiriksdottir, Gudny; Gudnason, Vilmundur; Marinac, Catherine R.; Davis, Megan; Koster, Annemarie; Caserotti, Paolo; Sveinsson, Thorarinn; Harris, Tamara; Chen, Kong Y.
2016-01-01
Study Objectives: To identify cross-sectional and seasonal patterns of sleep and physical activity (PA) in community-dwelling, older Icelandic adults using accelerometers. Methods: A seven-day free-living protocol of 244 (110 female) adults aged 79.7 ± 4.9 years was conducted as part of a larger population-based longitudinal observational-cohort study in the greater Reykjavik area of Iceland. A subpopulation (n = 72) repeated the 7-day measurement during seasonal periods with greater (13.4 ± 1.4 h) and lesser (7.7 ± 1.8 h) daylight. Results: Cross-sectional analyses using multiple linear regression models revealed that day length was a significant independent predictor of sleep duration, mid-sleep, and rise time (all p < 0.05). However, the actual within-individual differences in sleep patterns of the repeaters were rather subtle between periods of longer and shorter day-lengths. Compared to women, men had a shorter sleep duration (462 ± 80 vs. 487 ± 68 minutes, p = 0.008), earlier rise time, and a greater number of awakenings per night (46.5 ± 18.3 vs. 40.2 ± 15.7, p = 0.007), but sleep efficiency and onset latency were similar between the two sexes. Daily PA was also similar between men and women and between periods of longer and shorter day-lengths. BMI, age, gender, and overall PA all contributed to the variations in sleep parameters using multiple regression analysis. Conclusions: The sleep and PA characteristics of this unique population revealed some gender differences, but there was limited variation in response to significant daylight changes which may be due to long-term adaptation. Citation: Brychta RJ, Arnardottir NY, Johannsson E, Wright EC, Eiriksdottir G, Gudnason V, Marinac CR, Davis M, Koster A, Caserotti P, Sveinsson T, Harris T, Chen KY. Influence of day length and physical activity on sleep patterns in older Icelandic men and women. J Clin Sleep Med 2016;12(2):203–213. PMID:26414978
Webster, R J; Williams, A; Marchetti, F; Yauk, C L
2018-07-01
Mutations in germ cells pose potential genetic risks to offspring. However, de novo mutations are rare events that are spread across the genome and are difficult to detect. Thus, studies in this area have generally been under-powered, and no human germ cell mutagen has been identified. Whole Genome Sequencing (WGS) of human pedigrees has been proposed as an approach to overcome these technical and statistical challenges. WGS enables analysis of a much wider breadth of the genome than traditional approaches. Here, we performed power analyses to determine the feasibility of using WGS in human families to identify germ cell mutagens. Different statistical models were compared in the power analyses (ANOVA and multiple regression for one-child families, and mixed effect model sampling between two to four siblings per family). Assumptions were made based on parameters from the existing literature, such as the mutation-by-paternal age effect. We explored two scenarios: a constant effect due to an exposure that occurred in the past, and an accumulating effect where the exposure is continuing. Our analysis revealed the importance of modeling inter-family variability of the mutation-by-paternal age effect. Statistical power was improved by models accounting for the family-to-family variability. Our power analyses suggest that sufficient statistical power can be attained with 4-28 four-sibling families per treatment group, when the increase in mutations ranges from 40 to 10% respectively. Modeling family variability using mixed effect models provided a reduction in sample size compared to a multiple regression approach. Much larger sample sizes were required to detect an interaction effect between environmental exposures and paternal age. These findings inform study design and statistical modeling approaches to improve power and reduce sequencing costs for future studies in this area. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.
Quality of life among people living with hypertension in a rural Vietnam community.
Ha, Ninh Thi; Duy, Hoa Thi; Le, Ninh Hoang; Khanal, Vishnu; Moorin, Rachael
2014-08-11
To respond to growing prevalence of hypertension in Vietnam, it is critical to have an in-depth understanding about quality of life (QOL) among people living with hypertension and related factors. This study aimed to measure QOL among hypertensive people in a rural community in Vietnam, and its association with socio-demographic characteristics and factors related to treatment. This study was conducted in a rural community located 60 km from Ho Chi Minh City. Face-to-face interviews were conducted among 275 hypertensive people aged 50 years and above using WHOQOL-BREF questionnaire. Descriptive statistics were used to examine mean scores of quality of life. Cronbach's alpha coefficient and Pearson's correlation coefficient were applied to estimate the internal consistency, and the level of agreement between different domains of WHOQOL-BREF, respectively. Independent T-test and ANOVA test followed by multiple linear regression analyses were used to measure the association between QOL domains and independent variables. Both overall WHOQOL-BREF and each domain had a good internal consistency, ranging from 0.65 to 0.88. The QOL among hypertensive patients was found moderate in all domains, except for psychological domain that was fairly low (mean = 49.4). Backward multiple linear regressions revealed that being men, married, attainment of higher education, having physical activities at moderate level, and adherence to treatment were positively associated with QOL. However, older age and presence of co-morbidity were negatively associated with QOL. WHOQOL-BREF is a reliable instrument to measure QOL among hypertensive patients. The results revealed low QOL in psychological domain and inequality in QOL across socio-demographic characteristics. Given the results, encouraging physical activities and strengthening treatment adherence should be considered to improve QOL of hypertensive people, especially for psychological aspect. Actions to improve QOL among hypertensive patients targeted towards women, lower educated and unmarried patients are needed in the setting.
Cardoso, Flávia G R; Ferreira, Nádia S; Martinho, Frederico C; Nascimento, Gustavo G; Manhães, Luiz R C; Rocco, Marco A; Carvalho, Cláudio A T; Valera, Marcia C
2015-07-01
This clinical study was conducted to correlate the levels of endotoxins and bacterial counts found in primary endodontic infection with the volume of periapical bone destruction determined by cone-beam computed tomography (CBCT) analysis. Moreover, the levels of bacteria and endotoxins were correlated with the development of clinical features. Twenty-four root canals with primary endodontic disease and apical periodontitis were selected. Clinical features such as pain on palpation, pain on percussion, and previous episode of pain were recorded. The volume (cubic millimeters) of periapical bone destruction was determined by CBCT analysis. Endotoxins and bacterial samplings were collected by using sterile/apyrogenic paper points. Endotoxins were quantified by using limulus amebocyte lysate assay (KQCL test), and bacterial count (colony-forming units [CFU]/mL) was determined by using anaerobic culture techniques. Data were analyzed by Pearson correlation and multiple logistic regression (P < .05). Endotoxins and bacteria were detected in 100% of the root canal samples (24 of 24), with median values of 10.92 endotoxin units (EU)/mL (1.75-128 EU/mL) and 7.5 × 10(5) CFU/mL (3.20 × 10(5)-8.16 × 10(6) CFU/mL), respectively. The median volume of bone destruction determined by CBCT analysis was 100 mm(3) (10-450 mm(3)). The multiple regression analysis revealed a positive correlation between higher levels of endotoxins present in root canal infection and larger volume of bone destruction (P < .05). Moreover, higher levels of endotoxins were also correlated with the presence of previous pain (P < .05). Our findings revealed that the levels of endotoxins found in root canal infection are related to the volume of periapical bone destruction determined by CBCT analysis. Moreover, the levels of endotoxin are related to the presence of previous pain. Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.
Regression Commonality Analysis: A Technique for Quantitative Theory Building
ERIC Educational Resources Information Center
Nimon, Kim; Reio, Thomas G., Jr.
2011-01-01
When it comes to multiple linear regression analysis (MLR), it is common for social and behavioral science researchers to rely predominately on beta weights when evaluating how predictors contribute to a regression model. Presenting an underutilized statistical technique, this article describes how organizational researchers can use commonality…
Precision Efficacy Analysis for Regression.
ERIC Educational Resources Information Center
Brooks, Gordon P.
When multiple linear regression is used to develop a prediction model, sample size must be large enough to ensure stable coefficients. If the derivation sample size is inadequate, the model may not predict well for future subjects. The precision efficacy analysis for regression (PEAR) method uses a cross- validity approach to select sample sizes…
Kunnuji, Michael
2014-01-01
Research has shown that in countries such as Nigeria many urban dwellers live in a state of squalour and lack the basic necessities of food, clothing and shelter. The present study set out to examine the association between forms of basic deprivation--such as food deprivation, high occupancy ratio as a form of shelter deprivation, and inadequate clothing--and two sexual outcomes--timing of onset of penetrative sex and involvement in multiple sexual partnerships. The study used survey data from a sample of 480 girls resident in Iwaya community. A survival analysis of the timing of onset of sex and a regression model for involvement in multiple sexual partnerships reveal that among the forms of deprivation explored, food deprivation is the only significant predictor of the timing of onset of sex and involvement in multiple sexual partnerships. The study concludes that the sexual activities of poor out-of-school girls are partly explained by their desire to overcome food deprivation and recommends that government and non-governmental-organisation programmes working with young people should address the problem of basic deprivation among adolescent girls.
Rasmussen, Patrick P.; Gray, John R.; Glysson, G. Douglas; Ziegler, Andrew C.
2009-01-01
In-stream continuous turbidity and streamflow data, calibrated with measured suspended-sediment concentration data, can be used to compute a time series of suspended-sediment concentration and load at a stream site. Development of a simple linear (ordinary least squares) regression model for computing suspended-sediment concentrations from instantaneous turbidity data is the first step in the computation process. If the model standard percentage error (MSPE) of the simple linear regression model meets a minimum criterion, this model should be used to compute a time series of suspended-sediment concentrations. Otherwise, a multiple linear regression model using paired instantaneous turbidity and streamflow data is developed and compared to the simple regression model. If the inclusion of the streamflow variable proves to be statistically significant and the uncertainty associated with the multiple regression model results in an improvement over that for the simple linear model, the turbidity-streamflow multiple linear regression model should be used to compute a suspended-sediment concentration time series. The computed concentration time series is subsequently used with its paired streamflow time series to compute suspended-sediment loads by standard U.S. Geological Survey techniques. Once an acceptable regression model is developed, it can be used to compute suspended-sediment concentration beyond the period of record used in model development with proper ongoing collection and analysis of calibration samples. Regression models to compute suspended-sediment concentrations are generally site specific and should never be considered static, but they represent a set period in a continually dynamic system in which additional data will help verify any change in sediment load, type, and source.
Jacob, Benjamin G; Novak, Robert J; Toe, Laurent; Sanfo, Moussa S; Afriyie, Abena N; Ibrahim, Mohammed A; Griffith, Daniel A; Unnasch, Thomas R
2012-01-01
The standard methods for regression analyses of clustered riverine larval habitat data of Simulium damnosum s.l. a major black-fly vector of Onchoceriasis, postulate models relating observational ecological-sampled parameter estimators to prolific habitats without accounting for residual intra-cluster error correlation effects. Generally, this correlation comes from two sources: (1) the design of the random effects and their assumed covariance from the multiple levels within the regression model; and, (2) the correlation structure of the residuals. Unfortunately, inconspicuous errors in residual intra-cluster correlation estimates can overstate precision in forecasted S.damnosum s.l. riverine larval habitat explanatory attributes regardless how they are treated (e.g., independent, autoregressive, Toeplitz, etc). In this research, the geographical locations for multiple riverine-based S. damnosum s.l. larval ecosystem habitats sampled from 2 pre-established epidemiological sites in Togo were identified and recorded from July 2009 to June 2010. Initially the data was aggregated into proc genmod. An agglomerative hierarchical residual cluster-based analysis was then performed. The sampled clustered study site data was then analyzed for statistical correlations using Monthly Biting Rates (MBR). Euclidean distance measurements and terrain-related geomorphological statistics were then generated in ArcGIS. A digital overlay was then performed also in ArcGIS using the georeferenced ground coordinates of high and low density clusters stratified by Annual Biting Rates (ABR). This data was overlain onto multitemporal sub-meter pixel resolution satellite data (i.e., QuickBird 0.61m wavbands ). Orthogonal spatial filter eigenvectors were then generated in SAS/GIS. Univariate and non-linear regression-based models (i.e., Logistic, Poisson and Negative Binomial) were also employed to determine probability distributions and to identify statistically significant parameter estimators from the sampled data. Thereafter, Durbin-Watson test statistics were used to test the null hypothesis that the regression residuals were not autocorrelated against the alternative that the residuals followed an autoregressive process in AUTOREG. Bayesian uncertainty matrices were also constructed employing normal priors for each of the sampled estimators in PROC MCMC. The residuals revealed both spatially structured and unstructured error effects in the high and low ABR-stratified clusters. The analyses also revealed that the estimators, levels of turbidity and presence of rocks were statistically significant for the high-ABR-stratified clusters, while the estimators distance between habitats and floating vegetation were important for the low-ABR-stratified cluster. Varying and constant coefficient regression models, ABR- stratified GIS-generated clusters, sub-meter resolution satellite imagery, a robust residual intra-cluster diagnostic test, MBR-based histograms, eigendecomposition spatial filter algorithms and Bayesian matrices can enable accurate autoregressive estimation of latent uncertainity affects and other residual error probabilities (i.e., heteroskedasticity) for testing correlations between georeferenced S. damnosum s.l. riverine larval habitat estimators. The asymptotic distribution of the resulting residual adjusted intra-cluster predictor error autocovariate coefficients can thereafter be established while estimates of the asymptotic variance can lead to the construction of approximate confidence intervals for accurately targeting productive S. damnosum s.l habitats based on spatiotemporal field-sampled count data.
Dagenais, Emmanuelle; Rouleau, Isabelle; Tremblay, Alexandra; Demers, Mélanie; Roger, Élaine; Jobin, Céline; Duquette, Pierre
2016-01-01
Patients diagnosed with multiple sclerosis (MS) often report prospective memory (PM) deficits. Although PM is important for daily functioning, it is not formally assessed in clinical practice. The aim of this study was to examine the role of executive functions in MS patients' PM revealed by the effect of strength of cue-action association on PM performance. Thirty-nine MS patients were compared to 18 healthy controls matched for age, gender, and education on a PM task modulating the strength of association between the cue and the intended action. Deficits in MS patients affecting both prospective and retrospective components of PM were confirmed using 2 × 2 × 2 mixed analyses of variance (ANOVAs). Among patients, multiple regression analyses revealed that the impairment was modulated by the efficiency of executive functions, whereas retrospective memory seemed to have little impact on PM performance, contrary to expectation. More specifically, results of 2 × 2 × 2 mixed-model analyses of covariance (ANCOVAs) showed that low-executive patients had more difficulty detecting and, especially, retrieving the appropriate action when the cue and the action were unrelated, whereas high-executive patients' performance seemed to be virtually unaffected by the cue-action association. Using an objective measure, these findings confirm the presence of PM deficits in MS. They also suggest that such deficits depend on executive functioning and can be reduced when automatic PM processes are engaged through semantic cue-action association. They underscore the importance of assessing PM in clinical settings through a cognitive evaluation and offer an interesting avenue for rehabilitation.
The prediction of intelligence in preschool children using alternative models to regression.
Finch, W Holmes; Chang, Mei; Davis, Andrew S; Holden, Jocelyn E; Rothlisberg, Barbara A; McIntosh, David E
2011-12-01
Statistical prediction of an outcome variable using multiple independent variables is a common practice in the social and behavioral sciences. For example, neuropsychologists are sometimes called upon to provide predictions of preinjury cognitive functioning for individuals who have suffered a traumatic brain injury. Typically, these predictions are made using standard multiple linear regression models with several demographic variables (e.g., gender, ethnicity, education level) as predictors. Prior research has shown conflicting evidence regarding the ability of such models to provide accurate predictions of outcome variables such as full-scale intelligence (FSIQ) test scores. The present study had two goals: (1) to demonstrate the utility of a set of alternative prediction methods that have been applied extensively in the natural sciences and business but have not been frequently explored in the social sciences and (2) to develop models that can be used to predict premorbid cognitive functioning in preschool children. Predictions of Stanford-Binet 5 FSIQ scores for preschool-aged children is used to compare the performance of a multiple regression model with several of these alternative methods. Results demonstrate that classification and regression trees provided more accurate predictions of FSIQ scores than does the more traditional regression approach. Implications of these results are discussed.
Optimization of fixture layouts of glass laser optics using multiple kernel regression.
Su, Jianhua; Cao, Enhua; Qiao, Hong
2014-05-10
We aim to build an integrated fixturing model to describe the structural properties and thermal properties of the support frame of glass laser optics. Therefore, (a) a near global optimal set of clamps can be computed to minimize the surface shape error of the glass laser optic based on the proposed model, and (b) a desired surface shape error can be obtained by adjusting the clamping forces under various environmental temperatures based on the model. To construct the model, we develop a new multiple kernel learning method and call it multiple kernel support vector functional regression. The proposed method uses two layer regressions to group and order the data sources by the weights of the kernels and the factors of the layers. Because of that, the influences of the clamps and the temperature can be evaluated by grouping them into different layers.
Prediction of anthropometric foot characteristics in children.
Morrison, Stewart C; Durward, Brian R; Watt, Gordon F; Donaldson, Malcolm D C
2009-01-01
The establishment of growth reference values is needed in pediatric practice where pathologic conditions can have a detrimental effect on the growth and development of the pediatric foot. This study aims to use multiple regression to evaluate the effects of multiple predictor variables (height, age, body mass, and gender) on anthropometric characteristics of the peripubescent foot. Two hundred children aged 9 to 12 years were recruited, and three anthropometric measurements of the pediatric foot were recorded (foot length, forefoot width, and navicular height). Multiple regression analysis was conducted, and coefficients for gender, height, and body mass all had significant relationships for the prediction of forefoot width and foot length (P < or = .05, r > or = 0.7). The coefficients for gender and body mass were not significant for the prediction of navicular height (P > or = .05), whereas height was (P < or = .05). Normative growth reference values and prognostic regression equations are presented for the peripubescent foot.
Optimizing methods for linking cinematic features to fMRI data.
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.
Weighted regression analysis and interval estimators
Donald W. Seegrist
1974-01-01
A method for deriving the weighted least squares estimators for the parameters of a multiple regression model. Confidence intervals for expected values, and prediction intervals for the means of future samples are given.
Chang, Ying-Chih; Yeh, Tsu-Ming; Pai, Fan-Yun; Huang, Tai-Peng
2018-05-10
This study intends to discuss the effects of participants’ involvement, perceived value, and leisure benefits on recommendation intention in the sport of karate. The questionnaires were collected online by karate clubs on Facebook and included 369 valid participants. The research findings show that karate participants from different places of residence do not display significant differences in involvement, perceived value, leisure benefits, and recommendation intention. Furthermore, “attraction” in the involvement category reveals the highest mean, “paid spirit and energy being worthy” in perceived value appears as the highest mean, and “physiological benefits” in leisure benefits shows the highest mean. The Pearson correlation analysis result presents significant strong positive correlations between involvement, perceived value, leisure benefits, and recommendation intention. Finally, multiple regression analysis reveals that leisure benefits, except “physiological benefits”, show notably positive effects on recommendation intention. According to the research results, suggestions are proposed for the reference of karate teaching business managers, participants, and future research.
Chang, Ying-Chih; Pai, Fan-Yun; Huang, Tai-Peng
2018-01-01
This study intends to discuss the effects of participants’ involvement, perceived value, and leisure benefits on recommendation intention in the sport of karate. The questionnaires were collected online by karate clubs on Facebook and included 369 valid participants. The research findings show that karate participants from different places of residence do not display significant differences in involvement, perceived value, leisure benefits, and recommendation intention. Furthermore, “attraction” in the involvement category reveals the highest mean, “paid spirit and energy being worthy” in perceived value appears as the highest mean, and “physiological benefits” in leisure benefits shows the highest mean. The Pearson correlation analysis result presents significant strong positive correlations between involvement, perceived value, leisure benefits, and recommendation intention. Finally, multiple regression analysis reveals that leisure benefits, except “physiological benefits”, show notably positive effects on recommendation intention. According to the research results, suggestions are proposed for the reference of karate teaching business managers, participants, and future research. PMID:29748459
LaVoi, Nicole M; Stellino, Megan Babkes
2008-09-01
The authors examined achievement goal orientation (J. L. Duda & J. G. Nicholls, 1992), parental influence (M. L. Babkes & M. R. Weiss, 1999), and the parent-initiated motivational climate (S. A. White, 1996, 1998) in combination to broaden understanding of competitive male youth hockey players' (N = 259) perceptions of the parent-created sport climate and its relation to their self-reported good and poor sport behaviors (GPSB). Exploratory factor analysis revealed a multidimensional measure of GPSB. Multiple regression analyses indicated that athletes' GPSB were significantly predicted by different forms of parental influence. Canonical correlations revealed a complex picture of the contributions of goal orientation and the parent-created sport climate on boys' GPSB in youth hockey. Results expand knowledge of the influence that parents have in youth sport and emphasize the importance of understanding how children's interpretations of parental beliefs and behaviors affect their choices to engage in good and poor sport behaviors.
The relationship between psychosocial maturity and assertiveness in males and females.
Goldman, J A; Olczak, P V
1981-02-01
The relationship between psychosocial maturity (psychological health) and assertiveness was investigated in a sample of United States college males and females. Results revealed a moderately high positive relationship between psychosocial maturity (PSM) and self-reported assertiveness on the Rathus and Galassi scales for both sexes. This relationship was slightly stronger (in terms of variance accounted for) for males than females, significant differences being obtained for Intimacy on the Rathus scale and PSM and Intimacy on the Galassi scale. Multiple regression analyses revealed that the personality components most consistently accounting for major portions of the variance in predicting male assertiveness scores on both the Rathus Assertiveness Schedule and the College Self-Expression Scale were Intimacy and Initiative, while in predicting female assertiveness, only Initiative was involved. The findings were related to previous research, recent work on the androgyny construct (instrumental vs. expressive behaviors), and exhortations for increased cooperation between schools of psychotherapy to establish it as a more unified discipline.
Logic regression and its extensions.
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.
Chen, Ying-Jen; Ho, Meng-Yang; Chen, Kwan-Ju; Hsu, Chia-Fen; Ryu, Shan-Jin
2009-08-01
The aims of the present study were to (i) investigate if traditional Chinese word reading ability can be used for estimating premorbid general intelligence; and (ii) to provide multiple regression equations for estimating premorbid performance on Raven's Standard Progressive Matrices (RSPM), using age, years of education and Chinese Graded Word Reading Test (CGWRT) scores as predictor variables. Four hundred and twenty-six healthy volunteers (201 male, 225 female), aged 16-93 years (mean +/- SD, 41.92 +/- 18.19 years) undertook the tests individually under supervised conditions. Seventy percent of subjects were randomly allocated to the derivation group (n = 296), and the rest to the validation group (n = 130). RSPM score was positively correlated with CGWRT score and years of education. RSPM and CGWRT scores and years of education were also inversely correlated with age, but the declining trend for RSPM performance against age was steeper than that for CGWRT performance. Separate multiple regression equations were derived for estimating RSPM scores using different combinations of age, years of education, and CGWRT score for both groups. The multiple regression coefficient of each equation ranged from 0.71 to 0.80 with the standard error of estimate between 7 and 8 RSPM points. When fitting the data of one group to the equations derived from its counterpart group, the cross-validation multiple regression coefficients ranged from 0.71 to 0.79. There were no significant differences in the 'predicted-obtained' RSPM discrepancies between any equations. The regression equations derived in the present study may provide a basis for estimating premorbid RSPM performance.
Tay, Cheryl Sihui; Sterzing, Thorsten; Lim, Chen Yen; Ding, Rui; Kong, Pui Wah
2017-05-01
This study examined (a) the strength of four individual footwear perception factors to influence the overall preference of running shoes and (b) whether these perception factors satisfied the nonmulticollinear assumption in a regression model. Running footwear must fulfill multiple functional criteria to satisfy its potential users. Footwear perception factors, such as fit and cushioning, are commonly used to guide shoe design and development, but it is unclear whether running-footwear users are able to differentiate one factor from another. One hundred casual runners assessed four running shoes on a 15-cm visual analogue scale for four footwear perception factors (fit, cushioning, arch support, and stability) as well as for overall preference during a treadmill running protocol. Diagnostic tests showed an absence of multicollinearity between factors, where values for tolerance ranged from .36 to .72, corresponding to variance inflation factors of 2.8 to 1.4. The multiple regression model of these four footwear perception variables accounted for 77.7% to 81.6% of variance in overall preference, with each factor explaining a unique part of the total variance. Casual runners were able to rate each footwear perception factor separately, thus assigning each factor a true potential to improve overall preference for the users. The results also support the use of a multiple regression model of footwear perception factors to predict overall running shoe preference. Regression modeling is a useful tool for running-shoe manufacturers to more precisely evaluate how individual factors contribute to the subjective assessment of running footwear.
A population-based study on the association between rheumatoid arthritis and voice problems.
Hah, J Hun; An, Soo-Youn; Sim, Songyong; Kim, So Young; Oh, Dong Jun; Park, Bumjung; Kim, Sung-Gyun; Choi, Hyo Geun
2016-07-01
The objective of this study was to investigate whether rheumatoid arthritis increases the frequency of organic laryngeal lesions and the subjective voice complaint rate in those with no organic laryngeal lesion. We performed a cross-sectional study using the data from 19,368 participants (418 rheumatoid arthritis patients and 18,950 controls) of the 2008-2011 Korea National Health and Nutrition Examination Survey. The associations between rheumatoid arthritis and organic laryngeal lesions/subjective voice complaints were analyzed using simple/multiple logistic regression analysis with complex sample adjusting for confounding factors, including age, sex, smoking status, stress level, and body mass index, which could provoke voice problems. Vocal nodules, vocal polyp, and vocal palsy were not associated with rheumatoid arthritis in a multiple regression analysis, and only laryngitis showed a positive association (adjusted odds ratio, 1.59; 95 % confidence interval, 1.01-2.52; P = 0.047). Rheumatoid arthritis was associated with subjective voice discomfort in a simple regression analysis, but not in a multiple regression analysis. Participants with rheumatoid arthritis were older, more often female, and had higher stress levels than those without rheumatoid arthritis. These factors were associated with subjective voice complaints in both simple and multiple regression analyses. Rheumatoid arthritis was not associated with organic laryngeal diseases except laryngitis. Rheumatoid arthritis did not increase the odds ratio for subjective voice complaints. Voice problems in participants with rheumatoid arthritis originated from the characteristics of the rheumatoid arthritis group (higher mean age, female sex, and stress level) rather than rheumatoid arthritis itself.
Predicting MHC-II binding affinity using multiple instance regression
EL-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant
2011-01-01
Reliably predicting the ability of antigen peptides to bind to major histocompatibility complex class II (MHC-II) molecules is an essential step in developing new vaccines. Uncovering the amino acid sequence correlates of the binding affinity of MHC-II binding peptides is important for understanding pathogenesis and immune response. The task of predicting MHC-II binding peptides is complicated by the significant variability in their length. Most existing computational methods for predicting MHC-II binding peptides focus on identifying a nine amino acids core region in each binding peptide. We formulate the problems of qualitatively and quantitatively predicting flexible length MHC-II peptides as multiple instance learning and multiple instance regression problems, respectively. Based on this formulation, we introduce MHCMIR, a novel method for predicting MHC-II binding affinity using multiple instance regression. We present results of experiments using several benchmark datasets that show that MHCMIR is competitive with the state-of-the-art methods for predicting MHC-II binding peptides. An online web server that implements the MHCMIR method for MHC-II binding affinity prediction is freely accessible at http://ailab.cs.iastate.edu/mhcmir. PMID:20855923
Burgette, Lane F; Reiter, Jerome P
2013-06-01
Multinomial outcomes with many levels can be challenging to model. Information typically accrues slowly with increasing sample size, yet the parameter space expands rapidly with additional covariates. Shrinking all regression parameters towards zero, as often done in models of continuous or binary response variables, is unsatisfactory, since setting parameters equal to zero in multinomial models does not necessarily imply "no effect." We propose an approach to modeling multinomial outcomes with many levels based on a Bayesian multinomial probit (MNP) model and a multiple shrinkage prior distribution for the regression parameters. The prior distribution encourages the MNP regression parameters to shrink toward a number of learned locations, thereby substantially reducing the dimension of the parameter space. Using simulated data, we compare the predictive performance of this model against two other recently-proposed methods for big multinomial models. The results suggest that the fully Bayesian, multiple shrinkage approach can outperform these other methods. We apply the multiple shrinkage MNP to simulating replacement values for areal identifiers, e.g., census tract indicators, in order to protect data confidentiality in public use datasets.
Weintraub, Amy; Mellins, Claude; Warne, Patricia; Dolezal, Curtis; Elkington, Katherine; Bucek, Amelia; Leu, Cheng-Shiun; Bamji, Mahrukh; Wiznia, Andrew; Abrams, Elaine J
2017-01-01
Similar to same-age peers, perinatally HIV-infected (PHIV+) youth in the US are engaging in sex, including condomless sex. Understanding decisions about serostatus disclosure to sexual partners is important to domestic and global HIV prevention efforts, since large numbers of PHIV+ children are entering adolescence and becoming sexually active. Using Social Action Theory (SAT) to inform variable selection, we examined correlates of disclosure among 98 PHIV+ adolescents/young adults in New York City. Over half of these youth reported not disclosing to any casual partners (59%) and to any partners when using condoms (55%). In simple regression analyses, increased disclosure was associated with older age; being female; earlier age of learning one’s serostatus; and increased STD knowledge, disclosure intentions, and parent-child communication. Multiple regression analyses revealed a strong fit with the SAT model. As with adults, disclosure to sexual partners is difficult for PHIV+ youth and challenges prevention efforts. Effective interventions that help youth with disclosure decisions are needed to curb the epidemic. PMID:26874846
Factors influencing mercury concentrations in walleyes in northern Wisconsin lakes
Wiener, J.G.; Martini, R.E.; Sheffy, T.B.; Glass, G.E.
1990-01-01
The authors examined relations between mercury concentrations in walleyes Stizostedion vitreum and the characteristics of clear-water Wisconsin lakes, which spanned a broad range of pH values (5.0-8.1) and acid- neutralizing capacities (-9 to 1,017 mu eq/L). Total concentrations of mercury in axial muscle tissue of walleyes (total length, 25-56 cm) varied from 0.12 to 1.74 mu g/g wet weight. Concentrations were greatest in fish from the eight lakes with pH less than 7.0; concentrations in these fish equaled or exceeded 0.5 mu g/g in 88% of the samples analyzed and 1.0 mu g/g in 44%. In the five lakes with pH of 7.0 and above, concentrations exceeded 0.5 mu g/g in only 1 of 21 walleyes. Multiple regression revealed that lake pH and total length of fish accounted for 69% of the variation in mercury concentration in walleyes. Regression models with total length and either waterborne calcium or acid-neutralizing capacity as independent variables accounted for 67% of the variation in concentration.
Predictors of quality of life for fathers and mothers of children with autistic disorder.
Dardas, Latefa Ali; Ahmad, Muayyad M
2014-06-01
A constant challenge for Quality of Life (QoL) research is tapping the most predictive indicators for a specific population. This study has sought to examine predictors of QoL for fathers and mothers of children with Autistic Disorder. Two multiple regression analyses were performed for fathers (N=70) and mothers (N=114) of children with Autistic Disorder. Six predictors were entered into the regression equation: Parental Distress (PD), Parent-Child Dysfunction Interaction (PCDI), Difficult Child Characteristics (DC), Household income, and the child's with Autistic Disorder age and number of siblings. The analyses revealed that only PD was a significant predictor for both parent's QoL, whereas DC, household income, and number of siblings were able to predict only mothers' QoL. To our knowledge, this is the first study to focus on predictors of QoL among both fathers and mothers of children with Autistic Disorder. The results from the current study can have several implications for professionals and researchers targeting the primary force contributing to the wellbeing of children with Autistic Disorder, the parents. Copyright © 2014 Elsevier Ltd. All rights reserved.
Serum resistin is associated with the severity of microangiopathies in type 2 diabetes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Osawa, Haruhiko; Ochi, Masaaki; Kato, Kenichi
2007-04-06
Resistin, secreted from adipocytes, causes insulin resistance and diabetes in rodents. To determine the relation between serum resistin and diabetic microangiopathies in humans, we analyzed 238 Japanese T2DM subjects. Mean serum resistin was higher in subjects with either advanced retinopathy (preproliferative or proliferative) (P = 0.0130), advanced nephropathy (stage III or IV) (P = 0.0151), or neuropathy (P = 0.0013). Simple regression analysis showed that serum resistin was positively correlated with retinopathy stage (P = 0.0212), nephropathy stage (P = 0.0052), and neuropathy (P = 0.0013). Multiple regression analysis adjusted for age, gender, and BMI, revealed that serum resistin wasmore » correlated with retinopathy stage (P = 0.0144), nephropathy stage (P = 0.0111), and neuropathy (P = 0.0053). Serum resistin was positively correlated with the number of advanced microangiopathies, independent of age, gender, BMI, and either the duration of T2DM (P = 0.0318) or serum creatinine (P = 0.0092). Therefore, serum resistin was positively correlated with the severity of microangiopathies in T2DM.« less
Fossati, Andrea; Somma, Antonella; Borroni, Serena; Maffei, Cesare; Markon, Kristian E; Krueger, Robert F
2016-02-01
In order to evaluate if measures of DSM-5 Alternative PD Model domains predicted interview-based scores of general personality pathology when compared to self-report measures of DSM-IV Axis II/DSM-5 Section II PD criteria, 300 Italian community adults were administered the Iowa Personality Disorder Screen (IPDS) interview, the Personality Inventory for DSM-5 (PID-5), and the Personality Diagnostic Questionnaire-4+ (PDQ-4+). Multiple regression analyses showed that the five PID-5 domain scales collectively explained an adequate rate of the variance of the IPDS interview total score. This result was slightly lower than the amount of variance in the IPDS total score explained by the 10 PDQ-4+ scales. The PID-5 traits scales performed better than the PDQ-4+, although the difference was marginal. Hierarchical regression analyses revealed that the PID-5 domain and trait scales provided a moderate, but significant increase in the prediction of the general level of personality pathology above and beyond the PDQ-4+ scales.
Kernel analysis of partial least squares (PLS) regression models.
Shinzawa, Hideyuki; Ritthiruangdej, Pitiporn; Ozaki, Yukihiro
2011-05-01
An analytical technique based on kernel matrix representation is demonstrated to provide further chemically meaningful insight into partial least squares (PLS) regression models. The kernel matrix condenses essential information about scores derived from PLS or principal component analysis (PCA). Thus, it becomes possible to establish the proper interpretation of the scores. A PLS model for the total nitrogen (TN) content in multiple Thai fish sauces is built with a set of near-infrared (NIR) transmittance spectra of the fish sauce samples. The kernel analysis of the scores effectively reveals that the variation of the spectral feature induced by the change in protein content is substantially associated with the total water content and the protein hydration. Kernel analysis is also carried out on a set of time-dependent infrared (IR) spectra representing transient evaporation of ethanol from a binary mixture solution of ethanol and oleic acid. A PLS model to predict the elapsed time is built with the IR spectra and the kernel matrix is derived from the scores. The detailed analysis of the kernel matrix provides penetrating insight into the interaction between the ethanol and the oleic acid.
Family conflict and depression in HIV-negative heterosexuals: the role of methamphetamine use.
Semple, Shirley J; Strathdee, Steffanie A; Zians, Jim; Patterson, Thomas L
2009-06-01
Previous research has reported elevated levels of depressive symptoms among methamphetamine users, but little attention has been paid to possible links between family environment and psychological distress. This study examined relationships between family conflict, substance use, and depressive symptoms in a sample of 104 heterosexual methamphetamine users in San Diego, California. Eighty-nine percent of the sample reported conflict with a family member in the past year. Conflict was reported most often with parents and siblings. Sources of conflict included drug use, lifestyle issues, interpersonal and communication issues, and concern for other family members. In regression analyses, being female, being a polydrug user, and facing social and legal stressors were associated with higher levels of family conflict. Multiple regression analyses also revealed a positive association between family conflict and depressive symptoms. Contrary to expectation, methamphetamine dose did not moderate the relationship between family conflict and depressive symptoms. Reducing family conflict may be an important first step toward ameliorating depressive symptoms and creating more supportive environments for methamphetamine users who are in urgent need of effective interventions. Copyright (c) 2009 APA, all rights reserved.
Socioeconomic Disparities in Telephone-Based Treatment of Tobacco Dependence
Varghese, Merilyn; Stitzer, Maxine; Landes, Reid; Brackman, S. Laney; Munn, Tiffany
2014-01-01
Objectives. We examined socioeconomic disparities in tobacco dependence treatment outcomes from a free, proactive telephone counseling quitline. Methods. We delivered cognitive–behavioral treatment and nicotine patches to 6626 smokers and examined socioeconomic differences in demographic, clinical, environmental, and treatment use factors. We used logistic regressions and generalized estimating equations (GEE) to model abstinence and account for socioeconomic differences in the models. Results. The odds of achieving long-term abstinence differed by socioeconomic status (SES). In the GEE model, the odds of abstinence for the highest SES participants were 1.75 times those of the lowest SES participants. Logistic regression models revealed no treatment outcome disparity at the end of treatment, but significant disparities 3 and 6 months after treatment. Conclusions. Although quitlines often increase access to treatment for some lower SES smokers, significant socioeconomic disparities in treatment outcomes raise questions about whether current approaches are contributing to tobacco-related socioeconomic health disparities. Strategies to improve treatment outcomes for lower SES smokers might include novel methods to address multiple factors associated with socioeconomic disparities. PMID:24922165
Family conflict and depression in HIV-negative heterosexuals: The role of methamphetamine use
Semple, Shirley J.; Strathdee, Steffanie A.; Zians, Jim; Patterson, Thomas L.
2009-01-01
Previous research has reported elevated levels of depressive symptoms among methamphetamine users, but little attention has been paid to possible links between family environment and psychological distress. This study examined relationships between family conflict, substance use, and depressive symptoms in a sample of 104 heterosexual methamphetamine users in San Diego, CA. Eighty-nine percent of the sample reported conflict with a family member in the past year. Conflict was reported most often with parents and siblings. Sources of conflict included drug use, lifestyle issues, interpersonal and communication issues, and concern for other family members. In regression analyses, being female, being a polydrug user, and facing social and legal stressors were associated with higher levels of family conflict. Multiple regression analyses also revealed a positive association between family conflict and depressive symptoms. Contrary to expectation, methamphetamine dose did not moderate the relationship between family conflict and depressive symptoms. Reducing family conflict may be an important first step toward ameliorating depressive symptoms and creating more supportive environments for methamphetamine users who are in urgent need of effective interventions. PMID:19586151
Kim, Tae Kyung; Lee, H-C; Lee, S G; Han, K-T; Park, E-C
2017-01-01
Introduction Reports of sexual harassment are becoming more frequent in Republic of Korea (ROK) Armed Forces. This study aimed to analyse the impact of sexual harassment on mental health among female military personnel of the ROK Armed Forces. Methods Data from the 2014 Military Health Survey were used. Instances of sexual harassment were recorded as ‘yes’ or ‘no’. Analysis of variance (ANOVA) was carried out to compare Kessler Psychological Distress Scale 10 (K-10) scores. Multiple logistic regression analysis was performed to identify associations between sexual harassment and K-10 scores. Results Among 228 female military personnel, 13 (5.7%) individuals experienced sexual harassment. Multiple logistic regression analysis revealed that sexual harassment had a significantly negative impact on K-10 scores (3.486, p<0.04). Higher K-10 scores among individuals experiencing sexual harassment were identified in the unmarried (including never-married) group (6.761, p<0.04), the short-term military service group (12.014, p<0.03) and the group whose length of service was <2 years (11.067, p<0.02). Conclusions Sexual harassment has a negative impact on mental health. Factors associated with worse mental health scores included service classification and length of service. The results provide helpful information with which to develop measures for minimising the negative psychological effects from sexual harassment and promoting sexual harassment prevention policy. PMID:27084842
Erkenekli, Kudret; Oztas, Efser; Kuscu, Elif; Keskin, Uğur; Kurt, Yasemin Gulcan; Tas, Ahmet; Yilmaz, Nafiye
2017-01-01
Dyslipidemia is common in women with polycystic ovary syndrome (PCOS) irrespective of age. Our aim was to investigate soluble tumor necrosis factor like weak inducer of apoptosis (sTWEAK), a cardiovascular risk marker in PCOS, and to determine if it is associated with dyslipidemia in youth. A prospective-observational study was carried out including 35 PCOS patients and 35 healthy controls. Serum sTWEAK levels were measured using commercially available kits. Multiple logistic regression analysis was then performed to verify the statistically significant differences in the possible predictors of dyslipidemia. Serum sTWEAK levels and the percentage of women with dyslipidemia were significantly higher in the PCOS group (p = 0.024 and p < 0.001, respectively). Participants were further divided into 2 subgroups based on the presence of dyslipidemia. The percentage of women with PCOS was significantly higher in the dyslipidemic group when compared with controls; 70.7 vs. 20.7%, respectively (p < 0.001). Multiple logistic regression analysis revealed that both the presence of PCOS (OR 7.924, 95% CI 2.117-29.657, p = 0.002) and increased levels of sTWEAK (>693 pg/ml; OR 3.810, 95% CI 1.075-13.501, p = 0.038) were independently associated with dyslipidemia. Increased levels of both sTWEAK and PCOS were found to be independently associated with dyslipidemia in youth. © 2016 S. Karger AG, Basel.
Adult correlates of early behavioral maladjustment: a study of injured drivers.
Ryb, Gabriel; Dischinger, Patricia; Smith, Gordon; Soderstrom, Carl
2008-10-01
To establish whether a history of school suspension (HSS) predicts adult driver behavior. 323 injured drivers were interviewed as part of a study of psychoactive substance use disorders (PSUD) and injury. Drivers with a HSS were compared to those without HSS in relation to demographics, SES, PSUD, risky behaviors, trauma history and driving history using student's t test and chi-square. Multiple logistic regression models were constructed to adjust for demographics, SES and PSUD. HSS drivers represented 31% of the population and were younger, more likely to be male and had higher rates of alcohol and drug dependence than drivers without HSS. Educational achievement was worse for drivers with HSS. Drivers with HSS were more likely to have a history of prior vehicular trauma and assault. Seat-belt non-use, drinking and driving, riding with drunk driver, binge drinking, driving fast for the thrill, license suspension and drinking and driving convictions were more common among drivers with HSS. In multiple logistic regression models adjusting for demographics and SES, HSS revealed higher odds ratios for the same outcomes. After adding PSUD to the models HSS remained significant only for seat belt non use, binge drinking and previous assault history. HSS is associated with risky behaviors, repeated vehicular injury, and poor driver history. The association with driver history, however, disappears when PSUD are included in the models. The association of HSS (a marker of early behavioral maladjustment) with behavioral risks suggests that undiagnosed psychopathology may be linked to injury recidivism.
[Patients' reaction to pharmacists wearing a mask during their consultations].
Tamura, Eri; Kishimoto, Keiko; Fukushima, Noriko
2013-01-01
This study sought to determine the effect of pharmacists wearing a mask on the consultation intention of patients who do not have a trusting relationship with the pharmacists. We conducted a questionnaire survey of customers at a Tokyo drugstore in August 2012. Subjects answered a questionnaire after watching two medical teaching videos, one in which the pharmacist was wearing a mask and the other in which the pharmacist was not wearing a mask. Data analysis was performed using a paired t-test and multiple logistic regression. The paired t-test revealed a significant difference in 'Maintenance Problem' between the two pharmacist situations. After excluding factors not associated with wearing a mask, multiple logistic regression analysis identified three independent variables with a significant effect on participants not wanting to consult with a pharmacist wearing a mask. Positive factors were 'active-inactive' and 'frequency mask use', a negative factor was 'age'. Our study has shown that pharmacists wearing a mask may be a factor that prevents patients from consulting with pharmacist. Those patients whose intention to consult might be affected by the pharmacists wearing a mask tended to be younger, to have no habit of wearing masks preventively themselves, and to form a negative opinion of such pharmacists. Therefore, it was estimated that pharmacists who wear masks need to provide medical education by asking questions more positively than when they do not wear a mask in order to prevent the patient worrying about oneself.
Zacarias, Antonio Eugenio; Macassa, Gloria; Soares, Joaquim JF; Svanström, Leif; Antai, Diddy
2012-01-01
Background Little knowledge exists in Mozambique and sub-Saharan Africa about the mental health (symptoms of depression, anxiety, and somatization) of women victims and perpetrators of intimate partner violence (IPV) by type of abuse (psychological aggression, physical assault without/with injury, and sexual coercion). This study scrutinizes factors associated with mental health among women victims and perpetrators of IPV over the 12 months prior to the study. Methods and materials Mental health data were analyzed with bivariate and multiple regression methods for 1442 women aged 15–49 years who contacted Forensic Services at Maputo Central Hospital (Maputo City, Mozambique) for IPV victimization between April 1, 2007 and March 31, 2008. Results In bivariate analyses, victims and perpetrators of IPVs scored higher on symptoms of mental health than their unaffected counterparts. Multiple regressions revealed that controlling behaviors, mental health comorbidity, social support, smoking, childhood abuse, sleep difficulties, age, and lack of education were more important in explaining symptoms of mental health than demographics/socioeconomics or life-style factors. Victimization and perpetration across all types of IPV were not associated with symptoms of mental health. Conclusion In our sample, victimization and perpetration were not important factors in explaining mental ill health, contrary to previous findings. More research into the relationship between women’s IPV victimization and perpetration and mental health is warranted as well as the influence of controlling behaviors on mental health. PMID:23071419
Kose, E; Hirai, T; Seki, T; Hidaka, S; Hamamoto, T
2018-05-16
Anticholinergic drugs are associated with risks of falls, confusion and cognitive dysfunction. However, the effect of anticholinergic drug use on rehabilitation outcomes after a stroke is poorly documented. We therefore aimed to establish whether the anticholinergic load was associated with functional recovery among geriatric patients convalescing after stroke. Consecutive geriatric stroke patients admitted and discharged from a convalescence rehabilitation ward between 2010 and 2016 were included in this retrospective cohort study. Anticholinergic load was assessed by the Anticholinergic Risk Scale (ARS), and functional recovery was assessed by the Functional Independence Measure (FIM). The primary outcome was cognitive FIM (FIM-C) gain, but we also assessed the interaction of other putative factors identified from univariate analysis. Multivariate analyses were performed, adjusting for confounding factors. We included 418 participants (171 males, 247 females) with a median age of 78 years (interquartile range, 72-84 years). Multiple regression analysis revealed that ARS change, length of stay, and epilepsy were independently and negatively correlated with cognitive FIM gain. Multiple logistic regression analysis indicated that the "Comprehension" and "Memory" items of the cognitive FIM gain were independently and negatively associated with anticholinergic load. A causal relationship cannot be established, but increased ARS scores during hospitalization may predict limited cognitive functional improvement in geriatric patients after stroke. Alternatively, cognitive impairment may lead to increased use of anticholinergic drugs. © 2018 John Wiley & Sons Ltd.
Hwang, In Cheol; Ahn, Hong Yup; Park, Sang Min; Shim, Jae Yong; Kim, Kyoung Kon
2013-03-01
There is scant research concerning the prediction of imminent death, and current studies simply list events "that have already occurred" around 48 h of the death. We sought to determine what events herald the onset of dying process using the length of time from "any change" to death. This is a prospective observational study with chart audit. Inclusion criteria were terminal cancer patients who passed away in a palliative care unit. The analysis was limited to 181 patients who had medical records for their final week. Commonly observed events in the terminally ill were determined and their significant changes were defined beforehand. We selected the statistically significant changes by multiple logistic regression analysis and evaluated their predictive values for "death within 48 h." The median age was 67 years and there were 103 male patients. After adjusting for age, sex, primary cancer site, metastatic site, and cancer treatment, multiple logistic regression analyses for association between the events and "death within 48 h" revealed some significant changes: confused mental state, decreased blood pressure, increased pulse pressure, low oxygen saturation, death rattle, and decreased conscious level. The events that had higher predictability for death within 48 h were decreased blood pressure and low oxygen saturation, and the positive and negative predictive values of their combination were 95.0 and 81.4%, respectively. The most reliable events to predict impending death were decreased blood pressure and low oxygen saturation.
Kyo, Tetsuhiro; Matsumoto, Yoko; Tochigi, Kasumi; Yuzawa, Mitsuko; Yamaguchi, Takuhiro; Komoto, Atsushi; Shimozuma, Kojiro; Fukuhara, Shunichi
2006-09-01
To quantify quality of life (QOL) changes in patients who have received a single session of photodynamic therapy (PDT) for subfoveal choroidal neovascularization, secondary to age-related macular degeneration (AMD), and to identify factors that correlate with the QOL changes. The QOL changes in 88 patients with AMD were scored with the 25-Item National Eye Institute Visual Function Questionnaire (VFQ-25) before and 3 months after a single PDT with routine ophthalmologic examinations. We used multiple regression analysis to evaluate VFQ-25 sub-scale scores and ophthalmologic findings in these patients before PDT, to identify impact on the effectiveness of PDT. We also evaluated changes in ophthalmologic findings influencing the QOL score. The sub-scale scores for both 'mental health' (p = 0.02) and 'role limitation' (p = 0.03) improved significantly in all 88 cases, but only 'mental health' improved significantly in 34 cases in which PDT was effective. Multiple regression analysis in all 88 cases revealed that the factors contributing significantly to improvement in 'mental health' were a lower pre-PDT 'mental health' score (p < 0.01) and the presence of fibrous tissue (p = 0.01) before the PDT session. The lower the role limitation before PDT (p < 0.01), the more significant was the improvement in this score. Although no baseline sub-scale score was identified as predicting the effectiveness of a single PDT session, the scores for both 'mental health' and 'role limitation' improved.
NASA Astrophysics Data System (ADS)
Wrona, Thilo; Taylor, Kevin G.; Jackson, Christopher A.-L.; Huuse, Mads; Najorka, Jens; Pan, Indranil
2017-04-01
Silica diagenesis has the potential to drastically change the physical and fluid flow properties of its host strata and therefore plays a key role in the development of sedimentary basins. The specific processes involved in silica diagenesis are, however, still poorly explained by existing models. This knowledge gap is addressed by investigating the effect of silica diagenesis on the porosity of Cenozoic mudstones of the North Viking Graben, northern North Sea through a multiple linear regression analysis. First, we identify and quantify the mineralogy of these rocks by scanning electron microscopy and X-ray diffraction, respectively. Mineral contents and host rock porosity data inferred from wireline data of two exploration wells are then analyzed by multiple linear regressions. This robust statistical analysis reveals that biogenic opal-A is a significant control and authigenic opal-CT is a minor influence on the porosity of these rocks. These results suggest that the initial porosity of siliceous mudstones increases with biogenic opal-A production during deposition and that the porosity reduction during opal-A/CT transformation results from opal-A dissolution. These findings advance our understanding of compaction, dewatering, and lithification of siliceous sediments and rocks. Moreover, this study provides a recipe for the derivation of the key controls (e.g., composition) on a rock property (e.g., porosity) that can be applied to a variety of problems in rock physics.
The Relationship of Hypochondriasis to Anxiety, Depressive, and Somatoform Disorders
Scarella, Timothy M.; Laferton, Johannes A. C.; Ahern, David K.; Fallon, Brian A.; Barsky, Arthur
2015-01-01
Background Though the phenotype of anxiety about medical illness has long been recognized, there continues to be debate as to whether it is a distinct psychiatric disorder and, if so, to which diagnostic category it belongs. Our objective was to investigate the pattern of psychiatric co-morbidity in hypochondriasis and to assess the relationship of health anxiety to anxiety, depressive, and somatoform disorders. Methods Data were collected as part of a clinical trial on treatment methods for hypochondriasis. 194 participants meeting criteria for DSM-IV hypochondriasis were assessed by sociodemographic variables, results of structured diagnostic interviews, and validated instruments for assessing various symptom dimensions of psychopathology. Results The majority of individuals with hypochondriasis had co-morbid psychiatric illness; the mean number of co-morbid diagnoses was 1.4, and 35.1% had hypochondriasis as their only diagnosis. Participants were more likely to have only co-morbid anxiety disorders than only co-morbid depressive or somatoform disorders. Multiple regression analysis of continuous measures of symptoms revealed the strongest correlation of health anxiety with anxiety symptoms, and a weaker correlation with somatoform symptoms; in multiple regression analysis, there was no correlation between health anxiety and depressive symptoms. Conclusion Our findings suggest that the entity of health anxiety (Hypochondriasis in DSM-IV, Illness Anxiety Disorder in DSM-5) is a clinical syndrome distinct from other psychiatric disorders. Analysis of co-morbidity patterns and continuous measures of symptoms suggest its appropriate classification is with anxiety rather than somatoform or mood disorders. PMID:26785798
NASA Astrophysics Data System (ADS)
Mills, Leila A.
This study examines middle school students' perceptions of a future career in a science, math, engineering, or technology (STEM) career field. Gender, grade, predispositions to STEM contents, and learner dispositions are examined for changing perceptions and development in career-related choice behavior. Student perceptions as measured by validated measurement instruments are analyzed pre and post participation in a STEM intervention energy-monitoring program that was offered in several U.S. middle schools during the 2009-2010, 2010-2011 school years. A multiple linear regression (MLR) model, developed by incorporating predictors identified by an examination of the literature and a hypothesis-generating pilot study for prediction of STEM career interest, is introduced. Theories on the career choice development process from authors such as Ginzberg, Eccles, and Lent are examined as the basis for recognition of career concept development among students. Multiple linear regression statistics, correlation analysis, and analyses of means are used to examine student data from two separate program years. Study research questions focus on predictive ability, RSQ, of MLR models by gender/grade, and significance of model predictors in order to determine the most significant predictors of STEM career interest, and changes in students' perceptions pre and post program participation. Analysis revealed increases in the perceptions of a science career, decreases in perceptions of a STEM career, increase of the significance of science and mathematics to predictive models, and significant increases in students' perceptions of creative tendencies.
Application of WHOQOL-BREF in Measuring Quality of Life in Health-Care Staff.
Gholami, Ali; Jahromi, Leila Moosavi; Zarei, Esmail; Dehghan, Azizallah
2013-07-01
The objective of this study was to evaluate the quality of life of Neyshabur health-care staff and some factors associated with it with use of WHOQOL-BREF scale. This cross-sectional study was conducted on 522 staff of Neyshabur health-care centers from May to July 2011. Cronbach's alpha coefficient was applied to examine the internal consistency of WHOQOL-BREF scale; Pearson's correlation coefficient was used to determine the level of agreement between different domains of WHOQOL-BREF. Paired t-test was used to compare difference between score means of different domains. T-independent test was performed for group analysis and Multiple Linear Regression was used to control confounding effects. In this study, a good internal consistency (α = 0.925) for WHOQOL-BREF and its four domains was observed. The highest and the lowest mean scores of WHOQOL-BREF domains was found for physical health domain (Mean = 15.26) and environmental health domain (Mean = 13.09) respectively. Backward multiple linear regression revealed that existence chronic disease in staff was significantly associated with four domains of WHOQOL-BREF, education years was associated with two domains (Psychological and Environmental) and sex was associated with psychological domain (P < 0.05). The findings from this study confirm that the WHOQOL-BREF questionnaire is a reliable instrument to measure quality of life in health-care staff. From the data, it appears that Neyshabur health-care staff has WHOQOL-BREF scores that might be considered to indicate a relatively moderate quality of life.
Morioka, Hisayoshi; Itani, Osamu; Osaki, Yoneatsu; Higuchi, Susumu; Jike, Maki; Kaneita, Yoshitaka; Kanda, Hideyuki; Nakagome, Sachi; Ohida, Takashi
2017-03-01
This study aimed to clarify the associations between the frequency and amount of alcohol consumption and problematic Internet use, such as Internet addiction and excessive Internet use. A self-administered questionnaire survey was administered to students enrolled in randomly selected junior and senior high schools throughout Japan, and responses from 100,050 students (51,587 males and 48,463 females) were obtained. Multiple logistic regression analyses were performed in order to examine the associations between alcohol use and problematic Internet, use such as Internet addiction (Young Diagnostic Questionnaire for Internet Addiction ≥5) and excessive Internet use (≥5 h/day). The results of multiple logistic regression analyses indicated that the adjusted odds ratios for Internet addiction (YDQ ≥5) and excessive Internet use (≥5 h/day) became higher as the number of days in which alcohol had been consumed during the previous 30 days increased. In addition, the adjusted odds ratio for excessive Internet use (≥5 h/day) indicated a dose-dependent association with the amount of alcohol consumed per session. This study revealed that adolescents showing problematic Internet use consumed alcohol more frequently and consumed a greater amount of alcohol than those without problematic Internet use. These findings suggest a close association between drinking and problematic Internet use among Japanese adolescents. Copyright © 2016 The Authors. Production and hosting by Elsevier B.V. All rights reserved.
Sensky, T; Leger, C; Gilmour, S
1996-01-01
Failure by people on chronic haemodialysis to adhere adequately to dietary and fluid restrictions can have serious medical consequences. Numerous psychosocial factors possibly associated with adherence have been investigated in previous research. However, most previous studies have examined one or a few variables in isolation, and have tended to focus on sociodemographic variables not easily amenable to intervention. Much previous work has tended to ignore potential differences in adherence between male and female dialysands. Sociodemographic and psychosocial factors associated with adherence to dietary and fluid restrictions were investigated in 45 people on haemodialysis attending one renal unit, excluding those with a residual urine volume > 500 ml/day. Multiple regression analyses were used to estimate the contribution to adherence of a range of variables, including gender, age, duration of dialysis, affective disturbance, past psychiatric history, health locus of control, social adjustment and social supports. Adherence to diet (measured by predialysis serum potassium) and to fluid restriction (interdialysis weight gain) were not linked, and had different psychosocial correlates. Regression models of four different aspects of adherence revealed very distinct psychosocial correlates, with contributions to adherence from complex interactions between psychosocial and cognitive variables, notably gender, age, social adjustment, health locus of control, and depression. The findings cast doubt on the results of many previous studies which have used simple models of adherence. Adherence is likely to be influenced in a complex manner by multiple factors including age, gender, locus of control, social adjustment, and past psychiatric history.
Frisbie, Kathryn; Converso, Judith
2016-05-24
From 2010 to 2012, the for-profit sector of higher education in the United States (otherwise known as career colleges) existed in a turbulent environment, characterized by regulatory, media, and public scrutiny. While virtually all career colleges experienced enrollment declines during this period, by 2012 some colleges were starting to see this trend stabilize or reverse, whereas others did not. The purpose of this study was to determine if the differences in career colleges' enrollment trends could be attributed to organizational resilience. A quantitative correlation study using a multiple regression analysis was conducted to determine the nature of the relationship between organizational resilience and the enrollment fluctuations of 59 career colleges located throughout the United States. The correlation between organizational resilience levels and enrollment fluctuations was fair to moderate and significant, r = 0.40, p < 0.05. A multiple-regression analysis revealed that the model significantly explained the impact of the six organizational resilience factors on enrollment fluctuations, F = 4.15, p < 0.01. The R2 for the model was 0.32, and the adjusted R2 was 0.25. In terms of individual organizational resilience factors, two tested either significantly or moderately significantly: avoidance-skepticism and critical understanding or sensemaking. Recommendations for college leaders include monitoring the level of avoidance to ensure a healthy balance of skepticism regarding new situations and incorporating strategies to help organizational members increase their levels of critical understanding or sensemaking.
Imai, Kenji; Takai, Koji; Watanabe, Satoshi; Hanai, Tatsunori; Suetsugu, Atsushi; Shiraki, Makoto; Shimizu, Masahito
2017-09-22
Sarcopenia impairs survival in patients with hepatocellular carcinoma (HCC). This study aimed to clarify the factors that contribute to decreased skeletal muscle volume in patients with HCC. The third lumbar vertebra skeletal muscle index (L3 SMI) in 351 consecutive patients with HCC was calculated to identify sarcopenia. Sarcopenia was defined as an L3 SMI value ≤ 29.0 cm²/m² for women and ≤ 36.0 cm²/m² for men. The factors affecting L3 SMI were analyzed by multiple linear regression analysis and tree-based models. Of the 351 HCC patients, 33 were diagnosed as having sarcopenia and showed poor prognosis compared with non-sarcopenia patients ( p = 0.007). However, this significant difference disappeared after the adjustments for age, sex, Child-Pugh score, maximum tumor size, tumor number, and the degree of portal vein invasion by propensity score matching analysis. Multiple linear regression analysis showed that age ( p = 0.015) and sex ( p < 0.0001) were significantly correlated with a decrease in L3 SMI. Tree-based models revealed that sex (female) is the most significant factor that affects L3 SMI. In male patients, L3 SMI was decreased by aging, increased Child-Pugh score (≥56 years), and enlarged tumor size (<56 years). Maintaining liver functional reserve and early diagnosis and therapy for HCC are vital to prevent skeletal muscle depletion and improve the prognosis of patients with HCC.
Quantile Regression in the Study of Developmental Sciences
ERIC Educational Resources Information Center
Petscher, Yaacov; Logan, Jessica A. R.
2014-01-01
Linear regression analysis is one of the most common techniques applied in developmental research, but only allows for an estimate of the average relations between the predictor(s) and the outcome. This study describes quantile regression, which provides estimates of the relations between the predictor(s) and outcome, but across multiple points of…
Maintenance Operations in Mission Oriented Protective Posture Level IV (MOPPIV)
1987-10-01
Repair FADAC Printed Circuit Board ............. 6 3. Data Analysis Techniques ............................. 6 a. Multiple Linear Regression... ANALYSIS /DISCUSSION ............................... 12 1. Exa-ple of Regression Analysis ..................... 12 S2. Regression results for all tasks...6 * TABLE 9. Task Grouping for Analysis ........................ 7 "TABXLE 10. Remove/Replace H60A3 Power Pack................. 8 TABLE
Curcic, Marijana; Buha, Aleksandra; Stankovic, Sanja; Milovanovic, Vesna; Bulat, Zorica; Đukić-Ćosić, Danijela; Antonijević, Evica; Vučinić, Slavica; Matović, Vesna; Antonijevic, Biljana
2017-02-01
The objective of this study was to assess toxicity of Cd and BDE-209 mixture on haematological parameters in subacutely exposed rats and to determine the presence and type of interactions between these two chemicals using multiple factorial regression analysis. Furthermore, for the assessment of interaction type, an isobologram based methodology was applied and compared with multiple factorial regression analysis. Chemicals were given by oral gavage to the male Wistar rats weighing 200-240g for 28days. Animals were divided in 16 groups (8/group): control vehiculum group, three groups of rats were treated with 2.5, 7.5 or 15mg Cd/kg/day. These doses were chosen on the bases of literature data and reflect relatively high Cd environmental exposure, three groups of rats were treated with 1000, 2000 or 4000mg BDE-209/kg/bw/day, doses proved to induce toxic effects in rats. Furthermore, nine groups of animals were treated with different mixtures of Cd and BDE-209 containing doses of Cd and BDE-209 stated above. Blood samples were taken at the end of experiment and red blood cells, white blood cells and platelets counts were determined. For interaction assessment multiple factorial regression analysis and fitted isobologram approach were used. In this study, we focused on multiple factorial regression analysis as a method for interaction assessment. We also investigated the interactions between Cd and BDE-209 by the derived model for the description of the obtained fitted isobologram curves. Current study indicated that co-exposure to Cd and BDE-209 can result in significant decrease in RBC count, increase in WBC count and decrease in PLT count, when compared with controls. Multiple factorial regression analysis used for the assessment of interactions type between Cd and BDE-209 indicated synergism for the effect on RBC count and no interactions i.e. additivity for the effects on WBC and PLT counts. On the other hand, isobologram based approach showed slight antagonism for the effects on RBC and WBC while no interactions were proved for the joint effect on PLT count. These results confirm that the assessment of interactions between chemicals in the mixture greatly depends on the concept or method used for this evaluation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Kanada, Yoshikiyo; Sakurai, Hiroaki; Sugiura, Yoshito; Arai, Tomoaki; Koyama, Soichiro; Tanabe, Shigeo
2017-11-01
[Purpose] To create a regression formula in order to estimate 1RM for knee extensors, based on the maximal isometric muscle strength measured using a hand-held dynamometer and data regarding the body composition. [Subjects and Methods] Measurement was performed in 21 healthy males in their twenties to thirties. Single regression analysis was performed, with measurement values representing 1RM and the maximal isometric muscle strength as dependent and independent variables, respectively. Furthermore, multiple regression analysis was performed, with data regarding the body composition incorporated as another independent variable, in addition to the maximal isometric muscle strength. [Results] Through single regression analysis with the maximal isometric muscle strength as an independent variable, the following regression formula was created: 1RM (kg)=0.714 + 0.783 × maximal isometric muscle strength (kgf). On multiple regression analysis, only the total muscle mass was extracted. [Conclusion] A highly accurate regression formula to estimate 1RM was created based on both the maximal isometric muscle strength and body composition. Using a hand-held dynamometer and body composition analyzer, it was possible to measure these items in a short time, and obtain clinically useful results.
NASA Technical Reports Server (NTRS)
Stolzer, Alan J.; Halford, Carl
2007-01-01
In a previous study, multiple regression techniques were applied to Flight Operations Quality Assurance-derived data to develop parsimonious model(s) for fuel consumption on the Boeing 757 airplane. The present study examined several data mining algorithms, including neural networks, on the fuel consumption problem and compared them to the multiple regression results obtained earlier. Using regression methods, parsimonious models were obtained that explained approximately 85% of the variation in fuel flow. In general data mining methods were more effective in predicting fuel consumption. Classification and Regression Tree methods reported correlation coefficients of .91 to .92, and General Linear Models and Multilayer Perceptron neural networks reported correlation coefficients of about .99. These data mining models show great promise for use in further examining large FOQA databases for operational and safety improvements.
Gurung, Arun Bahadur; Aguan, Kripamoy; Mitra, Sivaprasad; Bhattacharjee, Atanu
2017-06-01
In Alzheimer's disease (AD), the level of Acetylcholine (ACh) neurotransmitter is reduced. Since Acetylcholinesterase (AChE) cleaves ACh, inhibitors of AChE are very much sought after for AD treatment. The side effects of current inhibitors necessitate development of newer AChE inhibitors. Isoalloxazine derivatives have proved to be promising (AChE) inhibitors. However, their structure-activity relationship studies have not been reported till date. In the present work, various quantitative structure-activity relationship (QSAR) building methods such as multiple linear regression (MLR), partial least squares ,and principal component regression were employed to derive 3D-QSAR models using steric and electrostatic field descriptors. Statistically significant model was obtained using MLR coupled with stepwise selection method having r 2 = .9405, cross validated r 2 (q 2 ) = .6683, and a high predictability (pred_r 2 = .6206 and standard error, pred_r 2 se = .2491). Steric and electrostatic contribution plot revealed three electrostatic fields E_496, E_386 and E_577 and one steric field S_60 contributing towards biological activity. A ligand-based 3D-pharmacophore model was generated consisting of eight pharmacophore features. Isoalloxazine derivatives were docked against human AChE, which revealed critical residues implicated in hydrogen bonds as well as hydrophobic interactions. The binding modes of docked complexes (AChE_IA1 and AChE_IA14) were validated by molecular dynamics simulation which showed their stable trajectories in terms of root mean square deviation and molecular mechanics/Poisson-Boltzmann surface area binding free energy analysis revealed key residues contributing significantly to overall binding energy. The present study may be useful in the design of more potent Isoalloxazine derivatives as AChE inhibitors.
Chin, Weng-Yee; Wan, Eric Yuk Fai; Dowrick, Christopher; Arroll, Bruce; Lam, Cindy Lo Kuen
2018-04-26
The aim of this study was to explore the relationship between patient self-reported Patient Health Questionnaire-9 (PHQ-9) symptoms and doctor diagnosis of depression using a tree analysis approach. This was a secondary analysis on a dataset obtained from 10 179 adult primary care patients and 59 primary care physicians (PCPs) across Hong Kong. Patients completed a waiting room survey collecting data on socio-demographics and the PHQ-9. Blinded doctors documented whether they thought the patient had depression. Data were analyzed using multiple logistic regression and conditional inference decision tree modeling. PCPs diagnosed 594 patients with depression. Logistic regression identified gender, age, employment status, past history of depression, family history of mental illness and recent doctor visit as factors associated with a depression diagnosis. Tree analyses revealed different pathways of association between PHQ-9 symptoms and depression diagnosis for patients with and without past depression. The PHQ-9 symptom model revealed low mood, sense of worthlessness, fatigue, sleep disturbance and functional impairment as early classifiers. The PHQ-9 total score model revealed cut-off scores of >12 and >15 were most frequently associated with depression diagnoses in patients with and without past depression. A past history of depression is the most significant factor associated with the diagnosis of depression. PCPs appear to utilize a hypothetical-deductive problem-solving approach incorporating pre-test probability, with different associated factors for patients with and without past depression. Diagnostic thresholds may be too low for patients with past depression and too high for those without, potentially leading to over and under diagnosis of depression.
Integrative eQTL analysis of tumor and host omics data in individuals with bladder cancer.
Pineda, Silvia; Van Steen, Kristel; Malats, Núria
2017-09-01
Integrative analyses of several omics data are emerging. The data are usually generated from the same source material (i.e., tumor sample) representing one level of regulation. However, integrating different regulatory levels (i.e., blood) with those from tumor may also reveal important knowledge about the human genetic architecture. To model this multilevel structure, an integrative-expression quantitative trait loci (eQTL) analysis applying two-stage regression (2SR) was proposed. This approach first regressed tumor gene expression levels with tumor markers and the adjusted residuals from the previous model were then regressed with the germline genotypes measured in blood. Previously, we demonstrated that penalized regression methods in combination with a permutation-based MaxT method (Global-LASSO) is a promising tool to fix some of the challenges that high-throughput omics data analysis imposes. Here, we assessed whether Global-LASSO can also be applied when tumor and blood omics data are integrated. We further compared our strategy with two 2SR-approaches, one using multiple linear regression (2SR-MLR) and other using LASSO (2SR-LASSO). We applied the three models to integrate genomic, epigenomic, and transcriptomic data from tumor tissue with blood germline genotypes from 181 individuals with bladder cancer included in the TCGA Consortium. Global-LASSO provided a larger list of eQTLs than the 2SR methods, identified a previously reported eQTLs in prostate stem cell antigen (PSCA), and provided further clues on the complexity of APBEC3B loci, with a minimal false-positive rate not achieved by 2SR-MLR. It also represents an important contribution for omics integrative analysis because it is easy to apply and adaptable to any type of data. © 2017 WILEY PERIODICALS, INC.
Not-for-profit hospital CEO performance and pay: some evidence from Connecticut.
Kramer, Jeffrey; Santerre, Rexford E
2010-01-01
This paper uses observations from a panel data set of 35 chief executive officers (CEOs) from 29 not-for-profit hospitals in Connecticut over the period 1998 to 2006 to investigate the relationship between CEO performance and pay. Both economic and charity performance measures are specified in the empirical model. The multiple regression results reveal that not-for-profit hospital CEOs, at least in Connecticut, are driven at the margin to increase the occupancy rate of privately insured patients at the expense of uncompensated care and public-pay patients. This type of behavior on the part of not-for-profit hospital CEOs calls into question the desirability of allowing these hospitals a tax exemption on earned income, property, and purchases.
Environmental management and labour productivity: The moderating role of capital intensity.
Lannelongue, Gustavo; Gonzalez-Benito, Javier; Quiroz, Idaisa
2017-04-01
Recent years have seen firms improve their environmental practices, although the question still remains as to whether or not investing in such practices is or is not beneficial or simply a matter of image. This study focuses on labour productivity as a measure of performance, and we argue that the impact of greater environmental performance on that productivity is moderated by capital intensity. A sample of 2823 plants provides empirical evidence to support our approach. Specifically, the analyses, making use of estimates based on multiple regression models, reveal that environmental management has a positive impact on labour productivity in organisations with low capital intensity, although that impact becomes negative in cases of high capital intensity. Copyright © 2016 Elsevier Ltd. All rights reserved.
QSAR study of curcumine derivatives as HIV-1 integrase inhibitors.
Gupta, Pawan; Sharma, Anju; Garg, Prabha; Roy, Nilanjan
2013-03-01
A QSAR study was performed on curcumine derivatives as HIV-1 integrase inhibitors using multiple linear regression. The statistically significant model was developed with squared correlation coefficients (r(2)) 0.891 and cross validated r(2) (r(2) cv) 0.825. The developed model revealed that electronic, shape, size, geometry, substitution's information and hydrophilicity were important atomic properties for determining the inhibitory activity of these molecules. The model was also tested successfully for external validation (r(2) pred = 0.849) as well as Tropsha's test for model predictability. Furthermore, the domain analysis was carried out to evaluate the prediction reliability of external set molecules. The model was statistically robust and had good predictive power which can be successfully utilized for screening of new molecules.
Harsh parenting and child externalizing behavior: skin conductance level reactivity as a moderator.
Erath, Stephen A; El-Sheikh, Mona; Mark Cummings, E
2009-01-01
Skin conductance level reactivity (SCLR) was examined as a moderator of the association between harsh parenting and child externalizing behavior. Participants were 251 boys and girls (8-9 years). Mothers and fathers provided reports of harsh parenting and their children's externalizing behavior; children also provided reports of harsh parenting. SCLR was assessed in response to a socioemotional stress task and a problem-solving challenge task. Regression analyses revealed that the association between harsh parenting and externalizing behavior was stronger among children with lower SCLR, as compared to children with higher SCLR. SCLR may be a more robust moderator among boys compared to girls. Results are discussed with regard to theories on antisocial behavior and multiple-domain models of child development.
Andres, Fanny; Castanier, Carole; Le Scanff, Christine
2014-02-01
The present study aims to explore the mediating effects of conscientiousness and alexithymia in the relationship between parental attachment style and alcohol use in a large sample of athletic young people. Participants included 434 French sport sciences students. Alcohol use, parental attachment style, conscientiousness and alexithymia were assessed. The hypotheses were tested by using regression and bootstrapping mediation analyses. Maternal insecure attachment style is positively associated with alcohol use. The current study highlights a multiple pathway in this relationship. The results reveal the mediating effect of low conscientiousness and alexithymia between maternal insecure attachment and alcohol use. Athletes' alcohol use seems to be the result of a complex association of underlying psychological factors. © 2013.
Berlin, Kathryn; Kruger, Tina; Klenosky, David B
2018-01-01
This mixed-methods study compares active older women in different physically based leisure activities and explores the difference in subjective ratings of successful aging and quantifiable predictors of success. A survey was administered to 256 women, 60-92 years of age, engaged in a sports- or exercise-based activity. Quantitative data were analyzed through ANOVA and multiple regression. Qualitative data (n = 79) was analyzed using the approach associated with means-end theory. While participants quantitatively appeared similar in terms of successful aging, qualitative interviews revealed differences in activity motivation. Women involved in sports highlighted social/psychological benefits, while those involved in exercise-based activities stressed fitness outcomes.
Intrinsic motivation, extrinsic motivation, and learning English as a foreign language.
Shaikholeslami, Razieh; Khayyer, Mohammad
2006-12-01
The objective of this study was to examine the relationships of amotivation, extrinsic motivation, and intrinsic motivation with learning the English language. The 230 Iranian students at Shiraz University were tested using the Language Learning Orientations Scales to measure Amotivation, Extrinsic Motivation, and Intrinsic Motivation as explanatory variables. Grade point average in English exams was selected as a measure of English learning Achievement. Multiple regression analysis revealed that learning Achievement scores were predicted by scores on the Amotivation subscale, Introjected Regulation subscale, Knowledge subscale, and Stimulation subscale, whereas, the External and Identified Regulation and Accomplishment subscales did not have a significant relationship with Achievement. The results are discussed in terms of differences in Iranian context and culture.
Cross Validation of Selection of Variables in Multiple Regression.
1979-12-01
55 vii CROSS VALIDATION OF SELECTION OF VARIABLES IN MULTIPLE REGRESSION I Introduction Background Long term DoD planning gcals...028545024 .31109000 BF * SS - .008700618 .0471961 Constant - .70977903 85.146786 55 had adequate predictive capabilities; the other two models (the...71ZCO F111D Control 54 73EGO FlIID Computer, General Purpose 55 73EPO FII1D Converter-Multiplexer 56 73HAO flllD Stabilizer Platform 57 73HCO F1ID
Byun, Bo-Ram; Kim, Yong-Il; Maki, Koutaro; Son, Woo-Sung
2015-01-01
This study was aimed to examine the correlation between skeletal maturation status and parameters from the odontoid process/body of the second vertebra and the bodies of third and fourth cervical vertebrae and simultaneously build multiple regression models to be able to estimate skeletal maturation status in Korean girls. Hand-wrist radiographs and cone beam computed tomography (CBCT) images were obtained from 74 Korean girls (6–18 years of age). CBCT-generated cervical vertebral maturation (CVM) was used to demarcate the odontoid process and the body of the second cervical vertebra, based on the dentocentral synchondrosis. Correlation coefficient analysis and multiple linear regression analysis were used for each parameter of the cervical vertebrae (P < 0.05). Forty-seven of 64 parameters from CBCT-generated CVM (independent variables) exhibited statistically significant correlations (P < 0.05). The multiple regression model with the greatest R 2 had six parameters (PH2/W2, UW2/W2, (OH+AH2)/LW2, UW3/LW3, D3, and H4/W4) as independent variables with a variance inflation factor (VIF) of <2. CBCT-generated CVM was able to include parameters from the second cervical vertebral body and odontoid process, respectively, for the multiple regression models. This suggests that quantitative analysis might be used to estimate skeletal maturation status. PMID:25878721
Patino, Reynaldo; VanLandeghem, Matthew M.; Goodbred, Steven L.; Orsak, Erik; Jenkins, Jill A.; Echols, Kathy R.; Rosen, Michael R.; Torres, Leticia
2015-01-01
Adult male Common Carp were sampled in 2007/08 over a full reproductive cycle at Lake Mead National Recreation Area. Sites sampled included a stream dominated by treated wastewater effluent, a lake basin receiving the streamflow, an upstream lake basin (reference), and a site below Hoover Dam. Individual body burdens for 252 contaminants were measured, and biological variables assessed included physiological [plasma vitellogenin (VTG), estradiol-17β (E2), 11-ketotestosterone (11KT)] and organ [gonadosomatic index (GSI)] endpoints. Patterns in contaminant composition and biological condition were determined by Principal Component Analysis, and their associations modeled by Principal Component Regression. Three spatially distinct but temporally stable gradients of contaminant distribution were recognized: a contaminant mixture typical of wastewaters (PBDEs, methyl triclosan, galaxolide), PCBs, and DDTs. Two spatiotemporally variable patterns of biological condition were recognized: a primary pattern consisting of reproductive condition variables (11KT, E2, GSI), and a secondary pattern including general condition traits (condition factor, hematocrit, fork length). VTG was low in all fish, indicating low estrogenic activity of water at all sites. Wastewater contaminants associated negatively with GSI, 11KT and E2; PCBs associated negatively with GSI and 11KT; and DDTs associated positively with GSI and 11KT. Regression of GSI on sex steroids revealed a novel, nonlinear association between these variables. Inclusion of sex steroids in the GSI regression on contaminants rendered wastewater contaminants nonsignificant in the model and reduced the influence of PCBs and DDTs. Thus, the influence of contaminants on GSI may have been partially driven by organismal modes-of-action that include changes in sex steroid production. The positive association of DDTs with 11KT and GSI suggests that lifetime, sub-lethal exposures to DDTs have effects on male carp opposite of those reported by studies where exposure concentrations were relatively high. Lastly, this study highlighted advantages of multivariate/multiple regression approaches for exploring associations between complex contaminant mixtures and gradients and reproductive condition in wild fishes.
Terai, Naim; Spoerl, Eberhard; Pillunat, Lutz E; Kuhlisch, Eberhard; Schmidt, Eckart; Boehm, Andreas G
2011-09-01
To investigate the relationship between central corneal thickness (CCT) and optic disc size in patients with primary open-angle glaucoma (POAG) in a hospital-based population. Data for the right eyes of 1435 White patients with POAG were included in a retrospective hospital-based study. All eyes underwent optic nerve head imaging using Heidelberg Retina Tomograph II (HRT II; Heidelberg Engineering, Heidelberg, Germany) and CCT measurement by ultrasound corneal pachymetry. Eyes with prior intraocular or corneal surgery were excluded. Low-quality HRT II images were also excluded. The impact of age, gender, CCT, intraocular pressure, cylindrical and spherical refractive error as independent factors on optic disc size was investigated in a multiple linear regression analysis. The data for 1104 right eyes qualified for participation in the study. The median age of these patients was 65 years. The median CCT was 547 μm (25th-75th percentile 522-575 μm). The median optic disc size was 2.21 mm(2) (25th-75th percentile 1.89-2.60 mm(2)). Multiple linear regression analysis revealed that age (p = 0.001), CCT (p = 0.001) and spherical equivalent (p = 0.049) were correlated to disc size according to the following formula: disc area = -0.004 × age - 0.001 × CCT - 0.014 × spherical equivalent +3.290. R(2) of the whole model was 0.021. Univariate regression analysis between age and disc area provided R(2) = 0.008 with p = 0.002. Univariate regression analysis between disc area and CCT provided R(2) = 0.005 with p = 0.02. In this retrospective hospital-based study we could not detect a clinically relevant correlation between optic disc size and CCT. The correlation between CCT and disc size and between age and disc size were statistically significant, but the R(2) values were very low. The results of the study are biased because of its hospital-based design, so the results of the study need to be confirmed in a large population-based study. © 2009 The Authors. Journal compilation © 2009 Acta Ophthalmol.
2014-01-01
Background Greater use of antibiotics during the past 50 years has exerted selective pressure on susceptible bacteria and may have favoured the survival of resistant strains. Existing information on antibiotic resistance patterns from pathogens circulating among community-based patients is substantially less than from hospitalized patients on whom guidelines are often based. We therefore chose to assess the relationship between the antibiotic resistance pattern of bacteria circulating in the community and the consumption of antibiotics in the community. Methods Both gray literature and published scientific literature in English and other European languages was examined. Multiple regression analysis was used to analyse whether studies found a positive relationship between antibiotic consumption and resistance. A subsequent meta-analysis and meta-regression was conducted for studies for which a common effect size measure (odds ratio) could be calculated. Results Electronic searches identified 974 studies but only 243 studies were considered eligible for inclusion by the two independent reviewers who extracted the data. A binomial test revealed a positive relationship between antibiotic consumption and resistance (p < .001) but multiple regression modelling did not produce any significant predictors of study outcome. The meta-analysis generated a significant pooled odds ratio of 2.3 (95% confidence interval 2.2 to 2.5) with a meta-regression producing several significant predictors (F(10,77) = 5.82, p < .01). Countries in southern Europe produced a stronger link between consumption and resistance than other regions. Conclusions Using a large set of studies we found that antibiotic consumption is associated with the development of antibiotic resistance. A subsequent meta-analysis, with a subsample of the studies, generated several significant predictors. Countries in southern Europe produced a stronger link between consumption and resistance than other regions so efforts at reducing antibiotic consumption may need to be strengthened in this area. Increased consumption of antibiotics may not only produce greater resistance at the individual patient level but may also produce greater resistance at the community, country, and regional levels, which can harm individual patients. PMID:24405683
NASA Astrophysics Data System (ADS)
ul-Haq, Zia; Rana, Asim Daud; Tariq, Salman; Mahmood, Khalid; Ali, Muhammad; Bashir, Iqra
2018-03-01
We have applied regression analyses for the modeling of tropospheric NO2 (tropo-NO2) as the function of anthropogenic nitrogen oxides (NOx) emissions, aerosol optical depth (AOD), and some important meteorological parameters such as temperature (Temp), precipitation (Preci), relative humidity (RH), wind speed (WS), cloud fraction (CLF) and outgoing long-wave radiation (OLR) over different climatic zones and land use/land cover types in South Asia during October 2004-December 2015. Simple linear regression shows that, over South Asia, tropo-NO2 variability is significantly linked to AOD, WS, NOx, Preci and CLF. Also zone-5, consisting of tropical monsoon areas of eastern India and Myanmar, is the only study zone over which all the selected parameters show their influence on tropo-NO2 at statistical significance levels. In stepwise multiple linear modeling, tropo-NO2 column over landmass of South Asia, is significantly predicted by the combination of RH (standardized regression coefficient, β = - 49), AOD (β = 0.42) and NOx (β = 0.25). The leading predictors of tropo-NO2 columns over zones 1-5 are OLR, AOD, Temp, OLR, and RH respectively. Overall, as revealed by the higher correlation coefficients (r), the multiple regressions provide reasonable models for tropo-NO2 over South Asia (r = 0.82), zone-4 (r = 0.90) and zone-5 (r = 0.93). The lowest r (of 0.66) has been found for hot semi-arid region in northwestern Indus-Ganges Basin (zone-2). The highest value of β for urban area AOD (of 0.42) is observed for megacity Lahore, located in warm semi-arid zone-2 with large scale crop-residue burning, indicating strong influence of aerosols on the modeled tropo-NO2 column. A statistical significant correlation (r = 0.22) at the 0.05 level is found between tropo-NO2 and AOD over Lahore. Also NOx emissions appear as the highest contributor (β = 0.59) for modeled tropo-NO2 column over megacity Dhaka.
Patiño, Reynaldo; VanLandeghem, Matthew M; Goodbred, Steven L; Orsak, Erik; Jenkins, Jill A; Echols, Kathy; Rosen, Michael R; Torres, Leticia
2015-08-01
Adult male Common Carp were sampled in 2007/08 over a full reproductive cycle at Lake Mead National Recreation Area. Sites sampled included a stream dominated by treated wastewater effluent, a lake basin receiving the streamflow, an upstream lake basin (reference), and a site below Hoover Dam. Individual body burdens for 252 contaminants were measured, and biological variables assessed included physiological [plasma vitellogenin (VTG), estradiol-17β (E2), 11-ketotestosterone (11KT)] and organ [gonadosomatic index (GSI)] endpoints. Patterns in contaminant composition and biological condition were determined by Principal Component Analysis, and their associations modeled by Principal Component Regression. Three spatially distinct but temporally stable gradients of contaminant distribution were recognized: a contaminant mixture typical of wastewaters (PBDEs, methyl triclosan, galaxolide), PCBs, and DDTs. Two spatiotemporally variable patterns of biological condition were recognized: a primary pattern consisting of reproductive condition variables (11KT, E2, GSI), and a secondary pattern including general condition traits (condition factor, hematocrit, fork length). VTG was low in all fish, indicating low estrogenic activity of water at all sites. Wastewater contaminants associated negatively with GSI, 11KT and E2; PCBs associated negatively with GSI and 11KT; and DDTs associated positively with GSI and 11KT. Regression of GSI on sex steroids revealed a novel, nonlinear association between these variables. Inclusion of sex steroids in the GSI regression on contaminants rendered wastewater contaminants nonsignificant in the model and reduced the influence of PCBs and DDTs. Thus, the influence of contaminants on GSI may have been partially driven by organismal modes-of-action that include changes in sex steroid production. The positive association of DDTs with 11KT and GSI suggests that lifetime, sub-lethal exposures to DDTs have effects on male carp opposite of those reported by studies where exposure concentrations were relatively high. Lastly, this study highlighted advantages of multivariate/multiple regression approaches for exploring associations between complex contaminant mixtures and gradients and reproductive condition in wild fishes. Published by Elsevier Inc.
NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel
2017-08-01
Cluster-level dynamic treatment regimens can be used to guide sequential treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level dynamic treatment regimen, the treatment is potentially adapted and re-adapted over time based on changes in the cluster that could be impacted by prior intervention, including aggregate measures of the individuals or patients that compose it. Cluster-randomized sequential multiple assignment randomized trials can be used to answer multiple open questions preventing scientists from developing high-quality cluster-level dynamic treatment regimens. In a cluster-randomized sequential multiple assignment randomized trial, sequential randomizations occur at the cluster level and outcomes are observed at the individual level. This manuscript makes two contributions to the design and analysis of cluster-randomized sequential multiple assignment randomized trials. First, a weighted least squares regression approach is proposed for comparing the mean of a patient-level outcome between the cluster-level dynamic treatment regimens embedded in a sequential multiple assignment randomized trial. The regression approach facilitates the use of baseline covariates which is often critical in the analysis of cluster-level trials. Second, sample size calculators are derived for two common cluster-randomized sequential multiple assignment randomized trial designs for use when the primary aim is a between-dynamic treatment regimen comparison of the mean of a continuous patient-level outcome. The methods are motivated by the Adaptive Implementation of Effective Programs Trial which is, to our knowledge, the first-ever cluster-randomized sequential multiple assignment randomized trial in psychiatry.
Adjusted variable plots for Cox's proportional hazards regression model.
Hall, C B; Zeger, S L; Bandeen-Roche, K J
1996-01-01
Adjusted variable plots are useful in linear regression for outlier detection and for qualitative evaluation of the fit of a model. In this paper, we extend adjusted variable plots to Cox's proportional hazards model for possibly censored survival data. We propose three different plots: a risk level adjusted variable (RLAV) plot in which each observation in each risk set appears, a subject level adjusted variable (SLAV) plot in which each subject is represented by one point, and an event level adjusted variable (ELAV) plot in which the entire risk set at each failure event is represented by a single point. The latter two plots are derived from the RLAV by combining multiple points. In each point, the regression coefficient and standard error from a Cox proportional hazards regression is obtained by a simple linear regression through the origin fit to the coordinates of the pictured points. The plots are illustrated with a reanalysis of a dataset of 65 patients with multiple myeloma.
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
NASA Astrophysics Data System (ADS)
Sahabiev, I. A.; Ryazanov, S. S.; Kolcova, T. G.; Grigoryan, B. R.
2018-03-01
The three most common techniques to interpolate soil properties at a field scale—ordinary kriging (OK), regression kriging with multiple linear regression drift model (RK + MLR), and regression kriging with principal component regression drift model (RK + PCR)—were examined. The results of the performed study were compiled into an algorithm of choosing the most appropriate soil mapping technique. Relief attributes were used as the auxiliary variables. When spatial dependence of a target variable was strong, the OK method showed more accurate interpolation results, and the inclusion of the auxiliary data resulted in an insignificant improvement in prediction accuracy. According to the algorithm, the RK + PCR method effectively eliminates multicollinearity of explanatory variables. However, if the number of predictors is less than ten, the probability of multicollinearity is reduced, and application of the PCR becomes irrational. In that case, the multiple linear regression should be used instead.
Genetic Programming Transforms in Linear Regression Situations
NASA Astrophysics Data System (ADS)
Castillo, Flor; Kordon, Arthur; Villa, Carlos
The chapter summarizes the use of Genetic Programming (GP) inMultiple Linear Regression (MLR) to address multicollinearity and Lack of Fit (LOF). The basis of the proposed method is applying appropriate input transforms (model respecification) that deal with these issues while preserving the information content of the original variables. The transforms are selected from symbolic regression models with optimal trade-off between accuracy of prediction and expressional complexity, generated by multiobjective Pareto-front GP. The chapter includes a comparative study of the GP-generated transforms with Ridge Regression, a variant of ordinary Multiple Linear Regression, which has been a useful and commonly employed approach for reducing multicollinearity. The advantages of GP-generated model respecification are clearly defined and demonstrated. Some recommendations for transforms selection are given as well. The application benefits of the proposed approach are illustrated with a real industrial application in one of the broadest empirical modeling areas in manufacturing - robust inferential sensors. The chapter contributes to increasing the awareness of the potential of GP in statistical model building by MLR.
A Solution to Separation and Multicollinearity in Multiple Logistic Regression
Shen, Jianzhao; Gao, Sujuan
2010-01-01
In dementia screening tests, item selection for shortening an existing screening test can be achieved using multiple logistic regression. However, maximum likelihood estimates for such logistic regression models often experience serious bias or even non-existence because of separation and multicollinearity problems resulting from a large number of highly correlated items. Firth (1993, Biometrika, 80(1), 27–38) proposed a penalized likelihood estimator for generalized linear models and it was shown to reduce bias and the non-existence problems. The ridge regression has been used in logistic regression to stabilize the estimates in cases of multicollinearity. However, neither solves the problems for each other. In this paper, we propose a double penalized maximum likelihood estimator combining Firth’s penalized likelihood equation with a ridge parameter. We present a simulation study evaluating the empirical performance of the double penalized likelihood estimator in small to moderate sample sizes. We demonstrate the proposed approach using a current screening data from a community-based dementia study. PMID:20376286
A Solution to Separation and Multicollinearity in Multiple Logistic Regression.
Shen, Jianzhao; Gao, Sujuan
2008-10-01
In dementia screening tests, item selection for shortening an existing screening test can be achieved using multiple logistic regression. However, maximum likelihood estimates for such logistic regression models often experience serious bias or even non-existence because of separation and multicollinearity problems resulting from a large number of highly correlated items. Firth (1993, Biometrika, 80(1), 27-38) proposed a penalized likelihood estimator for generalized linear models and it was shown to reduce bias and the non-existence problems. The ridge regression has been used in logistic regression to stabilize the estimates in cases of multicollinearity. However, neither solves the problems for each other. In this paper, we propose a double penalized maximum likelihood estimator combining Firth's penalized likelihood equation with a ridge parameter. We present a simulation study evaluating the empirical performance of the double penalized likelihood estimator in small to moderate sample sizes. We demonstrate the proposed approach using a current screening data from a community-based dementia study.
NASA Technical Reports Server (NTRS)
Whitlock, C. H.; Kuo, C. Y.
1979-01-01
The objective of this paper is to define optical physics and/or environmental conditions under which the linear multiple-regression should be applicable. An investigation of the signal-response equations is conducted and the concept is tested by application to actual remote sensing data from a laboratory experiment performed under controlled conditions. Investigation of the signal-response equations shows that the exact solution for a number of optical physics conditions is of the same form as a linearized multiple-regression equation, even if nonlinear contributions from surface reflections, atmospheric constituents, or other water pollutants are included. Limitations on achieving this type of solution are defined.
Salanova, Marisa; Llorens, Susana; Cifre, Eva
2013-01-01
This paper tests the structure and the predictors of two psychological experiences of technostress associated with the use of information and communication technologies (ICT), i.e., technostrain (users report feelings of anxiety, fatigue, scepticism and inefficacy beliefs related to the use of technologies) and technoaddiction (users feel bad due to an excessive and compulsive use of these technologies). The study included a sample of 1072 ICT users (N = 675 nonintensive ICT users and N = 397 intensive ICT users). Results from multigroup confirmatory factor analyses among non-intensive and intensive ICT users showed, as expected, the four-factor structure of technostrain in both samples. Secondly, and also as expected, confirmatory factorial analyses revealed that technostress experiences are characterized not only by technostrain but also by an excessive and compulsive use of ICT. Moreover, multiple analyses of variance showed significant differences between non-intensive and intensive ICT users (1) in the dimensions of technostress and (2) in specific job demands and job/personal resources. Finally, linear multiple regression analyses revealed that technostrain is positively predicted by work overload, role ambiguity, emotional overload, mobbing and obstacles hindering ICT use, as well as by lack of autonomy, transformational leadership, social support, ICT use facilitators and mental competences. Work overload, role ambiguity and mobbing, as well as the lack of emotional competences, positively predict technoaddiction. Theoretical and practical implications, in addition to future research, are discussed.
100-m Breaststroke Swimming Performance in Youth Swimmers: The Predictive Value of Anthropometrics.
Sammoud, Senda; Nevill, Alan Michael; Negra, Yassine; Bouguezzi, Raja; Chaabene, Helmi; Hachana, Younés
2018-03-16
This study aimed to estimate the optimal body size, limb segment length, and girth or breadth ratios of 100-m breaststroke performance in youth swimmers. In total, 59 swimmers [male: n = 39, age = 11.5 (1.3) y; female: n = 20, age = 12.0 (1.0) y] participated in this study. To identify size/shape characteristics associated with 100-m breaststroke swimming performance, we computed a multiplicative allometric log-linear regression model, which was refined using backward elimination. Results showed that the 100-m breaststroke performance revealed a significant negative association with fat mass and a significant positive association with the segment length ratio (arm ratio = hand length/forearm length) and limb girth ratio (girth ratio = forearm girth/wrist girth). In addition, leg length, biacromial breadth, and biiliocristal breadth revealed significant positive associations with the 100-m breaststroke performance. However, height and body mass did not contribute to the model, suggesting that the advantage of longer levers was limb-specific rather than a general whole-body advantage. In fact, it is only by adopting multiplicative allometric models that the previously mentioned ratios could have been derived. These results highlighted the importance of considering anthropometric characteristics of youth breaststroke swimmers for talent identification and/or athlete monitoring purposes. In addition, these findings may assist orienting swimmers to the appropriate stroke based on their anthropometric characteristics.
Increased plasma/serum levels of prolactin in multiple sclerosis: a meta-analysis.
Wei, Wei; Liu, Lei; Cheng, Zhong-Le; Hu, Bo
2017-08-01
Prolactin (PRL) is a polypeptide hormone that is known to stimulate humoral and cell mediated immune responses. PRL levels have been investigated in several autoimmune diseases including multiple sclerosis (MS); however, these have yielded different and inconsistent results. This study aims to perform a more precise evaluation on the plasma/serum PRL levels in MS patients, and to explore the available influential factors. Research related to plasma/serum PRL levels in MS patients and healthy controls were gathered using PubMed, EMBASE and The Cochrane Library database (until Mar 31 2016). Pooled standard mean difference (SMD) with 95% confidence interval (CI) was calculated by fixed-effects or random-effect model analysis. Heterogeneity test was performed by the Q statistic and quantified using I 2 , and publication bias was evaluated using a funnel plot and Egger's linear regression test. 516 articles were obtained after searching databases, and 8 studies with 426 MS patients and 296 controls were finally included. Meta-analysis revealed that, compared with the control group, the MS group had significantly higher plasma/serum PRL levels, with the SMD of 0.55 and 95%CI (0.39, 0.72). Subgroup analyses showed that region, age and disease duration were associated with PRL level in MS patients. In summary, our meta-analysis revealed a significantly higher PRL level in MS patients than healthy controls, and it is influenced by region, age and disease duration.
Barton, J. Clayborn; Barton, James C.
2015-01-01
Abstract Background: In some reports, serum ferritin (SF) has been associated with insulin resistance and metabolic syndrome. Methods: We studied non-Hispanic whites without diabetes mellitus in a postscreening examination. Participants included cases [HFE C282Y homozygosity; and transferrin saturation (TS) >50% and SF >300 μg/L (males) and TS >45% and SF >200 μg/dL (females), regardless of HFE genotype] and controls [HFE wild-type (wt/wt) and TS/SF 25th–75th percentiles]. We excluded participants with overnight fasts <8 hr, cirrhosis, hepatitis B or C, pregnancy, or missing data. Observations were age, sex, C282Y homozygosity, body mass index (BMI), systolic and diastolic blood pressures (SBP, DBP), lymphocytes, alanine aminotransferase (ALT), aspartate aminotransferase (AST), C-reactive protein (CRP), TS, SF, and glucose/insulin. Insulin resistance was defined as homeostasis model assessment of insulin resistance (HOMA-IR) 4th quartile (≥2.70). Results: A total of 407 women and 362 men (mean age 54 years) included 188 C282Y homozygotes and 371 wt/wt. Significant trends across HOMA-IR quartiles included age, male sex, BMI, SBP, DBP, lymphocytes, ALT, CRP >0.5 mg/dL (positive), and TS (negative). Multiple regression on HOMA-IR revealed significant associations with male sex, BMI, SBP, lymphocytes, ALT, CRP>0.5 mg/dL (positive), and DBP and SF (negative). Logistic regression on HOMA-IR 4th quartile revealed significant positive associations with age, male sex, BMI, and lymphocytes. Metabolic syndrome occurred in 53 participants (6.9%). Logistic regression on metabolic syndrome revealed these odds ratios: HOMA-IR 4th quartile [9.1 (4.8, 17.3)] and CRP >0.5 mg/dL [2.9 (1.6, 5.4)]. Conclusions: Age, male sex, BMI, and lymphocytes were positively associated with HOMA-IR after correction for other factors. HOMA-IR 4th quartile and CRP >0.5 mg/dL predicted metabolic syndrome. PMID:25423072
Acton, Ronald T; Barton, J Clayborn; Barton, James C
2015-03-01
In some reports, serum ferritin (SF) has been associated with insulin resistance and metabolic syndrome. We studied non-Hispanic whites without diabetes mellitus in a postscreening examination. Participants included cases [HFE C282Y homozygosity; and transferrin saturation (TS) >50% and SF >300 μg/L (males) and TS >45% and SF >200 μg/dL (females), regardless of HFE genotype] and controls [HFE wild-type (wt/wt) and TS/SF 25th-75th percentiles]. We excluded participants with overnight fasts <8 hr, cirrhosis, hepatitis B or C, pregnancy, or missing data. Observations were age, sex, C282Y homozygosity, body mass index (BMI), systolic and diastolic blood pressures (SBP, DBP), lymphocytes, alanine aminotransferase (ALT), aspartate aminotransferase (AST), C-reactive protein (CRP), TS, SF, and glucose/insulin. Insulin resistance was defined as homeostasis model assessment of insulin resistance (HOMA-IR) 4th quartile (≥2.70). A total of 407 women and 362 men (mean age 54 years) included 188 C282Y homozygotes and 371 wt/wt. Significant trends across HOMA-IR quartiles included age, male sex, BMI, SBP, DBP, lymphocytes, ALT, CRP >0.5 mg/dL (positive), and TS (negative). Multiple regression on HOMA-IR revealed significant associations with male sex, BMI, SBP, lymphocytes, ALT, CRP>0.5 mg/dL (positive), and DBP and SF (negative). Logistic regression on HOMA-IR 4th quartile revealed significant positive associations with age, male sex, BMI, and lymphocytes. Metabolic syndrome occurred in 53 participants (6.9%). Logistic regression on metabolic syndrome revealed these odds ratios: HOMA-IR 4th quartile [9.1 (4.8, 17.3)] and CRP >0.5 mg/dL [2.9 (1.6, 5.4)]. Age, male sex, BMI, and lymphocytes were positively associated with HOMA-IR after correction for other factors. HOMA-IR 4th quartile and CRP >0.5 mg/dL predicted metabolic syndrome.
RRegrs: an R package for computer-aided model selection with multiple regression models.
Tsiliki, Georgia; Munteanu, Cristian R; Seoane, Jose A; Fernandez-Lozano, Carlos; Sarimveis, Haralambos; Willighagen, Egon L
2015-01-01
Predictive regression models can be created with many different modelling approaches. Choices need to be made for data set splitting, cross-validation methods, specific regression parameters and best model criteria, as they all affect the accuracy and efficiency of the produced predictive models, and therefore, raising model reproducibility and comparison issues. Cheminformatics and bioinformatics are extensively using predictive modelling and exhibit a need for standardization of these methodologies in order to assist model selection and speed up the process of predictive model development. A tool accessible to all users, irrespectively of their statistical knowledge, would be valuable if it tests several simple and complex regression models and validation schemes, produce unified reports, and offer the option to be integrated into more extensive studies. Additionally, such methodology should be implemented as a free programming package, in order to be continuously adapted and redistributed by others. We propose an integrated framework for creating multiple regression models, called RRegrs. The tool offers the option of ten simple and complex regression methods combined with repeated 10-fold and leave-one-out cross-validation. Methods include Multiple Linear regression, Generalized Linear Model with Stepwise Feature Selection, Partial Least Squares regression, Lasso regression, and Support Vector Machines Recursive Feature Elimination. The new framework is an automated fully validated procedure which produces standardized reports to quickly oversee the impact of choices in modelling algorithms and assess the model and cross-validation results. The methodology was implemented as an open source R package, available at https://www.github.com/enanomapper/RRegrs, by reusing and extending on the caret package. The universality of the new methodology is demonstrated using five standard data sets from different scientific fields. Its efficiency in cheminformatics and QSAR modelling is shown with three use cases: proteomics data for surface-modified gold nanoparticles, nano-metal oxides descriptor data, and molecular descriptors for acute aquatic toxicity data. The results show that for all data sets RRegrs reports models with equal or better performance for both training and test sets than those reported in the original publications. Its good performance as well as its adaptability in terms of parameter optimization could make RRegrs a popular framework to assist the initial exploration of predictive models, and with that, the design of more comprehensive in silico screening applications.Graphical abstractRRegrs is a computer-aided model selection framework for R multiple regression models; this is a fully validated procedure with application to QSAR modelling.
2017-01-01
Analyzing lipid composition and distribution within the brain is important to study white matter pathologies that present focal demyelination lesions, such as multiple sclerosis. Some lesions can endogenously re-form myelin sheaths. Therapies aim to enhance this repair process in order to reduce neurodegeneration and disability progression in patients. In this context, a lipidomic analysis providing both precise molecular classification and well-defined localization is crucial to detect changes in myelin lipid content. Here we develop a correlated heterospectral lipidomic (HSL) approach based on coregistered Raman spectroscopy, desorption electrospray ionization mass spectrometry (DESI-MS), and immunofluorescence imaging. We employ HSL to study the structural and compositional lipid profile of demyelination and remyelination in an induced focal demyelination mouse model and in multiple sclerosis lesions from patients ex vivo. Pixelwise coregistration of Raman spectroscopy and DESI-MS imaging generated a heterospectral map used to interrelate biomolecular structure and composition of myelin. Multivariate regression analysis enabled Raman-based assessment of highly specific lipid subtypes in complex tissue for the first time. This method revealed the temporal dynamics of remyelination and provided the first indication that newly formed myelin has a different lipid composition compared to normal myelin. HSL enables detailed molecular myelin characterization that can substantially improve upon the current understanding of remyelination in multiple sclerosis and provides a strategy to assess remyelination treatments in animal models. PMID:29392175
Louys, Julien; Meloro, Carlo; Elton, Sarah; Ditchfield, Peter; Bishop, Laura C
2015-01-01
We test the performance of two models that use mammalian communities to reconstruct multivariate palaeoenvironments. While both models exploit the correlation between mammal communities (defined in terms of functional groups) and arboreal heterogeneity, the first uses a multiple multivariate regression of community structure and arboreal heterogeneity, while the second uses a linear regression of the principal components of each ecospace. The success of these methods means the palaeoenvironment of a particular locality can be reconstructed in terms of the proportions of heavy, moderate, light, and absent tree canopy cover. The linear regression is less biased, and more precisely and accurately reconstructs heavy tree canopy cover than the multiple multivariate model. However, the multiple multivariate model performs better than the linear regression for all other canopy cover categories. Both models consistently perform better than randomly generated reconstructions. We apply both models to the palaeocommunity of the Upper Laetolil Beds, Tanzania. Our reconstructions indicate that there was very little heavy tree cover at this site (likely less than 10%), with the palaeo-landscape instead comprising a mixture of light and absent tree cover. These reconstructions help resolve the previous conflicting palaeoecological reconstructions made for this site. Copyright © 2014 Elsevier Ltd. All rights reserved.