Clinical Utility of Cancellation on the WISC-IV

ERIC Educational Resources Information Center

Zhu, Jianjun; Chen, Hsinyi

2013-01-01

This study examined empirical evidence for clinical utility of the Wechsler Intelligence Scale for Children, fourth edition (WISC-IV) cancellation subtest by comparing data from 597 clinical and 597 matched control children. The results of dependent t and sequential logistic regression analyses demonstrated that (a) children with intellectual…

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws.

PubMed

Xiao, Xiao; White, Ethan P; Hooten, Mevin B; Durham, Susan L

2011-10-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain.

Association between social contact frequency and negative symptoms, psychosocial functioning and quality of life in patients with schizophrenia.

PubMed

Siegrist, Karin; Millier, Aurelie; Amri, Ikbal; Aballéa, Samuel; Toumi, Mondher

2015-12-30

The lack of social contacts may be an important element in the presumed vicious circle aggravating, or at least stabilising negative symptoms in patients with schizophrenia. A European 2-year cohort study collected negative symptom scores, psychosocial functioning scores, objective social contact frequency scores and quality of life scores every 6 months. Bivariate analyses, correlation analyses, multivariate regressions and random effects regressions were conducted to describe relations between social contact and outcomes of interest and to gain a better understanding of this relation over time. Using data from 1208 patients with schizophrenia, a link between social contact frequency and negative symptom scores, functioning and quality of life at baseline was established. Regression models confirmed the significant association between social contact and negative symptoms as well as psychosocial functioning. This study aimed at demonstrating the importance of social contact for deficient behavioural aspects of schizophrenia. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Attitudes toward Seeking Professional Help for an Eating Disorder: The Role of Stigma and Anticipated Outcomes

ERIC Educational Resources Information Center

Hackler, Ashley H.; Vogel, David L.; Wade, Nathaniel G.

2010-01-01

This study examined the relationship between self-stigma, anticipated risks and benefits associated with seeking counseling, and attitudes toward seeking counseling among college students with disordered eating attitudes and behaviors. The results of hierarchical regression analyses demonstrated that self-stigma and the anticipated risks and…

Family Selection and Child Care Experiences: Implications for Studies of Child Outcomes.

ERIC Educational Resources Information Center

Burchinal, Margaret R.; Nelson, Lauren

2000-01-01

Discusses family selection issues that should be considered in child care research, and evidence demonstrating why each should be considered. Issues include whether causal inferences can be made from observational studies and the impact on conclusions from regression analyses that include highly correlated measures of child care experiences,…

Jewish Women's Psychological Well-Being: The Role of Attachment, Separation, and Jewish Identity

ERIC Educational Resources Information Center

Goldberg, Julie L.; O'Brien, Karen M.

2005-01-01

The purpose of this study was to examine the contributions of attachment, separation, and Jewish identity to psychological well-being in a sample of 115 late adolescent Jewish women. Results from multiple regression analyses demonstrated that attachment to parents, separation from parents, and Jewish identity collectively accounted for variance in…

Disentangling WTP per QALY data: different analytical approaches, different answers.

PubMed

Gyrd-Hansen, Dorte; Kjaer, Trine

2012-03-01

A large random sample of the Danish general population was asked to value health improvements by way of both the time trade-off elicitation technique and willingness-to-pay (WTP) using contingent valuation methods. The data demonstrate a high degree of heterogeneity across respondents in their relative valuations on the two scales. This has implications for data analysis. We show that the estimates of WTP per QALY are highly sensitive to the analytical strategy. For both open-ended and dichotomous choice data we demonstrate that choice of aggregated approach (ratios of means) or disaggregated approach (means of ratios) affects estimates markedly as does the interpretation of the constant term (which allows for disproportionality across the two scales) in the regression analyses. We propose that future research should focus on why some respondents are unwilling to trade on the time trade-off scale, on how to interpret the constant value in the regression analyses, and on how best to capture the heterogeneity in preference structures when applying mixed multinomial logit. Copyright © 2011 John Wiley & Sons, Ltd.

Building a new predictor for multiple linear regression technique-based corrective maintenance turnaround time.

PubMed

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.

How and for whom does web-based acceptance and commitment therapy work? Mediation and moderation analyses of web-based ACT for depressive symptoms.

PubMed

Pots, Wendy T M; Trompetter, Hester R; Schreurs, Karlein M G; Bohlmeijer, Ernst T

2016-05-23

Acceptance and Commitment Therapy (ACT) has been demonstrated to be effective in reducing depressive symptoms. However, little is known how and for whom therapeutic change occurs, specifically in web-based interventions. This study focuses on the mediators, moderators and predictors of change during a web-based ACT intervention. Data from 236 adults from the general population with mild to moderate depressive symptoms, randomized to either web-based ACT (n = 82) or one of two control conditions (web-based Expressive Writing (EW; n = 67) and a waiting list (n = 87)), were analysed. Single and multiple mediation analyses, and exploratory linear regression analyses were performed using PROCESS and linear regression analyses, to examine mediators, moderators and predictors on pre- to post- and follow-up treatment change of depressive symptoms. The treatment effect of ACT versus the waiting list was mediated by psychological flexibility and two mindfulness facets. The treatment effect of ACT versus EW was not significantly mediated. The moderator analyses demonstrated that the effects of web-based ACT did not vary according to baseline patient characteristics when compared to both control groups. However, higher baseline depressive symptoms and positive mental health and lower baseline anxiety were identified as predictors of outcome across all conditions. Similar results are found for follow-up. The findings of this study corroborate the evidence that psychological flexibility and mindfulness are distinct process mechanisms that mediate the effects of web-based ACT intervention. The results indicate that there are no restrictions to the allocation of web-based ACT intervention and that web-based ACT can work for different subpopulations. Netherlands Trial Register NTR2736 . Registered 6 February 2011.

A psycholinguistic database for traditional Chinese character naming.

PubMed

Chang, Ya-Ning; Hsu, Chun-Hsien; Tsai, Jie-Li; Chen, Chien-Liang; Lee, Chia-Ying

2016-03-01

In this study, we aimed to provide a large-scale set of psycholinguistic norms for 3,314 traditional Chinese characters, along with their naming reaction times (RTs), collected from 140 Chinese speakers. The lexical and semantic variables in the database include frequency, regularity, familiarity, consistency, number of strokes, homophone density, semantic ambiguity rating, phonetic combinability, semantic combinability, and the number of disyllabic compound words formed by a character. Multiple regression analyses were conducted to examine the predictive powers of these variables for the naming RTs. The results demonstrated that these variables could account for a significant portion of variance (55.8%) in the naming RTs. An additional multiple regression analysis was conducted to demonstrate the effects of consistency and character frequency. Overall, the regression results were consistent with the findings of previous studies on Chinese character naming. This database should be useful for research into Chinese language processing, Chinese education, or cross-linguistic comparisons. The database can be accessed via an online inquiry system (http://ball.ling.sinica.edu.tw/namingdatabase/index.html).

Relation of Opportunity to Learn Advanced Math to the Educational Attainment of Rural Youth

ERIC Educational Resources Information Center

Irvin, Matthew; Byun, Soo-yong; Smiley, Whitney S.; Hutchins, Bryan C.

2017-01-01

Our study examined the relation of advanced math course taking to the educational attainment of rural youth. We used data from the Educational Longitudinal Study of 2002. Regression analyses demonstrated that when previous math achievement is accounted for, rural students take advanced math at a significantly lower rate than urban students.…

On the Validity of Validity Scales: The Importance of Defensive Responding in the Prediction of Institutional Misconduct

ERIC Educational Resources Information Center

Edens, John F.; Ruiz, Mark A.

2006-01-01

This study examined the effects of defensive responding on the prediction of institutional misconduct among male inmates (N = 349) who completed the Personality Assessment Inventory (L. C. Morey, 1991). Hierarchical logistic regression analyses demonstrated significant main effects for the Antisocial Features (ANT) scale as well as main effects…

Improving validation methods for molecular diagnostics: application of Bland-Altman, Deming and simple linear regression analyses in assay comparison and evaluation for next-generation sequencing

PubMed Central

Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L

2018-01-01

Aims A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R2), using R2 as the primary metric of assay agreement. However, the use of R2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. Methods We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Results Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. Conclusions The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. PMID:28747393

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws

USGS Publications Warehouse

Xiao, X.; White, E.P.; Hooten, M.B.; Durham, S.L.

2011-01-01

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain. ?? 2011 by the Ecological Society of America.

Measurement error and outcome distributions: Methodological issues in regression analyses of behavioral coding data.

PubMed

Holsclaw, Tracy; Hallgren, Kevin A; Steyvers, Mark; Smyth, Padhraic; Atkins, David C

2015-12-01

Behavioral coding is increasingly used for studying mechanisms of change in psychosocial treatments for substance use disorders (SUDs). However, behavioral coding data typically include features that can be problematic in regression analyses, including measurement error in independent variables, non normal distributions of count outcome variables, and conflation of predictor and outcome variables with third variables, such as session length. Methodological research in econometrics has shown that these issues can lead to biased parameter estimates, inaccurate standard errors, and increased Type I and Type II error rates, yet these statistical issues are not widely known within SUD treatment research, or more generally, within psychotherapy coding research. Using minimally technical language intended for a broad audience of SUD treatment researchers, the present paper illustrates the nature in which these data issues are problematic. We draw on real-world data and simulation-based examples to illustrate how these data features can bias estimation of parameters and interpretation of models. A weighted negative binomial regression is introduced as an alternative to ordinary linear regression that appropriately addresses the data characteristics common to SUD treatment behavioral coding data. We conclude by demonstrating how to use and interpret these models with data from a study of motivational interviewing. SPSS and R syntax for weighted negative binomial regression models is included in online supplemental materials. (c) 2016 APA, all rights reserved).

Measurement error and outcome distributions: Methodological issues in regression analyses of behavioral coding data

PubMed Central

Holsclaw, Tracy; Hallgren, Kevin A.; Steyvers, Mark; Smyth, Padhraic; Atkins, David C.

2015-01-01

Behavioral coding is increasingly used for studying mechanisms of change in psychosocial treatments for substance use disorders (SUDs). However, behavioral coding data typically include features that can be problematic in regression analyses, including measurement error in independent variables, non-normal distributions of count outcome variables, and conflation of predictor and outcome variables with third variables, such as session length. Methodological research in econometrics has shown that these issues can lead to biased parameter estimates, inaccurate standard errors, and increased type-I and type-II error rates, yet these statistical issues are not widely known within SUD treatment research, or more generally, within psychotherapy coding research. Using minimally-technical language intended for a broad audience of SUD treatment researchers, the present paper illustrates the nature in which these data issues are problematic. We draw on real-world data and simulation-based examples to illustrate how these data features can bias estimation of parameters and interpretation of models. A weighted negative binomial regression is introduced as an alternative to ordinary linear regression that appropriately addresses the data characteristics common to SUD treatment behavioral coding data. We conclude by demonstrating how to use and interpret these models with data from a study of motivational interviewing. SPSS and R syntax for weighted negative binomial regression models is included in supplementary materials. PMID:26098126

Distress and Diabetes Treatment Adherence: A Mediating Role for Perceived Control

PubMed Central

Gonzalez, Jeffrey S.; Shreck, Erica; Psaros, Christina; Safren, Steven A.

2014-01-01

Objective To understand independent pathways linking emotional distress, medication adherence and glycemic control in adults with type 2 diabetes, as well as the potential mediating effects of perceived control over illness and self-efficacy. Methods Adults with type 2 diabetes (N = 142) were recruited for an intervention study evaluating cognitive behavioral therapy for adherence and depression. Depressive symptom severity was assessed via semi-structured interview. Validated self-reports assessed diabetes-related distress, perceived control over diabetes (perceived control), self-efficacy for diabetes self-management and medication adherence. Glycemic control was evaluated by hemoglobin A1c (A1C). Only baseline data were included in correlational and linear regression analyses. Results Perceived control was an important mediator for both medication adherence and A1C outcomes. Specifically, regression analyses demonstrated that diabetes distress, but not depression severity, was significantly related to medication adherence and A1C. Self-efficacy and perceived control were also independently associated with medication adherence and A1C. Mediation analyses demonstrated a significant indirect effect for diabetes distress and medication adherence, through perceived control and self-efficacy. The relationship between distress and A1C was accounted for by an indirect effect through perceived control. Conclusion Results demonstrate that diabetes-related emotional distress is associated with poorer treatment adherence and glycemic control among adults with type 2 diabetes; these relationships were partially mediated through perceived control over diabetes. Perceptions of one’s personal ability to influence diabetes may be important in understanding the pathway between emotional distress and poor diabetes treatment outcomes. PMID:25110840

Agreement between methods of measurement of mean aortic wall thickness by MRI.

PubMed

Rosero, Eric B; Peshock, Ronald M; Khera, Amit; Clagett, G Patrick; Lo, Hao; Timaran, Carlos

2009-03-01

To assess the agreement between three methods of calculation of mean aortic wall thickness (MAWT) using magnetic resonance imaging (MRI). High-resolution MRI of the infrarenal abdominal aorta was performed on 70 subjects with a history of coronary artery disease who were part of a multi-ethnic population-based sample. MAWT was calculated as the mean distance between the adventitial and luminal aortic boundaries using three different methods: average distance at four standard positions (AWT-4P), average distance at 100 automated positions (AWT-100P), and using a mathematical computation derived from the total vessel and luminal areas (AWT-VA). Bland-Altman plots and Passing-Bablok regression analyses were used to assess agreement between methods. Bland-Altman analyses demonstrated a positive bias of 3.02+/-7.31% between the AWT-VA and the AWT-4P methods, and of 1.76+/-6.82% between the AWT-100P and the AWT-4P methods. Passing-Bablok regression analyses demonstrated constant bias between the AWT-4P method and the other two methods. Proportional bias was, however, not evident among the three methods. MRI methods of measurement of MAWT using a limited number of positions of the aortic wall systematically underestimate the MAWT value compared with the method that calculates MAWT from the vessel areas. Copyright (c) 2009 Wiley-Liss, Inc.

Prediction of adherent placenta in pregnancy with placenta previa using ultrasonography and magnetic resonance imaging.

PubMed

Tanimura, Kenji; Yamasaki, Yui; Ebina, Yasuhiko; Deguchi, Masashi; Ueno, Yoshiko; Kitajima, Kazuhiro; Yamada, Hideto

2015-04-01

Adherent placenta is a life-threatening condition in pregnancy, and is often complicated by placenta previa. The aim of this prospective study was to determine prenatal imaging findings that predict the presence of adherent placenta in pregnancies with placenta previa. The study included 58 consecutive pregnant women with placenta previa who underwent both ultrasonography and magnetic resonance imaging prenatally. Ultrasonographic findings of anterior placental location, grade 2 or higher placental lacunae (PL≥G2), loss of retroplacental hypoechoic clear zone (LCZ) and the presence of turbulent blood flow in the arteries were evaluated, in addition to MRI findings. Forty-three women underwent cesarean section alone; 15 women with adherent placenta underwent cesarean section followed by hysterectomy with pathological examination. To determine imaging findings that predict adherent placenta, univariate and multivariate logistic regression analyses were performed. Univariate logistic regression analyses demonstrated that anterior placental location, PL≥G2, LCZ, and MRI were associated with the presence of adherent placenta. Multivariate analyses revealed that LCZ (p<0.01, odds ratio 15.6, 95%CI 2.1-114.6) was a single significant predictor of adherent placenta in women with placenta previa. This prospective study demonstrated for the first time that US findings, especially LCZ, might be useful for identifying patients at high risk for adherent placenta among pregnant women with placenta previa. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Mortality rates in OECD countries converged during the period 1990-2010.

PubMed

Bremberg, Sven G

2017-06-01

Since the scientific revolution of the 18th century, human health has gradually improved, but there is no unifying theory that explains this improvement in health. Studies of macrodeterminants have produced conflicting results. Most studies have analysed health at a given point in time as the outcome; however, the rate of improvement in health might be a more appropriate outcome. Twenty-eight OECD member countries were selected for analysis in the period 1990-2010. The main outcomes studied, in six age groups, were the national rates of decrease in mortality in the period 1990-2010. The effects of seven potential determinants on the rates of decrease in mortality were analysed in linear multiple regression models using least squares, controlling for country-specific history constants, which represent the mortality rate in 1990. The multiple regression analyses started with models that only included mortality rates in 1990 as determinants. These models explained 87% of the intercountry variation in the children aged 1-4 years and 51% in adults aged 55-74 years. When added to the regression equations, the seven determinants did not seem to significantly increase the explanatory power of the equations. The analyses indicated a decrease in mortality in all nations and in all age groups. The development of mortality rates in the different nations demonstrated significant catch-up effects. Therefore an important objective of the national public health sector seems to be to reduce the delay between international research findings and the universal implementation of relevant innovations.

Personality and attention: Levels of neuroticism and extraversion can predict attentional performance during a change detection task.

PubMed

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.

Comparing lagged linear correlation, lagged regression, Granger causality, and vector autoregression for uncovering associations in EHR data.

PubMed

Levine, Matthew E; Albers, David J; Hripcsak, George

2016-01-01

Time series analysis methods have been shown to reveal clinical and biological associations in data collected in the electronic health record. We wish to develop reliable high-throughput methods for identifying adverse drug effects that are easy to implement and produce readily interpretable results. To move toward this goal, we used univariate and multivariate lagged regression models to investigate associations between twenty pairs of drug orders and laboratory measurements. Multivariate lagged regression models exhibited higher sensitivity and specificity than univariate lagged regression in the 20 examples, and incorporating autoregressive terms for labs and drugs produced more robust signals in cases of known associations among the 20 example pairings. Moreover, including inpatient admission terms in the model attenuated the signals for some cases of unlikely associations, demonstrating how multivariate lagged regression models' explicit handling of context-based variables can provide a simple way to probe for health-care processes that confound analyses of EHR data.

A difference in systolic blood pressure between arms is a novel predictor of the development and progression of diabetic nephropathy in patients with type 2 diabetes.

PubMed

Okada, Hiroshi; Fukui, Michiaki; Tanaka, Muhei; Matsumoto, Shinobu; Iwase, Hiroya; Kobayashi, Kanae; Asano, Mai; Yamazaki, Masahiro; Hasegawa, Goji; Nakamura, Naoto

2013-10-01

Recent studies have suggested that a difference in systolic blood pressure (SBP) between arms is associated with both vascular disease and mortality. The aim of this study was to investigate the relationship between a difference in SBP between arms and change in urinary albumin excretion or development of albuminuria in patients with type 2 diabetes. We measured SBP in 408 consecutive patients with type 2 diabetes, and calculated a difference in SBP between arms. We performed follow-up study to assess change in urinary albumin excretion or development of albuminuria, mean interval of which was 4.6 ± 1.7 years. We then evaluated the relationship of a difference in SBP between arms to diabetic nephropathy using multiple regression analysis and multiple Cox regression model. Multiple regression analyses demonstrated that a difference in SBP between arms was independently associated with change in urinary albumin excretion (β = 0.1869, P = 0.0010). Adjusted Cox regression analyses demonstrated that a difference in SBP between arms was associated with an increased hazard of development of albuminuria; hazard ratio was 1.215 (95% confidence interval 1.077-1.376). Moreover, the risk of development of albuminuria was increased in patients with a difference in SBP of equal to or more than 10 mmHg between arms; hazard ratio was 4.168 (95% confidence interval 1.478-11.70). A difference in SBP between arms could be a novel predictor of the development and progression of diabetic nephropathy in patients with type 2 diabetes. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Mechanism of Change in Cognitive-Behavioral Treatment of Panic Disorder: Evidence for the Fear of Fear Mediational Hypothesis

ERIC Educational Resources Information Center

Smits, Jasper A. J.; Powers, Mark B.; Cho, Yongrae; Telch, Michael J.

2004-01-01

Numerous clinical trials have demonstrated the efficacy of cognitive-behavioral treatment (CBT) for panic disorder. However, studies investigating the mechanisms responsible for improvement with CBT are lacking. The authors used regression analyses outlined by R. M. Baron and D. A. Kenny (1986) to test whether a reduction in fear of fear (FOF)…

Cortical localization of cognitive function by regression of performance on event-related potentials

NASA Technical Reports Server (NTRS)

Montgomery, R. W.; Montgomery, L. D.; Guisado, R.

1992-01-01

This paper demonstrates a new method of mapping cortical localization of cognitive function, using electroencephalographic data. Cross-subject regression analyses are used to identify cortical sites and post-stimulus latencies where there is a high correlation between subjects' performance and their cognitive event-related potential amplitude. The procedure was tested using a mental arithmetic task and was found to identify essentially the same cortical regions that have been associated with such tasks on the basis of research with patients suffering localized cortical lesions. Thus, it appears to offer an inexpensive, noninvasive tool for exploring the dynamics of localization in neurologically normal subjects.

Improving validation methods for molecular diagnostics: application of Bland-Altman, Deming and simple linear regression analyses in assay comparison and evaluation for next-generation sequencing.

PubMed

Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L

2018-02-01

A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R 2 ), using R 2 as the primary metric of assay agreement. However, the use of R 2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Intermediate and advanced topics in multilevel logistic regression analysis

PubMed Central

Merlo, Juan

2017-01-01

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

Intermediate and advanced topics in multilevel logistic regression analysis.

PubMed

Austin, Peter C; Merlo, Juan

2017-09-10

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

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

PubMed

Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg

2009-11-01

G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.

AMP kinase-related kinase NUAK2 affects tumor growth, migration, and clinical outcome of human melanoma.

PubMed

Namiki, Takeshi; Tanemura, Atsushi; Valencia, Julio C; Coelho, Sergio G; Passeron, Thierry; Kawaguchi, Masakazu; Vieira, Wilfred D; Ishikawa, Masashi; Nishijima, Wataru; Izumo, Toshiyuki; Kaneko, Yasuhiko; Katayama, Ichiro; Yamaguchi, Yuji; Yin, Lanlan; Polley, Eric C; Liu, Hongfang; Kawakami, Yutaka; Eishi, Yoshinobu; Takahashi, Eishi; Yokozeki, Hiroo; Hearing, Vincent J

2011-04-19

The identification of genes that participate in melanomagenesis should suggest strategies for developing therapeutic modalities. We used a public array comparative genomic hybridization (CGH) database and real-time quantitative PCR (qPCR) analyses to identify the AMP kinase (AMPK)-related kinase NUAK2 as a candidate gene for melanomagenesis, and we analyzed its functions in melanoma cells. Our analyses had identified a locus at 1q32 where genomic gain is strongly associated with tumor thickness, and we used real-time qPCR analyses and regression analyses to identify NUAK2 as a candidate gene at that locus. Associations of relapse-free survival and overall survival of 92 primary melanoma patients with NUAK2 expression measured using immunohistochemistry were investigated using Kaplan-Meier curves, log rank tests, and Cox regression models. Knockdown of NUAK2 induces senescence and reduces S-phase, decreases migration, and down-regulates expression of mammalian target of rapamycin (mTOR). In vivo analysis demonstrated that knockdown of NUAK2 suppresses melanoma tumor growth in mice. Survival analysis showed that the risk of relapse is greater in acral melanoma patients with high levels of NUAK2 expression than in acral melanoma patients with low levels of NUAK2 expression (hazard ratio = 3.88; 95% confidence interval = 1.44-10.50; P = 0.0075). These data demonstrate that NUAK2 expression is significantly associated with the oncogenic features of melanoma cells and with the survival of acral melanoma patients. NUAK2 may provide a drug target to suppress melanoma progression. This study further supports the importance of NUAK2 in cancer development and tumor progression, while AMPK has antioncogenic properties.

Associations between Grawe's general mechanisms of change and Young's early maladaptive schemas in psychotherapy research: a comparative study of change processes.

PubMed

Mander, Johannes V; Jacob, Gitta A; Götz, Lea; Sammet, Isa; Zipfel, Stephan; Teufel, Martin

2015-01-01

The study aimed at analyzing associations between Grawe's general mechanisms of change and Young's early maladaptive schemas (EMS). Therefore, 98 patients completed the Scale for the Multiperspective Assessment of General Change Mechanisms in Psychotherapy (SACiP), the Young Shema Questionnaire-Short Form Revised (YSQ S3R), and diverse outcome measures at the beginning and end of treatment. Our results are important for clinical applications, as we demonstrated strong predictive effects of change mechanisms on schema domains using regression analyses and cross-lagged panel models. Resource activation experiences seem to be especially crucial in fostering alterations in EMS, as this change mechanism demonstrated significant associations with several schema domains. Future research should investigate these aspects in more detail using observer-based micro-process analyses.

Early Warning Signals of Financial Crises with Multi-Scale Quantile Regressions of Log-Periodic Power Law Singularities.

PubMed

Zhang, Qun; Zhang, Qunzhi; Sornette, Didier

2016-01-01

We augment the existing literature using the Log-Periodic Power Law Singular (LPPLS) structures in the log-price dynamics to diagnose financial bubbles by providing three main innovations. First, we introduce the quantile regression to the LPPLS detection problem. This allows us to disentangle (at least partially) the genuine LPPLS signal and the a priori unknown complicated residuals. Second, we propose to combine the many quantile regressions with a multi-scale analysis, which aggregates and consolidates the obtained ensembles of scenarios. Third, we define and implement the so-called DS LPPLS Confidence™ and Trust™ indicators that enrich considerably the diagnostic of bubbles. Using a detailed study of the "S&P 500 1987" bubble and presenting analyses of 16 historical bubbles, we show that the quantile regression of LPPLS signals contributes useful early warning signals. The comparison between the constructed signals and the price development in these 16 historical bubbles demonstrates their significant predictive ability around the real critical time when the burst/rally occurs.

A prospective study of differential sources of school-related social support and adolescent global life satisfaction.

PubMed

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.

Girl child marriage and its association with national rates of HIV, maternal health, and infant mortality across 97 countries.

PubMed

Raj, Anita; Boehmer, Ulrike

2013-04-01

This study was designed to assess associations between national rates of girl child marriage and national rates of HIV and maternal and child health (MCH) concerns, using national indicator data from 2009 United Nations reports. Current analyses were limited to the N = 97 nations (of 188 nations) for which girl child marriage data were available. Regression analyses adjusted for development and world region demonstrate that nations with higher rates of girl child marriage are significantly more likely to contend with higher rates of maternal and infant mortality and nonutilization of maternal health services, but not HIV.

An Improved Framework for Confound Regression and Filtering for Control of Motion Artifact in the Preprocessing of Resting-State Functional Connectivity Data

PubMed Central

Satterthwaite, Theodore D.; Elliott, Mark A.; Gerraty, Raphael T.; Ruparel, Kosha; Loughead, James; Calkins, Monica E.; Eickhoff, Simon B.; Hakonarson, Hakon; Gur, Ruben C.; Gur, Raquel E.; Wolf, Daniel H.

2013-01-01

Several recent reports in large, independent samples have demonstrated the influence of motion artifact on resting-state functional connectivity MRI (rsfc-MRI). Standard rsfc-MRI preprocessing typically includes regression of confounding signals and band-pass filtering. However, substantial heterogeneity exists in how these techniques are implemented across studies, and no prior study has examined the effect of differing approaches for the control of motion-induced artifacts. To better understand how in-scanner head motion affects rsfc-MRI data, we describe the spatial, temporal, and spectral characteristics of motion artifacts in a sample of 348 adolescents. Analyses utilize a novel approach for describing head motion on a voxelwise basis. Next, we systematically evaluate the efficacy of a range of confound regression and filtering techniques for the control of motion-induced artifacts. Results reveal that the effectiveness of preprocessing procedures on the control of motion is heterogeneous, and that improved preprocessing provides a substantial benefit beyond typical procedures. These results demonstrate that the effect of motion on rsfc-MRI can be substantially attenuated through improved preprocessing procedures, but not completely removed. PMID:22926292

Nutrition Risk in Critically Ill Versus the Nutritional Risk Screening 2002: Are They Comparable for Assessing Risk of Malnutrition in Critically Ill Patients?

PubMed

Canales, Cecilia; Elsayes, Ali; Yeh, D Dante; Belcher, Donna; Nakayama, Anna; McCarthy, Caitlin M; Chokengarmwong, Nalin; Quraishi, Sadeq A

2018-05-30

Malnutrition influences clinical outcomes. Although various screening tools are available to assess nutrition status, their use in the intensive care unit (ICU) has not been rigorously studied. Our goal was to compare the Nutrition Risk in Critically Ill (NUTRIC) to the Nutritional Risk Screening (NRS) 2002 in terms of their associations with macronutrient deficit in ICU patients. We performed a retrospective analysis to investigate the relationship between NUTRIC vs NRS 2002 and macronutrient deficit (protein and calories) in critically ill patients. We performed linear regression analyses, controlling for age, sex, race, body mass index, and ICU length of stay. We then dichotomized our primary exposures and outcomes to perform logistic regression analyses, controlling for the same covariates. The analytic cohort included 312 adults. Mean NUTRIC and NRS 2002 scores were 4 ± 2 and 4 ± 1, respectively. Linear regression demonstrated that each increment in NUTRIC score was associated with a 49 g higher protein deficit (β = 48.70: 95% confidence interval [CI] 29.23-68.17) and a 752 kcal higher caloric deficit (β = 751.95; 95% CI 447.80-1056.09). Logistic regression demonstrated that NUTRIC scores >4 had over twice the odds of protein deficits ≥300 g (odds ratio [OR] 2.35; 95% CI 1.43-3.85) and caloric deficits ≥6000 kcal (OR 2.73; 95% CI 1.66-4.50) compared with NUTRIC scores ≤4. We did not observe an association of NRS 2002 scores with macronutrient deficit. Our data suggest that NUTRIC is superior to NRS 2002 for assessing malnutrition risk in ICU patients. Randomized, controlled studies are needed to determine whether nutrition interventions, stratified by NUTRIC score, can improve patient outcomes. © 2018 American Society for Parenteral and Enteral Nutrition.

Transmission clustering among newly diagnosed HIV patients in Chicago, 2008 to 2011: using phylogenetics to expand knowledge of regional HIV transmission patterns

PubMed Central

Lubelchek, Ronald J.; Hoehnen, Sarah C.; Hotton, Anna L.; Kincaid, Stacey L.; Barker, David E.; French, Audrey L.

2014-01-01

Introduction HIV transmission cluster analyses can inform HIV prevention efforts. We describe the first such assessment for transmission clustering among HIV patients in Chicago. Methods We performed transmission cluster analyses using HIV pol sequences from newly diagnosed patients presenting to Chicago’s largest HIV clinic between 2008 and 2011. We compared sequences via progressive pairwise alignment, using neighbor joining to construct an un-rooted phylogenetic tree. We defined clusters as >2 sequences among which each sequence had at least one partner within a genetic distance of ≤ 1.5%. We used multivariable regression to examine factors associated with clustering and used geospatial analysis to assess geographic proximity of phylogenetically clustered patients. Results We compared sequences from 920 patients; median age 35 years; 75% male; 67% Black, 23% Hispanic; 8% had a Rapid Plasma Reagin (RPR) titer ≥ 1:16 concurrent with their HIV diagnosis. We had HIV transmission risk data for 54%; 43% identified as men who have sex with men (MSM). Phylogenetic analysis demonstrated 123 patients (13%) grouped into 26 clusters, the largest having 20 members. In multivariable regression, age < 25, Black race, MSM status, male gender, higher HIV viral load, and RPR ≥ 1:16 associated with clustering. We did not observe geographic grouping of genetically clustered patients. Discussion Our results demonstrate high rates of HIV transmission clustering, without local geographic foci, among young Black MSM in Chicago. Applied prospectively, phylogenetic analyses could guide prevention efforts and help break the cycle of transmission. PMID:25321182

The teamwork in assertive community treatment (TACT) scale: development and validation.

PubMed

Wholey, Douglas R; Zhu, Xi; Knoke, David; Shah, Pri; Zellmer-Bruhn, Mary; Witheridge, Thomas F

2012-11-01

Team design is meticulously specified for assertive community treatment (ACT) teams, yet performance can vary across ACT teams, even those with high fidelity. By developing and validating the Teamwork in Assertive Community Treatment (TACT) scale, investigators examined the role of team processes in ACT performance. The TACT scale measuring ACT teamwork was developed from a conceptual model grounded in organizational research and adapted for the ACT and mental health context. TACT subscales were constructed after exploratory and confirmatory factor analyses. The reliability, discriminant validity, predictive validity, temporal stability, internal consistency, and within-team agreement were established with surveys from approximately 300 members of 26 Minnesota ACT teams who completed the questionnaire three times, at six-month intervals. Nine TACT subscales emerged from the analyses: exploration, exploitation of new and existing knowledge, psychological safety, goal agreement, conflict, constructive controversy, information accessibility, encounter preparedness, and consumer-centered care. These nine subscales demonstrated fit and temporal stability (confirmatory factor analysis), high internal consistency (Cronbach's alpha), and within-team agreement and between-team differences (rwg and intraclass correlations). Correlational analyses of the subscales revealed that they measure related yet distinctive aspects of ACT team processes, and regression analyses demonstrated predictive validity (encounter preparedness is related to staff outcomes). The TACT scale demonstrated high reliability and validity and can be included in research and evaluation of teamwork in ACT and mental health teams.

Maladaptive interpersonal schemas as sensitive and specific markers of borderline personality disorder among psychiatric inpatients.

PubMed

Cohen, Lisa J; Tanis, Thachell; Ardalan, Firouz; Yaseen, Zimri; Galynker, Igor

2016-08-30

Diagnostic criteria for borderline personality disorder (BPD) and mood and psychotic disorders characterized by major mood episodes (i.e., major depressive, bipolar and schizoaffective disorder) share marked overlap in symptom presentation, complicating differential diagnosis. The current study tests the hypothesis that maladaptive interpersonal schemas (MIS) are characteristic of BPD, but not of the major mood disorders. One hundred psychiatric inpatients were assessed by SCID I, SCID II and the Young Schema Questionnaire (YSQ-S2). Logistic regression analyses tested the association between MIS (measured by the YSQ-S2) and BPD, bipolar, major depressive and schizoaffective disorder. Receiver operator characteristic (ROC) curve analyses assessed the sensitivity and specificity of MIS as a marker of BPD. After covariation for comorbidity with each of the 3 mood disorders, BPD was robustly associated with 4 out of 5 schema domains. In contrast, only one of fifteen regression analyses demonstrated a significant association between any mood disorder and schema domain after covariation for comorbid BPD. ROC analyses of the 5 schema domains suggested Disconnection/Rejection had the greatest power for identification of BPD cases. These data support the specific role of maladaptive interpersonal schemas in BPD and potentially contribute to greater conceptual clarity about the distinction between BPD and the major mood disorders. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Comparisons of Office and 24-Hour Ambulatory Blood Pressure Monitoring in Children with Obstructive Sleep Apnea.

PubMed

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.

Sitting Time in Adults 65 Years and Over: Behavior, Knowledge, and Intentions to Change.

PubMed

Alley, Stephanie; van Uffelen, Jannique G Z; Duncan, Mitch J; De Cocker, Katrien; Schoeppe, Stephanie; Rebar, Amanda L; Vandelanotte, Corneel

2018-04-01

This study examined sitting time, knowledge, and intentions to change sitting time in older adults. An online survey was completed by 494 Australians aged 65+. Average daily sitting was high (9.0 hr). Daily sitting time was the highest during TV (3.3 hr), computer (2.1 hr), and leisure (1.7 hr). A regression analysis demonstrated that women were more knowledgeable about the health risks of sitting compared to men. The percentage of older adults intending to sit less were the highest for TV (24%), leisure (24%), and computer (19%) sitting time. Regression analyses demonstrated that intentions varied by gender (for TV sitting), education (leisure and work sitting), body mass index (computer, leisure, and transport sitting), and physical activity (TV, computer, and leisure sitting). Interventions should target older adults' TV, computer, and leisure time sitting, with a focus on intentions in older males and older adults with low education, those who are active, and those with a normal weight.

Patterns of medicinal plant use: an examination of the Ecuadorian Shuar medicinal flora using contingency table and binomial analyses.

PubMed

Bennett, Bradley C; Husby, Chad E

2008-03-28

Botanical pharmacopoeias are non-random subsets of floras, with some taxonomic groups over- or under-represented. Moerman [Moerman, D.E., 1979. Symbols and selectivity: a statistical analysis of Native American medical ethnobotany, Journal of Ethnopharmacology 1, 111-119] introduced linear regression/residual analysis to examine these patterns. However, regression, the commonly-employed analysis, suffers from several statistical flaws. We use contingency table and binomial analyses to examine patterns of Shuar medicinal plant use (from Amazonian Ecuador). We first analyzed the Shuar data using Moerman's approach, modified to better meet requirements of linear regression analysis. Second, we assessed the exact randomization contingency table test for goodness of fit. Third, we developed a binomial model to test for non-random selection of plants in individual families. Modified regression models (which accommodated assumptions of linear regression) reduced R(2) to from 0.59 to 0.38, but did not eliminate all problems associated with regression analyses. Contingency table analyses revealed that the entire flora departs from the null model of equal proportions of medicinal plants in all families. In the binomial analysis, only 10 angiosperm families (of 115) differed significantly from the null model. These 10 families are largely responsible for patterns seen at higher taxonomic levels. Contingency table and binomial analyses offer an easy and statistically valid alternative to the regression approach.

Use and misuse of motor-vehicle crash death rates in assessing highway-safety performance.

PubMed

O'Neill, Brian; Kyrychenko, Sergey Y

2006-12-01

The objectives of the article are to assess the extent to which comparisons of motor-vehicle crash death rates can be used to determine the effectiveness of highway-safety policies over time in a country or to compare policy effectiveness across countries. Motor-vehicle crash death rates per mile traveled in the 50 U.S. states from 1980 to 2003 are used to show the influence on these rates of factors independent of highway-safety interventions. Multiple regression models relating state death rates to various measures related to urbanization and demographics are used. The analyses demonstrate strong relationships between state death rates and urbanization and demographics. Almost 60% of the variability among the state death rates can be explained by the independent variables in the multiple regression models. When the death rates for passenger vehicle occupants (i.e., excluding motorcycle, pedestrian, and other deaths) are used in the regression models, almost 70% of the variability in the rates can be explained by urbanization and demographics. The analyses presented in the article demonstrate that motor-vehicle crash death rates are strongly influenced by factors unrelated to highway-safety countermeasures. Overall death rates should not be used as a basis for judging the effectiveness (or ineffectiveness) of specific highway-safety countermeasures or to assess overall highway-safety policies, especially across jurisdictions. There can be no substitute for the use of carefully designed scientific evaluations of highway-safety interventions that use outcome measures directly related to the intervention; e.g., motorcyclist deaths should be used to assess the effectiveness of motorcycle helmet laws. While this may seem obvious, there are numerous examples in the literature of death rates from all crashes being used to assess the effectiveness of interventions aimed at specific subsets of crashes.

Can a toxin gene NAAT be used to predict toxin EIA and the severity of Clostridium difficile infection?

PubMed

Garvey, Mark I; Bradley, Craig W; Wilkinson, Martyn A C; Holden, Elisabeth

2017-01-01

Diagnosis of C. difficile infection (CDI) is controversial because of the many laboratory methods available and their lack of ability to distinguish between carriage, mild or severe disease. Here we describe whether a low C. difficile toxin B nucleic acid amplification test (NAAT) cycle threshold (CT) can predict toxin EIA, CDI severity and mortality. A three-stage algorithm was employed for CDI testing, comprising a screening test for glutamate dehydrogenase (GDH), followed by a NAAT, then a toxin enzyme immunoassay (EIA). All diarrhoeal samples positive for GDH and NAAT between 2012 and 2016 were analysed. The performance of the NAAT CT value as a classifier of toxin EIA outcome was analysed using a ROC curve; patient mortality was compared to CTs and toxin EIA via linear regression models. A CT value ≤26 was associated with ≥72% toxin EIA positivity; applying a logistic regression model we demonstrated an association between low CT values and toxin EIA positivity. A CT value of ≤26 was significantly associated ( p  = 0.0262) with increased one month mortality, severe cases of CDI or failure of first line treatment. The ROC curve probabilities demonstrated a CT cut off value of 26.6. Here we demonstrate that a CT ≤26 indicates more severe CDI and is associated with higher mortality. Samples with a low CT value are often toxin EIA positive, questioning the need for this additional EIA test. A CT ≤26 could be used to assess the potential for severity of CDI and guide patient treatment.

Intimate Partner Violence in Interracial and Monoracial Couples

PubMed Central

Martin, Brittny A.; Cui, Ming; Ueno, Koji; Fincham, Frank D.

2012-01-01

This study investigated intimate partner violence in interracial and monoracial relationships. Using a nationally representative sample, regression analyses indicated that interracial couples demonstrated a higher level of mutual IPV than monoracial white couples but a level similar to monoracial black couples. There were significant gender differences in IPV, with women reporting lower levels of victimization than men. Regarding relationship status, cohabiting couples demonstrated the highest levels of IPV and dating couples reported the lowest levels. Regarding interactions among couple racial composition, relationship status, and respondents’ gender, an interaction between racial composition and relationship status was found. Implications for practitioners and directions for future research are discussed. PMID:23554541

Expression profiling reveals distinct sets of genes altered during induction and regression of cardiac hypertrophy

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

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

PubMed Central

2013-01-01

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

Conditional Poisson models: a flexible alternative to conditional logistic case cross-over analysis.

PubMed

Armstrong, Ben G; Gasparrini, Antonio; Tobias, Aurelio

2014-11-24

The time stratified case cross-over approach is a popular alternative to conventional time series regression for analysing associations between time series of environmental exposures (air pollution, weather) and counts of health outcomes. These are almost always analyzed using conditional logistic regression on data expanded to case-control (case crossover) format, but this has some limitations. In particular adjusting for overdispersion and auto-correlation in the counts is not possible. It has been established that a Poisson model for counts with stratum indicators gives identical estimates to those from conditional logistic regression and does not have these limitations, but it is little used, probably because of the overheads in estimating many stratum parameters. The conditional Poisson model avoids estimating stratum parameters by conditioning on the total event count in each stratum, thus simplifying the computing and increasing the number of strata for which fitting is feasible compared with the standard unconditional Poisson model. Unlike the conditional logistic model, the conditional Poisson model does not require expanding the data, and can adjust for overdispersion and auto-correlation. It is available in Stata, R, and other packages. By applying to some real data and using simulations, we demonstrate that conditional Poisson models were simpler to code and shorter to run than are conditional logistic analyses and can be fitted to larger data sets than possible with standard Poisson models. Allowing for overdispersion or autocorrelation was possible with the conditional Poisson model but when not required this model gave identical estimates to those from conditional logistic regression. Conditional Poisson regression models provide an alternative to case crossover analysis of stratified time series data with some advantages. The conditional Poisson model can also be used in other contexts in which primary control for confounding is by fine stratification.

Early Warning Signals of Financial Crises with Multi-Scale Quantile Regressions of Log-Periodic Power Law Singularities

PubMed Central

Zhang, Qun; Zhang, Qunzhi; Sornette, Didier

2016-01-01

We augment the existing literature using the Log-Periodic Power Law Singular (LPPLS) structures in the log-price dynamics to diagnose financial bubbles by providing three main innovations. First, we introduce the quantile regression to the LPPLS detection problem. This allows us to disentangle (at least partially) the genuine LPPLS signal and the a priori unknown complicated residuals. Second, we propose to combine the many quantile regressions with a multi-scale analysis, which aggregates and consolidates the obtained ensembles of scenarios. Third, we define and implement the so-called DS LPPLS Confidence™ and Trust™ indicators that enrich considerably the diagnostic of bubbles. Using a detailed study of the “S&P 500 1987” bubble and presenting analyses of 16 historical bubbles, we show that the quantile regression of LPPLS signals contributes useful early warning signals. The comparison between the constructed signals and the price development in these 16 historical bubbles demonstrates their significant predictive ability around the real critical time when the burst/rally occurs. PMID:27806093

Bayesian correction for covariate measurement error: A frequentist evaluation and comparison with regression calibration.

PubMed

Bartlett, Jonathan W; Keogh, Ruth H

2018-06-01

Bayesian approaches for handling covariate measurement error are well established and yet arguably are still relatively little used by researchers. For some this is likely due to unfamiliarity or disagreement with the Bayesian inferential paradigm. For others a contributory factor is the inability of standard statistical packages to perform such Bayesian analyses. In this paper, we first give an overview of the Bayesian approach to handling covariate measurement error, and contrast it with regression calibration, arguably the most commonly adopted approach. We then argue why the Bayesian approach has a number of statistical advantages compared to regression calibration and demonstrate that implementing the Bayesian approach is usually quite feasible for the analyst. Next, we describe the closely related maximum likelihood and multiple imputation approaches and explain why we believe the Bayesian approach to generally be preferable. We then empirically compare the frequentist properties of regression calibration and the Bayesian approach through simulation studies. The flexibility of the Bayesian approach to handle both measurement error and missing data is then illustrated through an analysis of data from the Third National Health and Nutrition Examination Survey.

Types of suggestibility: Relationships among compliance, indirect, and direct suggestibility.

PubMed

Polczyk, Romuald; Pasek, Tomasz

2006-10-01

It is commonly believed that direct suggestibility, referring to overt influence, and indirect suggestibility, in which the intention to influence is hidden, correlate poorly. This study demonstrates that they are substantially related, provided that they tap similar areas of influence. Test results from 103 students, 55 women and 48 men, were entered into regression analyses. Indirect suggestibility, as measured by the Sensory Suggestibility Scale for Groups, and compliance, measured by the Gudjonsson Compliance Scale, were predictors of direct suggestibility, assessed with the Barber Suggestibility Scale. Spectral analyses showed that indirect suggestibility is more related to difficult tasks on the BSS, but compliance is more related to easy tasks on this scale.

Age differences in the psychological consequences of Hurricane Hugo.

PubMed

Thompson, M P; Norris, F H; Hanacek, B

1993-12-01

At 12, 18, and 24 months after Hurricane Hugo, 831 adults were interviewed regarding their disaster-related stressors and present psychological state. The study's purposes were to assess whether age influenced one's vulnerability to postdisaster stress and to evaluate four different perspectives on disaster recovery that have been previously used to explain age differences. Regression analyses demonstrated that disaster exposure had substantial and pervasive psychological effects. The analyses also revealed a curvilinear interaction between disaster exposure and age. Younger people exhibited the most distress in the absence of disaster, but middle-aged people did so in its presence. Differential exposure, resources, and inoculation all failed to explain these differences, however, the burden perspective had considerable explanatory power.

Inhibitory saccadic dysfunction is associated with cerebellar injury in multiple sclerosis.

PubMed

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.

Use of Multiple Regression and Use-Availability Analyses in Determining Habitat Selection by Gray Squirrels (Sciurus Carolinensis)

Treesearch

John W. Edwards; Susan C. Loeb; David C. Guynn

1994-01-01

Multiple regression and use-availability analyses are two methods for examining habitat selection. Use-availability analysis is commonly used to evaluate macrohabitat selection whereas multiple regression analysis can be used to determine microhabitat selection. We compared these techniques using behavioral observations (n = 5534) and telemetry locations (n = 2089) of...

Estimated prevalence of halitosis: a systematic review and meta-regression analysis.

PubMed

Silva, Manuela F; Leite, Fábio R M; Ferreira, Larissa B; Pola, Natália M; Scannapieco, Frank A; Demarco, Flávio F; Nascimento, Gustavo G

2018-01-01

This study aims to conduct a systematic review to determine the prevalence of halitosis in adolescents and adults. Electronic searches were performed using four different databases without restrictions: PubMed, Scopus, Web of Science, and SciELO. Population-based observational studies that provided data about the prevalence of halitosis in adolescents and adults were included. Additionally, meta-analyses, meta-regression, and sensitivity analyses were conducted to synthesize the evidence. A total of 584 articles were initially found and considered for title and abstract evaluation. Thirteen articles met inclusion criteria. The combined prevalence of halitosis was found to be 31.8% (95% CI 24.6-39.0%). Methodological aspects such as the year of publication and the socioeconomic status of the country where the study was conducted seemed to influence the prevalence of halitosis. Our results demonstrated that the estimated prevalence of halitosis was 31.8%, with high heterogeneity between studies. The results suggest a worldwide trend towards a rise in halitosis prevalence. Given the high prevalence of halitosis and its complex etiology, dental professionals should be aware of their roles in halitosis prevention and treatment.

EDUCATION AND CORONARY HEART DISEASE RISK: POTENTIAL MECHANISMS SUCH AS LITERACY, PERCEIVED CONSTRAINT AND DEPRESSIVE SYMPTOMS

PubMed Central

Loucks, Eric B.; Gilman, Stephen E.; Howe, Chanelle; Kawachi, Ichiro; Kubzansky, Laura D.; Rudd, Rima E.; Martin, Laurie T.; Nandi, Arijit; Wilhelm, Aude; Buka, Stephen L.

2015-01-01

OBJECTIVE Education is inversely associated with coronary heart disease (CHD) risk, however the mechanisms are poorly understood. The study objectives were to evaluate the extent to which rarely measured factors (literacy, time preference, sense of control) and more commonly measured factors (income, depressive symptomatology, body mass index) in the education-CHD literature explain the associations between education and CHD risk. METHOD The study sample included 346 participants, aged 38–47 years (59.5% women), of the New England Family Study birth cohort. Ten-year CHD risk was calculated using the validated Framingham risk algorithm that utilizes diabetes, smoking, blood pressure, total cholesterol, HDL cholesterol, age and gender. Multivariable regression and mediation analyses were performed. RESULTS Regression analyses adjusting for age, race/ethnicity and childhood confounders (e.g. parental socioeconomic status, intelligence) demonstrated that relative to those with ≥college education, men and women with

Sub-hubs of baseline functional brain networks are related to early improvement following two-week pharmacological therapy for major depressive disorder.

PubMed

Shen, Yuedi; Yao, Jiashu; Jiang, Xueyan; Zhang, Lei; Xu, Luoyi; Feng, Rui; Cai, Liqiang; Liu, Jing; Wang, Jinhui; Chen, Wei

2015-08-01

Accumulating evidence suggests that early improvement after two-week antidepressant treatment is predictive of later outcomes of patients with major depressive disorder (MDD); however, whether this early improvement is associated with baseline neural architecture remains largely unknown. Utilizing resting-state functional MRI data and graph-based network approaches, this study calculated voxel-wise degree centrality maps for 24 MDD patients at baseline and linked them with changes in the Hamilton Rating Scale for Depression (HAMD) scores after two weeks of medication. Six clusters exhibited significant correlations of their baseline degree centrality with treatment-induced HAMD changes for the patients, which were mainly categorized into the posterior default-mode network (i.e., the left precuneus, supramarginal gyrus, middle temporal gyrus, and right angular gyrus) and frontal regions. Receiver operating characteristic curve and logistic regression analyses convergently revealed excellent performance of these regions in discriminating the early improvement status for the patients, especially the angular gyrus (sensitivity and specificity of 100%). Moreover, the angular gyrus was identified as the optimal regressor as determined by stepwise regression. Interestingly, these regions possessed higher centrality than others in the brain (P < 10(-3)) although they were not the most highly connected hubs. Finally, we demonstrate a high reproducibility of our findings across several factors (e.g., threshold choice, anatomical distance, and temporal cutting) in our analyses. Together, these preliminary exploratory analyses demonstrate the potential of neuroimaging-based network analysis in predicting the early therapeutic improvement of MDD patients and have important implications in guiding earlier personalized therapeutic regimens for possible treatment-refractory depression. © 2015 Wiley Periodicals, Inc.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-05-15

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

Multilevel regression analyses to investigate the relationship between two variables over time: examining the longitudinal association between intrusion and avoidance.

PubMed

Suvak, Michael K; Walling, Sherry M; Iverson, Katherine M; Taft, Casey T; Resick, Patricia A

2009-12-01

Multilevel modeling is a powerful and flexible framework for analyzing nested data structures (e.g., repeated measures or longitudinal designs). The authors illustrate a series of multilevel regression procedures that can be used to elucidate the nature of the relationship between two variables across time. The goal is to help trauma researchers become more aware of the utility of multilevel modeling as a tool for increasing the field's understanding of posttraumatic adaptation. These procedures are demonstrated by examining the relationship between two posttraumatic symptoms, intrusion and avoidance, across five assessment points in a sample of rape and robbery survivors (n = 286). Results revealed that changes in intrusion were highly correlated with changes in avoidance over the 18-month posttrauma period.

Computational tools for exact conditional logistic regression.

PubMed

Corcoran, C; Mehta, C; Patel, N; Senchaudhuri, P

Logistic regression analyses are often challenged by the inability of unconditional likelihood-based approximations to yield consistent, valid estimates and p-values for model parameters. This can be due to sparseness or separability in the data. Conditional logistic regression, though useful in such situations, can also be computationally unfeasible when the sample size or number of explanatory covariates is large. We review recent developments that allow efficient approximate conditional inference, including Monte Carlo sampling and saddlepoint approximations. We demonstrate through real examples that these methods enable the analysis of significantly larger and more complex data sets. We find in this investigation that for these moderately large data sets Monte Carlo seems a better alternative, as it provides unbiased estimates of the exact results and can be executed in less CPU time than can the single saddlepoint approximation. Moreover, the double saddlepoint approximation, while computationally the easiest to obtain, offers little practical advantage. It produces unreliable results and cannot be computed when a maximum likelihood solution does not exist. Copyright 2001 John Wiley & Sons, Ltd.

The arcsine is asinine: the analysis of proportions in ecology.

PubMed

Warton, David I; Hui, Francis K C

2011-01-01

The arcsine square root transformation has long been standard procedure when analyzing proportional data in ecology, with applications in data sets containing binomial and non-binomial response variables. Here, we argue that the arcsine transform should not be used in either circumstance. For binomial data, logistic regression has greater interpretability and higher power than analyses of transformed data. However, it is important to check the data for additional unexplained variation, i.e., overdispersion, and to account for it via the inclusion of random effects in the model if found. For non-binomial data, the arcsine transform is undesirable on the grounds of interpretability, and because it can produce nonsensical predictions. The logit transformation is proposed as an alternative approach to address these issues. Examples are presented in both cases to illustrate these advantages, comparing various methods of analyzing proportions including untransformed, arcsine- and logit-transformed linear models and logistic regression (with or without random effects). Simulations demonstrate that logistic regression usually provides a gain in power over other methods.

Bayesian generalized least squares regression with application to log Pearson type 3 regional skew estimation

NASA Astrophysics Data System (ADS)

Reis, D. S.; Stedinger, J. R.; Martins, E. S.

2005-10-01

This paper develops a Bayesian approach to analysis of a generalized least squares (GLS) regression model for regional analyses of hydrologic data. The new approach allows computation of the posterior distributions of the parameters and the model error variance using a quasi-analytic approach. Two regional skew estimation studies illustrate the value of the Bayesian GLS approach for regional statistical analysis of a shape parameter and demonstrate that regional skew models can be relatively precise with effective record lengths in excess of 60 years. With Bayesian GLS the marginal posterior distribution of the model error variance and the corresponding mean and variance of the parameters can be computed directly, thereby providing a simple but important extension of the regional GLS regression procedures popularized by Tasker and Stedinger (1989), which is sensitive to the likely values of the model error variance when it is small relative to the sampling error in the at-site estimator.

Comparative study of contrast-enhanced ultrasound qualitative and quantitative analysis for identifying benign and malignant breast tumor lumps.

PubMed

Liu, Jian; Gao, Yun-Hua; Li, Ding-Dong; Gao, Yan-Chun; Hou, Ling-Mi; Xie, Ting

2014-01-01

To compare the value of contrast-enhanced ultrasound (CEUS) qualitative and quantitative analysis in the identification of breast tumor lumps. Qualitative and quantitative indicators of CEUS for 73 cases of breast tumor lumps were retrospectively analyzed by univariate and multivariate approaches. Logistic regression was applied and ROC curves were drawn for evaluation and comparison. The CEUS qualitative indicator-generated regression equation contained three indicators, namely enhanced homogeneity, diameter line expansion and peak intensity grading, which demonstrated prediction accuracy for benign and malignant breast tumor lumps of 91.8%; the quantitative indicator-generated regression equation only contained one indicator, namely the relative peak intensity, and its prediction accuracy was 61.5%. The corresponding areas under the ROC curve for qualitative and quantitative analyses were 91.3% and 75.7%, respectively, which exhibited a statistically significant difference by the Z test (P<0.05). The ability of CEUS qualitative analysis to identify breast tumor lumps is better than with quantitative analysis.

Performance evaluation of the automated nucleated red blood cell enumeration on Sysmex XN analyser.

PubMed

Tantanate, C; Klinbua, C

2015-06-01

Presence of peripheral blood nucleated red blood cell (NRBC) is associated with pathological conditions and leads to the overestimation of white blood cell count in automated haematology analysers (HA). The authors evaluated NRBC enumeration by a new HA Sysmex XN (XN) to demonstrate the precision and comparability to manual count (MC) at the various NRBC values. Specimens with initially NRBC positive were included. For precision assessment, 8 levels of NRBCs were repeatedly analysed. For comparison study, 234 specimens were analysed by both XN and MC. For precision study, the percentage of coefficient of variation ranged from 14% to 45.6% and 1.2% to 4.4% for MC and XN, respectively. For comparison study between XN and MC, NRBCs ranged from 0% to 612.5%. Regression analysis demonstrated an r(2) of 0.98. The mean bias of 14.1% with 95% limits of agreement between -48.76% and 76.95% was found. The NRBC counts from XN appeared to be more in accordance with MC when the NRBCs were lower than 200% with the concordance rate of 94.2%. The automated NRBC enumeration by XN was precise and could replace the traditional MC, especially for the specimens with NRBCs lower than 200%. © 2014 John Wiley & Sons Ltd.

The use of segmented regression in analysing interrupted time series studies: an example in pre-hospital ambulance care.

PubMed

Taljaard, Monica; McKenzie, Joanne E; Ramsay, Craig R; Grimshaw, Jeremy M

2014-06-19

An interrupted time series design is a powerful quasi-experimental approach for evaluating effects of interventions introduced at a specific point in time. To utilize the strength of this design, a modification to standard regression analysis, such as segmented regression, is required. In segmented regression analysis, the change in intercept and/or slope from pre- to post-intervention is estimated and used to test causal hypotheses about the intervention. We illustrate segmented regression using data from a previously published study that evaluated the effectiveness of a collaborative intervention to improve quality in pre-hospital ambulance care for acute myocardial infarction (AMI) and stroke. In the original analysis, a standard regression model was used with time as a continuous variable. We contrast the results from this standard regression analysis with those from segmented regression analysis. We discuss the limitations of the former and advantages of the latter, as well as the challenges of using segmented regression in analysing complex quality improvement interventions. Based on the estimated change in intercept and slope from pre- to post-intervention using segmented regression, we found insufficient evidence of a statistically significant effect on quality of care for stroke, although potential clinically important effects for AMI cannot be ruled out. Segmented regression analysis is the recommended approach for analysing data from an interrupted time series study. Several modifications to the basic segmented regression analysis approach are available to deal with challenges arising in the evaluation of complex quality improvement interventions.

Predictive Accuracy of Violence Risk Scale-Sexual Offender Version Risk and Change Scores in Treated Canadian Aboriginal and Non-Aboriginal Sexual Offenders.

PubMed

Olver, Mark E; Sowden, Justina N; Kingston, Drew A; Nicholaichuk, Terry P; Gordon, Audrey; Beggs Christofferson, Sarah M; Wong, Stephen C P

2018-04-01

The present study examined the predictive properties of Violence Risk Scale-Sexual Offender version (VRS-SO) risk and change scores among Aboriginal and non-Aboriginal sexual offenders in a combined sample of 1,063 Canadian federally incarcerated men. All men participated in sexual offender treatment programming through the Correctional Service of Canada (CSC) at sites across its five regions. The Static-99R was also examined for comparison purposes. In total, 393 of the men were identified as Aboriginal (i.e., First Nations, Métis, Circumpolar) while 670 were non-Aboriginal and primarily White. Aboriginal men scored significantly higher on the Static-99R and VRS-SO and had higher rates of sexual and violent recidivism; however, there were no significant differences between Aboriginal and non-Aboriginal groups on treatment change with both groups demonstrating close to a half-standard deviation of change pre and post treatment. VRS-SO risk and change scores significantly predicted sexual and violent recidivism over fixed 5- and 10-year follow-ups for both racial/ancestral groups. Cox regression survival analyses also demonstrated positive treatment changes to be significantly associated with reductions in sexual and violent recidivism among Aboriginal and non-Aboriginal men after controlling baseline risk. A series of follow-up Cox regression analyses demonstrated that risk and change score information accounted for much of the observed differences between Aboriginal and non-Aboriginal men in rates of sexual recidivism; however, marked group differences persisted in rates of general violent recidivism even after controlling for these covariates. The results support the predictive properties of VRS-SO risk and change scores with treated Canadian Aboriginal sexual offenders.

Gender Gaps in Mathematics, Science and Reading Achievements in Muslim Countries: Evidence from Quantile Regression Analyses

ERIC Educational Resources Information Center

Shafiq, M. Najeeb

2011-01-01

Using quantile regression analyses, this study examines gender gaps in mathematics, science, and reading in Azerbaijan, Indonesia, Jordan, the Kyrgyz Republic, Qatar, Tunisia, and Turkey among 15 year-old students. The analyses show that girls in Azerbaijan achieve as well as boys in mathematics and science and overachieve in reading. In Jordan,…

Multinomial Logistic Regression Predicted Probability Map To Visualize The Influence Of Socio-Economic Factors On Breast Cancer Occurrence in Southern Karnataka

NASA Astrophysics Data System (ADS)

Madhu, B.; Ashok, N. C.; Balasubramanian, S.

2014-11-01

Multinomial logistic regression analysis was used to develop statistical model that can predict the probability of breast cancer in Southern Karnataka using the breast cancer occurrence data during 2007-2011. Independent socio-economic variables describing the breast cancer occurrence like age, education, occupation, parity, type of family, health insurance coverage, residential locality and socioeconomic status of each case was obtained. The models were developed as follows: i) Spatial visualization of the Urban- rural distribution of breast cancer cases that were obtained from the Bharat Hospital and Institute of Oncology. ii) Socio-economic risk factors describing the breast cancer occurrences were complied for each case. These data were then analysed using multinomial logistic regression analysis in a SPSS statistical software and relations between the occurrence of breast cancer across the socio-economic status and the influence of other socio-economic variables were evaluated and multinomial logistic regression models were constructed. iii) the model that best predicted the occurrence of breast cancer were identified. This multivariate logistic regression model has been entered into a geographic information system and maps showing the predicted probability of breast cancer occurrence in Southern Karnataka was created. This study demonstrates that Multinomial logistic regression is a valuable tool for developing models that predict the probability of breast cancer Occurrence in Southern Karnataka.

The development and validation of the Physical Appearance Comparison Scale-Revised (PACS-R).

PubMed

Schaefer, Lauren M; Thompson, J Kevin

2014-04-01

The Physical Appearance Comparison Scale (PACS; Thompson, Heinberg, & Tantleff, 1991) was revised to assess appearance comparisons relevant to women and men in a wide variety of contexts. The revised scale (Physical Appearance Comparison Scale-Revised, PACS-R) was administered to 1176 college females. In Study 1, exploratory factor analysis and parallel analysis using one half of the sample suggested a single factor structure for the PACS-R. Study 2 utilized the remaining half of the sample to conduct confirmatory factor analysis, item analysis, and to examine the convergent validity of the scale. These analyses resulted in an 11-item measure that demonstrated excellent internal consistency and convergent validity with measures of body satisfaction, eating pathology, sociocultural influences on appearance, and self-esteem. Regression analyses demonstrated the utility of the PACS-R in predicting body satisfaction and eating pathology. Overall, results indicate that the PACS-R is a reliable and valid tool for assessing appearance comparison tendencies in women. Copyright © 2014. Published by Elsevier Ltd.

A general framework for the use of logistic regression models in meta-analysis.

PubMed

Simmonds, Mark C; Higgins, Julian Pt

2016-12-01

Where individual participant data are available for every randomised trial in a meta-analysis of dichotomous event outcomes, "one-stage" random-effects logistic regression models have been proposed as a way to analyse these data. Such models can also be used even when individual participant data are not available and we have only summary contingency table data. One benefit of this one-stage regression model over conventional meta-analysis methods is that it maximises the correct binomial likelihood for the data and so does not require the common assumption that effect estimates are normally distributed. A second benefit of using this model is that it may be applied, with only minor modification, in a range of meta-analytic scenarios, including meta-regression, network meta-analyses and meta-analyses of diagnostic test accuracy. This single model can potentially replace the variety of often complex methods used in these areas. This paper considers, with a range of meta-analysis examples, how random-effects logistic regression models may be used in a number of different types of meta-analyses. This one-stage approach is compared with widely used meta-analysis methods including Bayesian network meta-analysis and the bivariate and hierarchical summary receiver operating characteristic (ROC) models for meta-analyses of diagnostic test accuracy. © The Author(s) 2014.

Social vulnerability and bullying in children with Asperger syndrome.

PubMed

Sofronoff, Kate; Dark, Elizabeth; Stone, Valerie

2011-05-01

Children with Asperger syndrome (AS) have IQ within the normal range but specific impairments in theory of mind, social interaction and communication skills. The majority receive education in mainstream schools and research suggests they are bullied more than typically developing peers. The current study aimed to evaluate factors that predict bullying for such children and also to examine a new measure, the Social Vulnerability Scale (SVS). One hundred and thirty three parents of children with AS completed the SVS and of these 92 parents completed both the SVS and questionnaires measuring anxiety, anger, behaviour problems, social skills and bullying. Regression analyses revealed that these variables together strongly predicted bullying, but that social vulnerability was the strongest predictor. Test-re-test and internal consistency analyses of the SVS demonstrated sound psychometric properties and factor analyses revealed two sub-scales: gullibility and credulity. Limitations of the study are acknowledged and suggestions for future research discussed.

Paternal Autonomy Restriction, Neighborhood Safety, and Child Anxiety Trajectory in Community Youth.

PubMed

Cooper-Vince, Christine E; Chan, Priscilla T; Pincus, Donna B; Comer, Jonathan S

2014-07-01

Intrusive parenting, primarily examined among middle to upper-middle class mothers, has been positively associated with the presence and severity of anxiety in children. This study employed cross-sectional linear regression and longitudinal latent growth curve analyses to evaluate the main and interactive effects of early childhood paternal autonomy restriction (AR) and neighborhood safety (NS) on the trajectory of child anxiety in a sample of 596 community children and fathers from the NICHD SECYD. Longitudinal analyses revealed that greater paternal AR at age 6 was actually associated with greater decreases in child anxiety in later childhood. Cross-sectional analyses revealed main effects for NS across childhood, and interactive effects of paternal AR and NS that were present only in early childhood, whereby children living in safer neighborhoods demonstrated increased anxiety when experiencing lower levels of paternal AR. Findings further clarify for whom and when paternal AR impacts child anxiety in community youth.

Paternal Autonomy Restriction, Neighborhood Safety, and Child Anxiety Trajectory in Community Youth

PubMed Central

Cooper-Vince, Christine E.; Chan, Priscilla T.; Pincus, Donna B.; Comer, Jonathan S.

2014-01-01

Intrusive parenting, primarily examined among middle to upper-middle class mothers, has been positively associated with the presence and severity of anxiety in children. This study employed cross-sectional linear regression and longitudinal latent growth curve analyses to evaluate the main and interactive effects of early childhood paternal autonomy restriction (AR) and neighborhood safety (NS) on the trajectory of child anxiety in a sample of 596 community children and fathers from the NICHD SECYD. Longitudinal analyses revealed that greater paternal AR at age 6 was actually associated with greater decreases in child anxiety in later childhood. Cross-sectional analyses revealed main effects for NS across childhood, and interactive effects of paternal AR and NS that were present only in early childhood, whereby children living in safer neighborhoods demonstrated increased anxiety when experiencing lower levels of paternal AR. Findings further clarify for whom and when paternal AR impacts child anxiety in community youth. PMID:25242837

Core OCD Symptoms: Exploration of Specificity and Relations with Psychopathology

PubMed Central

Stasik, Sara M.; Naragon-Gainey, Kristin; Chmielewski, Michael; Watson, David

2012-01-01

Obsessive-compulsive disorder (OCD) is a heterogeneous condition, comprised of multiple symptom domains. This study used aggregate composite scales representing three core OCD dimensions (Checking, Cleaning, Rituals), as well as Hoarding, to examine the discriminant validity, diagnostic specificity, and predictive ability of OCD symptom scales. The core OCD scales demonstrated strong patterns of convergent and discriminant validity – suggesting that these dimensions are distinct from other self-reported symptoms – whereas hoarding symptoms correlated just as strongly with OCD and non-OCD symptoms in most analyses. Across analyses, our results indicated that Checking is a particularly strong, specific marker of OCD diagnosis, whereas the specificity of Cleaning and Hoarding to OCD was less strong. Finally, the OCD Checking scale was the only significant predictor of OCD diagnosis in logistic regression analyses. Results are discussed with regard to the importance of assessing OCD symptom dimensions separately and implications for classification. PMID:23026094

The effect of psychotherapeutic interventions on positive and negative affect in depression: A systematic review and meta-analysis.

PubMed

Boumparis, Nikolaos; Karyotaki, Eirini; Kleiboer, Annet; Hofmann, Stefan G; Cuijpers, Pim

2016-09-15

Depression is a mental disorder characterized by high and dysregulated negative affect in addition to diminished positive affect. To our knowledge, there has been no systematic review of the impact of psychotherapeutic interventions on these affective dimensions. Two comprehensive literature searches for all randomized controlled trials of psychotherapy in adults with depression were performed. The first from 1996 to December 31, 2014 and the second from January 1, 2015 to December 31, 2015. The primary outcome was the mean score of positive and negative affect. Depressive symptoms were measured to be included as a predictor in the meta-regression analyses. Ten studies with 793 adults with depression were included. All studies assessed positive and negative affect. Psychotherapeutic interventions resulted in significantly increased positive affect (g=0.41; 95% CI: 0.16-0.66 p=0.001), and significantly decreased negative affect (g=0.32; 95% CI: 0.15-0.78, p=0.001) in depressed adults. Because of the small number and substantial heterogeneity of the existing studies the meta-regression analyses produced conflicting results. As a consequence, we were unable to sufficiently demonstrate whether NA and depressive symptoms are in fact correlated or not. Given the small number and heterogeneity of the included studies, the findings should be considered with caution. Psychotherapeutic interventions demonstrate low to moderate effects in enhancing positive and reducing negative affect in depressed adults. Copyright © 2016 Elsevier B.V. All rights reserved.

Screening for beryllium disease among construction trade workers at Department of Energy nuclear sites.

PubMed

Welch, Laura; Ringen, Knut; Bingham, Eula; Dement, John; Takaro, Tim; McGowan, William; Chen, Anna; Quinn, Patricia

2004-09-01

To determine whether current and former construction workers are at significant risk for occupational illnesses from work at the Department of Energy's (DOE) nuclear weapons facilities, screening programs were undertaken at the Hanford Nuclear Reservation, Oak Ridge Reservation, and the Savannah River Site. Medical examination for beryllium disease used a medical history and a beryllium blood lymphocyte proliferation test (BeLPT). Stratified and multivariate logistic regression analyses were used to explore the risk of disease by age, race, sex, trade, duration of DOE employment, reported work in buildings where beryllium was used, and time since last DOE site employment. Of the 3,842 workers included in this study, 34% reported exposure to beryllium. Overall, 2.2% of workers had at least one abnormal BeLPT test, and 1.4% were also abnormal on a second test. Regression analyses demonstrated increased risk of having at least one abnormal BeLPT to be associated with ever working in a site building where beryllium activities had taken place. The prevalence of beryllium sensitivity and chronic beryllium disease (CBD) in construction workers is described and the positive predictive value of the BeLPT in a population with less intense exposure to beryllium than other populations that have been screened is discussed. The BeLPT findings and finding of cases of CBD demonstrate that some of these workers had significant exposure, most likely, during maintenance, repair, renovation, or demolition in facilities where beryllium was used.

Can biomechanical variables predict improvement in crouch gait?

PubMed Central

Hicks, Jennifer L.; Delp, Scott L.; Schwartz, Michael H.

2011-01-01

Many patients respond positively to treatments for crouch gait, yet surgical outcomes are inconsistent and unpredictable. In this study, we developed a multivariable regression model to determine if biomechanical variables and other subject characteristics measured during a physical exam and gait analysis can predict which subjects with crouch gait will demonstrate improved knee kinematics on a follow-up gait analysis. We formulated the model and tested its performance by retrospectively analyzing 353 limbs of subjects who walked with crouch gait. The regression model was able to predict which subjects would demonstrate ‘improved’ and ‘unimproved’ knee kinematics with over 70% accuracy, and was able to explain approximately 49% of the variance in subjects’ change in knee flexion between gait analyses. We found that improvement in stance phase knee flexion was positively associated with three variables that were drawn from knowledge about the biomechanical contributors to crouch gait: i) adequate hamstrings lengths and velocities, possibly achieved via hamstrings lengthening surgery, ii) normal tibial torsion, possibly achieved via tibial derotation osteotomy, and iii) sufficient muscle strength. PMID:21616666

Modelling of capital asset pricing by considering the lagged effects

NASA Astrophysics Data System (ADS)

Sukono; Hidayat, Y.; Bon, A. Talib bin; Supian, S.

2017-01-01

In this paper the problem of modelling the Capital Asset Pricing Model (CAPM) with the effect of the lagged is discussed. It is assumed that asset returns are analysed influenced by the market return and the return of risk-free assets. To analyse the relationship between asset returns, the market return, and the return of risk-free assets, it is conducted by using a regression equation of CAPM, and regression equation of lagged distributed CAPM. Associated with the regression equation lagged CAPM distributed, this paper also developed a regression equation of Koyck transformation CAPM. Results of development show that the regression equation of Koyck transformation CAPM has advantages, namely simple as it only requires three parameters, compared with regression equation of lagged distributed CAPM.

The importance of extent of choroid plexus cauterization in addition to endoscopic third ventriculostomy for infantile hydrocephalus: a retrospective North American observational study using propensity score-adjusted analysis.

PubMed

Fallah, Aria; Weil, Alexander G; Juraschka, Kyle; Ibrahim, George M; Wang, Anthony C; Crevier, Louis; Tseng, Chi-Hong; Kulkarni, Abhaya V; Ragheb, John; Bhatia, Sanjiv

2017-12-01

OBJECTIVE Combined endoscopic third ventriculostomy (ETC) and choroid plexus cauterization (CPC)-ETV/CPC- is being investigated to increase the rate of shunt independence in infants with hydrocephalus. The degree of CPC necessary to achieve improved rates of shunt independence is currently unknown. METHODS Using data from a single-center, retrospective, observational cohort study involving patients who underwent ETV/CPC for treatment of infantile hydrocephalus, comparative statistical analyses were performed to detect a difference in need for subsequent CSF diversion procedure in patients undergoing partial CPC (describes unilateral CPC or bilateral CPC that only extended from the foramen of Monro [FM] to the atrium on one side) or subtotal CPC (describes CPC extending from the FM to the posterior temporal horn bilaterally) using a rigid neuroendoscope. Propensity scores for extent of CPC were calculated using age and etiology. Propensity scores were used to perform 1) case-matching comparisons and 2) Cox multivariable regression, adjusting for propensity score in the unmatched cohort. Cox multivariable regression adjusting for age and etiology, but not propensity score was also performed as a third statistical technique. RESULTS Eighty-four patients who underwent ETV/CPC had sufficient data to be included in the analysis. Subtotal CPC was performed in 58 patients (69%) and partial CPC in 26 (31%). The ETV/CPC success rates at 6 and 12 months, respectively, were 49% and 41% for patients undergoing subtotal CPC and 35% and 31% for those undergoing partial CPC. Cox multivariate regression in a 48-patient cohort case-matched by propensity score demonstrated no added effect of increased extent of CPC on ETV/CPC survival (HR 0.868, 95% CI 0.422-1.789, p = 0.702). Cox multivariate regression including all patients, with adjustment for propensity score, demonstrated no effect of extent of CPC on ETV/CPC survival (HR 0.845, 95% CI 0.462-1.548, p = 0.586). Cox multivariate regression including all patients, with adjustment for age and etiology, but not propensity score, demonstrated no effect of extent of CPC on ETV/CPC survival (HR 0.908, 95% CI 0.495-1.664, p = 0.755). CONCLUSIONS Using multiple comparative statistical analyses, no difference in need for subsequent CSF diversion procedure was detected between patients in this cohort who underwent partial versus subtotal CPC. Further investigation regarding whether there is truly no difference between partial versus subtotal extent of CPC in larger patient populations and whether further gain in CPC success can be achieved with complete CPC is warranted.

Use of probabilistic weights to enhance linear regression myoelectric control

NASA Astrophysics Data System (ADS)

Smith, Lauren H.; Kuiken, Todd A.; Hargrove, Levi J.

2015-12-01

Objective. Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Approach. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts’ law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Main results. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p < 0.05) by preventing extraneous movement at additional DOFs. Similar results were seen in experiments with two transradial amputees. Though goodness-of-fit evaluations suggested that the EMG feature distributions showed some deviations from the Gaussian, equal-covariance assumptions used in this experiment, the assumptions were sufficiently met to provide improved performance compared to linear regression control. Significance. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.

Use of principal-component, correlation, and stepwise multiple-regression analyses to investigate selected physical and hydraulic properties of carbonate-rock aquifers

USGS Publications Warehouse

Brown, C. Erwin

1993-01-01

Correlation analysis in conjunction with principal-component and multiple-regression analyses were applied to laboratory chemical and petrographic data to assess the usefulness of these techniques in evaluating selected physical and hydraulic properties of carbonate-rock aquifers in central Pennsylvania. Correlation and principal-component analyses were used to establish relations and associations among variables, to determine dimensions of property variation of samples, and to filter the variables containing similar information. Principal-component and correlation analyses showed that porosity is related to other measured variables and that permeability is most related to porosity and grain size. Four principal components are found to be significant in explaining the variance of data. Stepwise multiple-regression analysis was used to see how well the measured variables could predict porosity and (or) permeability for this suite of rocks. The variation in permeability and porosity is not totally predicted by the other variables, but the regression is significant at the 5% significance level. ?? 1993.

SOCR Analyses - an Instructional Java Web-based Statistical Analysis Toolkit.

PubMed

Chu, Annie; Cui, Jenny; Dinov, Ivo D

2009-03-01

The Statistical Online Computational Resource (SOCR) designs web-based tools for educational use in a variety of undergraduate courses (Dinov 2006). Several studies have demonstrated that these resources significantly improve students' motivation and learning experiences (Dinov et al. 2008). SOCR Analyses is a new component that concentrates on data modeling and analysis using parametric and non-parametric techniques supported with graphical model diagnostics. Currently implemented analyses include commonly used models in undergraduate statistics courses like linear models (Simple Linear Regression, Multiple Linear Regression, One-Way and Two-Way ANOVA). In addition, we implemented tests for sample comparisons, such as t-test in the parametric category; and Wilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, in the non-parametric category. SOCR Analyses also include several hypothesis test models, such as Contingency tables, Friedman's test and Fisher's exact test.The code itself is open source (http://socr.googlecode.com/), hoping to contribute to the efforts of the statistical computing community. The code includes functionality for each specific analysis model and it has general utilities that can be applied in various statistical computing tasks. For example, concrete methods with API (Application Programming Interface) have been implemented in statistical summary, least square solutions of general linear models, rank calculations, etc. HTML interfaces, tutorials, source code, activities, and data are freely available via the web (www.SOCR.ucla.edu). Code examples for developers and demos for educators are provided on the SOCR Wiki website.In this article, the pedagogical utilization of the SOCR Analyses is discussed, as well as the underlying design framework. As the SOCR project is on-going and more functions and tools are being added to it, these resources are constantly improved. The reader is strongly encouraged to check the SOCR site for most updated information and newly added models.

Impact of Contextual Factors on Prostate Cancer Risk and Outcomes

DTIC Science & Technology

2013-07-01

framework with random effects (“frailty models”) while the case-control analyses (Aim 4) will use multilevel unconditional logistic regression models...contextual-level SES on prostate cancer risk within racial/ethnic groups. The survival analyses (Aims 1-3) will utilize a proportional hazards regression

An Investigation of Executive Functioning in Pediatric Anxiety.

PubMed

Murphy, Yolanda E; Luke, Anna; Brennan, Elle; Francazio, Sarah; Christopher, Isabella; Flessner, Christopher A

2018-01-01

Although science's understanding (e.g., etiology, maintaining factors, etc.) of pediatric anxiety and related problems has grown substantially over recent years, several aspects to anxiety in youths remain elusive, particularly with relation to executive functioning. To this end, the current study sought to examine several facets to executive functioning (i.e., cognitive flexibility, inhibition, planning, working memory) within a transdiagnostic sample of youths exhibiting varying degrees of anxiety symptoms. One hundred six youths completed a comprehensive battery, including several self-report measures (e.g., Multidimensional Anxiety Scale for Children [MASC] or MASC-2) and an automated neurocognitive battery of several executive functioning tasks (Intradimensional/Extradimensional [IDED], Stop Signal [SST], Spatial Span [SSP], Stockings of Cambridge [SOC] tasks). Regression analyses indicated that youths exhibiting marked anxiety symptoms demonstrated increased planning time and probability of inhibition compared with youths with minimal or no anxiety symptoms. Youths with marked anxiety symptoms similarly demonstrated better cognitive flexibility (i.e., set shifting) compared with youths with minimal anxiety. In addition, analyses indicated a trend such that youths exhibiting marked anxiety symptoms demonstrated poorer working memory compared with youths with no anxiety symptoms. Group classification did not predict remaining outcomes. Limitations and future areas of research are discussed.

Glomerular structural-functional relationship models of diabetic nephropathy are robust in type 1 diabetic patients.

PubMed

Mauer, Michael; Caramori, Maria Luiza; Fioretto, Paola; Najafian, Behzad

2015-06-01

Studies of structural-functional relationships have improved understanding of the natural history of diabetic nephropathy (DN). However, in order to consider structural end points for clinical trials, the robustness of the resultant models needs to be verified. This study examined whether structural-functional relationship models derived from a large cohort of type 1 diabetic (T1D) patients with a wide range of renal function are robust. The predictability of models derived from multiple regression analysis and piecewise linear regression analysis was also compared. T1D patients (n = 161) with research renal biopsies were divided into two equal groups matched for albumin excretion rate (AER). Models to explain AER and glomerular filtration rate (GFR) by classical DN lesions in one group (T1D-model, or T1D-M) were applied to the other group (T1D-test, or T1D-T) and regression analyses were performed. T1D-M-derived models explained 70 and 63% of AER variance and 32 and 21% of GFR variance in T1D-M and T1D-T, respectively, supporting the substantial robustness of the models. Piecewise linear regression analyses substantially improved predictability of the models with 83% of AER variance and 66% of GFR variance explained by classical DN glomerular lesions alone. These studies demonstrate that DN structural-functional relationship models are robust, and if appropriate models are used, glomerular lesions alone explain a major proportion of AER and GFR variance in T1D patients. © The Author 2014. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Socioeconomic determinants of childhood overweight and obesity in China: the long arm of institutional power

PubMed Central

Fu, Qiang; George, Linda K.

2018-01-01

Abstract Previous studies have widely reported that the association between socioeconomic status (SES) and childhood overweight and obesity in China is significant and positive, which lends little support to the fundamental-cause perspective. Using multiple waves (1997, 2000, 2004 and 2006) of the China Health and Nutrition Survey (CHNS) (N = 2,556, 2,063, 1,431 and 1,242, respectively) and continuous BMI cut-points obtained from a polynomial method, (mixed-effect) logistic regression analyses show that parental state-sector employment, an important, yet overlooked, indicator of political power during the market transformation has changed from a risk factor for childhood overweight/obesity in 1997 to a protective factor for childhood overweight/obesity in 2006. Results from quantile regression analyses generate the same conclusions and demonstrate that the protective effect of parental state sector employment at high percentiles of BMI is robust under different estimation strategies. By bridging the fundamental causes perspective and theories of market transformation, this research not only documents the effect of political power on childhood overweight/obesity but also calls for the use of multifaceted, culturally-relevant stratification measures in testing the fundamental cause perspective across time and space. PMID:26178452

Robust Machine Learning Variable Importance Analyses of Medical Conditions for Health Care Spending.

PubMed

Rose, Sherri

2018-03-11

To propose nonparametric double robust machine learning in variable importance analyses of medical conditions for health spending. 2011-2012 Truven MarketScan database. I evaluate how much more, on average, commercially insured enrollees with each of 26 of the most prevalent medical conditions cost per year after controlling for demographics and other medical conditions. This is accomplished within the nonparametric targeted learning framework, which incorporates ensemble machine learning. Previous literature studying the impact of medical conditions on health care spending has almost exclusively focused on parametric risk adjustment; thus, I compare my approach to parametric regression. My results demonstrate that multiple sclerosis, congestive heart failure, severe cancers, major depression and bipolar disorders, and chronic hepatitis are the most costly medical conditions on average per individual. These findings differed from those obtained using parametric regression. The literature may be underestimating the spending contributions of several medical conditions, which is a potentially critical oversight. If current methods are not capturing the true incremental effect of medical conditions, undesirable incentives related to care may remain. Further work is needed to directly study these issues in the context of federal formulas. © Health Research and Educational Trust.

Subacute casemix classification for stroke rehabilitation in Australia. How well does AN-SNAP v2 explain variance in outcomes?

PubMed

Kohler, Friedbert; Renton, Roger; Dickson, Hugh G; Estell, John; Connolly, Carol E

2011-02-01

We sought the best predictors for length of stay, discharge destination and functional improvement for inpatients undergoing rehabilitation following a stroke and compared these predictors against AN-SNAP v2. The Oxfordshire classification subgroup, sociodemographic data and functional data were collected for patients admitted between 1997 and 2007, with a diagnosis of recent stroke. The data were factor analysed using Principal Components Analysis for categorical data (CATPCA). Categorical regression analyses was performed to determine the best predictors of length of stay, discharge destination, and functional improvement. A total of 1154 patients were included in the study. Principal components analysis indicated that the data were effectively unidimensional, with length of stay being the most important component. Regression analysis demonstrated that the best predictor was the admission motor FIM score, explaining 38.9% of variance for length of stay, 37.4%.of variance for functional improvement and 16% of variance for discharge destination. The best explanatory variable in our inpatient rehabilitation service is the admission motor FIM. AN- SNAP v2 classification is a less effective explanatory variable. This needs to be taken into account when using AN-SNAP v2 classification for clinical or funding purposes.

Phylogenetically diverse macrophyte community promotes species diversity of mobile epi-benthic invertebrates

NASA Astrophysics Data System (ADS)

Nakamoto, Kenta; Hayakawa, Jun; Kawamura, Tomohiko; Kodama, Masafumi; Yamada, Hideaki; Kitagawa, Takashi; Watanabe, Yoshiro

2018-07-01

Various aspects of plant diversity such as species diversity and phylogenetic diversity enhance the species diversity of associated animals in terrestrial systems. In marine systems, however, the effects of macrophyte diversity on the species diversity of associated animals have received little attention. Here, we sampled in a subtropical seagrass-seaweed mixed bed to elucidate the effect of the macrophyte phylogenetic diversity based on the taxonomic relatedness as well as the macrophyte species diversity on species diversity of mobile epi-benthic invertebrates. Using regression analyses for each macrophyte parameter as well as multiple regression analyses, we found that the macrophyte phylogenetic diversity (taxonomic diversity index: Delta) positively influenced the invertebrate species richness and diversity index (H‧). Although the macrophyte species richness and H‧ also positively influenced the invertebrate species richness, the best fit model for invertebrate species richness did not include them, suggesting that the macrophyte species diversity indirectly influenced invertebrate species diversity. Possible explanations of the effects of macrophyte Delta on the invertebrate species diversity were the niche complementarity effect and the selection effect. This is the first study which demonstrates that macrophyte phylogenetic diversity has a strong effect on the species diversity of mobile epi-benthic invertebrates.

Trauma centrality and PTSD in veterans returning from Iraq and Afghanistan.

PubMed

Brown, Adam D; Antonius, Daniel; Kramer, Michael; Root, James C; Hirst, William

2010-08-01

Research has demonstrated that the extent to which an individual integrates a traumatic event into their identity ("trauma centrality") positively correlates with posttraumatic stress disorder (PTSD) symptom severity. No research to date has examined trauma centrality in individuals exposed to combat stress. This study investigated trauma centrality using the abridged Centrality of Event Scale (Berntsen & Rubin, 2006) among Operation Enduring Freedom/Operation Iraqi Freedom combat veterans (n = 46). Multiple regression analyses demonstrated that trauma centrality predicted PTSD symptoms. Trauma centrality and PTSD symptoms remained significantly correlated when controlling for depression in subgroups of veterans with or without probable PTSD. This study replicates and extends findings that placing trauma at the center of one's identity is associated with PTSD symptomatology.

New variable selection methods for zero-inflated count data with applications to the substance abuse field

PubMed Central

Buu, Anne; Johnson, Norman J.; Li, Runze; Tan, Xianming

2011-01-01

Zero-inflated count data are very common in health surveys. This study develops new variable selection methods for the zero-inflated Poisson regression model. Our simulations demonstrate the negative consequences which arise from the ignorance of zero-inflation. Among the competing methods, the one-step SCAD method is recommended because it has the highest specificity, sensitivity, exact fit, and lowest estimation error. The design of the simulations is based on the special features of two large national databases commonly used in the alcoholism and substance abuse field so that our findings can be easily generalized to the real settings. Applications of the methodology are demonstrated by empirical analyses on the data from a well-known alcohol study. PMID:21563207

Biological integrity in mid-atlantic coastal plains headwater streams.

PubMed

Megan, Mehaffey H; Nash, Maliha S; Neale, Anne C; Pitchford, Ann M

2007-01-01

The objective of this study was to assess the applicability of using landscape variables in conjunction with water quality and benthic data to efficiently estimate stream condition of select headwater streams in the Mid-Atlantic Coastal Plains. Eighty-two streams with riffle sites were selected from eight-two independent watersheds across the region for sampling and analyses. Clustering of the watersheds by landscape resulted in three distinct groups (forest, crop, and urban) which coincided with watersheds dominant land cover or use. We used non-parametric analyses to test differences in benthos and water chemistry between groups, and used regression analyses to evaluate responses of benthic communities to water chemistry within each of the landscape groups. We found that typical water chemistry measures associated with urban runoff such as specific conductance and dissolved chloride were significantly higher in the urban group. In the crop group, we found variables commonly associated with farming such as nutrients and pesticides significantly greater than in the other two groups. Regression analyses demonstrated that the numbers of tolerant and facultative macroinvertebrates increased significantly in forested watersheds with small shifts in pollutants, while in human use dominated watersheds the intolerant macroinvertebrates were more sensitive to shifts in chemicals present at lower concentrations. The results from this study suggest that landscape based clustering can be used to link upstream landscape characteristics, water chemistry and biotic integrity in order to assess stream condition and likely cause of degradation without the use of reference sites. Notice: Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy.

Big Five personality characteristics are associated with depression subtypes and symptom dimensions of depression in older adults.

PubMed

Koorevaar, A M L; Hegeman, J M; Lamers, F; Dhondt, A D F; van der Mast, R C; Stek, M L; Comijs, H C

2017-12-01

This study examined the associations of personality characteristics with both subtypes and symptom dimensions of depression in older adults. Three hundred and seventy-eight depressed older adults participated in the Netherlands Study of Depression in Older Persons. Personality characteristics were assessed by the NEO-Five Factor Inventory. Subtypes and symptom dimensions of depression were determined using the Composite International Diagnostic Interview and the Inventory of Depressive Symptomatology (IDS). Multinomial logistic regression analyses were performed to examine the associations between personality and atypical, melancholic, and unspecified subtypes of major depression. Linear regression analyses examined the associations between personality and the IDS mood, somatic, and motivation symptom dimensions. The analyses were adjusted for confounders and additionally adjusted for depression severity. Neuroticism, Extraversion, Conscientiousness, and Agreeableness were associated with specified (atypical or melancholic) major depression compared with unspecified major depression in the bivariate analyses but lost their significance after adjustments for functional limitations and severity of depression. Neuroticism was positively associated with the IDS mood and motivation symptom dimensions, also in the adjusted models. Further, Extraversion and Agreeableness were negatively associated with the IDS mood symptom dimension, and Extraversion and Conscientiousness were negatively associated with the IDS motivation symptom dimension. None was associated with the IDS somatic symptom dimension. This study demonstrated the association of personality characteristics with mood and motivational symptoms of late-life depression. The lacking ability of personality to differentiate between melancholic and atypical depression seems to be largely explained by severity of depressive symptoms. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Developmental Regression in Autism Spectrum Disorders

ERIC Educational Resources Information Center

Rogers, Sally J.

2004-01-01

The occurrence of developmental regression in autism is one of the more puzzling features of this disorder. Although several studies have documented the validity of parental reports of regression using home videos, accumulating data suggest that most children who demonstrate regression also demonstrated previous, subtle, developmental differences.…

Evolution of an adaptive behavior and its sensory receptors promotes eye regression in blind cavefish.

PubMed

Yoshizawa, Masato; Yamamoto, Yoshiyuki; O'Quin, Kelly E; Jeffery, William R

2012-12-27

How and why animals lose eyesight during adaptation to the dark and food-limited cave environment has puzzled biologists since the time of Darwin. More recently, several different adaptive hypotheses have been proposed to explain eye degeneration based on studies in the teleost Astyanax mexicanus, which consists of blind cave-dwelling (cavefish) and sighted surface-dwelling (surface fish) forms. One of these hypotheses is that eye regression is the result of indirect selection for constructive characters that are negatively linked to eye development through the pleiotropic effects of Sonic Hedgehog (SHH) signaling. However, subsequent genetic analyses suggested that other mechanisms also contribute to eye regression in Astyanax cavefish. Here, we introduce a new approach to this problem by investigating the phenotypic and genetic relationships between a suite of non-visual constructive traits and eye regression. Using quantitative genetic analysis of crosses between surface fish, the Pachón cavefish population and their hybrid progeny, we show that the adaptive vibration attraction behavior (VAB) and its sensory receptors, superficial neuromasts (SN) specifically found within the cavefish eye orbit (EO), are genetically correlated with reduced eye size. The quantitative trait loci (QTL) for these three traits form two clusters of congruent or overlapping QTL on Astyanax linkage groups (LG) 2 and 17, but not at the shh locus on LG 13. Ablation of EO SN in cavefish demonstrated a major role for these sensory receptors in VAB expression. Furthermore, experimental induction of eye regression in surface fish via shh overexpression showed that the absence of eyes was insufficient to promote the appearance of VAB or EO SN. We conclude that natural selection for the enhancement of VAB and EO SN indirectly promotes eye regression in the Pachón cavefish population through an antagonistic relationship involving genetic linkage or pleiotropy among the genetic factors underlying these traits. This study demonstrates a trade-off between the evolution of a non-visual sensory system and eye regression during the adaptive evolution of Astyanax to the cave environment.

Shrinkage regression-based methods for microarray missing value imputation.

PubMed

Wang, Hsiuying; Chiu, Chia-Chun; Wu, Yi-Ching; Wu, Wei-Sheng

2013-01-01

Missing values commonly occur in the microarray data, which usually contain more than 5% missing values with up to 90% of genes affected. Inaccurate missing value estimation results in reducing the power of downstream microarray data analyses. Many types of methods have been developed to estimate missing values. Among them, the regression-based methods are very popular and have been shown to perform better than the other types of methods in many testing microarray datasets. To further improve the performances of the regression-based methods, we propose shrinkage regression-based methods. Our methods take the advantage of the correlation structure in the microarray data and select similar genes for the target gene by Pearson correlation coefficients. Besides, our methods incorporate the least squares principle, utilize a shrinkage estimation approach to adjust the coefficients of the regression model, and then use the new coefficients to estimate missing values. Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the existing regression-based methods do. Imputation of missing values is a very important aspect of microarray data analyses because most of the downstream analyses require a complete dataset. Therefore, exploring accurate and efficient methods for estimating missing values has become an essential issue. Since our proposed shrinkage regression-based methods can provide accurate missing value estimation, they are competitive alternatives to the existing regression-based methods.

Covariate Imbalance and Adjustment for Logistic Regression Analysis of Clinical Trial Data

PubMed Central

Ciolino, Jody D.; Martin, Reneé H.; Zhao, Wenle; Jauch, Edward C.; Hill, Michael D.; Palesch, Yuko Y.

2014-01-01

In logistic regression analysis for binary clinical trial data, adjusted treatment effect estimates are often not equivalent to unadjusted estimates in the presence of influential covariates. This paper uses simulation to quantify the benefit of covariate adjustment in logistic regression. However, International Conference on Harmonization guidelines suggest that covariate adjustment be pre-specified. Unplanned adjusted analyses should be considered secondary. Results suggest that that if adjustment is not possible or unplanned in a logistic setting, balance in continuous covariates can alleviate some (but never all) of the shortcomings of unadjusted analyses. The case of log binomial regression is also explored. PMID:24138438

An Empirical Study of Eight Nonparametric Tests in Hierarchical Regression.

ERIC Educational Resources Information Center

Harwell, Michael; Serlin, Ronald C.

When normality does not hold, nonparametric tests represent an important data-analytic alternative to parametric tests. However, the use of nonparametric tests in educational research has been limited by the absence of easily performed tests for complex experimental designs and analyses, such as factorial designs and multiple regression analyses,…

How Many Subjects Does It Take to Do a Regression Analysis?

ERIC Educational Resources Information Center

Green, Samuel B.

1991-01-01

An evaluation of the rules-of-thumb used to determine the minimum number of subjects required to conduct multiple regression analyses suggests that researchers who use a rule of thumb rather than power analyses trade simplicity of use for accuracy and specificity of response. Insufficient power is likely to result. (SLD)

Hydrology and trout populations of cold-water rivers of Michigan and Wisconsin

USGS Publications Warehouse

Hendrickson, G.E.; Knutilla, R.L.

1974-01-01

Statistical multiple-regression analyses showed significant relationships between trout populations and hydrologic parameters. Parameters showing the higher levels of significance were temperature, hardness of water, percentage of gravel bottom, percentage of bottom vegetation, variability of streamflow, and discharge per unit drainage area. Trout populations increase with lower levels of annual maximum water temperatures, with increase in water hardness, and with increase in percentage of gravel and bottom vegetation. Trout populations also increase with decrease in variability of streamflow, and with increase in discharge per unit drainage area. Most hydrologic parameters were significant when evaluated collectively, but no parameter, by itself, showed a high degree of correlation with trout populations in regression analyses that included all the streams sampled. Regression analyses of stream segments that were restricted to certain limits of hardness, temperature, or percentage of gravel bottom showed improvements in correlation. Analyses of trout populations, in pounds per acre and pounds per mile and hydrologic parameters resulted in regression equations from which trout populations could be estimated with standard errors of 89 and 84 per cent, respectively.

Model Estimation Using Ridge Regression with the Variance Normalization Criterion. Interim Report No. 2. The Education and Inequality in Canada Project.

ERIC Educational Resources Information Center

Lee, Wan-Fung; Bulcock, Jeffrey Wilson

The purposes of this study are: (1) to demonstrate the superiority of simple ridge regression over ordinary least squares regression through theoretical argument and empirical example; (2) to modify ridge regression through use of the variance normalization criterion; and (3) to demonstrate the superiority of simple ridge regression based on the…

The predictive value of the antioxidative function of HDL for cardiovascular disease and graft failure in renal transplant recipients.

PubMed

Leberkühne, Lynn J; Ebtehaj, Sanam; Dimova, Lidiya G; Dikkers, Arne; Dullaart, Robin P F; Bakker, Stephan J L; Tietge, Uwe J F

2016-06-01

Protection of low-density lipoproteins (LDL) against oxidative modification is a key anti-atherosclerotic property of high-density lipoproteins (HDL). This study evaluated the predictive value of the HDL antioxidative function for cardiovascular mortality, all-cause mortality and chronic graft failure in renal transplant recipients (RTR). The capacity of HDL to inhibit native LDL oxidation was determined in vitro in a prospective cohort of renal transplant recipients (RTR, n = 495, median follow-up 7.0 years). The HDL antioxidative functionality was significantly higher in patients experiencing graft failure (57.4 ± 9.7%) than in those without (54.2 ± 11.3%; P = 0.039), while there were no differences for cardiovascular and all-cause mortality. Specifically glomerular filtration rate (P = 0.001) and C-reactive protein levels (P = 0.006) associated independently with antioxidative functionality in multivariate linear regression analyses. Cox regression analysis demonstrated a significant relationship between antioxidative functionality of HDL and graft failure in age-adjusted analyses, but significance was lost following adjustment for baseline kidney function and inflammatory load. No significant association was found between HDL antioxidative functionality and cardiovascular and all-cause mortality. This study demonstrates that the antioxidative function of HDL (i) does not predict cardiovascular or all-cause mortality in RTR, but (ii) conceivably contributes to the development of graft failure, however, not independent of baseline kidney function and inflammatory load. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Characteristics of GHG flux from water-air interface along a reclaimed water intake area of the Chaobai River in Shunyi, Beijing

NASA Astrophysics Data System (ADS)

He, Baonan; He, Jiangtao; Wang, Jian; Li, Jie; Wang, Fei

2018-01-01

To understand greenhouse gas (GHG) flux in reclaimed water intake area impact on urban climate, 'static chamber' method was used to investigate the spatio-diurnal variations and the influence factors of GHG fluxes at water-air interface from Jian River to Chaobai River. Results showed that the average fluxes of CO2 from the Jian River and the Chaobai River were 73.46 mg(m2·h)-1 and -64.75 mg(m2·h)-1, respectively. CO2 was emitted the most in the Jian River, but it was absorbed from the atmosphere in the Chaobai River. Unary linear regression analyses demonstrated that Chlorophyll a (Chl a) and pH variation controlled the carbon source and sink from the Jian River to the Chaobai River. The diurnal variation of CO2 fluxes was higher at night than in the daytime in the Jian River, and it was the inverse in the Chaobai River, which highly correlated with dissociative CO2 and HCO3- transformation to CO32-. The average fluxes of CH4 from the Jian River and Chaobai River were 0.973 mg(m2·h)-1 and 5.556 mg(m2·h)-1, respectively, which increased along the water flow direction. Unary and multiple linear regression analyses demonstrated that Chl a and total organic carbon (TOC) controlled the increase of CH4 along the flow direction. The diurnal variation of CH4 fluxes was slightly higher in the daytime than at night due to the effect of water temperature.

Non-Linear Association between Cerebral Amyloid Deposition and White Matter Microstructure in Cognitively Healthy Older Adults.

PubMed

Wolf, Dominik; Fischer, Florian U; Scheurich, Armin; Fellgiebel, Andreas

2015-01-01

Cerebral amyloid-β accumulation and changes in white matter (WM) microstructure are imaging characteristics in clinical Alzheimer's disease and have also been reported in cognitively healthy older adults. However, the relationship between amyloid deposition and WM microstructure is not well understood. Here, we investigated the impact of quantitative cerebral amyloid load on WM microstructure in a group of cognitively healthy older adults. AV45-positron emission tomography and diffusion tensor imaging (DTI) scans of forty-four participants (age-range: 60 to 89 years) from the Alzheimer's Disease Neuroimaging Initiative were analyzed. Fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (DR), and axial diffusivity (DA) were calculated to characterize WM microstructure. Regression analyses demonstrated non-linear (quadratic) relationships between amyloid deposition and FA, MD, as well as RD in widespread WM regions. At low amyloid burden, higher deposition was associated with increased FA as well as decreased MD and DR. At higher amyloid burden, higher deposition was associated with decreased FA as well as increased MD and DR. Additional regression analyses demonstrated an interaction effect between amyloid load and global WM FA, MD, DR, and DA on cognition, suggesting that cognition is only affected when amyloid is increasing and WM integrity is decreasing. Thus, increases in FA and decreases in MD and RD with increasing amyloid load at low levels of amyloid burden may indicate compensatory processes that preserve cognitive functioning. Potential mechanisms underlying the observed non-linear association between amyloid deposition and DTI metrics of WM microstructure are discussed.

Predictors of college-student food security and fruit and vegetable intake differ by housing type.

PubMed

Mirabitur, Erica; Peterson, Karen E; Rathz, Colleen; Matlen, Stacey; Kasper, Nicole

2016-10-01

We assessed whether college-student characteristics associate with food security and fruit and vegetable (FV) intake and whether these associations differ in students in housing with and without food provision. 514 randomly-sampled students from a large, Midwestern, public university in 2012 and 2013 METHODS: Ordered logistic regression tested how student characteristics associate with food security. Linear regression tested how student characteristics associate with FV intake. Analyses were stratified by housing type - that is, housing with food provision (dormitory, fraternity/sorority house, cooperative) vs. housing without food provision. Only among those living in housing without food provision, males (p = 0.04), students without car access (p = 0.005), and those with marginal (p = 0.001) or low (p = 0.001) food security demonstrated lower FV intake. Housing with food provision may buffer the effects of student characteristics on food.

Effects of mining-associated lead and zinc soil contamination on native floristic quality.

PubMed

Struckhoff, Matthew A; Stroh, Esther D; Grabner, Keith W

2013-04-15

We assessed the quality of plant communities across a range of lead (Pb) and zinc (Zn) soil concentrations at a variety of sites associated with Pb mining in southeast Missouri, USA. In a novel application, two standard floristic quality measures, Mean Coefficient of Conservatism (Mean C) and Floristic Quality Index (FQI), were examined in relation to concentrations of Pb and Zn, soil nutrients, and other soil characteristics. Nonmetric Multidimensional Scaling and Regression Tree Analyses identified soil Pb and Zn concentrations as primary explanatory variables for plant community composition and indicated negative relationships between soil metals concentrations and both Mean C and FQI. Univariate regression also demonstrated significant negative relationships between metals concentrations and floristic quality. The negative effects of metals in native soils with otherwise relatively undisturbed conditions indicate that elevated soil metals concentrations adversely affect native floristic quality where no other human disturbance is evident. Published by Elsevier Ltd.

Effects of mining-associated lead and zinc soil contamination on native floristic quality

USGS Publications Warehouse

Struckhoff, Matthew A.; Stroh, Esther D.; Grabner, Keith W.

2013-01-01

We assessed the quality of plant communities across a range of lead (Pb) and zinc (Zn) soil concentrations at a variety of sites associated with Pb mining in southeast Missouri, USA. In a novel application, two standard floristic quality measures, Mean Coefficient of Conservatism (Mean C) and Floristic Quality Index (FQI), were examined in relation to concentrations of Pb and Zn, soil nutrients, and other soil characteristics. Nonmetric Multidimensional Scaling and Regression Tree Analyses identified soil Pb and Zn concentrations as primary explanatory variables for plant community composition and indicated negative relationships between soil metals concentrations and both Mean C and FQI. Univariate regression also demonstrated significant negative relationships between metals concentrations and floristic quality. The negative effects of metals in native soils with otherwise relatively undisturbed conditions indicate that elevated soil metals concentrations adversely affect native floristic quality where no other human disturbance is evident.

BAYESIAN LARGE-SCALE MULTIPLE REGRESSION WITH SUMMARY STATISTICS FROM GENOME-WIDE ASSOCIATION STUDIES1

PubMed Central

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

Bayesian Unimodal Density Regression for Causal Inference

ERIC Educational Resources Information Center

Karabatsos, George; Walker, Stephen G.

2011-01-01

Karabatsos and Walker (2011) introduced a new Bayesian nonparametric (BNP) regression model. Through analyses of real and simulated data, they showed that the BNP regression model outperforms other parametric and nonparametric regression models of common use, in terms of predictive accuracy of the outcome (dependent) variable. The other,…

Bayesian models for comparative analysis integrating phylogenetic uncertainty.

PubMed

de Villemereuil, Pierre; Wells, Jessie A; Edwards, Robert D; Blomberg, Simon P

2012-06-28

Uncertainty in comparative analyses can come from at least two sources: a) phylogenetic uncertainty in the tree topology or branch lengths, and b) uncertainty due to intraspecific variation in trait values, either due to measurement error or natural individual variation. Most phylogenetic comparative methods do not account for such uncertainties. Not accounting for these sources of uncertainty leads to false perceptions of precision (confidence intervals will be too narrow) and inflated significance in hypothesis testing (e.g. p-values will be too small). Although there is some application-specific software for fitting Bayesian models accounting for phylogenetic error, more general and flexible software is desirable. We developed models to directly incorporate phylogenetic uncertainty into a range of analyses that biologists commonly perform, using a Bayesian framework and Markov Chain Monte Carlo analyses. We demonstrate applications in linear regression, quantification of phylogenetic signal, and measurement error models. Phylogenetic uncertainty was incorporated by applying a prior distribution for the phylogeny, where this distribution consisted of the posterior tree sets from Bayesian phylogenetic tree estimation programs. The models were analysed using simulated data sets, and applied to a real data set on plant traits, from rainforest plant species in Northern Australia. Analyses were performed using the free and open source software OpenBUGS and JAGS. Incorporating phylogenetic uncertainty through an empirical prior distribution of trees leads to more precise estimation of regression model parameters than using a single consensus tree and enables a more realistic estimation of confidence intervals. In addition, models incorporating measurement errors and/or individual variation, in one or both variables, are easily formulated in the Bayesian framework. We show that BUGS is a useful, flexible general purpose tool for phylogenetic comparative analyses, particularly for modelling in the face of phylogenetic uncertainty and accounting for measurement error or individual variation in explanatory variables. Code for all models is provided in the BUGS model description language.

Bayesian models for comparative analysis integrating phylogenetic uncertainty

PubMed Central

2012-01-01

Background Uncertainty in comparative analyses can come from at least two sources: a) phylogenetic uncertainty in the tree topology or branch lengths, and b) uncertainty due to intraspecific variation in trait values, either due to measurement error or natural individual variation. Most phylogenetic comparative methods do not account for such uncertainties. Not accounting for these sources of uncertainty leads to false perceptions of precision (confidence intervals will be too narrow) and inflated significance in hypothesis testing (e.g. p-values will be too small). Although there is some application-specific software for fitting Bayesian models accounting for phylogenetic error, more general and flexible software is desirable. Methods We developed models to directly incorporate phylogenetic uncertainty into a range of analyses that biologists commonly perform, using a Bayesian framework and Markov Chain Monte Carlo analyses. Results We demonstrate applications in linear regression, quantification of phylogenetic signal, and measurement error models. Phylogenetic uncertainty was incorporated by applying a prior distribution for the phylogeny, where this distribution consisted of the posterior tree sets from Bayesian phylogenetic tree estimation programs. The models were analysed using simulated data sets, and applied to a real data set on plant traits, from rainforest plant species in Northern Australia. Analyses were performed using the free and open source software OpenBUGS and JAGS. Conclusions Incorporating phylogenetic uncertainty through an empirical prior distribution of trees leads to more precise estimation of regression model parameters than using a single consensus tree and enables a more realistic estimation of confidence intervals. In addition, models incorporating measurement errors and/or individual variation, in one or both variables, are easily formulated in the Bayesian framework. We show that BUGS is a useful, flexible general purpose tool for phylogenetic comparative analyses, particularly for modelling in the face of phylogenetic uncertainty and accounting for measurement error or individual variation in explanatory variables. Code for all models is provided in the BUGS model description language. PMID:22741602

Logistic regression applied to natural hazards: rare event logistic regression with replications

NASA Astrophysics Data System (ADS)

Guns, M.; Vanacker, V.

2012-06-01

Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

Pragmatic estimation of a spatio-temporal air quality model with irregular monitoring data

NASA Astrophysics Data System (ADS)

Sampson, Paul D.; Szpiro, Adam A.; Sheppard, Lianne; Lindström, Johan; Kaufman, Joel D.

2011-11-01

Statistical analyses of health effects of air pollution have increasingly used GIS-based covariates for prediction of ambient air quality in "land use" regression models. More recently these spatial regression models have accounted for spatial correlation structure in combining monitoring data with land use covariates. We present a flexible spatio-temporal modeling framework and pragmatic, multi-step estimation procedure that accommodates essentially arbitrary patterns of missing data with respect to an ideally complete space by time matrix of observations on a network of monitoring sites. The methodology incorporates a model for smooth temporal trends with coefficients varying in space according to Partial Least Squares regressions on a large set of geographic covariates and nonstationary modeling of spatio-temporal residuals from these regressions. This work was developed to provide spatial point predictions of PM 2.5 concentrations for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) using irregular monitoring data derived from the AQS regulatory monitoring network and supplemental short-time scale monitoring campaigns conducted to better predict intra-urban variation in air quality. We demonstrate the interpretation and accuracy of this methodology in modeling data from 2000 through 2006 in six U.S. metropolitan areas and establish a basis for likelihood-based estimation.

Pumps and warmers during amnioinfusion: is either necessary?

PubMed

Glantz, J C; Letteney, D L

1996-01-01

To determine if there is evidence from published reports that the use of infusion pumps or solution warmers during amnioinfusion is beneficial. We identified all English-language amnioinfusion reports published since 1983 through Medline and references. Fourteen prospective papers with at least 40 subjects were identified. For the amnioinfusion and control groups in each study, odds ratios (OR) were calculated for cesarean delivery, fetal distress, meconium below the cords, low 5-minute Apgar score, and endometritis. Cumulative ORs were calculated using the Mantel-Haenszel inverse variance method. This process was repeated after separation into pump-gravity and warmed-unwarmed groups. Multiple regression analyses were performed. Amnioinfusion improved the ability of the fetus to tolerate labor (fetal distress OR 0.40), decreased the incidence of meconium below the cords (OR 0.16), and decreased the rate of cesarean delivery (OR 0.56). There were no demonstrable benefits associated with the use of warmers or pumps. In multiple regression analysis, infusion pumps were associated with a significantly increased risk of fetal distress (P = .01). The use of amnioinfusion is associated with a decreased risk of fetal distress, meconium below the cords, and cesarean delivery. To date, there is no demonstrable benefit using infusion pumps or solution warmers during amnioinfusion.

Using existing case-mix methods to fund trauma cases.

PubMed

Monakova, Julia; Blais, Irene; Botz, Charles; Chechulin, Yuriy; Picciano, Gino; Basinski, Antoni

2010-01-01

Policymakers frequently face the need to increase funding in isolated and frequently heterogeneous (clinically and in terms of resource consumption) patient subpopulations. This article presents a methodologic solution for testing the appropriateness of using existing grouping and weighting methodologies for funding subsets of patients in the scenario where a case-mix approach is preferable to a flat-rate based payment system. Using as an example the subpopulation of trauma cases of Ontario lead trauma hospitals, the statistical techniques of linear and nonlinear regression models, regression trees, and spline models were applied to examine the fit of the existing case-mix groups and reference weights for the trauma cases. The analyses demonstrated that for funding Ontario trauma cases, the existing case-mix systems can form the basis for rational and equitable hospital funding, decreasing the need to develop a different grouper for this subset of patients. This study confirmed that Injury Severity Score is a poor predictor of costs for trauma patients. Although our analysis used the Canadian case-mix classification system and cost weights, the demonstrated concept of using existing case-mix systems to develop funding rates for specific subsets of patient populations may be applicable internationally.

A novel method linking neural connectivity to behavioral fluctuations: Behavior-regressed connectivity.

PubMed

Passaro, Antony D; Vettel, Jean M; McDaniel, Jonathan; Lawhern, Vernon; Franaszczuk, Piotr J; Gordon, Stephen M

2017-03-01

During an experimental session, behavioral performance fluctuates, yet most neuroimaging analyses of functional connectivity derive a single connectivity pattern. These conventional connectivity approaches assume that since the underlying behavior of the task remains constant, the connectivity pattern is also constant. We introduce a novel method, behavior-regressed connectivity (BRC), to directly examine behavioral fluctuations within an experimental session and capture their relationship to changes in functional connectivity. This method employs the weighted phase lag index (WPLI) applied to a window of trials with a weighting function. Using two datasets, the BRC results are compared to conventional connectivity results during two time windows: the one second before stimulus onset to identify predictive relationships, and the one second after onset to capture task-dependent relationships. In both tasks, we replicate the expected results for the conventional connectivity analysis, and extend our understanding of the brain-behavior relationship using the BRC analysis, demonstrating subject-specific BRC maps that correspond to both positive and negative relationships with behavior. Comparison with Existing Method(s): Conventional connectivity analyses assume a consistent relationship between behaviors and functional connectivity, but the BRC method examines performance variability within an experimental session to understand dynamic connectivity and transient behavior. The BRC approach examines connectivity as it covaries with behavior to complement the knowledge of underlying neural activity derived from conventional connectivity analyses. Within this framework, BRC may be implemented for the purpose of understanding performance variability both within and between participants. Published by Elsevier B.V.

The relationship between mental disorders, quality of life, and pregnancy: findings from a nationally representative sample.

PubMed

Mota, Natalie; Cox, Brian J; Enns, Murray W; Calhoun, Laura; Sareen, Jitender

2008-08-01

The present study examined health-related quality of life (HRQOL) and the prevalence of mental disorders in pregnant and past-year pregnant women compared to non-pregnant women. Data came from the National Epidemiologic Survey on Alcohol and Related Conditions. Three groups of women (ages 18-44) were compared: currently pregnant (n=451), past-year pregnant (n=1061), and not pregnant (n=10,544). Past-year mood, anxiety and substance use disorders were assessed by the Alcohol Use Disorder and Associated Disabilities Interview Schedule-DSM-IV version. HRQOL was measured by the Medical Outcomes Study Short Form (SF-12). All analyses included sociodemographics as covariates. Multiple logistic regression analyses showed that pregnant women were less likely than non-pregnant women to have depression and alcohol abuse or dependence; and less likely than past-year pregnant women to have depression and mania. Past-year pregnant women were less likely than non-pregnant women to have social phobia and alcohol dependence or abuse. Multiple linear regression analyses demonstrated that pregnant and non-pregnant women had higher mental component scores than past-year pregnant women. Physical component scores were lower in pregnant women than in non-pregnant and past-year pregnant groups. This was a cross-sectional survey and the causality of relationships cannot be inferred. Results suggest that pregnant women have a lower likelihood of mental disorder than both non-pregnant and past-year pregnant women.

Reprint of: Relationship between cataract severity and socioeconomic status.

PubMed

Wesolosky, Jason D; Rudnisky, Christopher J

2015-06-01

To determine the relationship between cataract severity and socioeconomic status (SES). Retrospective, observational case series. A total of 1350 eyes underwent phacoemulsification cataract extraction by a single surgeon using an Alcon Infiniti system. Cataract severity was measured using phaco time in seconds. SES was measured using area-level aggregate census data: median income, education, proportion of common-law couples, and employment rate. Preoperative best corrected visual acuity was obtained and converted to logarithm of the minimum angle of resolution values. For patients undergoing bilateral surgery, the generalized estimating equation was used to account for the correlation between eyes. Univariate analyses were performed using simple regression, and multivariate analyses were performed to account for variables with significant relationships (p < 0.05) on univariate testing. Sensitivity analyses were performed to assess the effect of including patient age in the controlled analyses. Multivariate analyses demonstrated that cataracts were more severe when the median income was lower (p = 0.001) and the proportion of common-law couples living in a patient's community (p = 0.012) and the unemployment rate (p = 0.002) were higher. These associations persisted even when controlling for patient age. Patients of lower SES have more severe cataracts. Copyright © 2015. Published by Elsevier Inc.

The relationship between white matter brain metabolites and cognition in normal aging: the GENIE study.

PubMed

Charlton, R A; McIntyre, D J O; Howe, F A; Morris, R G; Markus, H S

2007-08-20

Magnetic resonance spectroscopy (MRS) has demonstrated age-related changes in brain metabolites that may underlie micro-structural brain changes, but few studies have examined their relationship with cognitive decline. We performed a cross-sectional study of brain metabolism and cognitive function in 82 healthy adults (aged 50-90) participating in the GENIE (St GEorge's Neuropsychology and Imaging in the Elderly) study. Absolute metabolite concentrations were measured by proton chemical shift imaging within voxels placed in the centrum semiovale white matter. Cognitive abilities assessed were executive function, working memory, information processing speed, long-term memory and fluid intelligence. Correlations showed that all cognitive domains declined with age. Total creatine (tCr) concentration increased with age (r=0.495, p<0.001). Regression analyses were performed for each cognitive variable, including estimated intelligence and the metabolites, with age then added as a final step. A significant relationship was observed between tCr and executive function, long-term memory, and fluid intelligence, although these relationships did not remain significant after age was added as a final step in the regression. The regression analysis also demonstrated a significant relationship between N-acetylaspartate (NAA) and executive function. As there was no age-related decline in NAA, this argues against axonal loss with age; however the relationship between NAA and executive function independent of age and estimated intelligence is consistent with white matter axonal integrity having an important role in executive function in normal individuals.

Validation of a prediction model that allows direct comparison of the Oxford Knee Score and American Knee Society clinical rating system.

PubMed

Maempel, J F; Clement, N D; Brenkel, I J; Walmsley, P J

2015-04-01

This study demonstrates a significant correlation between the American Knee Society (AKS) Clinical Rating System and the Oxford Knee Score (OKS) and provides a validated prediction tool to estimate score conversion. A total of 1022 patients were prospectively clinically assessed five years after TKR and completed AKS assessments and an OKS questionnaire. Multivariate regression analysis demonstrated significant correlations between OKS and the AKS knee and function scores but a stronger correlation (r = 0.68, p < 0.001) when using the sum of the AKS knee and function scores. Addition of body mass index and age (other statistically significant predictors of OKS) to the algorithm did not significantly increase the predictive value. The simple regression model was used to predict the OKS in a group of 236 patients who were clinically assessed nine to ten years after TKR using the AKS system. The predicted OKS was compared with actual OKS in the second group. Intra-class correlation demonstrated excellent reliability (r = 0.81, 95% confidence intervals 0.75 to 0.85) for the combined knee and function score when used to predict OKS. Our findings will facilitate comparison of outcome data from studies and registries using either the OKS or the AKS scores and may also be of value for those undertaking meta-analyses and systematic reviews. ©2015 The British Editorial Society of Bone & Joint Surgery.

Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic.

PubMed

Bowden, Jack; Del Greco M, Fabiola; Minelli, Cosetta; Davey Smith, George; Sheehan, Nuala A; Thompson, John R

2016-12-01

: MR-Egger regression has recently been proposed as a method for Mendelian randomization (MR) analyses incorporating summary data estimates of causal effect from multiple individual variants, which is robust to invalid instruments. It can be used to test for directional pleiotropy and provides an estimate of the causal effect adjusted for its presence. MR-Egger regression provides a useful additional sensitivity analysis to the standard inverse variance weighted (IVW) approach that assumes all variants are valid instruments. Both methods use weights that consider the single nucleotide polymorphism (SNP)-exposure associations to be known, rather than estimated. We call this the `NO Measurement Error' (NOME) assumption. Causal effect estimates from the IVW approach exhibit weak instrument bias whenever the genetic variants utilized violate the NOME assumption, which can be reliably measured using the F-statistic. The effect of NOME violation on MR-Egger regression has yet to be studied. An adaptation of the I2 statistic from the field of meta-analysis is proposed to quantify the strength of NOME violation for MR-Egger. It lies between 0 and 1, and indicates the expected relative bias (or dilution) of the MR-Egger causal estimate in the two-sample MR context. We call it IGX2 . The method of simulation extrapolation is also explored to counteract the dilution. Their joint utility is evaluated using simulated data and applied to a real MR example. In simulated two-sample MR analyses we show that, when a causal effect exists, the MR-Egger estimate of causal effect is biased towards the null when NOME is violated, and the stronger the violation (as indicated by lower values of IGX2 ), the stronger the dilution. When additionally all genetic variants are valid instruments, the type I error rate of the MR-Egger test for pleiotropy is inflated and the causal effect underestimated. Simulation extrapolation is shown to substantially mitigate these adverse effects. We demonstrate our proposed approach for a two-sample summary data MR analysis to estimate the causal effect of low-density lipoprotein on heart disease risk. A high value of IGX2 close to 1 indicates that dilution does not materially affect the standard MR-Egger analyses for these data. : Care must be taken to assess the NOME assumption via the IGX2 statistic before implementing standard MR-Egger regression in the two-sample summary data context. If IGX2 is sufficiently low (less than 90%), inferences from the method should be interpreted with caution and adjustment methods considered. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.

Club Drug Use in Hispanic College Students

PubMed Central

Resor, Michelle R.; Cooper, Theodore V.

2010-01-01

Club drug use and correlates were examined among 251 Hispanic college students on the Texas - México border. Participants completed questionnaires on substance use, club drug attitudes and beliefs, sexual risk-taking behaviors, depressive symptoms, and acculturation. One-quarter of participants reported club drug use. Regression analyses demonstrated that frequency and history of lifetime use were consistently associated with more permissive drug attitudes and other substance use but not sexual risk-taking, depression symptoms, or acculturation. Acculturation was negatively associated with frequency of club drug use, yet positively associated with use of other illicit substances. Avenues for future studies are suggested. PMID:20653638

Application of remote sensing for fishery resources assessment and monitoring. [Gulf of Mexico

NASA Technical Reports Server (NTRS)

Savastano, K. J. (Principal Investigator)

1975-01-01

The author has identified the following significant results. The distribution and abundance of white marlin correlated with the chlorophyll, water temperature, and Secchi depth sea truth measurements. Results of correlation analyses for dolphin were inconclusive. Predicition models for white marlin were developed using stepwise multiple regression and discriminant function analysis techniques which demonstrated a potential for increasing the probability of game fishing success. The S190A and B imagery was density sliced/color enhanced with white marlin location superimposed on the image, but no density/white marlin relationship could be established.

Residualization is not the answer: Rethinking how to address multicollinearity.

PubMed

York, Richard

2012-11-01

Here I show that a commonly used procedure to address problems stemming from collinearity and multicollinearity among independent variables in regression analysis, "residualization", leads to biased coefficient and standard error estimates and does not address the fundamental problem of collinearity, which is a lack of information. I demonstrate this using visual representations of collinearity, hypothetical experimental designs, and analyses of both artificial and real world data. I conclude by noting the importance of examining methodological practices to ensure that their validity can be established based on rational criteria. Copyright © 2012 Elsevier Inc. All rights reserved.

Mining Health App Data to Find More and Less Successful Weight Loss Subgroups

PubMed Central

2016-01-01

Background More than half of all smartphone app downloads involve weight, diet, and exercise. If successful, these lifestyle apps may have far-reaching effects for disease prevention and health cost-savings, but few researchers have analyzed data from these apps. Objective The purposes of this study were to analyze data from a commercial health app (Lose It!) in order to identify successful weight loss subgroups via exploratory analyses and to verify the stability of the results. Methods Cross-sectional, de-identified data from Lose It! were analyzed. This dataset (n=12,427,196) was randomly split into 24 subsamples, and this study used 3 subsamples (combined n=972,687). Classification and regression tree methods were used to explore groupings of weight loss with one subsample, with descriptive analyses to examine other group characteristics. Data mining validation methods were conducted with 2 additional subsamples. Results In subsample 1, 14.96% of users lost 5% or more of their starting body weight. Classification and regression tree analysis identified 3 distinct subgroups: “the occasional users” had the lowest proportion (4.87%) of individuals who successfully lost weight; “the basic users” had 37.61% weight loss success; and “the power users” achieved the highest percentage of weight loss success at 72.70%. Behavioral factors delineated the subgroups, though app-related behavioral characteristics further distinguished them. Results were replicated in further analyses with separate subsamples. Conclusions This study demonstrates that distinct subgroups can be identified in “messy” commercial app data and the identified subgroups can be replicated in independent samples. Behavioral factors and use of custom app features characterized the subgroups. Targeting and tailoring information to particular subgroups could enhance weight loss success. Future studies should replicate data mining analyses to increase methodology rigor. PMID:27301853

Factors associated with the practice of nursing staff sharing information about patients' nutritional status with their colleagues in hospitals.

PubMed

Kawasaki, Y; Tamaura, Y; Akamatsu, R; Sakai, M; Fujiwara, K

2018-01-01

Nursing staff have an important role in patients' nutritional care. The aim of this study was to demonstrate how the practice of sharing a patient's nutritional status with colleagues was affected by the nursing staff's attitude, knowledge and their priority to provide nutritional care. The participants were 492 nursing staff. We obtained participants' demographic data, the practice of sharing patients' nutritional information and information about participants' knowledge, attitude and priority of providing nutritional care by the questionnaire. We performed partial correlation analyses and linear regression analyses to describe the relationship between the total scores of the practice of sharing patients' nutritional information based on their knowledge, attitude and priority to provide nutritional care. Among the 492 participants, 396 nursing staff (80.5%) completed the questionnaire and were included in analyses. Mean±s.d. of total score of the 396 participants was 8.4±3.1. Nursing staff shared information when they had a high nutritional knowledge (r=0.36, P<0.01) and attitude (r=0.13, P<0.05); however, their correlation coefficients were low. In the linear regression analyses, job categories (β=-0.28, P<0.01), knowledge (β=0.33, P<0.01) and attitude (β=0.10, P<0.05) were independently associated with the practice of sharing information. Nursing staff's priority to provide nutritional care practice was not significantly associated with the practice of sharing information. Knowledge and attitude were independently associated with the practice of sharing patients' nutrition information with colleagues, regardless of their priority to provide nutritional care. An effective approach should be taken to improve the practice of providing nutritional care practice.

Gender Gaps in Mathematics, Science and Reading Achievements in Muslim Countries: A Quantile Regression Approach

ERIC Educational Resources Information Center

Shafiq, M. Najeeb

2013-01-01

Using quantile regression analyses, this study examines gender gaps in mathematics, science, and reading in Azerbaijan, Indonesia, Jordan, the Kyrgyz Republic, Qatar, Tunisia, and Turkey among 15-year-old students. The analyses show that girls in Azerbaijan achieve as well as boys in mathematics and science and overachieve in reading. In Jordan,…

Analysis of Palm Oil Production, Export, and Government Consumption to Gross Domestic Product of Five Districts in West Kalimantan by Panel Regression

NASA Astrophysics Data System (ADS)

Sulistianingsih, E.; Kiftiah, M.; Rosadi, D.; Wahyuni, H.

2017-04-01

Gross Domestic Product (GDP) is an indicator of economic growth in a region. GDP is a panel data, which consists of cross-section and time series data. Meanwhile, panel regression is a tool which can be utilised to analyse panel data. There are three models in panel regression, namely Common Effect Model (CEM), Fixed Effect Model (FEM) and Random Effect Model (REM). The models will be chosen based on results of Chow Test, Hausman Test and Lagrange Multiplier Test. This research analyses palm oil about production, export, and government consumption to five district GDP are in West Kalimantan, namely Sanggau, Sintang, Sambas, Ketapang and Bengkayang by panel regression. Based on the results of analyses, it concluded that REM, which adjusted-determination-coefficient is 0,823, is the best model in this case. Also, according to the result, only Export and Government Consumption that influence GDP of the districts.

Epidemiologic programs for computers and calculators. A microcomputer program for multiple logistic regression by unconditional and conditional maximum likelihood methods.

PubMed

Campos-Filho, N; Franco, E L

1989-02-01

A frequent procedure in matched case-control studies is to report results from the multivariate unmatched analyses if they do not differ substantially from the ones obtained after conditioning on the matching variables. Although conceptually simple, this rule requires that an extensive series of logistic regression models be evaluated by both the conditional and unconditional maximum likelihood methods. Most computer programs for logistic regression employ only one maximum likelihood method, which requires that the analyses be performed in separate steps. This paper describes a Pascal microcomputer (IBM PC) program that performs multiple logistic regression by both maximum likelihood estimation methods, which obviates the need for switching between programs to obtain relative risk estimates from both matched and unmatched analyses. The program calculates most standard statistics and allows factoring of categorical or continuous variables by two distinct methods of contrast. A built-in, descriptive statistics option allows the user to inspect the distribution of cases and controls across categories of any given variable.

[Sanitation and racial inequality conditions in urban Brazil: an analysis focused on the indigenous population based on the 2010 Population Census].

PubMed

Raupp, Ludimila; Fávaro, Thatiana Regina; Cunha, Geraldo Marcelo; Santos, Ricardo Ventura

2017-01-01

The aims of this study were to analyze and describe the presence and infrastructure of basic sanitation in the urban areas of Brazil, contrasting indigenous with non-indigenous households. Methods: A cross-sectional study based on microdata from the 2010 Census was conducted. The analyses were based on descriptive statistics (prevalence) and the construction of multiple logistic regression models (adjusted by socioeconomic and demographic covariates). The odds ratios were estimated for the association between the explanatory variables (covariates) and the outcome variables (water supply, sewage, garbage collection, and adequate sanitation). The statistical significance level established was 5%. Among the analyzed services, sewage proved to be the most precarious. Regarding race or color, indigenous households presented the lowest rate of sanitary infrastructure in Urban Brazil. The adjusted regression showed that, in general, indigenous households were at a disadvantage when compared to other categories of race or color, especially in terms of the presence of garbage collection services. These inequalities were much more pronounced in the South and Southeastern regions. The analyses of this study not only confirm the profile of poor conditions and infrastructure of the basic sanitation of indigenous households in urban areas, but also demonstrate the persistence of inequalities associated with race or color in the country.

System Synthesis in Preliminary Aircraft Design using Statistical Methods

NASA Technical Reports Server (NTRS)

DeLaurentis, Daniel; Mavris, Dimitri N.; Schrage, Daniel P.

1996-01-01

This paper documents an approach to conceptual and preliminary aircraft design in which system synthesis is achieved using statistical methods, specifically design of experiments (DOE) and response surface methodology (RSM). These methods are employed in order to more efficiently search the design space for optimum configurations. In particular, a methodology incorporating three uses of these techniques is presented. First, response surface equations are formed which represent aerodynamic analyses, in the form of regression polynomials, which are more sophisticated than generally available in early design stages. Next, a regression equation for an overall evaluation criterion is constructed for the purpose of constrained optimization at the system level. This optimization, though achieved in a innovative way, is still traditional in that it is a point design solution. The methodology put forward here remedies this by introducing uncertainty into the problem, resulting a solutions which are probabilistic in nature. DOE/RSM is used for the third time in this setting. The process is demonstrated through a detailed aero-propulsion optimization of a high speed civil transport. Fundamental goals of the methodology, then, are to introduce higher fidelity disciplinary analyses to the conceptual aircraft synthesis and provide a roadmap for transitioning from point solutions to probabalistic designs (and eventually robust ones).

Socioeconomic determinants of childhood overweight and obesity in China: the long arm of institutional power.

PubMed

Fu, Qiang; George, Linda K

2015-07-01

Previous studies have widely reported that the association between socioeconomic status (SES) and childhood overweight and obesity in China is significant and positive, which lends little support to the fundamental-cause perspective. Using multiple waves (1997, 2000, 2004 and 2006) of the China Health and Nutrition Survey (CHNS) (N = 2,556, 2,063, 1,431 and 1,242, respectively) and continuous BMI cut-points obtained from a polynomial method, (mixed-effect) logistic regression analyses show that parental state-sector employment, an important, yet overlooked, indicator of political power during the market transformation has changed from a risk factor for childhood overweight/obesity in 1997 to a protective factor for childhood overweight/obesity in 2006. Results from quantile regression analyses generate the same conclusions and demonstrate that the protective effect of parental state sector employment at high percentiles of BMI is robust under different estimation strategies. By bridging the fundamental causes perspective and theories of market transformation, this research not only documents the effect of political power on childhood overweight/obesity but also calls for the use of multifaceted, culturally-relevant stratification measures in testing the fundamental cause perspective across time and space. © 2015 Foundation for the Sociology of Health & Illness.

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…

Random regression analyses using B-splines to model growth of Australian Angus cattle

PubMed Central

Meyer, Karin

2005-01-01

Regression on the basis function of B-splines has been advocated as an alternative to orthogonal polynomials in random regression analyses. Basic theory of splines in mixed model analyses is reviewed, and estimates from analyses of weights of Australian Angus cattle from birth to 820 days of age are presented. Data comprised 84 533 records on 20 731 animals in 43 herds, with a high proportion of animals with 4 or more weights recorded. Changes in weights with age were modelled through B-splines of age at recording. A total of thirteen analyses, considering different combinations of linear, quadratic and cubic B-splines and up to six knots, were carried out. Results showed good agreement for all ages with many records, but fluctuated where data were sparse. On the whole, analyses using B-splines appeared more robust against "end-of-range" problems and yielded more consistent and accurate estimates of the first eigenfunctions than previous, polynomial analyses. A model fitting quadratic B-splines, with knots at 0, 200, 400, 600 and 821 days and a total of 91 covariance components, appeared to be a good compromise between detailedness of the model, number of parameters to be estimated, plausibility of results, and fit, measured as residual mean square error. PMID:16093011

Refining cost-effectiveness analyses using the net benefit approach and econometric methods: an example from a trial of anti-depressant treatment.

PubMed

Sabes-Figuera, Ramon; McCrone, Paul; Kendricks, Antony

2013-04-01

Economic evaluation analyses can be enhanced by employing regression methods, allowing for the identification of important sub-groups and to adjust for imperfect randomisation in clinical trials or to analyse non-randomised data. To explore the benefits of combining regression techniques and the standard Bayesian approach to refine cost-effectiveness analyses using data from randomised clinical trials. Data from a randomised trial of anti-depressant treatment were analysed and a regression model was used to explore the factors that have an impact on the net benefit (NB) statistic with the aim of using these findings to adjust the cost-effectiveness acceptability curves. Exploratory sub-samples' analyses were carried out to explore possible differences in cost-effectiveness. Results The analysis found that having suffered a previous similar depression is strongly correlated with a lower NB, independent of the outcome measure or follow-up point. In patients with previous similar depression, adding an selective serotonin reuptake inhibitors (SSRI) to supportive care for mild-to-moderate depression is probably cost-effective at the level used by the English National Institute for Health and Clinical Excellence to make recommendations. This analysis highlights the need for incorporation of econometric methods into cost-effectiveness analyses using the NB approach.

A comparison of Cox and logistic regression for use in genome-wide association studies of cohort and case-cohort design.

PubMed

Staley, James R; Jones, Edmund; Kaptoge, Stephen; Butterworth, Adam S; Sweeting, Michael J; Wood, Angela M; Howson, Joanna M M

2017-06-01

Logistic regression is often used instead of Cox regression to analyse genome-wide association studies (GWAS) of single-nucleotide polymorphisms (SNPs) and disease outcomes with cohort and case-cohort designs, as it is less computationally expensive. Although Cox and logistic regression models have been compared previously in cohort studies, this work does not completely cover the GWAS setting nor extend to the case-cohort study design. Here, we evaluated Cox and logistic regression applied to cohort and case-cohort genetic association studies using simulated data and genetic data from the EPIC-CVD study. In the cohort setting, there was a modest improvement in power to detect SNP-disease associations using Cox regression compared with logistic regression, which increased as the disease incidence increased. In contrast, logistic regression had more power than (Prentice weighted) Cox regression in the case-cohort setting. Logistic regression yielded inflated effect estimates (assuming the hazard ratio is the underlying measure of association) for both study designs, especially for SNPs with greater effect on disease. Given logistic regression is substantially more computationally efficient than Cox regression in both settings, we propose a two-step approach to GWAS in cohort and case-cohort studies. First to analyse all SNPs with logistic regression to identify associated variants below a pre-defined P-value threshold, and second to fit Cox regression (appropriately weighted in case-cohort studies) to those identified SNPs to ensure accurate estimation of association with disease.

Regression and multivariate models for predicting particulate matter concentration level.

PubMed

Nazif, Amina; Mohammed, Nurul Izma; Malakahmad, Amirhossein; Abualqumboz, Motasem S

2018-01-01

The devastating health effects of particulate matter (PM 10 ) exposure by susceptible populace has made it necessary to evaluate PM 10 pollution. Meteorological parameters and seasonal variation increases PM 10 concentration levels, especially in areas that have multiple anthropogenic activities. Hence, stepwise regression (SR), multiple linear regression (MLR) and principal component regression (PCR) analyses were used to analyse daily average PM 10 concentration levels. The analyses were carried out using daily average PM 10 concentration, temperature, humidity, wind speed and wind direction data from 2006 to 2010. The data was from an industrial air quality monitoring station in Malaysia. The SR analysis established that meteorological parameters had less influence on PM 10 concentration levels having coefficient of determination (R 2 ) result from 23 to 29% based on seasoned and unseasoned analysis. While, the result of the prediction analysis showed that PCR models had a better R 2 result than MLR methods. The results for the analyses based on both seasoned and unseasoned data established that MLR models had R 2 result from 0.50 to 0.60. While, PCR models had R 2 result from 0.66 to 0.89. In addition, the validation analysis using 2016 data also recognised that the PCR model outperformed the MLR model, with the PCR model for the seasoned analysis having the best result. These analyses will aid in achieving sustainable air quality management strategies.

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…

A difference in systolic blood pressure between arms and between lower limbs is a novel risk marker for diabetic nephropathy in patients with type 2 diabetes.

PubMed

Okada, Hiroshi; Fukui, Michiaki; Tanaka, Muhei; Matsumoto, Shinobu; Mineoka, Yusuke; Nakanishi, Naoko; Asano, Mai; Yamazaki, Masahiro; Hasegawa, Goji; Nakamura, Naoto

2013-05-01

Recent studies have demonstrated that a difference in systolic blood pressure (SBP) between arms is associated with both vascular disease and mortality. The aim of this study was to investigate the relationship between a difference in SBP between arms and between lower limbs and the degree of albuminuria, which is an established marker for cardiovascular disease and diabetic nephropathy in patients with Type 2 diabetes. We measured blood pressure in the arms and lower limbs of 314 consecutive patients with Type 2 diabetes, and we calculated a difference in SBP between arms and between lower limbs. We then evaluated the relationship of the difference in SBP between arms and between lower limbs to the degree of urinary albumin excretion (UAE). The average difference in SBP between arms and between lower limbs was 3.52±3.94 and 9.66±14.1 mm Hg, respectively. Multiple regression analyses demonstrated that a difference in SBP between arms (β=0.172, P=0.0239) and between lower limbs (β=0.238, P=0.0033) independently correlated with the logarithm of the UAE. Multiple logistic regression analyses showed that a difference in SBP of 10 mm Hg between arms (odds ratio 12.23 (95% CI 1.130-132.35), P<0.0393) and a difference in SBP of 15 mm Hg between lower limbs (odds ratio 4.291 (95% CI 1.403-13.123), P<0.0106) correlated with the risk of albuminuria. A difference in SBP between arms and between lower limbs, therefore, could be a novel risk marker for diabetic nephropathy in patients with Type 2 diabetes.

Performance and effects of land cover type on synthetic surface reflectance data and NDVI estimates for assessment and monitoring of semi-arid rangeland

USGS Publications Warehouse

Olexa, Edward M.; Lawrence, Rick L

2014-01-01

Federal land management agencies provide stewardship over much of the rangelands in the arid andsemi-arid western United States, but they often lack data of the proper spatiotemporal resolution andextent needed to assess range conditions and monitor trends. Recent advances in the blending of com-plementary, remotely sensed data could provide public lands managers with the needed information.We applied the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) to five Landsat TMand concurrent Terra MODIS scenes, and used pixel-based regression and difference image analyses toevaluate the quality of synthetic reflectance and NDVI products associated with semi-arid rangeland. Pre-dicted red reflectance data consistently demonstrated higher accuracy, less bias, and stronger correlationwith observed data than did analogous near-infrared (NIR) data. The accuracy of both bands tended todecline as the lag between base and prediction dates increased; however, mean absolute errors (MAE)were typically ≤10%. The quality of area-wide NDVI estimates was less consistent than either spectra lband, although the MAE of estimates predicted using early season base pairs were ≤10% throughout the growing season. Correlation between known and predicted NDVI values and agreement with the 1:1regression line tended to decline as the prediction lag increased. Further analyses of NDVI predictions,based on a 22 June base pair and stratified by land cover/land use (LCLU), revealed accurate estimates through the growing season; however, inter-class performance varied. This work demonstrates the successful application of the STARFM algorithm to semi-arid rangeland; however, we encourage evaluation of STARFM’s performance on a per product basis, stratified by LCLU, with attention given to the influence of base pair selection and the impact of the time lag.

Poor sleep quality and nightmares are associated with non-suicidal self-injury in adolescents.

PubMed

Liu, Xianchen; Chen, Hua; Bo, Qi-Gui; Fan, Fang; Jia, Cun-Xian

2017-03-01

Non-suicidal self-injury (NSSI) is prevalent and is associated with increased risk of suicidal behavior in adolescents. This study examined which sleep variables are associated with NSSI, independently from demographics and mental health problems in Chinese adolescents. Participants consisted of 2090 students sampled from three high schools in Shandong, China and had a mean age of 15.49 years. Participants completed a sleep and health questionnaire to report their demographic and family information, sleep duration and sleep problems, impulsiveness, hopelessness, internalizing and externalizing problems, and NSSI. A series of regression analyses were conducted to examine the associations between sleep variables and NSSI. Of the sample, 12.6 % reported having ever engaged in NSSI and 8.8 % engaged during the last year. Univariate logistic analyses demonstrated that multiple sleep variables including short sleep duration, insomnia symptoms, poor sleep quality, sleep insufficiency, unrefreshed sleep, sleep dissatisfaction, daytime sleepiness, fatigue, snoring, and nightmares were associated with increased risk of NSSI. After adjusting for demographic and mental health variables, NSSI was significantly associated with sleeping <6 h per night, poor sleep quality, sleep dissatisfaction, daytime sleepiness, and frequent nightmares. Stepwise logistic regression model demonstrated that poor sleep quality (OR = 2.18, 95 % CI = 1.37-3.47) and frequent nightmares (OR = 2.88, 95 % CI = 1.45-5.70) were significantly independently associated with NSSI. In conclusion, while multiple sleep variables are associated with NSSI, poor sleep quality and frequent nightmares are independent risk factors of NSSI. These findings may have important implications for further research of sleep self-harm mechanisms and early detection and prevention of NSSI in adolescents.

Measuring the statistical validity of summary meta‐analysis and meta‐regression results for use in clinical practice

PubMed Central

Riley, Richard D.

2017-01-01

An important question for clinicians appraising a meta‐analysis is: are the findings likely to be valid in their own practice—does the reported effect accurately represent the effect that would occur in their own clinical population? To this end we advance the concept of statistical validity—where the parameter being estimated equals the corresponding parameter for a new independent study. Using a simple (‘leave‐one‐out’) cross‐validation technique, we demonstrate how we may test meta‐analysis estimates for statistical validity using a new validation statistic, Vn, and derive its distribution. We compare this with the usual approach of investigating heterogeneity in meta‐analyses and demonstrate the link between statistical validity and homogeneity. Using a simulation study, the properties of Vn and the Q statistic are compared for univariate random effects meta‐analysis and a tailored meta‐regression model, where information from the setting (included as model covariates) is used to calibrate the summary estimate to the setting of application. Their properties are found to be similar when there are 50 studies or more, but for fewer studies Vn has greater power but a higher type 1 error rate than Q. The power and type 1 error rate of Vn are also shown to depend on the within‐study variance, between‐study variance, study sample size, and the number of studies in the meta‐analysis. Finally, we apply Vn to two published meta‐analyses and conclude that it usefully augments standard methods when deciding upon the likely validity of summary meta‐analysis estimates in clinical practice. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:28620945

Measuring the statistical validity of summary meta-analysis and meta-regression results for use in clinical practice.

PubMed

Willis, Brian H; Riley, Richard D

2017-09-20

An important question for clinicians appraising a meta-analysis is: are the findings likely to be valid in their own practice-does the reported effect accurately represent the effect that would occur in their own clinical population? To this end we advance the concept of statistical validity-where the parameter being estimated equals the corresponding parameter for a new independent study. Using a simple ('leave-one-out') cross-validation technique, we demonstrate how we may test meta-analysis estimates for statistical validity using a new validation statistic, Vn, and derive its distribution. We compare this with the usual approach of investigating heterogeneity in meta-analyses and demonstrate the link between statistical validity and homogeneity. Using a simulation study, the properties of Vn and the Q statistic are compared for univariate random effects meta-analysis and a tailored meta-regression model, where information from the setting (included as model covariates) is used to calibrate the summary estimate to the setting of application. Their properties are found to be similar when there are 50 studies or more, but for fewer studies Vn has greater power but a higher type 1 error rate than Q. The power and type 1 error rate of Vn are also shown to depend on the within-study variance, between-study variance, study sample size, and the number of studies in the meta-analysis. Finally, we apply Vn to two published meta-analyses and conclude that it usefully augments standard methods when deciding upon the likely validity of summary meta-analysis estimates in clinical practice. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Assessing Principal Component Regression Prediction of Neurochemicals Detected with Fast-Scan Cyclic Voltammetry

PubMed Central

2011-01-01

Principal component regression is a multivariate data analysis approach routinely used to predict neurochemical concentrations from in vivo fast-scan cyclic voltammetry measurements. This mathematical procedure can rapidly be employed with present day computer programming languages. Here, we evaluate several methods that can be used to evaluate and improve multivariate concentration determination. The cyclic voltammetric representation of the calculated regression vector is shown to be a valuable tool in determining whether the calculated multivariate model is chemically appropriate. The use of Cook’s distance successfully identified outliers contained within in vivo fast-scan cyclic voltammetry training sets. This work also presents the first direct interpretation of a residual color plot and demonstrated the effect of peak shifts on predicted dopamine concentrations. Finally, separate analyses of smaller increments of a single continuous measurement could not be concatenated without substantial error in the predicted neurochemical concentrations due to electrode drift. Taken together, these tools allow for the construction of more robust multivariate calibration models and provide the first approach to assess the predictive ability of a procedure that is inherently impossible to validate because of the lack of in vivo standards. PMID:21966586

Assessing principal component regression prediction of neurochemicals detected with fast-scan cyclic voltammetry.

PubMed

Keithley, Richard B; Wightman, R Mark

2011-06-07

Principal component regression is a multivariate data analysis approach routinely used to predict neurochemical concentrations from in vivo fast-scan cyclic voltammetry measurements. This mathematical procedure can rapidly be employed with present day computer programming languages. Here, we evaluate several methods that can be used to evaluate and improve multivariate concentration determination. The cyclic voltammetric representation of the calculated regression vector is shown to be a valuable tool in determining whether the calculated multivariate model is chemically appropriate. The use of Cook's distance successfully identified outliers contained within in vivo fast-scan cyclic voltammetry training sets. This work also presents the first direct interpretation of a residual color plot and demonstrated the effect of peak shifts on predicted dopamine concentrations. Finally, separate analyses of smaller increments of a single continuous measurement could not be concatenated without substantial error in the predicted neurochemical concentrations due to electrode drift. Taken together, these tools allow for the construction of more robust multivariate calibration models and provide the first approach to assess the predictive ability of a procedure that is inherently impossible to validate because of the lack of in vivo standards.

Are your covariates under control? How normalization can re-introduce covariate effects.

PubMed

Pain, Oliver; Dudbridge, Frank; Ronald, Angelica

2018-04-30

Many statistical tests rely on the assumption that the residuals of a model are normally distributed. Rank-based inverse normal transformation (INT) of the dependent variable is one of the most popular approaches to satisfy the normality assumption. When covariates are included in the analysis, a common approach is to first adjust for the covariates and then normalize the residuals. This study investigated the effect of regressing covariates against the dependent variable and then applying rank-based INT to the residuals. The correlation between the dependent variable and covariates at each stage of processing was assessed. An alternative approach was tested in which rank-based INT was applied to the dependent variable before regressing covariates. Analyses based on both simulated and real data examples demonstrated that applying rank-based INT to the dependent variable residuals after regressing out covariates re-introduces a linear correlation between the dependent variable and covariates, increasing type-I errors and reducing power. On the other hand, when rank-based INT was applied prior to controlling for covariate effects, residuals were normally distributed and linearly uncorrelated with covariates. This latter approach is therefore recommended in situations were normality of the dependent variable is required.

SOCR Analyses – an Instructional Java Web-based Statistical Analysis Toolkit

PubMed Central

Chu, Annie; Cui, Jenny; Dinov, Ivo D.

2011-01-01

The Statistical Online Computational Resource (SOCR) designs web-based tools for educational use in a variety of undergraduate courses (Dinov 2006). Several studies have demonstrated that these resources significantly improve students' motivation and learning experiences (Dinov et al. 2008). SOCR Analyses is a new component that concentrates on data modeling and analysis using parametric and non-parametric techniques supported with graphical model diagnostics. Currently implemented analyses include commonly used models in undergraduate statistics courses like linear models (Simple Linear Regression, Multiple Linear Regression, One-Way and Two-Way ANOVA). In addition, we implemented tests for sample comparisons, such as t-test in the parametric category; and Wilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, in the non-parametric category. SOCR Analyses also include several hypothesis test models, such as Contingency tables, Friedman's test and Fisher's exact test. The code itself is open source (http://socr.googlecode.com/), hoping to contribute to the efforts of the statistical computing community. The code includes functionality for each specific analysis model and it has general utilities that can be applied in various statistical computing tasks. For example, concrete methods with API (Application Programming Interface) have been implemented in statistical summary, least square solutions of general linear models, rank calculations, etc. HTML interfaces, tutorials, source code, activities, and data are freely available via the web (www.SOCR.ucla.edu). Code examples for developers and demos for educators are provided on the SOCR Wiki website. In this article, the pedagogical utilization of the SOCR Analyses is discussed, as well as the underlying design framework. As the SOCR project is on-going and more functions and tools are being added to it, these resources are constantly improved. The reader is strongly encouraged to check the SOCR site for most updated information and newly added models. PMID:21546994

PARAMETRIC AND NON PARAMETRIC (MARS: MULTIVARIATE ADDITIVE REGRESSION SPLINES) LOGISTIC REGRESSIONS FOR PREDICTION OF A DICHOTOMOUS RESPONSE VARIABLE WITH AN EXAMPLE FOR PRESENCE/ABSENCE OF AMPHIBIANS

EPA Science Inventory

The purpose of this report is to provide a reference manual that could be used by investigators for making informed use of logistic regression using two methods (standard logistic regression and MARS). The details for analyses of relationships between a dependent binary response ...

A Simulation Investigation of Principal Component Regression.

ERIC Educational Resources Information Center

Allen, David E.

Regression analysis is one of the more common analytic tools used by researchers. However, multicollinearity between the predictor variables can cause problems in using the results of regression analyses. Problems associated with multicollinearity include entanglement of relative influences of variables due to reduced precision of estimation,…

Value of the portal venous phase in evaluation of treated hepatocellular carcinoma following transcatheter arterial chemoembolisation.

PubMed

Lam, A; Fernando, D; Sirlin, C C; Nayyar, M; Goodwin, S C; Imagawa, D K; Lall, C

2017-11-01

To evaluate the utility of the portal venous phase on multiphasic computed tomography (CT) after treatment of hepatocellular carcinoma (HCC) with trans-arterial chemoembolisation (TACE). This was a retrospective review of patients who underwent TACE for HCC between 1 April 2012 and 21 December 2014, with appropriate multiphasic, pre- and post-procedural CT examinations. The maximum non-contrast, arterial phase, and portal venous phase attenuation values of the tumour and tumour bed were evaluated within a region of interest (ROI), with values adjusted against background hepatic parenchyma. Linear regression analyses were performed for both the arterial and venous phases, to assess the level of enhancement and to determine if the venous phase had additional value in this setting. A total of 86 cases from 51 patients were reviewed. All pre-procedural CT examinations of lesions demonstrated arterial phase enhancement with portal venous and delayed phase washout compatible with HCC. The post-procedural CT examinations following TACE revealed expected decreased arterial enhancement. Sixty-five cases (76%) showed persistent non-enhancement on the portal venous phase following embolisation therapy. A total of 21 cases (24%), however, demonstrated progressive portal venous hyper enhancement. Linear regression analysis demonstrated a statistical significance between the difference in maximal arterial and portal venous enhancement in these cases. Following TACE, the treated lesion may demonstrate portal venous phase hyper-enhancement within the tumour bed. As such, full attention should be given to these images for comprehensive evaluation of tumour response following treatment. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Artificial Neural Network for the Prediction of Chromosomal Abnormalities in Azoospermic Males.

PubMed

Akinsal, Emre Can; Haznedar, Bulent; Baydilli, Numan; Kalinli, Adem; Ozturk, Ahmet; Ekmekçioğlu, Oğuz

2018-02-04

To evaluate whether an artifical neural network helps to diagnose any chromosomal abnormalities in azoospermic males. The data of azoospermic males attending to a tertiary academic referral center were evaluated retrospectively. Height, total testicular volume, follicle stimulating hormone, luteinising hormone, total testosterone and ejaculate volume of the patients were used for the analyses. In artificial neural network, the data of 310 azoospermics were used as the education and 115 as the test set. Logistic regression analyses and discriminant analyses were performed for statistical analyses. The tests were re-analysed with a neural network. Both logistic regression analyses and artificial neural network predicted the presence or absence of chromosomal abnormalities with more than 95% accuracy. The use of artificial neural network model has yielded satisfactory results in terms of distinguishing patients whether they have any chromosomal abnormality or not.

Association between response rates and survival outcomes in patients with newly diagnosed multiple myeloma. A systematic review and meta-regression analysis.

PubMed

Mainou, Maria; Madenidou, Anastasia-Vasiliki; Liakos, Aris; Paschos, Paschalis; Karagiannis, Thomas; Bekiari, Eleni; Vlachaki, Efthymia; Wang, Zhen; Murad, Mohammad Hassan; Kumar, Shaji; Tsapas, Apostolos

2017-06-01

We performed a systematic review and meta-regression analysis of randomized control trials to investigate the association between response to initial treatment and survival outcomes in patients with newly diagnosed multiple myeloma (MM). Response outcomes included complete response (CR) and the combined outcome of CR or very good partial response (VGPR), while survival outcomes were overall survival (OS) and progression-free survival (PFS). We used random-effect meta-regression models and conducted sensitivity analyses based on definition of CR and study quality. Seventy-two trials were included in the systematic review, 63 of which contributed data in meta-regression analyses. There was no association between OS and CR in patients without autologous stem cell transplant (ASCT) (regression coefficient: .02, 95% confidence interval [CI] -0.06, 0.10), in patients undergoing ASCT (-.11, 95% CI -0.44, 0.22) and in trials comparing ASCT with non-ASCT patients (.04, 95% CI -0.29, 0.38). Similarly, OS did not correlate with the combined metric of CR or VGPR, and no association was evident between response outcomes and PFS. Sensitivity analyses yielded similar results. This meta-regression analysis suggests that there is no association between conventional response outcomes and survival in patients with newly diagnosed MM. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Predicting consumer preferences for mineral composition of bottled and tap water.

PubMed

Platikanov, Stefan; Hernández, Alejandra; González, Susana; Luis Cortina, Jose; Tauler, Roma; Devesa, Ricard

2017-01-01

The overall liking for taste of water was correlated with the mineral composition of selected bottled and tap waters. Sixty-nine untrained volunteers assessed and rated twenty-five different commercial bottled and tap waters from. Water samples were physicochemical characterised by analysing conductivity, pH, total dissolved solids (TDS) and major anions and cations: HCO 3 - , SO 4 2- , Cl - , NO 3 - , Ca 2+ , Mg 2+ , Na + , and K + . Residual chlorine levels were also analysed in the tap water samples. Globally, volunteers preferred waters rich in calcium bicarbonate and sulfate, rather than in sodium chloride. This study also demonstrated that it was possible to accurately predict the overall liking by a Partial Least Squares regression using either all measured physicochemical parameters or a reduced number of them. These results were in agreement with previously published results using trained panellists. Copyright © 2016 Elsevier B.V. All rights reserved.

Tree-ring variation in western larch (Larix occidentalis Nutt. ) exposed to sulfur dioxide emissions

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

Fox, C.A.; Kincaid, W.B.; Nash, T.H. III

1984-12-01

Tree-ring analysis of western larch (Larix occidentialis Nutt) demonstrated both direct and indirect affects of sulfur dioxide emissions from the lead/zinc smelter at Trail, B.C. Tree cores were collected from 5 stands known to have been polluted and from 3 control stands. Age effects were removed by fitting theoretical growth curves, and macrocliate was modeled using the average of the controls and two laged values thereof. Separate analyses were performed for years before and after installation of two tall stacks, for drought and nondrought years, and for years prior to initiation of smelting. Regression analyses revealed a negative effect onmore » annual growth that diminished with increasing distance from the smelter and during drought years. Furthermore, chronology statistics suggested an increase in sensitivity to climate that persisted decades beyond implementation of pollution controls, which reduced emissions 10-fold. 38 references, 6 figures, 3 tables.« less

Higher direct bilirubin levels during mid-pregnancy are associated with lower risk of gestational diabetes mellitus.

PubMed

Liu, Chaoqun; Zhong, Chunrong; Zhou, Xuezhen; Chen, Renjuan; Wu, Jiangyue; Wang, Weiye; Li, Xiating; Ding, Huisi; Guo, Yanfang; Gao, Qin; Hu, Xingwen; Xiong, Guoping; Yang, Xuefeng; Hao, Liping; Xiao, Mei; Yang, Nianhong

2017-01-01

Bilirubin concentrations have been recently reported to be negatively associated with type 2 diabetes mellitus. We examined the association between bilirubin concentrations and gestational diabetes mellitus. In a prospective cohort study, 2969 pregnant women were recruited prior to 16 weeks of gestation and were followed up until delivery. The value of bilirubin was tested and oral glucose tolerance test was conducted to screen gestational diabetes mellitus. The relationship between serum bilirubin concentration and gestational weeks was studied by two-piecewise linear regression. A subsample of 1135 participants with serum bilirubin test during 16-18 weeks gestation was conducted to research the association between serum bilirubin levels and risk of gestational diabetes mellitus by logistic regression. Gestational diabetes mellitus developed in 8.5 % of the participants (223 of 2969). Two-piecewise linear regression analyses demonstrated that the levels of bilirubin decreased with gestational week up to the turning point 23 and after that point, levels of bilirubin were increased slightly. In multiple logistic regression analysis, the relative risk of developing gestational diabetes mellitus was lower in the highest tertile of direct bilirubin than that in the lowest tertile (RR 0.60; 95 % CI, 0.35-0.89). The results suggested that women with higher serum direct bilirubin levels during the second trimester of pregnancy have lower risk for development of gestational diabetes mellitus.

Structural vascular disease in Africans: Performance of ethnic-specific waist circumference cut points using logistic regression and neural network analyses: The SABPA study.

PubMed

Botha, J; de Ridder, J H; Potgieter, J C; Steyn, H S; Malan, L

2013-10-01

A recently proposed model for waist circumference cut points (RPWC), driven by increased blood pressure, was demonstrated in an African population. We therefore aimed to validate the RPWC by comparing the RPWC and the Joint Statement Consensus (JSC) models via Logistic Regression (LR) and Neural Networks (NN) analyses. Urban African gender groups (N=171) were stratified according to the JSC and RPWC cut point models. Ultrasound carotid intima media thickness (CIMT), blood pressure (BP) and fasting bloods (glucose, high density lipoprotein (HDL) and triglycerides) were obtained in a well-controlled setting. The RPWC male model (LR ROC AUC: 0.71, NN ROC AUC: 0.71) was practically equal to the JSC model (LR ROC AUC: 0.71, NN ROC AUC: 0.69) to predict structural vascular -disease. Similarly, the female RPWC model (LR ROC AUC: 0.84, NN ROC AUC: 0.82) and JSC model (LR ROC AUC: 0.82, NN ROC AUC: 0.81) equally predicted CIMT as surrogate marker for structural vascular disease. Odds ratios supported validity where prediction of CIMT revealed -clinical -significance, well over 1, for both the JSC and RPWC models in African males and females (OR 3.75-13.98). In conclusion, the proposed RPWC model was substantially validated utilizing linear and non-linear analyses. We therefore propose ethnic-specific WC cut points (African males, ≥90 cm; -females, ≥98 cm) to predict a surrogate marker for structural vascular disease. © J. A. Barth Verlag in Georg Thieme Verlag KG Stuttgart · New York.

Predicting Word Reading Ability: A Quantile Regression Study

ERIC Educational Resources Information Center

McIlraith, Autumn L.

2018-01-01

Predictors of early word reading are well established. However, it is unclear if these predictors hold for readers across a range of word reading abilities. This study used quantile regression to investigate predictive relationships at different points in the distribution of word reading. Quantile regression analyses used preschool and…

Missing heritability in the tails of quantitative traits? A simulation study on the impact of slightly altered true genetic models.

PubMed

Pütter, Carolin; Pechlivanis, Sonali; Nöthen, Markus M; Jöckel, Karl-Heinz; Wichmann, Heinz-Erich; Scherag, André

2011-01-01

Genome-wide association studies have identified robust associations between single nucleotide polymorphisms and complex traits. As the proportion of phenotypic variance explained is still limited for most of the traits, larger and larger meta-analyses are being conducted to detect additional associations. Here we investigate the impact of the study design and the underlying assumption about the true genetic effect in a bimodal mixture situation on the power to detect associations. We performed simulations of quantitative phenotypes analysed by standard linear regression and dichotomized case-control data sets from the extremes of the quantitative trait analysed by standard logistic regression. Using linear regression, markers with an effect in the extremes of the traits were almost undetectable, whereas analysing extremes by case-control design had superior power even for much smaller sample sizes. Two real data examples are provided to support our theoretical findings and to explore our mixture and parameter assumption. Our findings support the idea to re-analyse the available meta-analysis data sets to detect new loci in the extremes. Moreover, our investigation offers an explanation for discrepant findings when analysing quantitative traits in the general population and in the extremes. Copyright © 2011 S. Karger AG, Basel.

A method for fitting regression splines with varying polynomial order in the linear mixed model.

PubMed

Edwards, Lloyd J; Stewart, Paul W; MacDougall, James E; Helms, Ronald W

2006-02-15

The linear mixed model has become a widely used tool for longitudinal analysis of continuous variables. The use of regression splines in these models offers the analyst additional flexibility in the formulation of descriptive analyses, exploratory analyses and hypothesis-driven confirmatory analyses. We propose a method for fitting piecewise polynomial regression splines with varying polynomial order in the fixed effects and/or random effects of the linear mixed model. The polynomial segments are explicitly constrained by side conditions for continuity and some smoothness at the points where they join. By using a reparameterization of this explicitly constrained linear mixed model, an implicitly constrained linear mixed model is constructed that simplifies implementation of fixed-knot regression splines. The proposed approach is relatively simple, handles splines in one variable or multiple variables, and can be easily programmed using existing commercial software such as SAS or S-plus. The method is illustrated using two examples: an analysis of longitudinal viral load data from a study of subjects with acute HIV-1 infection and an analysis of 24-hour ambulatory blood pressure profiles.

Relationship between cataract severity and socioeconomic status.

PubMed

Wesolosky, Jason D; Rudnisky, Christopher J

2013-12-01

To determine the relationship between cataract severity and socioeconomic status (SES). Retrospective, observational case series. A total of 1350 eyes underwent phacoemulsification cataract extraction by a single surgeon using an Alcon Infiniti system. Cataract severity was measured using phaco time in seconds. SES was measured using area-level aggregate census data: median income, education, proportion of common-law couples, and employment rate. Preoperative best corrected visual acuity was obtained and converted to logarithm of the minimum angle of resolution values. For patients undergoing bilateral surgery, the generalized estimating equation was used to account for the correlation between eyes. Univariate analyses were performed using simple regression, and multivariate analyses were performed to account for variables with significant relationships (p < 0.05) on univariate testing. Sensitivity analyses were performed to assess the effect of including patient age in the controlled analyses. Multivariate analyses demonstrated that cataracts were more severe when the median income was lower (p = 0.001) and the proportion of common-law couples living in a patient's community (p = 0.012) and the unemployment rate (p = 0.002) were higher. These associations persisted even when controlling for patient age. Patients of lower SES have more severe cataracts. Copyright © 2013 Canadian Ophthalmological Society. Published by Elsevier Inc. All rights reserved.

Diesel engine exhaust and lung cancer risks - evaluation of the meta-analysis by Vermeulen et al. 2014.

PubMed

Morfeld, Peter; Spallek, Michael

2015-01-01

Vermeulen et al. 2014 published a meta-regression analysis of three relevant epidemiological US studies (Steenland et al. 1998, Garshick et al. 2012, Silverman et al. 2012) that estimated the association between occupational diesel engine exhaust (DEE) exposure and lung cancer mortality. The DEE exposure was measured as cumulative exposure to estimated respirable elemental carbon in μg/m(3)-years. Vermeulen et al. 2014 found a statistically significant dose-response association and described elevated lung cancer risks even at very low exposures. We performed an extended re-analysis using different modelling approaches (fixed and random effects regression analyses, Greenland/Longnecker method) and explored the impact of varying input data (modified coefficients of Garshick et al. 2012, results from Crump et al. 2015 replacing Silverman et al. 2012, modified analysis of Moehner et al. 2013). We reproduced the individual and main meta-analytical results of Vermeulen et al. 2014. However, our analysis demonstrated a heterogeneity of the baseline relative risk levels between the three studies. This heterogeneity was reduced after the coefficients of Garshick et al. 2012 were modified while the dose coefficient dropped by an order of magnitude for this study and was far from being significant (P = 0.6). A (non-significant) threshold estimate for the cumulative DEE exposure was found at 150 μg/m(3)-years when extending the meta-analyses of the three studies by hockey-stick regression modelling (including the modified coefficients for Garshick et al. 2012). The data used by Vermeulen and colleagues led to the highest relative risk estimate across all sensitivity analyses performed. The lowest relative risk estimate was found after exclusion of the explorative study by Steenland et al. 1998 in a meta-regression analysis of Garshick et al. 2012 (modified), Silverman et al. 2012 (modified according to Crump et al. 2015) and Möhner et al. 2013. The meta-coefficient was estimated to be about 10-20 % of the main effect estimate in Vermeulen et al. 2014 in this analysis. The findings of Vermeulen et al. 2014 should not be used without reservations in any risk assessments. This is particularly true for the low end of the exposure scale.

Morphology of sustentaculum tali: Biomechanical importance and correlation with angular dimensions of the talus.

PubMed

Mahato, Niladri Kumar

2011-12-01

The talus and the calcaneus share the bulk of load transmitted from the leg to the skeleton of the foot. The present study analyses the inter-relationship between the superior articular surface and the angular dimensions of the talus with the morphology of the sustentaculum tali. Identification of possible relationships between different angular parameters of the talus morphology and the sustentaculum tali in context of load transmission through the foot. One articular surface and three angular parameters at the junction of the head and the body were measured from dried human talar bones. Corresponding calcaneal samples were measured for four dimensions at the sustentaculum tali. Correlation and regression statistical values between parameters were worked out and analysed. Several parameters within the talus demonstrated significant correlations amongst themselves. The neck vertical angle showed a strong correlation with the articulating surface area below the head of the talus. The inter-relationship between articular and angular parameters within the talus demonstrates strong correlation for certain parameters. Data presented in the study may be helpful to adjust calcaneal and talar screw placement techniques, prosthesis designing and bio-mechanical studies at this important region. Copyright © 2011 Elsevier Ltd. All rights reserved.

Seasonal trends in tinnitus symptomatology: evidence from Internet search engine query data.

PubMed

Plante, David T; Ingram, David G

2015-10-01

The primary aim of this study was to test the hypothesis that the symptom of tinnitus demonstrates a seasonal pattern with worsening in the winter relative to the summer using Internet search engine query data. Normalized search volume for the term 'tinnitus' from January 2004 through December 2013 was retrieved from Google Trends. Seasonal effects were evaluated using cosinor regression models. Primary countries of interest were the United States and Australia. Secondary exploratory analyses were also performed using data from Germany, the United Kingdom, Canada, Sweden, and Switzerland. Significant seasonal effects for 'tinnitus' search queries were found in the United States and Australia (p < 0.00001 for both countries), with peaks in the winter and troughs in the summer. Secondary analyses demonstrated similarly significant seasonal effects for Germany (p < 0.00001), Canada (p < 0.00001), and Sweden (p = 0.0008), again with increased search volume in the winter relative to the summer. Our findings indicate that there are significant seasonal trends for Internet search queries for tinnitus, with a zenith in winter months. Further research is indicated to determine the biological mechanisms underlying these findings, as they may provide insights into the pathophysiology of this common and debilitating medical symptom.

A two-factor error model for quantitative steganalysis

NASA Astrophysics Data System (ADS)

Böhme, Rainer; Ker, Andrew D.

2006-02-01

Quantitative steganalysis refers to the exercise not only of detecting the presence of hidden stego messages in carrier objects, but also of estimating the secret message length. This problem is well studied, with many detectors proposed but only a sparse analysis of errors in the estimators. A deep understanding of the error model, however, is a fundamental requirement for the assessment and comparison of different detection methods. This paper presents a rationale for a two-factor model for sources of error in quantitative steganalysis, and shows evidence from a dedicated large-scale nested experimental set-up with a total of more than 200 million attacks. Apart from general findings about the distribution functions found in both classes of errors, their respective weight is determined, and implications for statistical hypothesis tests in benchmarking scenarios or regression analyses are demonstrated. The results are based on a rigorous comparison of five different detection methods under many different external conditions, such as size of the carrier, previous JPEG compression, and colour channel selection. We include analyses demonstrating the effects of local variance and cover saturation on the different sources of error, as well as presenting the case for a relative bias model for between-image error.

Service climate as a mediator of organizational empowerment in customer-service employees.

PubMed

Mendoza-Sierra, Maria Isabel; Orgambídez-Ramos, Alejandro; Carrasco-González, Ana María; León-Jariego, José Carlos

2014-01-01

The aim of this study is to examine the mediating role of the service climate between organizational empowerment (i.e., dynamic structural framework, control of workplace decisions, fluidity in information sharing) and service quality (functional and relational). 428 contact employees from 46 hotels participated in the survey. Correlations demonstrated that dynamic structural framework, control decisions, and fluidity in information sharing are related to both functional and relational service quality. Regression analyses and Sobel tests revealed that service climate totally mediated the relationship between all three dimensions of organizational empowerment and relational service quality. Implications for practice and future research are discussed.

Predictors of workplace violence among female sex workers in Tijuana, Mexico.

PubMed

Katsulis, Yasmina; Durfee, Alesha; Lopez, Vera; Robillard, Alyssa

2015-05-01

For sex workers, differences in rates of exposure to workplace violence are likely influenced by a variety of risk factors, including where one works and under what circumstances. Economic stressors, such as housing insecurity, may also increase the likelihood of exposure. Bivariate analyses demonstrate statistically significant associations between workplace violence and selected predictor variables, including age, drug use, exchanging sex for goods, soliciting clients outdoors, and experiencing housing insecurity. Multivariate regression analysis shows that after controlling for each of these variables in one model, only soliciting clients outdoors and housing insecurity emerge as statistically significant predictors for workplace violence. © The Author(s) 2014.

Classification and regression tree analysis vs. multivariable linear and logistic regression methods as statistical tools for studying haemophilia.

PubMed

Henrard, S; Speybroeck, N; Hermans, C

2015-11-01

Haemophilia is a rare genetic haemorrhagic disease characterized by partial or complete deficiency of coagulation factor VIII, for haemophilia A, or IX, for haemophilia B. As in any other medical research domain, the field of haemophilia research is increasingly concerned with finding factors associated with binary or continuous outcomes through multivariable models. Traditional models include multiple logistic regressions, for binary outcomes, and multiple linear regressions for continuous outcomes. Yet these regression models are at times difficult to implement, especially for non-statisticians, and can be difficult to interpret. The present paper sought to didactically explain how, why, and when to use classification and regression tree (CART) analysis for haemophilia research. The CART method is non-parametric and non-linear, based on the repeated partitioning of a sample into subgroups based on a certain criterion. Breiman developed this method in 1984. Classification trees (CTs) are used to analyse categorical outcomes and regression trees (RTs) to analyse continuous ones. The CART methodology has become increasingly popular in the medical field, yet only a few examples of studies using this methodology specifically in haemophilia have to date been published. Two examples using CART analysis and previously published in this field are didactically explained in details. There is increasing interest in using CART analysis in the health domain, primarily due to its ease of implementation, use, and interpretation, thus facilitating medical decision-making. This method should be promoted for analysing continuous or categorical outcomes in haemophilia, when applicable. © 2015 John Wiley & Sons Ltd.

Determination of polyphenolic compounds of red wines by UV-VIS-NIR spectroscopy and chemometrics tools.

PubMed

Martelo-Vidal, M J; Vázquez, M

2014-09-01

Spectral analysis is a quick and non-destructive method to analyse wine. In this work, trans-resveratrol, oenin, malvin, catechin, epicatechin, quercetin and syringic acid were determined in commercial red wines from DO Rías Baixas and DO Ribeira Sacra (Spain) by UV-VIS-NIR spectroscopy. Calibration models were developed using principal component regression (PCR) or partial least squares (PLS) regression. HPLC was used as reference method. The results showed that reliable PLS models were obtained to quantify all polyphenols for Rías Baixas wines. For Ribeira Sacra, feasible models were obtained to determine quercetin, epicatechin, oenin and syringic acid. PCR calibration models showed worst reliable of prediction than PLS models. For red wines from mencía grapes, feasible models were obtained for catechin and oenin, regardless the geographical origin. The results obtained demonstrate that UV-VIS-NIR spectroscopy can be used to determine individual polyphenolic compounds in red wines. Copyright © 2014 Elsevier Ltd. All rights reserved.

Retroillumination Photography Analysis Enhances Clinical Definition of Severe Fuchs Corneal Dystrophy.

PubMed

Eghrari, Allen O; Garrett, Brian S; Mumtaz, Aisha A; Edalati, Armand E; Meadows, Danielle N; McGlumphy, Elyse J; Iliff, Benjamin W; Gottsch, John D

2015-12-01

Retroillumination photography analysis (RPA) provides an objective assessment of the number and distribution of guttae in Fuchs corneal dystrophy. Here, we assess its correlation with clinical grading using slit-lamp biomicroscopy across varying levels of severity. Retroillumination photographs were conducted for 95 affected corneas with slit-lamp flash photography after pupillary dilation. Individual guttae were counted manually and the position of individual points recorded. Clinical grading using the Krachmer scale was documented for each eye during examination, and regression analyses were performed to identify the strength of association with number of guttae. We assessed range at each stage of clinical grading and used the Mann-Whitney U test to assess whether clinical grading levels demonstrated successively higher numbers of guttae. Krachmer score ranged from 1 to 5, with mean of 2.6. Mean numbers of guttae at each level of severity were 289 (1+), 999 (2+), 2669 (3+), 5474 (4+), and 7133 (5+). Each stage demonstrated significantly higher numbers of guttae than its preceding level except from 4+ to 5+ (P = 0.30), consistent with the definition of 4+ as the highest level defined by the presence of guttae. Higher levels of clinical grading were associated with larger ranges of guttae (P < 0.01). A linear regression model resulted in a strong fit between RPA and Krachmer score (r = 0.81). In this largest study of RPA data and comparison with subjective clinical grading of Fuchs dystrophy severity, RPA correlates strongly and demonstrates enhanced definition of severity at advanced stages of disease.

'Left behind' but not left alone: parental migration & the psychosocial health of children in Moldova.

PubMed

Vanore, Michaella; Mazzucato, Valentina; Siegel, Melissa

2015-05-01

In Moldova, large-scale and rapidly feminised migration flows have inspired a wave of qualitative reports on children "left behind". Despite this recent interest, few studies have empirically evaluated the effects of parental migration on the psychosocial health of such children. Using data collected from a nationally-representative household survey conducted in Moldova between September 2011 and February 2012, this paper analyses the psychosocial health outcomes of children of migrant parents by comparing them with children without migrant parents (n = 1979). Child psychosocial health is measured through caregiver-reported Strengths and Difficulties Questionnaire (SDQ) scores. Multivariate regression analyses show that parental migration seldom corresponds to worse emotional symptoms outcomes but does correspond to increased conduct problems. Separate analyses for male and female children show significant gendered differences. The results partially contest the negative results that have been the subject of qualitative reports and, in particular, demonstrate that the migration of mothers infrequently results in worse psychosocial outcomes for children-contrary to what has been assumed in the discourse about parental migration in Moldova. Copyright © 2014 Elsevier Ltd. All rights reserved.

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…

Regression Effects in Angoff Ratings: Examples from Credentialing Exams

ERIC Educational Resources Information Center

Wyse, Adam E.

2018-01-01

This article discusses regression effects that are commonly observed in Angoff ratings where panelists tend to think that hard items are easier than they are and easy items are more difficult than they are in comparison to estimated item difficulties. Analyses of data from two credentialing exams illustrate these regression effects and the…

Bayesian feature selection for high-dimensional linear regression via the Ising approximation with applications to genomics.

PubMed

Fisher, Charles K; Mehta, Pankaj

2015-06-01

Feature selection, identifying a subset of variables that are relevant for predicting a response, is an important and challenging component of many methods in statistics and machine learning. Feature selection is especially difficult and computationally intensive when the number of variables approaches or exceeds the number of samples, as is often the case for many genomic datasets. Here, we introduce a new approach--the Bayesian Ising Approximation (BIA)-to rapidly calculate posterior probabilities for feature relevance in L2 penalized linear regression. In the regime where the regression problem is strongly regularized by the prior, we show that computing the marginal posterior probabilities for features is equivalent to computing the magnetizations of an Ising model with weak couplings. Using a mean field approximation, we show it is possible to rapidly compute the feature selection path described by the posterior probabilities as a function of the L2 penalty. We present simulations and analytical results illustrating the accuracy of the BIA on some simple regression problems. Finally, we demonstrate the applicability of the BIA to high-dimensional regression by analyzing a gene expression dataset with nearly 30 000 features. These results also highlight the impact of correlations between features on Bayesian feature selection. An implementation of the BIA in C++, along with data for reproducing our gene expression analyses, are freely available at http://physics.bu.edu/∼pankajm/BIACode. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

An empirical study using permutation-based resampling in meta-regression

PubMed Central

2012-01-01

Background In meta-regression, as the number of trials in the analyses decreases, the risk of false positives or false negatives increases. This is partly due to the assumption of normality that may not hold in small samples. Creation of a distribution from the observed trials using permutation methods to calculate P values may allow for less spurious findings. Permutation has not been empirically tested in meta-regression. The objective of this study was to perform an empirical investigation to explore the differences in results for meta-analyses on a small number of trials using standard large sample approaches verses permutation-based methods for meta-regression. Methods We isolated a sample of randomized controlled clinical trials (RCTs) for interventions that have a small number of trials (herbal medicine trials). Trials were then grouped by herbal species and condition and assessed for methodological quality using the Jadad scale, and data were extracted for each outcome. Finally, we performed meta-analyses on the primary outcome of each group of trials and meta-regression for methodological quality subgroups within each meta-analysis. We used large sample methods and permutation methods in our meta-regression modeling. We then compared final models and final P values between methods. Results We collected 110 trials across 5 intervention/outcome pairings and 5 to 10 trials per covariate. When applying large sample methods and permutation-based methods in our backwards stepwise regression the covariates in the final models were identical in all cases. The P values for the covariates in the final model were larger in 78% (7/9) of the cases for permutation and identical for 22% (2/9) of the cases. Conclusions We present empirical evidence that permutation-based resampling may not change final models when using backwards stepwise regression, but may increase P values in meta-regression of multiple covariates for relatively small amount of trials. PMID:22587815

Publication bias in obesity treatment trials?

PubMed

Allison, D B; Faith, M S; Gorman, B S

1996-10-01

The present investigation examined the extent of publication bias (namely the tendency to publish significant findings and file away non-significant findings) within the obesity treatment literature. Quantitative literature synthesis of four published meta-analyses from the obesity treatment literature. Interventions in these studies included pharmacological, educational, child, and couples treatments. To assess publication bias, several regression procedures (for example weighted least-squares, random-effects multi-level modeling, and robust regression methods) were used to regress effect sizes onto their standard errors, or proxies thereof, within each of the four meta-analysis. A significant positive beta weight in these analyses signified publication bias. There was evidence for publication bias within two of the four published meta-analyses, such that reviews of published studies were likely to overestimate clinical efficacy. The lack of evidence for publication bias within the two other meta-analyses might have been due to insufficient statistical power rather than the absence of selection bias. As in other disciplines, publication bias appears to exist in the obesity treatment literature. Suggestions are offered for managing publication bias once identified or reducing its likelihood in the first place.

Elevated serum α-linolenic acid levels are associated with decreased chance of pregnancy after in vitro fertilization.

PubMed

Jungheim, Emily S; Macones, George A; Odem, Randall R; Patterson, Bruce W; Moley, Kelle H

2011-10-01

To analyze relationships between serum free fatty acid (FFA) concentrations and pregnancy. Prospective cohort. University hospital. Ninety-one women undergoing IVF. Serum was analyzed for total and specific serum FFAs, including myristic, palmitic, stearic, oleic, linoleic, and α-linolenic acids. Univariate analyses were used to identify specific FFAs and other factors associated with pregnancy after IVF. Logistic regression was performed modeling relationships between identified factors and chance of pregnancy. In unadjusted analyses, women with elevated serum α-linolenic acid (ALA) levels (highest quartile) demonstrated a decreased chance of pregnancy compared with women with the lowest levels (odds ratio 0.24, 95% confidence interval 0.052-0.792). No associations between other FFAs and pregnancy were identified. In a multivariable regression model, associations between elevated serum ALA levels and decreased chance of pregnancy remained after adjusting for patient age, body mass index, and history of endometriosis or previous live birth (adjusted odds ratio 0.139, 95% confidence interval 0.028-0.686). Elevated serum ALA levels are associated with decreased chance of pregnancy in women undergoing IVF. Further work is needed to determine whether ALA is involved in early reproductive processes and whether the relationship between ALA and pregnancy is associated with excess ALA intake, impaired ALA metabolism, or both. Copyright © 2011 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Factors Associated with Pain Severity in Children with Calcaneal Apophysitis (Sever Disease).

PubMed

James, Alicia M; Williams, Cylie M; Luscombe, Michelle; Hunter, Reshele; Haines, Terry P

2015-08-01

To identify any association between the pain experienced as a result of calcaneal apophysitis, anthropometric data, and lower limb measurements. This study was a cross-sectional study, nested within a wider randomized, comparative efficacy trial. One hundred twenty-four children between the ages of 8 and 14 years with a clinical diagnosis of calcaneal apophysitis were recruited for this study. Of the participating children, 72 were male. The measures recorded were height, weight, waist circumference, body mass index, foot posture, and ankle joint range of motion; comparison with normative values was also completed. Univariate and multivariable regression analyses were undertaken to identify factors associated with the severity of pain experienced (visual analog scale). The children within this study had a higher mean body mass index (P < .001), increased weight (P < .001), and were taller (P < .001) compared with normative values. The children also demonstrated differences in foot posture and ankle joint range of motion. Multivariable regression analyses identified that older participants (P = .046) and those who had experienced pain for longer (P = .043) reported higher pain severity. Children presenting with calcaneal apophysitis were anthropometrically different from their peers and had experienced a lengthy period of pain. Therefore, early management focussing on the anthropometric differences may minimize the intensity and duration of pain experienced. Registered with Australian New Zealand Clinical Trials Registry: ACTRN12609000696291. Copyright © 2015 Elsevier Inc. All rights reserved.

Task deactivation reductions and atrophy within parietal default mode regions are overlapping but only weakly correlated in mild cognitive impairment

PubMed Central

Threlkeld, Zachary D.; Jicha, Greg A.; Smith, Charles D.; Gold, Brian T.

2012-01-01

Reduced task deactivation within regions of the default mode network (DMN) has been frequently reported in Alzheimer’s disease (AD) and amnestic mild cognitive impairment (aMCI). As task deactivations reductions become increasingly used in the study of early AD states, it is important to understand their relationship to atrophy. To address this issue, the present study compared task deactivation reductions during a lexical decision task and atrophy in aMCI, using a series of parallel voxel-wise and region-wise analyses of fMRI and structural data. Our results identified multiple regions within parietal cortex as convergence areas of task deactivation and atrophy in aMCI. Relationships between parietal regions showing overlapping task deactivation reductions and atrophy in aMCI were then explored. Regression analyses demonstrated minimal correlation between task deactivation reductions and either local or global atrophy in aMCI. In addition, a logistic regression model which combined task deactivation reductions and atrophy in parietal DMN regions showed higher classificatory accuracy of aMCI than separate task deactivation or atrophy models. Results suggest that task deactivation reductions and atrophy in parietal regions provide complementary rather than redundant information in aMCI. Future longitudinal studies will be required to assess the utility of combining task deactivation reductions and atrophy in the detection of early AD. PMID:21860094

Self and near relative ratings of functional level one year after traumatic brain injury.

PubMed

Sandhaug, Maria; Andelic, Nada; Berntsen, Svein A; Seiler, Stephen; Mygland, Aase

2012-01-01

To quantify traumatic brain injury (TBI) patients' perceptions of own function by the Patient Competency Rating Scale (PCRS) one year after injury, and to examine self-awareness of functional deficits by comparing PCRS ratings from patients (PCRS-P) and PCRS ratings from near relatives (PCRS-R), and to identify predictors of awareness deficits. A cohort of 50 severe (n = 33) and moderate (n = 17) TBI patients. Awareness of deficits was investigated by subtracting PCRS relative ratings from PCRS patient ratings. Predictors of PCRS ratings and differences were assessed by stepwise multiple regression analyses. The average patient PCRS sum score was 122/150 (95% CI = 115; 129) as compared to a sum score of 117/150 (95% CI = 110; 125), given by their relatives (p = 0.93). The patients scored themselves slightly higher than their relatives in the domains of activities of daily living (ADL) and cognitive function (p < 0.001, p < 0.001). Regression analyses showed that Glasgow Coma Scale (GCS)score at admission to rehabilitation was the strongest predictor of patient PCRS (B = 3.314, p = 0.008). The strongest predictor of differences between patient and relative PCRS was GCS acute (B = -3.530, p = 0.001). TBI patients demonstrated a slight "awareness gap" in ADL and cognitive function. Low GCS in the acute phase and high age were the strongest predictors of self- awareness deficits.

Domain or not domain? That is the question: longitudinal semantic deterioration in Alzheimer's disease.

PubMed

Moreno-Martínez, F Javier; Goñi-Imízcoz, Miguel; Spitznagel, Mary Beth

2011-10-01

Category specific semantic impairment (e.g. living versus nonliving things) has been reported in association with various pathologies, including herpes simplex encephalitis and semantic dementia. However, evidence is inconsistent regarding whether this effect exists in diseases progressively impacting diverse cortical regions, such as Alzheimer's disease (AD). Ceiling effects producing non-Gaussian distributions and poor control for confounds such as nuisance variables (e.g. familiarity) may contribute to this discrepancy. Fourteen AD patients were longitudinally studied examining category effects on three semantic tasks (picture naming, naming to description and word to picture matching) matched across domain on all known nuisance variables (NV). To address non-Gaussian distributions, we run bootstrap analyses to determine whether NV, semantic domain or control performance best predicted AD patient performance. Multiple hierarchical regression analyses revealed that, whilst NV accounted for most of the explained variance in patients in the three tasks, the influence of semantic domain was substantially lower. Individual logistic regression demonstrated a significant category effect in only a few patients and healthy controls. No significant qualitative changes were observed in patients over time. Our results confirm the importance of NVs as predictors of AD patient performance, suggesting that the role of semantic domain is not a useful predictor of the progressive deterioration in AD. Copyright © 2011 Elsevier Inc. All rights reserved.

Between-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure–flow relation: The CARNet study

PubMed Central

Meel-van den Abeelen, Aisha S.S.; Simpson, David M.; Wang, Lotte J.Y.; Slump, Cornelis H.; Zhang, Rong; Tarumi, Takashi; Rickards, Caroline A.; Payne, Stephen; Mitsis, Georgios D.; Kostoglou, Kyriaki; Marmarelis, Vasilis; Shin, Dae; Tzeng, Yu-Chieh; Ainslie, Philip N.; Gommer, Erik; Müller, Martin; Dorado, Alexander C.; Smielewski, Peter; Yelicich, Bernardo; Puppo, Corina; Liu, Xiuyun; Czosnyka, Marek; Wang, Cheng-Yen; Novak, Vera; Panerai, Ronney B.; Claassen, Jurgen A.H.R.

2014-01-01

Transfer function analysis (TFA) is a frequently used method to assess dynamic cerebral autoregulation (CA) using spontaneous oscillations in blood pressure (BP) and cerebral blood flow velocity (CBFV). However, controversies and variations exist in how research groups utilise TFA, causing high variability in interpretation. The objective of this study was to evaluate between-centre variability in TFA outcome metrics. 15 centres analysed the same 70 BP and CBFV datasets from healthy subjects (n = 50 rest; n = 20 during hypercapnia); 10 additional datasets were computer-generated. Each centre used their in-house TFA methods; however, certain parameters were specified to reduce a priori between-centre variability. Hypercapnia was used to assess discriminatory performance and synthetic data to evaluate effects of parameter settings. Results were analysed using the Mann–Whitney test and logistic regression. A large non-homogeneous variation was found in TFA outcome metrics between the centres. Logistic regression demonstrated that 11 centres were able to distinguish between normal and impaired CA with an AUC > 0.85. Further analysis identified TFA settings that are associated with large variation in outcome measures. These results indicate the need for standardisation of TFA settings in order to reduce between-centre variability and to allow accurate comparison between studies. Suggestions on optimal signal processing methods are proposed. PMID:24725709

Soccer and sexual health education: a promising approach for reducing adolescent births in Haiti.

PubMed

Kaplan, Kathryn C; Lewis, Judy; Gebrian, Bette; Theall, Katherine

2015-05-01

To explore the effect of an innovative, integrative program in female sexual reproductive health (SRH) and soccer (or fútbol, in Haitian Creole) in rural Haiti by measuring the rate of births among program participants 15-19 years old and their nonparticipant peers. A retrospective cohort study using 2006-2009 data from the computerized data-tracking system of the Haitian Health Foundation (HHF), a U.S.-based nongovernmental organization serving urban and rural populations in Haiti, was used to assess births among girls 15-19 years old who participated in HHF's GenNext program, a combination education-soccer program for youth, based on SRH classes HHF nurses and community workers had been conducting in Haiti for mothers, fathers, and youth; girl-centered health screenings; and an all-female summer soccer league, during 2006-2009 (n = 4 251). Bivariate and multiple logistic regression analyses were carried out to assess differences in the rate of births among program participants according to their level of participation (SRH component only ("EDU") versus both the SRH and soccer components ("SO") compared to their village peers who did not participate. Hazard ratios (HRs) of birth rates were estimated using Cox regression analysis of childbearing data for the three different groups. In the multiple logistic regression analysis, only the girls in the "EDU" group had significantly fewer births than the nonparticipants after adjusting for confounders (odds ratio = 0.535; 95% confidence interval (CI) = 0.304, 0.940). The Cox regression analysis demonstrated that those in the EDU group (HR = 0.893; 95% CI = 0.802, 0.994) and to a greater degree those in the SO group (HR = 0.631; 95% CI = 0.558, 0.714) were significantly protected against childbearing between the ages of 15 and 19 years. HHF's GenNext program demonstrates the effectiveness of utilizing nurse educators, community mobilization, and youth participation in sports, education, and structured youth groups to promote and sustain health for adolescent girls and young women.

Drusen regression is associated with local changes in fundus autofluorescence in intermediate age-related macular degeneration.

PubMed

Toy, Brian C; Krishnadev, Nupura; Indaram, Maanasa; Cunningham, Denise; Cukras, Catherine A; Chew, Emily Y; Wong, Wai T

2013-09-01

To investigate the association of spontaneous drusen regression in intermediate age-related macular degeneration (AMD) with changes on fundus photography and fundus autofluorescence (FAF) imaging. Prospective observational case series. Fundus images from 58 eyes (in 58 patients) with intermediate AMD and large drusen were assessed over 2 years for areas of drusen regression that exceeded the area of circle C1 (diameter 125 μm; Age-Related Eye Disease Study grading protocol). Manual segmentation and computer-based image analysis were used to detect and delineate areas of drusen regression. Delineated regions were graded as to their appearance on fundus photographs and FAF images, and changes in FAF signal were graded manually and quantitated using automated image analysis. Drusen regression was detected in approximately half of study eyes using manual (48%) and computer-assisted (50%) techniques. At year-2, the clinical appearance of areas of drusen regression on fundus photography was mostly unremarkable, with a majority of eyes (71%) demonstrating no detectable clinical abnormalities, and the remainder (29%) showing minor pigmentary changes. However, drusen regression areas were associated with local changes in FAF that were significantly more prominent than changes on fundus photography. A majority of eyes (64%-66%) demonstrated a predominant decrease in overall FAF signal, while 14%-21% of eyes demonstrated a predominant increase in overall FAF signal. FAF imaging demonstrated that drusen regression in intermediate AMD was often accompanied by changes in local autofluorescence signal. Drusen regression may be associated with concurrent structural and physiologic changes in the outer retina. Published by Elsevier Inc.

CADDIS Volume 4. Data Analysis: Basic Analyses

EPA Pesticide Factsheets

Use of statistical tests to determine if an observation is outside the normal range of expected values. Details of CART, regression analysis, use of quantile regression analysis, CART in causal analysis, simplifying or pruning resulting trees.

Gender Differences in Relationship Between Resilience and Big Five Personality Traits in Japanese Adolescents.

PubMed

Iimura, Shuhei; Taku, Kanako

2017-01-01

Prior work has indicated that female adolescents mature more quickly than males with regard to the various personality dimensions. From the developmental perspectives, this study aimed to explore gender differences in the relationships between resilience and the Big Five personality traits in Japanese adolescents. Middle school students ( N = 310, 155 females, age range = 14-15 years) participated in an online survey. The results demonstrated that females had higher Conscientiousness than males. Stepwise regression analyses indicated that Neuroticism was the most influential predictor of resilience in females, whereas Extraversion was the most important predictor in males. Multigroup path analysis demonstrated that the effect of Neuroticism on resilience was greater for females; however, the effects of all other variables did not differ across genders. Considering gender differences is important to understand the relationship between resilience and the Big Five dimensions among adolescents.

The rise of global warming skepticism: exploring affective image associations in the United States over time.

PubMed

Smith, Nicholas; Leiserowitz, Anthony

2012-06-01

This article explores how affective image associations to global warming have changed over time. Four nationally representative surveys of the American public were conducted between 2002 and 2010 to assess public global warming risk perceptions, policy preferences, and behavior. Affective images (positive or negative feelings and cognitive representations) were collected and content analyzed. The results demonstrate a large increase in "naysayer" associations, indicating extreme skepticism about the issue of climate change. Multiple regression analyses found that holistic affect and "naysayer" associations were more significant predictors of global warming risk perceptions than cultural worldviews or sociodemographic variables, including political party and ideology. The results demonstrate the important role affective imagery plays in judgment and decision-making processes, how these variables change over time, and how global warming is currently perceived by the American public. © 2012 Society for Risk Analysis.

Authenticity and Relationship Satisfaction: Two Distinct Ways of Directing Power to Self-Esteem.

PubMed

Wang, Yi Nan

2015-01-01

Possessing power contributes to high self-esteem, but how power enhances self-esteem is still unknown. As power is associated with both self-oriented goals and social-responsibility goals, we proposed that power predicts self-esteem through two positive personal and interpersonal results: authenticity and relationship satisfaction. Three studies were carried out with a total of 505 Chinese participants, including college students and adults, who completed surveys that assessed personal power, self-esteem, authenticity, relationship satisfaction, communal orientation, and social desirability. Hierarchical multiple regression analyses demonstrated that power, authenticity, and relationship satisfaction each uniquely contributed to self-esteem. More importantly, multiple mediation analysis showed that authenticity and relationship satisfaction both mediated the effects of power on self-esteem, even when controlling for participants' communal orientation and social desirability. Our findings demonstrate that authenticity and relationship satisfaction represent two key mechanisms by which power is associated with self-esteem.

Authenticity and Relationship Satisfaction: Two Distinct Ways of Directing Power to Self-Esteem

PubMed Central

Wang, Yi Nan

2015-01-01

Possessing power contributes to high self-esteem, but how power enhances self-esteem is still unknown. As power is associated with both self-oriented goals and social-responsibility goals, we proposed that power predicts self-esteem through two positive personal and interpersonal results: authenticity and relationship satisfaction. Three studies were carried out with a total of 505 Chinese participants, including college students and adults, who completed surveys that assessed personal power, self-esteem, authenticity, relationship satisfaction, communal orientation, and social desirability. Hierarchical multiple regression analyses demonstrated that power, authenticity, and relationship satisfaction each uniquely contributed to self-esteem. More importantly, multiple mediation analysis showed that authenticity and relationship satisfaction both mediated the effects of power on self-esteem, even when controlling for participants’ communal orientation and social desirability. Our findings demonstrate that authenticity and relationship satisfaction represent two key mechanisms by which power is associated with self-esteem. PMID:26720814

Motor Unit Interpulse Intervals During High Force Contractions.

PubMed

Stock, Matt S; Thompson, Brennan J

2016-01-01

We examined the means, medians, and variability for motor-unit interpulse intervals (IPIs) during voluntary, high force contractions. Eight men (mean age = 22 years) attempted to perform isometric contractions at 90% of their maximal voluntary contraction force while bipolar surface electromyographic (EMG) signals were detected from the vastus lateralis and vastus medialis muscles. Surface EMG signal decomposition was used to determine the recruitment thresholds and IPIs of motor units that demonstrated accuracy levels ≥ 96.0%. Motor units with high recruitment thresholds demonstrated longer mean IPIs, but the coefficients of variation were similar across all recruitment thresholds. Polynomial regression analyses indicated that for both muscles, the relationship between the means and standard deviations of the IPIs was linear. The majority of IPI histograms were positively skewed. Although low-threshold motor units were associated with shorter IPIs, the variability among motor units with differing recruitment thresholds was comparable.

Fragile--Handle with Care: Regression Analyses That Include Categorical Data.

ERIC Educational Resources Information Center

Brown, Diane Peacock

In education and the social sciences, problems of interest to researchers and users of research often involve variables that do not meet the assumptions of regression in the area of an equal interval scale relative to a zero point. Various coding schemes exist that allow the use of regression while still answering the researcher's questions of…

Poor sleep moderates the relationship between daytime napping and inflammation in Black and White men.

PubMed

Jakubowski, Karen P; Boylan, Jennifer M; Cundiff, Jenny M; Matthews, Karen A

2017-10-01

To test whether napping was associated with 2 inflammatory markers with known relationships to cardiovascular disease: high-sensitivity C-reactive protein (hsCRP) and interleukin-6 (IL-6). Because IL-6 is known to impact central inflammatory processes that relate to sleep regulation, including subjective fatigue, we tested whether this relationship was moderated by sleep duration, sleep efficiency, and self-reported sleep quality. Cross-sectional. A community sample of Black and White men (N=253) completed a week of actigraphy and diary measures of sleep and napping and provided a fasting blood sample. Napping was measured as the proportion of days with at least 30 minutes napped and the average minutes napped per day. Linear regressions adjusted for race, socioeconomic status, employment, body mass index, smoking, medications that affect sleep or inflammation, working the nightshift, and day-sleeping status, followed by interaction terms between napping and sleep duration, efficiency, and quality, respectively. There were no significant main effects of actigraphy- or diary-measured napping on IL-6 or hsCRP. Moderation analyses indicated elevated IL-6 values among men who napped more days (by actigraphy) and demonstrated short sleep duration (P=.03). Moderation analyses also indicated elevated IL-6 among men who demonstrated greater average minutes napped (by actigraphy) and short sleep duration (P<.001), low efficiency (P=.03), and poor quality (P=.03). Moderation analyses involving diary napping or hsCRP were not significant. Actigraphy-assessed daytime napping is related to higher IL-6 in men who demonstrate worse sleep characteristics. Daytime napping may pose additional risk for inflammation beyond the known risk conferred by short sleep. Copyright © 2017 National Sleep Foundation. Published by Elsevier Inc. All rights reserved.

Integrated design and manufacturing for the high speed civil transport (a combined aerodynamics/propulsion optimization study)

NASA Technical Reports Server (NTRS)

Baecher, Juergen; Bandte, Oliver; DeLaurentis, Dan; Lewis, Kemper; Sicilia, Jose; Soboleski, Craig

1995-01-01

This report documents the efforts of a Georgia Tech High Speed Civil Transport (HSCT) aerospace student design team in completing a design methodology demonstration under NASA's Advanced Design Program (ADP). Aerodynamic and propulsion analyses are integrated into the synthesis code FLOPS in order to improve its prediction accuracy. Executing the integrated product and process development (IPPD) methodology proposed at the Aerospace Systems Design Laboratory (ASDL), an improved sizing process is described followed by a combined aero-propulsion optimization, where the objective function, average yield per revenue passenger mile ($/RPM), is constrained by flight stability, noise, approach speed, and field length restrictions. Primary goals include successful demonstration of the application of the response surface methodolgy (RSM) to parameter design, introduction to higher fidelity disciplinary analysis than normally feasible at the conceptual and early preliminary level, and investigations of relationships between aerodynamic and propulsion design parameters and their effect on the objective function, $/RPM. A unique approach to aircraft synthesis is developed in which statistical methods, specifically design of experiments and the RSM, are used to more efficiently search the design space for optimum configurations. In particular, two uses of these techniques are demonstrated. First, response model equations are formed which represent complex analysis in the form of a regression polynomial. Next, a second regression equation is constructed, not for modeling purposes, but instead for the purpose of optimization at the system level. Such an optimization problem with the given tools normally would be difficult due to the need for hard connections between the various complex codes involved. The statistical methodology presents an alternative and is demonstrated via an example of aerodynamic modeling and planform optimization for a HSCT.

Parental report of the early development of children with regressive autism: the delays-plus-regression phenotype.

PubMed

Ozonoff, Sally; Williams, Brenda J; Landa, Rebecca

2005-12-01

Most children with autism demonstrate developmental abnormalities in their first year, whereas others display regression after mostly normal development. Few studies have examined the early development of the latter group. This study developed a retrospective measure, the Early Development Questionnaire (EDQ), to collect specific, parent-reported information about development in the first 18 months. Based on their EDQ scores, 60 children with autism between the ages of 3 and 9 were divided into three groups: an early onset group (n = 29), a definite regression group (n = 23), and a heterogeneous mixed group (n = 8). Significant differences in early social development were found between the early onset and regression groups. However, over 50 percent of the children who experienced a regression demonstrated some early social deficits during the first year of life, long before regression and the apparent onset of autism. This group, tentatively labeled 'delays-plus-regression', deserves further study.

LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis.

PubMed

Zheng, Jie; Erzurumluoglu, A Mesut; Elsworth, Benjamin L; Kemp, John P; Howe, Laurence; Haycock, Philip C; Hemani, Gibran; Tansey, Katherine; Laurin, Charles; Pourcain, Beate St; Warrington, Nicole M; Finucane, Hilary K; Price, Alkes L; Bulik-Sullivan, Brendan K; Anttila, Verneri; Paternoster, Lavinia; Gaunt, Tom R; Evans, David M; Neale, Benjamin M

2017-01-15

LD score regression is a reliable and efficient method of using genome-wide association study (GWAS) summary-level results data to estimate the SNP heritability of complex traits and diseases, partition this heritability into functional categories, and estimate the genetic correlation between different phenotypes. Because the method relies on summary level results data, LD score regression is computationally tractable even for very large sample sizes. However, publicly available GWAS summary-level data are typically stored in different databases and have different formats, making it difficult to apply LD score regression to estimate genetic correlations across many different traits simultaneously. In this manuscript, we describe LD Hub - a centralized database of summary-level GWAS results for 173 diseases/traits from different publicly available resources/consortia and a web interface that automates the LD score regression analysis pipeline. To demonstrate functionality and validate our software, we replicated previously reported LD score regression analyses of 49 traits/diseases using LD Hub; and estimated SNP heritability and the genetic correlation across the different phenotypes. We also present new results obtained by uploading a recent atopic dermatitis GWAS meta-analysis to examine the genetic correlation between the condition and other potentially related traits. In response to the growing availability of publicly accessible GWAS summary-level results data, our database and the accompanying web interface will ensure maximal uptake of the LD score regression methodology, provide a useful database for the public dissemination of GWAS results, and provide a method for easily screening hundreds of traits for overlapping genetic aetiologies. The web interface and instructions for using LD Hub are available at http://ldsc.broadinstitute.org/ CONTACT: jie.zheng@bristol.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Statistical relations among earthquake magnitude, surface rupture length, and surface fault displacement

USGS Publications Warehouse

Bonilla, M.G.; Mark, R.K.; Lienkaemper, J.J.

1984-01-01

In order to refine correlations of surface-wave magnitude, fault rupture length at the ground surface, and fault displacement at the surface by including the uncertainties in these variables, the existing data were critically reviewed and a new data base was compiled. Earthquake magnitudes were redetermined as necessary to make them as consistent as possible with the Gutenberg methods and results, which necessarily make up much of the data base. Measurement errors were estimated for the three variables for 58 moderate to large shallow-focus earthquakes. Regression analyses were then made utilizing the estimated measurement errors. The regression analysis demonstrates that the relations among the variables magnitude, length, and displacement are stochastic in nature. The stochastic variance, introduced in part by incomplete surface expression of seismogenic faulting, variation in shear modulus, and regional factors, dominates the estimated measurement errors. Thus, it is appropriate to use ordinary least squares for the regression models, rather than regression models based upon an underlying deterministic relation with the variance resulting from measurement errors. Significant differences exist in correlations of certain combinations of length, displacement, and magnitude when events are qrouped by fault type or by region, including attenuation regions delineated by Evernden and others. Subdivision of the data results in too few data for some fault types and regions, and for these only regressions using all of the data as a group are reported. Estimates of the magnitude and the standard deviation of the magnitude of a prehistoric or future earthquake associated with a fault can be made by correlating M with the logarithms of rupture length, fault displacement, or the product of length and displacement. Fault rupture area could be reliably estimated for about 20 of the events in the data set. Regression of MS on rupture area did not result in a marked improvement over regressions that did not involve rupture area. Because no subduction-zone earthquakes are included in this study, the reported results do not apply to such zones.

Spatial quantile regression using INLA with applications to childhood overweight in Malawi.

PubMed

Mtambo, Owen P L; Masangwi, Salule J; Kazembe, Lawrence N M

2015-04-01

Analyses of childhood overweight have mainly used mean regression. However, using quantile regression is more appropriate as it provides flexibility to analyse the determinants of overweight corresponding to quantiles of interest. The main objective of this study was to fit a Bayesian additive quantile regression model with structured spatial effects for childhood overweight in Malawi using the 2010 Malawi DHS data. Inference was fully Bayesian using R-INLA package. The significant determinants of childhood overweight ranged from socio-demographic factors such as type of residence to child and maternal factors such as child age and maternal BMI. We observed significant positive structured spatial effects on childhood overweight in some districts of Malawi. We recommended that the childhood malnutrition policy makers should consider timely interventions based on risk factors as identified in this paper including spatial targets of interventions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Variable selection and model choice in geoadditive regression models.

PubMed

Kneib, Thomas; Hothorn, Torsten; Tutz, Gerhard

2009-06-01

Model choice and variable selection are issues of major concern in practical regression analyses, arising in many biometric applications such as habitat suitability analyses, where the aim is to identify the influence of potentially many environmental conditions on certain species. We describe regression models for breeding bird communities that facilitate both model choice and variable selection, by a boosting algorithm that works within a class of geoadditive regression models comprising spatial effects, nonparametric effects of continuous covariates, interaction surfaces, and varying coefficients. The major modeling components are penalized splines and their bivariate tensor product extensions. All smooth model terms are represented as the sum of a parametric component and a smooth component with one degree of freedom to obtain a fair comparison between the model terms. A generic representation of the geoadditive model allows us to devise a general boosting algorithm that automatically performs model choice and variable selection.

Application of Regression-Discontinuity Analysis in Pharmaceutical Health Services Research

PubMed Central

Zuckerman, Ilene H; Lee, Euni; Wutoh, Anthony K; Xue, Zhenyi; Stuart, Bruce

2006-01-01

Objective To demonstrate how a relatively underused design, regression-discontinuity (RD), can provide robust estimates of intervention effects when stronger designs are impossible to implement. Data Sources/Study Setting Administrative claims from a Mid-Atlantic state Medicaid program were used to evaluate the effectiveness of an educational drug utilization review intervention. Study Design Quasi-experimental design. Data Collection/Extraction Methods A drug utilization review study was conducted to evaluate a letter intervention to physicians treating Medicaid children with potentially excessive use of short-acting β2-agonist inhalers (SAB). The outcome measure is change in seasonally-adjusted SAB use 5 months pre- and postintervention. To determine if the intervention reduced monthly SAB utilization, results from an RD analysis are compared to findings from a pretest–posttest design using repeated-measure ANOVA. Principal Findings Both analyses indicated that the intervention significantly reduced SAB use among the high users. Average monthly SAB use declined by 0.9 canisters per month (p<.001) according to the repeated-measure ANOVA and by 0.2 canisters per month (p<.001) from RD analysis. Conclusions Regression-discontinuity design is a useful quasi-experimental methodology that has significant advantages in internal validity compared to other pre–post designs when assessing interventions in which subjects' assignment is based on cutoff scores for a critical variable. PMID:16584464

Linking land cover and water quality in New York City's water supply watersheds.

PubMed

Mehaffey, M H; Nash, M S; Wade, T G; Ebert, D W; Jones, K B; Rager, A

2005-08-01

The Catskill/Delaware reservoirs supply 90% of New York City's drinking water. The City has implemented a series of watershed protection measures, including land acquisition, aimed at preserving water quality in the Catskill/Delaware watersheds. The objective of this study was to examine how relationships between landscape and surface water measurements change between years. Thirty-two drainage areas delineated from surface water sample points (total nitrogen, total phosphorus, and fecal coliform bacteria concentrations) were used in step-wise regression analyses to test landscape and surface-water quality relationships. Two measurements of land use, percent agriculture and percent urban development, were positively related to water quality and consistently present in all regression models. Together these two land uses explained 25 to 75% of the regression model variation. However, the contribution of agriculture to water quality condition showed a decreasing trend with time as overall agricultural land cover decreased. Results from this study demonstrate that relationships between land cover and surface water concentrations of total nitrogen, total phosphorus, and fecal coliform bacteria counts over a large area can be evaluated using a relatively simple geographic information system method. Land managers may find this method useful for targeting resources in relation to a particular water quality concern, focusing best management efforts, and maximizing benefits to water quality with minimal costs.

Multicollinearity in spatial genetics: separating the wheat from the chaff using commonality analyses.

PubMed

Prunier, J G; Colyn, M; Legendre, X; Nimon, K F; Flamand, M C

2015-01-01

Direct gradient analyses in spatial genetics provide unique opportunities to describe the inherent complexity of genetic variation in wildlife species and are the object of many methodological developments. However, multicollinearity among explanatory variables is a systemic issue in multivariate regression analyses and is likely to cause serious difficulties in properly interpreting results of direct gradient analyses, with the risk of erroneous conclusions, misdirected research and inefficient or counterproductive conservation measures. Using simulated data sets along with linear and logistic regressions on distance matrices, we illustrate how commonality analysis (CA), a detailed variance-partitioning procedure that was recently introduced in the field of ecology, can be used to deal with nonindependence among spatial predictors. By decomposing model fit indices into unique and common (or shared) variance components, CA allows identifying the location and magnitude of multicollinearity, revealing spurious correlations and thus thoroughly improving the interpretation of multivariate regressions. Despite a few inherent limitations, especially in the case of resistance model optimization, this review highlights the great potential of CA to account for complex multicollinearity patterns in spatial genetics and identifies future applications and lines of research. We strongly urge spatial geneticists to systematically investigate commonalities when performing direct gradient analyses. © 2014 John Wiley & Sons Ltd.

Comparison of athlete-coach perceptions of internal and external load markers for elite junior tennis training.

PubMed

Murphy, Alistair P; Duffield, Rob; Kellett, Aaron; Reid, Machar

2014-09-01

To investigate the discrepancy between coach and athlete perceptions of internal load and notational analysis of external load in elite junior tennis. Fourteen elite junior tennis players and 6 international coaches were recruited. Ratings of perceived exertion (RPEs) were recorded for individual drills and whole sessions, along with a rating of mental exertion, coach rating of intended session exertion, and athlete heart rate (HR). Furthermore, total stroke count and unforced-error count were notated using video coding after each session, alongside coach and athlete estimations of shots and errors made. Finally, regression analyses explained the variance in the criterion variables of athlete and coach RPE. Repeated-measures analyses of variance and interclass correlation coefficients revealed that coaches significantly (P < .01) underestimated athlete session RPE, with only moderate correlation (r = .59) demonstrated between coach and athlete. However, athlete drill RPE (P = .14; r = .71) and mental exertion (P = .44; r = .68) were comparable and substantially correlated. No significant differences in estimated stroke count were evident between athlete and coach (P = .21), athlete notational analysis (P = .06), or coach notational analysis (P = .49). Coaches estimated significantly greater unforced errors than either athletes or notational analysis (P < .01). Regression analyses found that 54.5% of variance in coach RPE was explained by intended session exertion and coach drill RPE, while drill RPE and peak HR explained 45.3% of the variance in athlete session RPE. Coaches misinterpreted session RPE but not drill RPE, while inaccurately monitoring error counts. Improved understanding of external- and internal-load monitoring may help coach-athlete relationships in individual sports like tennis avoid maladaptive training.

External validation of the diffuse intrinsic pontine glioma survival prediction model: a collaborative report from the International DIPG Registry and the SIOPE DIPG Registry.

PubMed

Veldhuijzen van Zanten, Sophie E M; Lane, Adam; Heymans, Martijn W; Baugh, Joshua; Chaney, Brooklyn; Hoffman, Lindsey M; Doughman, Renee; Jansen, Marc H A; Sanchez, Esther; Vandertop, William P; Kaspers, Gertjan J L; van Vuurden, Dannis G; Fouladi, Maryam; Jones, Blaise V; Leach, James

2017-08-01

We aimed to perform external validation of the recently developed survival prediction model for diffuse intrinsic pontine glioma (DIPG), and discuss its utility. The DIPG survival prediction model was developed in a cohort of patients from the Netherlands, United Kingdom and Germany, registered in the SIOPE DIPG Registry, and includes age <3 years, longer symptom duration and receipt of chemotherapy as favorable predictors, and presence of ring-enhancement on MRI as unfavorable predictor. Model performance was evaluated by analyzing the discrimination and calibration abilities. External validation was performed using an unselected cohort from the International DIPG Registry, including patients from United States, Canada, Australia and New Zealand. Basic comparison with the results of the original study was performed using descriptive statistics, and univariate- and multivariable regression analyses in the validation cohort. External validation was assessed following a variety of analyses described previously. Baseline patient characteristics and results from the regression analyses were largely comparable. Kaplan-Meier curves of the validation cohort reproduced separated groups of standard (n = 39), intermediate (n = 125), and high-risk (n = 78) patients. This discriminative ability was confirmed by similar values for the hazard ratios across these risk groups. The calibration curve in the validation cohort showed a symmetric underestimation of the predicted survival probabilities. In this external validation study, we demonstrate that the DIPG survival prediction model has acceptable cross-cohort calibration and is able to discriminate patients with short, average, and increased survival. We discuss how this clinico-radiological model may serve a useful role in current clinical practice.

DTI measures identify mild and moderate TBI cases among patients with complex health problems: A receiver operating characteristic analysis of U.S. veterans.

PubMed

Main, Keith L; Soman, Salil; Pestilli, Franco; Furst, Ansgar; Noda, Art; Hernandez, Beatriz; Kong, Jennifer; Cheng, Jauhtai; Fairchild, Jennifer K; Taylor, Joy; Yesavage, Jerome; Wesson Ashford, J; Kraemer, Helena; Adamson, Maheen M

2017-01-01

Standard MRI methods are often inadequate for identifying mild traumatic brain injury (TBI). Advances in diffusion tensor imaging now provide potential biomarkers of TBI among white matter fascicles (tracts). However, it is still unclear which tracts are most pertinent to TBI diagnosis. This study ranked fiber tracts on their ability to discriminate patients with and without TBI. We acquired diffusion tensor imaging data from military veterans admitted to a polytrauma clinic (Overall n  = 109; Age: M  = 47.2, SD  = 11.3; Male: 88%; TBI: 67%). TBI diagnosis was based on self-report and neurological examination. Fiber tractography analysis produced 20 fiber tracts per patient. Each tract yielded four clinically relevant measures (fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity). We applied receiver operating characteristic (ROC) analyses to identify the most diagnostic tract for each measure. The analyses produced an optimal cutpoint for each tract. We then used kappa coefficients to rate the agreement of each cutpoint with the neurologist's diagnosis. The tract with the highest kappa was most diagnostic. As a check on the ROC results, we performed a stepwise logistic regression on each measure using all 20 tracts as predictors. We also bootstrapped the ROC analyses to compute the 95% confidence intervals for sensitivity, specificity, and the highest kappa coefficients. The ROC analyses identified two fiber tracts as most diagnostic of TBI: the left cingulum (LCG) and the left inferior fronto-occipital fasciculus (LIF). Like ROC, logistic regression identified LCG as most predictive for the FA measure but identified the right anterior thalamic tract (RAT) for the MD, RD, and AD measures. These findings are potentially relevant to the development of TBI biomarkers. Our methods also demonstrate how ROC analysis may be used to identify clinically relevant variables in the TBI population.

Longitudinal Evaluation of the Importance of Homework Assignment Completion for the Academic Performance of Middle School Students with ADHD

PubMed Central

Langberg, Joshua M.; Dvorsky, Melissa R.; Molitor, Stephen J.; Bourchtein, Elizaveta; Eddy, Laura D.; Smith, Zoe; Schultz, Brandon K.; Evans, Steven W.

2016-01-01

The primary goal of this study was to longitudinally evaluate the homework assignment completion patterns of middle school age adolescents with ADHD, their associations with academic performance, and malleable predictors of homework assignment completion. Analyses were conducted on a sample of 104 middle school students comprehensively diagnosed with ADHD and followed for 18 months. Multiple teachers for each student provided information about the percentage of homework assignments turned in at five separate timepoints and school grades were collected quarterly. Results showed that agreement between teachers with respect to students’ assignment completion was high, with an intraclass correlation of .879 at baseline. Students with ADHD were turning in an average of 12% fewer assignments each academic quarter in comparison to teacher-reported classroom averages. Regression analyses revealed a robust association between the percentage of assignments turned in at baseline and school grades 18 months later, even after controlling for baseline grades, achievement (reading and math), intelligence, family income, and race. Cross-lag analyses demonstrated that the association between assignment completion and grades was reciprocal, with assignment completion negatively impacting grades and low grades in turn being associated with decreased future homework completion. Parent ratings of homework materials management abilities at baseline significantly predicted the percentage of assignments turned in as reported by teachers 18 months later. These findings demonstrate that homework assignment completion problems are persistent across time and an important intervention target for adolescents with ADHD. PMID:26931065

A Comparison between the Use of Beta Weights and Structure Coefficients in Interpreting Regression Results

ERIC Educational Resources Information Center

Tong, Fuhui

2006-01-01

Background: An extensive body of researches has favored the use of regression over other parametric analyses that are based on OVA. In case of noteworthy regression results, researchers tend to explore magnitude of beta weights for the respective predictors. Purpose: The purpose of this paper is to examine both beta weights and structure…

Machine learning reveals orbital interaction in materials

NASA Astrophysics Data System (ADS)

Lam Pham, Tien; Kino, Hiori; Terakura, Kiyoyuki; Miyake, Takashi; Tsuda, Koji; Takigawa, Ichigaku; Chi Dam, Hieu

2017-12-01

We propose a novel representation of materials named an 'orbital-field matrix (OFM)', which is based on the distribution of valence shell electrons. We demonstrate that this new representation can be highly useful in mining material data. Experimental investigation shows that the formation energies of crystalline materials, atomization energies of molecular materials, and local magnetic moments of the constituent atoms in bimetal alloys of lanthanide metal and transition-metal can be predicted with high accuracy using the OFM. Knowledge regarding the role of the coordination numbers of the transition-metal and lanthanide elements in determining the local magnetic moments of the transition-metal sites can be acquired directly from decision tree regression analyses using the OFM.

Learning to be cruel?: exploring the onset and frequency of animal cruelty.

PubMed

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.

Social gradients in periodontal diseases among adolescents.

PubMed

López, Rodrigo; Fernández, Olaya; Baelum, Vibeke

2006-06-01

To investigate the association between socioeconomic position and periodontal diseases among adolescents. Data were obtained from 9203 Chilean high school students. Clinical examinations included direct recordings of clinical attachment level and the necrotizing ulcerative gingival lesions. Students answered a questionnaire on various dimensions of socioeconomic position. Seven periodontal outcomes were analyzed. Logistic regression analyses were used to identify socioeconomic variables associated with the periodontal outcomes. The occurrence of all periodontal outcomes investigated followed social gradients, and paternal income and parental education were the most influential variables. The study demonstrates the existence of significant social gradients in periodontal diseases already among adolescents. This is worrying, and indicates a new potential for further insight into the mechanisms of periodontal disease causation.

Relaxing the rule of ten events per variable in logistic and Cox regression.

PubMed

Vittinghoff, Eric; McCulloch, Charles E

2007-03-15

The rule of thumb that logistic and Cox models should be used with a minimum of 10 outcome events per predictor variable (EPV), based on two simulation studies, may be too conservative. The authors conducted a large simulation study of other influences on confidence interval coverage, type I error, relative bias, and other model performance measures. They found a range of circumstances in which coverage and bias were within acceptable levels despite less than 10 EPV, as well as other factors that were as influential as or more influential than EPV. They conclude that this rule can be relaxed, in particular for sensitivity analyses undertaken to demonstrate adequate control of confounding.

Retroillumination photography analysis enhances clinical definition of severe Fuchs Corneal Dystrophy

PubMed Central

Eghrari, Allen O.; Garrett, Brian S.; Mumtaz, Aisha A.; Edalati, Armand E.; Meadows, Danielle N.; McGlumphy, Elyse J.; Iliff, Benjamin W.; Gottsch, John D.

2015-01-01

Purpose Retroillumination photography analysis (RPA) provides objective assessment of the number and distribution of guttae in Fuchs Corneal Dystrophy. Here, we assess its correlation with clinical grading using slit-lamp biomicroscopy across varying levels of severity. Methods Retroillumination photographs were conducted of 95 affected corneas with slit-lamp flash photography after pupillary dilation. Individual guttae were counted manually and the position of individual points recorded. Clinical grading using the Krachmer scale was documented for each eye during examination, and regression analyses were performed to identify the strength of association with number of guttae. We assessed range at each stage of clinical grading, and utilized the Mann-Whitney U test to assess whether clinical grading levels demonstrated successively higher numbers of guttae. Results Krachmer score ranged from 1 to 5, with mean of 2.6. Mean numbers of guttae at each level of severity were 289 (1+), 999 (2+), 2669 (3+), 5474 (4+), and 7133 (5+). Each stage demonstrated significantly higher numbers of guttae than its preceding level except from 4+ to 5+ (p=0.30), consistent with the definition of 4+ as the highest level defined by presence of guttae. Higher levels of clinical grading were associated with larger ranges of guttae (p<0.01). A linear regression model resulted in a strong fit between RPA and Krachmer score (r=0.81). Conclusion In this largest study of RPA data and comparison with subjective clinical grading of FCD severity, RPA correlates strongly and demonstrates enhanced definition of severity at advanced stages of disease. PMID:26488628

Exchangeable Ions Are Responsible for the In Vitro Antibacterial Properties of Natural Clay Mixtures

PubMed Central

Otto, Caitlin C.; Haydel, Shelley E.

2013-01-01

We have identified a natural clay mixture that exhibits in vitro antibacterial activity against a broad spectrum of bacterial pathogens. We collected four samples from the same source and demonstrated through antibacterial susceptibility testing that these clay mixtures have markedly different antibacterial activity against Escherichia coli and methicillin-resistant Staphylococcus aureus (MRSA). Here, we used X-ray diffraction (XRD) and inductively coupled plasma – optical emission spectroscopy (ICP-OES) and – mass spectrometry (ICP-MS) to characterize the mineralogical and chemical features of the four clay mixture samples. XRD analyses of the clay mixtures revealed minor mineralogical differences between the four samples. However, ICP analyses demonstrated that the concentrations of many elements, Fe, Co, Cu, Ni, and Zn, in particular, vary greatly across the four clay mixture leachates. Supplementation of a non-antibacterial leachate containing lower concentrations of Fe, Co, Ni, Cu, and Zn to final ion concentrations and a pH equivalent to that of the antibacterial leachate generated antibacterial activity against E. coli and MRSA, confirming the role of these ions in the antibacterial clay mixture leachates. Speciation modeling revealed increased concentrations of soluble Cu2+ and Fe2+ in the antibacterial leachates, compared to the non-antibacterial leachates, suggesting these ionic species specifically are modulating the antibacterial activity of the leachates. Finally, linear regression analyses comparing the log10 reduction in bacterial viability to the concentration of individual ion species revealed positive correlations with Zn2+ and Cu2+ and antibacterial activity, a negative correlation with Fe3+, and no correlation with pH. Together, these analyses further indicate that the ion concentration of specific species (Fe2+, Cu2+, and Zn2+) are responsible for antibacterial activity and that killing activity is not solely attributed to pH. PMID:23691149

Ecologic regression analysis and the study of the influence of air quality on mortality.

PubMed Central

Selvin, S; Merrill, D; Wong, L; Sacks, S T

1984-01-01

This presentation focuses entirely on the use and evaluation of regression analysis applied to ecologic data as a method to study the effects of ambient air pollution on mortality rates. Using extensive national data on mortality, air quality and socio-economic status regression analyses are used to study the influence of air quality on mortality. The analytic methods and data are selected in such a way that direct comparisons can be made with other ecologic regression studies of mortality and air quality. Analyses are performed by use of two types of geographic areas, age-specific mortality of both males and females and three pollutants (total suspended particulates, sulfur dioxide and nitrogen dioxide). The overall results indicate no persuasive evidence exists of a link between air quality and general mortality levels. Additionally, a lack of consistency between the present results and previous published work is noted. Overall, it is concluded that linear regression analysis applied to nationally collected ecologic data cannot be used to usefully infer a causal relationship between air quality and mortality which is in direct contradiction to other major published studies. PMID:6734568

Application of Regulatory Focus Theory to Search Advertising.

PubMed

Mowle, Elyse N; Georgia, Emily J; Doss, Brian D; Updegraff, John A

The purpose of this paper is to test the utility of regulatory focus theory principles in a real-world setting; specifically, Internet hosted text advertisements. Effect of compatibility of the ad text with the regulatory focus of the consumer was examined. Advertisements were created using Google AdWords. Data were collected for the number of views and clicks each ad received. Effect of regulatory fit was measured using logistic regression. Logistic regression analyses demonstrated that there was a strong main effect for keyword, such that users were almost six times as likely to click on a promotion advertisement as a prevention advertisement, as well as a main effect for compatibility, such that users were twice as likely to click on an advertisement with content that was consistent with their keyword. Finally, there was a strong interaction of these two variables, such that the effect of consistent advertisements was stronger for promotion searches than for prevention searches. The effect of ad compatibility had medium to large effect sizes, suggesting that individuals' state may have more influence on advertising response than do individuals' traits (e.g. personality traits). Measurement of regulatory fit was limited by the constraints of Google AdWords. The results of this study provide a possible framework for ad creation for Internet advertisers. This paper is the first study to demonstrate the utility of regulatory focus theory in online advertising.

Integrative eQTL analysis of tumor and host omics data in individuals with bladder cancer.

PubMed

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.

The prospective role of defeat and entrapment in depression and anxiety: a 12-month longitudinal study.

PubMed

Griffiths, Alys Wyn; Wood, Alex M; Maltby, John; Taylor, Peter J; Tai, Sara

2014-04-30

The concepts of "defeat" (representing failed social struggle) and "entrapment" (representing an inability to escape from a situation) have emerged from the animal literature, providing insight into the health consequences of low social rank. Evolutionary models suggest that these constructs co-occur and can lead to the development of mental disorders, although there is limited empirical evidence supporting these predictions. Participants (N=172) were recruited from economically deprived areas in North England. Over half of participants (58%) met clinical cut-offs for depression and anxiety, therefore we conducted analyses to establish whether participant outcomes were dependent on baseline defeat and entrapment levels. Participants completed measures of defeat, entrapment, depression and anxiety at two time-points twelve months apart. Factor analysis demonstrated that defeat and entrapment were best defined as one factor, suggesting that the experiences co-occurred. Regression analyses demonstrated that changes in depression and anxiety between T1 and T2 were predicted from baseline levels of defeat and entrapment; however, changes in defeat and entrapment were also predicted from baseline depression and anxiety. There are implications for targeting perceptions of defeat and entrapment within psychological interventions for people experiencing anxiety and depression and screening individuals to identify those at risk of developing psychopathology. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Partners or Partners in Crime? The Relationship Between Criminal Associates and Criminogenic Thinking.

PubMed

Whited, William H; Wagar, Laura; Mandracchia, Jon T; Morgan, Robert D

2017-04-01

Meta-analyses examining the risk factors for recidivism have identified the importance of ties with criminal associates as well as thoughts and attitudes conducive to the continuance of criminal behavior (e.g., criminogenic thinking). Criminologists have theorized that a direct relationship exists between the association with criminal peers and the development of criminogenic thinking. The present study empirically explored the relationship between criminal associates and criminogenic thinking in 595 adult male inmates in the United States. It was hypothesized that the proportion of free time spent with and number of criminal associates would be associated with criminogenic thinking, as measured by two self-report instruments, the Measure of Offender Thinking Styles-Revised (MOTS-R) and the Psychological Inventory of Criminal Thinking Styles (PICTS). Hierarchal linear regression analyses demonstrated that the proportion of free time spent with criminal associates statistically predicted criminogenic thinking when controlling for demographic variables. The implications of these findings on correctional practice (including assessment and intervention) as well as future research are discussed.

Impact of Non-Suicidal Self-Injury Scale: Initial Psychometric Validation

PubMed Central

Burke, Taylor A.; Ammerman, Brooke A.; Hamilton, Jessica L.; Alloy, Lauren B.

2017-01-01

The current study examined the psychometric properties of the Impact of Non-Suicidal Self-Injury Scale (INS), a scale developed to assess the social, behavioral, and emotional consequences of engaging in non-suicidal self-injury (NSSI). University students (N=128) who endorsed a history of NSSI were administered the INS, as well as measures of hypothesized convergent and divergent validity. Results suggested that the INS is best conceptualized as a one-factor scale, and internal consistency analyses indicated excellent reliability. The INS was significantly correlated with well-known measures of NSSI severity (i.e., NSSI frequency, NSSI recency), and measures of suicide attempt history and emotional reactivity. Logistic regression analyses indicated that the INS contributed unique variance to the prediction of physical disfigurement (i.e., NSSI scarring) and clinically significant social anxiety, even after taking into account NSSI frequency. Furthermore, the INS demonstrated divergent validity. Implications for research on NSSI disorder and clinical practice are discussed. PMID:28824214

The role of early language abilities on math skills among Chinese children.

PubMed

Zhang, Juan; Fan, Xitao; Cheung, Sum Kwing; Meng, Yaxuan; Cai, Zhihui; Hu, Bi Ying

2017-01-01

The present study investigated the role of early language abilities in the development of math skills among Chinese K-3 students. About 2000 children in China, who were on average aged 6 years, were assessed for both informal math (e.g., basic number concepts such as counting objects) and formal math (calculations including addition and subtraction) skills, language abilities and nonverbal intelligence. Correlation analysis showed that language abilities were more strongly associated with informal than formal math skills, and regression analyses revealed that children's language abilities could uniquely predict both informal and formal math skills with age, gender, and nonverbal intelligence controlled. Mediation analyses demonstrated that the relationship between children's language abilities and formal math skills was partially mediated by informal math skills. The current findings indicate 1) Children's language abilities are of strong predictive values for both informal and formal math skills; 2) Language abilities impacts formal math skills partially through the mediation of informal math skills.

The role of early language abilities on math skills among Chinese children

PubMed Central

Fan, Xitao; Cheung, Sum Kwing; Cai, Zhihui; Hu, Bi Ying

2017-01-01

Background The present study investigated the role of early language abilities in the development of math skills among Chinese K-3 students. About 2000 children in China, who were on average aged 6 years, were assessed for both informal math (e.g., basic number concepts such as counting objects) and formal math (calculations including addition and subtraction) skills, language abilities and nonverbal intelligence. Methodology Correlation analysis showed that language abilities were more strongly associated with informal than formal math skills, and regression analyses revealed that children’s language abilities could uniquely predict both informal and formal math skills with age, gender, and nonverbal intelligence controlled. Mediation analyses demonstrated that the relationship between children’s language abilities and formal math skills was partially mediated by informal math skills. Results The current findings indicate 1) Children’s language abilities are of strong predictive values for both informal and formal math skills; 2) Language abilities impacts formal math skills partially through the mediation of informal math skills. PMID:28749950

Executive and motivational inhibition: associations with self-report measures related to inhibition.

PubMed

Shuster, Jill; Toplak, Maggie E

2009-06-01

Inhibition involves the withholding or suppressing of attention or responses to irrelevant or distracting stimuli. We examined the relationship between five experimental tasks of inhibition, represented by two measures of executive, intentional control inhibition and three measures of motivational inhibition characterized by bottom-up interruption of affective and reward/punishment sensitive mechanisms. Associations between these experimental tasks with three self-report measures related to inhibition were also examined. Correlational analyses indicated a small but significant association between the measures in the executive domain (stop task and Stroop task), but a lack of associations between the measures in the motivational domain (emotional Stroop task, a card playing task involving rewards and punishments, and a gambling task). Both measures of executive and motivational inhibition entered as significant predictors on the self-report measures related to inhibition in simultaneous regression analyses, but not consistently in the expected direction. The results suggest that inhibition is not a unitary construct, and demonstrate an association between experimental measures of inhibition and self-report measures related to inhibition.

The SPAIC-11 and SPAICP-11: Two brief child- and parent-rated measures of social anxiety.

PubMed

Bunnell, Brian E; Beidel, Deborah C; Liu, Liwen; Joseph, Dana L; Higa-McMillan, Charmaine

2015-12-01

The Social Phobia and Anxiety Inventory for Children-11 (SPAIC-11) and Social Phobia and Anxiety Inventory for Children's Parents-11 (SPAICP-11) were developed as brief versions of the Social Phobia and Anxiety Inventory--Child and Parent Versions via item response theory (IRT) using child and parent reports of social anxiety. A sample of 496 children was analyzed using IRT analyses, revealing 11 items that exhibit measurement equivalence across parent and child reports. Descriptive and psychometric data are provided for the child, parent, and combined total scores. Discriminant validity was demonstrated using logistic regression and receiver operating characteristic curve analyses. The SPAIC-11 and SPAICP-11 are psychometrically sound measures that are able to measure social anxiety invariantly across children and their parents. These brief measures which include combined parent and child perception of the child's social anxiety may provide notable benefits to clinical research. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion

PubMed Central

Power, Jonathan D; Barnes, Kelly A; Snyder, Abraham Z; Schlaggar, Bradley L; Petersen, Steven E

2011-01-01

Here, we demonstrate that subject motion produces substantial changes in the timecourses of resting state functional connectivity MRI (rs-fcMRI) data despite compensatory spatial registration and regression of motion estimates from the data. These changes cause systematic but spurious correlation structures throughout the brain. Specifically, many long-distance correlations are decreased by subject motion, whereas many short-distance correlations are increased. These changes in rs-fcMRI correlations do not arise from, nor are they adequately countered by, some common functional connectivity processing steps. Two indices of data quality are proposed, and a simple method to reduce motion-related effects in rs-fcMRI analyses is demonstrated that should be flexibly implementable across a variety of software platforms. We demonstrate how application of this technique impacts our own data, modifying previous conclusions about brain development. These results suggest the need for greater care in dealing with subject motion, and the need to critically revisit previous rs-fcMRI work that may not have adequately controlled for effects of transient subject movements. PMID:22019881

Modeling and Analysis of Process Parameters for Evaluating Shrinkage Problems During Plastic Injection Molding of a DVD-ROM Cover

NASA Astrophysics Data System (ADS)

Öktem, H.

2012-01-01

Plastic injection molding plays a key role in the production of high-quality plastic parts. Shrinkage is one of the most significant problems of a plastic part in terms of quality in the plastic injection molding. This article focuses on the study of the modeling and analysis of the effects of process parameters on the shrinkage by evaluating the quality of the plastic part of a DVD-ROM cover made with Acrylonitrile Butadiene Styrene (ABS) polymer material. An effective regression model was developed to determine the mathematical relationship between the process parameters (mold temperature, melt temperature, injection pressure, injection time, and cooling time) and the volumetric shrinkage by utilizing the analysis data. Finite element (FE) analyses designed by Taguchi (L27) orthogonal arrays were run in the Moldflow simulation program. Analysis of variance (ANOVA) was then performed to check the adequacy of the regression model and to determine the effect of the process parameters on the shrinkage. Experiments were conducted to control the accuracy of the regression model with the FE analyses obtained from Moldflow. The results show that the regression model agrees very well with the FE analyses and the experiments. From this, it can be concluded that this study succeeded in modeling the shrinkage problem in our application.

Aging, not menopause, is associated with higher prevalence of hyperuricemia among older women.

PubMed

Krishnan, Eswar; Bennett, Mihoko; Chen, Linjun

2014-11-01

This work aims to study the associations, if any, of hyperuricemia, gout, and menopause status in the US population. Using multiyear data from the National Health and Nutrition Examination Survey, we performed unmatched comparisons and one to three age-matched comparisons of women aged 20 to 70 years with and without hyperuricemia (serum urate ≥6 mg/dL). Analyses were performed using survey-weighted multiple logistic regression and conditional logistic regression, respectively. Overall, there were 1,477 women with hyperuricemia. Age and serum urate were significantly correlated. In unmatched analyses (n = 9,573 controls), postmenopausal women were older, were heavier, and had higher prevalence of renal impairment, hypertension, diabetes, and hyperlipidemia. In multivariable regression, after accounting for age, body mass index, glomerular filtration rate, and diuretic use, menopause was associated with hyperuricemia (odds ratio, 1.36; 95% CI, 1.05-1.76; P = 0.002). In corresponding multivariable regression using age-matched data (n = 4,431 controls), the odds ratio for menopause was 0.94 (95% CI, 0.83-1.06). Current use of hormone therapy was not associated with prevalent hyperuricemia in both unmatched and matched analyses. Age is a better statistical explanation for the higher prevalence of hyperuricemia among older women than menopause status.

Cognitive, emotive, and cognitive-behavioral correlates of suicidal ideation among Chinese adolescents in Hong Kong.

PubMed

Kwok, Sylvia Lai Yuk Ching; Shek, Daniel Tan Lei

2010-03-05

Utilizing Daniel Goleman's theory of emotional competence, Beck's cognitive theory, and Rudd's cognitive-behavioral theory of suicidality, the relationships between hopelessness (cognitive component), social problem solving (cognitive-behavioral component), emotional competence (emotive component), and adolescent suicidal ideation were examined. Based on the responses of 5,557 Secondary 1 to Secondary 4 students from 42 secondary schools in Hong Kong, results showed that suicidal ideation was positively related to adolescent hopelessness, but negatively related to emotional competence and social problem solving. While standard regression analyses showed that all the above variables were significant predictors of suicidal ideation, hierarchical regression analyses showed that hopelessness was the most important predictor of suicidal ideation, followed by social problem solving and emotional competence. Further regression analyses found that all four subscales of emotional competence, i.e., empathy, social skills, self-management of emotions, and utilization of emotions, were important predictors of male adolescent suicidal ideation. However, the subscale of social skills was not a significant predictor of female adolescent suicidal ideation. Standard regression analysis also revealed that all three subscales of social problem solving, i.e., negative problem orientation, rational problem solving, and impulsiveness/carelessness style, were important predictors of suicidal ideation. Theoretical and practice implications of the findings are discussed.

Serum Uric Acid Levels and Risk of Incident Hypertriglyceridemia: A Longitudinal Population-based Epidemiological Study.

PubMed

Zheng, Rongjiong; Ren, Ping; Chen, Qingmei; Yang, Tianmeng; Chen, Changxi; Mao, Yushan

2017-09-01

Hypertriglyceridemia is one of lipid metabolism abnormalities; however, it is still debatable whether serum uric acid is a cause or a consequence of hypertriglyceridemia. We performed the study to investigate the longitudinal association between serum uric acid levels and hypertriglyceridemia. The study included 4190 subjects without hypertriglyceridemia. The subjects had annual health examinations for 8 years to assess incident hyperglyceridemia, and the subjects were divided into groups based on the serum uric acid quartile. Cox regression models were used to analyze the risk factors of development hypertriglyceridemia. During follow-up, 1461 (34.9%) subjects developed hypertriglyceridemia over 8 years of follow-up. The cumulative incidence of hypertriglyceridemia was 28.2%, 29.1%, 36.9%, and 45.6% in quartile 1,2,3 and 4, respectively ( P for trend <0.001). Cox regression analyses indicated that serum uric acid levels were independently and positively associated with the risk of incident hypertriglyceridemia. Hypertriglyceridemia has become a serious public health problem. This longitudinal study demonstrates that high serum uric acid levels increase the risk of hypertriglyceridemia. © 2017 by the Association of Clinical Scientists, Inc.

Mixed kernel function support vector regression for global sensitivity analysis

NASA Astrophysics Data System (ADS)

Cheng, Kai; Lu, Zhenzhou; Wei, Yuhao; Shi, Yan; Zhou, Yicheng

2017-11-01

Global sensitivity analysis (GSA) plays an important role in exploring the respective effects of input variables on an assigned output response. Amongst the wide sensitivity analyses in literature, the Sobol indices have attracted much attention since they can provide accurate information for most models. In this paper, a mixed kernel function (MKF) based support vector regression (SVR) model is employed to evaluate the Sobol indices at low computational cost. By the proposed derivation, the estimation of the Sobol indices can be obtained by post-processing the coefficients of the SVR meta-model. The MKF is constituted by the orthogonal polynomials kernel function and Gaussian radial basis kernel function, thus the MKF possesses both the global characteristic advantage of the polynomials kernel function and the local characteristic advantage of the Gaussian radial basis kernel function. The proposed approach is suitable for high-dimensional and non-linear problems. Performance of the proposed approach is validated by various analytical functions and compared with the popular polynomial chaos expansion (PCE). Results demonstrate that the proposed approach is an efficient method for global sensitivity analysis.

Risk factors for autistic regression: results of an ambispective cohort study.

PubMed

Zhang, Ying; Xu, Qiong; Liu, Jing; Li, She-chang; Xu, Xiu

2012-08-01

A subgroup of children diagnosed with autism experience developmental regression featured by a loss of previously acquired abilities. The pathogeny of autistic regression is unknown, although many risk factors likely exist. To better characterize autistic regression and investigate the association between autistic regression and potential influencing factors in Chinese autistic children, we conducted an ambispective study with a cohort of 170 autistic subjects. Analyses by multiple logistic regression showed significant correlations between autistic regression and febrile seizures (OR = 3.53, 95% CI = 1.17-10.65, P = .025), as well as with a family history of neuropsychiatric disorders (OR = 3.62, 95% CI = 1.35-9.71, P = .011). This study suggests that febrile seizures and family history of neuropsychiatric disorders are correlated with autistic regression.

Space shuttle propulsion parameter estimation using optional estimation techniques

NASA Technical Reports Server (NTRS)

1983-01-01

A regression analyses on tabular aerodynamic data provided. A representative aerodynamic model for coefficient estimation. It also reduced the storage requirements for the "normal' model used to check out the estimation algorithms. The results of the regression analyses are presented. The computer routines for the filter portion of the estimation algorithm and the :"bringing-up' of the SRB predictive program on the computer was developed. For the filter program, approximately 54 routines were developed. The routines were highly subsegmented to facilitate overlaying program segments within the partitioned storage space on the computer.

Have geopolitics influenced decisions on American health foreign assistance efforts during the Obama presidency?

PubMed Central

Gupta, Vin; Tsai, Alexander C; Mason-Sharma, Alexandre; Goosby, Eric P; Jha, Ashish K; Kerry, Vanessa B

2018-01-01

Background This study sought to characterize the possible relationship between US geopolitical priorities and annual decisions on health foreign assistance among recipient nations between 2009 and 2016. Methods Data on total planned United States (US) foreign aid and health aid were collected for the 194 member nations of the World Health Organization (WHO) from publicly available databases. Trends in per-capita spending were examined between 2009 and 2016 across the six regions of the WHO (Africa, Americas, Eastern Mediterranean, Europe, Southeast Asia, and the Western Pacific). Data on US national security threats were obtained from the Council on Foreign Relations’ annual Preventive Priorities Survey. Multivariable regression models were fitted specifying planned health aid as the dependent variable and threat level of a recipient aid nation as the primary independent variable. Results Across the aggregate 80 planned recipient countries of US health aid over the duration of the study period, cumulative planned per-capita spending was stable (US$ 0.65 in both 2009 and 2016). The number of annual planned recipients of this aid declined from 74 in 2009 to 56 in 2016 (24.3% decline), with planned allocations decreasing in the Americas, Eastern Mediterranean, and Europe; corresponding increases were observed in Africa, Southeast Asia, and the Western Pacific. Regression analyses demonstrated a dose-response, whereby higher levels of threat were associated with larger declines in planned spending (critical threat nations: b = -3.81; 95% confidence interval (CI) -5.84 to -1.78, P ≤ 0.001) and one-year lagged (critical threat nations: b = -3.91; 95% CI, -5.94 to -1.88, P ≤ 0.001) analyses. Conclusions Higher threat levels are associated with less health aid. This is a novel finding, as prior studies have demonstrated a strong association between national security considerations and decisions on development aid. PMID:29740500

Have geopolitics influenced decisions on American health foreign assistance efforts during the Obama presidency?

PubMed

Gupta, Vin; Tsai, Alexander C; Mason-Sharma, Alexandre; Goosby, Eric P; Jha, Ashish K; Kerry, Vanessa B

2018-06-01

This study sought to characterize the possible relationship between US geopolitical priorities and annual decisions on health foreign assistance among recipient nations between 2009 and 2016. Data on total planned United States (US) foreign aid and health aid were collected for the 194 member nations of the World Health Organization (WHO) from publicly available databases. Trends in per-capita spending were examined between 2009 and 2016 across the six regions of the WHO (Africa, Americas, Eastern Mediterranean, Europe, Southeast Asia, and the Western Pacific). Data on US national security threats were obtained from the Council on Foreign Relations' annual Preventive Priorities Survey. Multivariable regression models were fitted specifying planned health aid as the dependent variable and threat level of a recipient aid nation as the primary independent variable. Across the aggregate 80 planned recipient countries of US health aid over the duration of the study period, cumulative planned per-capita spending was stable (US$ 0.65 in both 2009 and 2016). The number of annual planned recipients of this aid declined from 74 in 2009 to 56 in 2016 (24.3% decline), with planned allocations decreasing in the Americas, Eastern Mediterranean, and Europe; corresponding increases were observed in Africa, Southeast Asia, and the Western Pacific. Regression analyses demonstrated a dose-response, whereby higher levels of threat were associated with larger declines in planned spending (critical threat nations: b = -3.81; 95% confidence interval (CI) -5.84 to -1.78, P  ≤ 0.001) and one-year lagged (critical threat nations: b = -3.91; 95% CI, -5.94 to -1.88, P  ≤ 0.001) analyses. Higher threat levels are associated with less health aid. This is a novel finding, as prior studies have demonstrated a strong association between national security considerations and decisions on development aid.

Applied immuno-epidemiological research: an approach for integrating existing knowledge into the statistical analysis of multiple immune markers.

PubMed

Genser, Bernd; Fischer, Joachim E; Figueiredo, Camila A; Alcântara-Neves, Neuza; Barreto, Mauricio L; Cooper, Philip J; Amorim, Leila D; Saemann, Marcus D; Weichhart, Thomas; Rodrigues, Laura C

2016-05-20

Immunologists often measure several correlated immunological markers, such as concentrations of different cytokines produced by different immune cells and/or measured under different conditions, to draw insights from complex immunological mechanisms. Although there have been recent methodological efforts to improve the statistical analysis of immunological data, a framework is still needed for the simultaneous analysis of multiple, often correlated, immune markers. This framework would allow the immunologists' hypotheses about the underlying biological mechanisms to be integrated. We present an analytical approach for statistical analysis of correlated immune markers, such as those commonly collected in modern immuno-epidemiological studies. We demonstrate i) how to deal with interdependencies among multiple measurements of the same immune marker, ii) how to analyse association patterns among different markers, iii) how to aggregate different measures and/or markers to immunological summary scores, iv) how to model the inter-relationships among these scores, and v) how to use these scores in epidemiological association analyses. We illustrate the application of our approach to multiple cytokine measurements from 818 children enrolled in a large immuno-epidemiological study (SCAALA Salvador), which aimed to quantify the major immunological mechanisms underlying atopic diseases or asthma. We demonstrate how to aggregate systematically the information captured in multiple cytokine measurements to immunological summary scores aimed at reflecting the presumed underlying immunological mechanisms (Th1/Th2 balance and immune regulatory network). We show how these aggregated immune scores can be used as predictors in regression models with outcomes of immunological studies (e.g. specific IgE) and compare the results to those obtained by a traditional multivariate regression approach. The proposed analytical approach may be especially useful to quantify complex immune responses in immuno-epidemiological studies, where investigators examine the relationship among epidemiological patterns, immune response, and disease outcomes.

Effects of cereal fiber on bowel function: A systematic review of intervention trials

PubMed Central

de Vries, Jan; Miller, Paige E; Verbeke, Kristin

2015-01-01

AIM: To comprehensively review and quantitatively summarize results from intervention studies that examined the effects of intact cereal dietary fiber on parameters of bowel function. METHODS: A systematic literature search was conducted using PubMed and EMBASE. Supplementary literature searches included screening reference lists from relevant studies and reviews. Eligible outcomes were stool wet and dry weight, percentage water in stools, stool frequency and consistency, and total transit time. Weighted regression analyses generated mean change (± SD) in these measures per g/d of dietary fiber. RESULTS: Sixty-five intervention studies among generally healthy populations were identified. A quantitative examination of the effects of non-wheat sources of intact cereal dietary fibers was not possible due to an insufficient number of studies. Weighted regression analyses demonstrated that each extra g/d of wheat fiber increased total stool weight by 3.7 ± 0.09 g/d (P < 0.0001; 95%CI: 3.50-3.84), dry stool weight by 0.75 ± 0.03 g/d (P < 0.0001; 95%CI: 0.69-0.82), and stool frequency by 0.004 ± 0.002 times/d (P = 0.0346; 95%CI: 0.0003-0.0078). Transit time decreased by 0.78 ± 0.13 h per additional g/d (P < 0.0001; 95%CI: 0.53-1.04) of wheat fiber among those with an initial transit time greater than 48 h. CONCLUSION: Wheat dietary fiber, and predominately wheat bran dietary fiber, improves measures of bowel function. PMID:26269686

Ultrasonography guidance reduces complications and costs associated with thoracentesis procedures.

PubMed

Patel, Pankaj A; Ernst, Frank R; Gunnarsson, Candace L

2012-01-01

PURPOSE.: We performed an analysis of hospitalizations involving thoracentesis procedures to determine whether the use of ultrasonographic (US) guidance is associated with differences in complications or hospital costs as compared with not using US guidance. METHODS.: We used the Premier hospital database to identify patients with ICD-9 coded thoracentesis in 2008. Use of US guidance was identified using CPT-4 codes. We performed univariate and multivariable analyses of cost data and adjusted for patient demographics, hospital characteristics, patient morbidity severity, and mortality. Logistic regression models were developed for pneumothorax and hemorrhage adverse events, controlling for patient demographics, morbidity severity, mortality, and hospital size. RESULTS.: Of 19,339 thoracentesis procedures, 46% were performed with US guidance. Mean total hospitalization costs were $11,786 (±$10,535) and $12,408 (±$13,157) for patients with and without US guidance, respectively (p < 0.001). Unadjusted risk of pneumothorax or hemorrhage was lower with US guidance (p = 0.019 and 0.078, respectively). Logistic regression analyses demonstrate that US is associated with a 16.3% reduction likelihood of pneumothorax (adjusted odds ratio 0.837, 95% CI: 0.73-0.96; p= 0.014), and 38.7% reduction in likelihood of hemorrhage (adjusted odds ratio 0.613, 95% CI: 0.36-1.04; p = 0.071). CONCLUSIONS.: US-guided thoracentesis is associated with lower total hospital stay costs and lower incidence of pneumothorax and hemorrhage. © 2011 Wiley Periodicals, Inc. J Clin Ultrasound, 2011. Copyright © 2011 Wiley Periodicals, Inc.

Perceived family and peer invalidation as predictors of adolescent suicidal behaviors and self-mutilation.

PubMed

Yen, Shirley; Kuehn, Kevin; Tezanos, Katherine; Weinstock, Lauren M; Solomon, Joel; Spirito, Anthony

2015-03-01

The present study investigates the longitudinal relationship between perceived family and peer invalidation and adolescent suicidal events (SE) and self-mutilation (SM) in a 6 month follow-up (f/u) study of adolescents admitted to an inpatient psychiatric unit for suicide risk. Adolescents (n=119) and their parent(s) were administered interviews and self-report assessments at baseline and at a 6 month f/u, with 99 (83%) completing both assessments. The Adolescent Longitudinal Interval Follow-Up Evaluation (A-LIFE) was modified to provide weekly ratings (baseline and each week of f/u) for perceived family and peer invalidation. Regression analyses examined whether: 1) Prospectively rated perceived family and peer invalidation at baseline predicted SE and SM during f/u; and 2) chronicity of perceived invalidation operationalized as proportion of weeks at moderate to high invalidation during f/u was associated with SE and SM during f/u. Multiple regression analyses, controlling for previously identified covariates, revealed that perceived family invalidation predicted SE over f/u for boys only and perceived peer invalidation predicted SM over f/u in the overall sample. This was the case for both baseline and f/u ratings of perceived invalidation. Our results demonstrate the adverse impact of perceived family and peer invalidation. Specifically, boys who experienced high perceived family invalidation were more likely to have an SE over f/u. Both boys and girls who experienced high perceived peer invalidation were more likely to engage in SM over f/u.

Strengthen forensic entomology in court--the need for data exploration and the validation of a generalised additive mixed model.

PubMed

Baqué, Michèle; Amendt, Jens

2013-01-01

Developmental data of juvenile blow flies (Diptera: Calliphoridae) are typically used to calculate the age of immature stages found on or around a corpse and thus to estimate a minimum post-mortem interval (PMI(min)). However, many of those data sets don't take into account that immature blow flies grow in a non-linear fashion. Linear models do not supply a sufficient reliability on age estimates and may even lead to an erroneous determination of the PMI(min). According to the Daubert standard and the need for improvements in forensic science, new statistic tools like smoothing methods and mixed models allow the modelling of non-linear relationships and expand the field of statistical analyses. The present study introduces into the background and application of these statistical techniques by analysing a model which describes the development of the forensically important blow fly Calliphora vicina at different temperatures. The comparison of three statistical methods (linear regression, generalised additive modelling and generalised additive mixed modelling) clearly demonstrates that only the latter provided regression parameters that reflect the data adequately. We focus explicitly on both the exploration of the data--to assure their quality and to show the importance of checking it carefully prior to conducting the statistical tests--and the validation of the resulting models. Hence, we present a common method for evaluating and testing forensic entomological data sets by using for the first time generalised additive mixed models.

Functional recovery differences after stroke rehabilitation in patients with uni- or bilateral hemiparesis

PubMed Central

Bindawas, Saad M.; Mawajdeh, Hussam M.; Vennu, Vishal S.; Alhaidary, Hisham M.

2017-01-01

Objective: To examine the functional recovery differences after stroke rehabilitation in patients with uni- or bilateral hemiparesis. Methods: In this retrospective study, we included data from the medical record of all 383 patients with uni- or bilateral hemiparesis after stroke who were admitted to King Fahad Medical City-Rehabilitation Hospital between 2008 and 2014 in Riyadh, Kingdom of Saudi Arabia. According to the site of hemiparesis, we classified patients into 3 groups: right hemiparesis (n=208), left hemiparesis (n=157), and bilateral hemipareses (n=18). The patients (n=49) who did not have either site of hemiparesis were excluded. The Functional Independence Measures (FIM) instrument was used to assess the score at admission and discharge. A post hoc test was conducted to examine the functional recovery differences between groups. Multiple regression analyses were used to confirm the findings. Results: Amongst the three groups, there were significant (p<0.05) differences in the total-FIM score as well as motor- and cognitive-FIM sub-scores between admission and discharge of stroke rehabilitation. The differences were significantly greater in the bilateral hemipareses group than in either unilateral hemiparesis group. Multiple regression analyses also confirmed that the site of hemiparesis significantly (p<0.05) differs in the total-FIM score as well as motor-FIM and cognitive-FIM sub-scores. Conclusion: Our results demonstrate that differences in functional recovery after stroke rehabilitation may be influenced by the site of hemiparesis after stroke. PMID:28678212

Determination of grain-size characteristics from electromagnetic seabed mapping data: A NW Iberian shelf study

NASA Astrophysics Data System (ADS)

Baasch, Benjamin; Müller, Hendrik; von Dobeneck, Tilo; Oberle, Ferdinand K. J.

2017-05-01

The electric conductivity and magnetic susceptibility of sediments are fundamental parameters in environmental geophysics. Both can be derived from marine electromagnetic profiling, a novel, fast and non-invasive seafloor mapping technique. Here we present statistical evidence that electric conductivity and magnetic susceptibility can help to determine physical grain-size characteristics (size, sorting and mud content) of marine surficial sediments. Electromagnetic data acquired with the bottom-towed electromagnetic profiler MARUM NERIDIS III were analysed and compared with grain size data from 33 samples across the NW Iberian continental shelf. A negative correlation between mean grain size and conductivity (R=-0.79) as well as mean grain size and susceptibility (R=-0.78) was found. Simple and multiple linear regression analyses were carried out to predict mean grain size, mud content and the standard deviation of the grain-size distribution from conductivity and susceptibility. The comparison of both methods showed that multiple linear regression models predict the grain-size distribution characteristics better than the simple models. This exemplary study demonstrates that electromagnetic benthic profiling is capable to estimate mean grain size, sorting and mud content of marine surficial sediments at a very high significance level. Transfer functions can be calibrated using grains-size data from a few reference samples and extrapolated along shelf-wide survey lines. This study suggests that electromagnetic benthic profiling should play a larger role for coastal zone management, seafloor contamination and sediment provenance studies in worldwide continental shelf systems.

Birth Outcomes Among U.S. Women With Hearing Loss.

PubMed

Mitra, Monika; Akobirshoev, Ilhom; McKee, Michael M; Iezzoni, Lisa I

2016-12-01

The purpose of this study is to estimate the national occurrence of deliveries in women with hearing loss and to compare their birth outcomes to women without hearing loss. This study examined the 2008-2011 Nationwide Inpatient Sample of the Healthcare Cost and Utilization Project in 2015 to compare birth outcomes in women with hearing loss and without. Birth outcomes included preterm birth and low birth weight. Multivariate regression analyses compared birth outcomes between women with and without hearing loss, controlling for maternal age, racial and ethnic identity, type of health insurance, comorbidity, region of hospital, location and teaching status of the hospital, ownership of the hospital, and median household income for mother's ZIP code. Of an estimated 17.9 million deliveries, 10,462 occurred in women with hearing loss. In adjusted regression analyses controlling for demographic characteristics, women with hearing loss were significantly more likely than those without hearing loss to have preterm birth (OR=1.28, 95% CI=1.08, 1.52, p<0.001) and low birth weight (OR=1.43, 95% CI=1.09, 1.90, p<0.05). This study provides a first examination of the pregnancy outcomes among women with hearing loss in the U.S. This analysis demonstrates significant disparities in birth outcomes between women with and without hearing loss. Understanding and addressing the causes of these disparities is critical to improving pregnancy outcomes among women with hearing loss. Copyright © 2016 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Sampling and sensitivity analyses tools (SaSAT) for computational modelling

PubMed Central

Hoare, Alexander; Regan, David G; Wilson, David P

2008-01-01

SaSAT (Sampling and Sensitivity Analysis Tools) is a user-friendly software package for applying uncertainty and sensitivity analyses to mathematical and computational models of arbitrary complexity and context. The toolbox is built in Matlab®, a numerical mathematical software package, and utilises algorithms contained in the Matlab® Statistics Toolbox. However, Matlab® is not required to use SaSAT as the software package is provided as an executable file with all the necessary supplementary files. The SaSAT package is also designed to work seamlessly with Microsoft Excel but no functionality is forfeited if that software is not available. A comprehensive suite of tools is provided to enable the following tasks to be easily performed: efficient and equitable sampling of parameter space by various methodologies; calculation of correlation coefficients; regression analysis; factor prioritisation; and graphical output of results, including response surfaces, tornado plots, and scatterplots. Use of SaSAT is exemplified by application to a simple epidemic model. To our knowledge, a number of the methods available in SaSAT for performing sensitivity analyses have not previously been used in epidemiological modelling and their usefulness in this context is demonstrated. PMID:18304361

Does educational status impact adult mortality in Denmark? A twin approach.

PubMed

Madsen, Mia; Andersen, Anne-Marie Nybo; Christensen, Kaare; Andersen, Per Kragh; Osler, Merete

2010-07-15

To disentangle an independent effect of educational status on mortality risk from direct and indirect selection mechanisms, the authors used a discordant twin pair design, which allowed them to isolate the effect of education by means of adjustment for genetic and environmental confounding per design. The study is based on data from the Danish Twin Registry and Statistics Denmark. Using Cox regression, they estimated hazard ratios for mortality according to the highest attained education among 5,260 monozygotic and 11,088 dizygotic same-sex twin pairs born during 1921-1950 and followed during 1980-2008. Both standard cohort and intrapair analyses were conducted separately for zygosity, gender, and birth cohort. Educational differences in mortality were demonstrated in the standard cohort analyses but attenuated in the intrapair analyses in all subgroups but men born during 1921-1935, and no effect modification by zygosity was observed. Hence, the results are most compatible with an effect of early family environment in explaining the educational inequality in mortality. However, large educational differences were still reflected in mortality risk differences within twin pairs, thus supporting some degree of independent effect of education. In addition, the effect of education may be more pronounced in older cohorts of Danish men.

Basic statistical analyses of candidate nickel-hydrogen cells for the Space Station Freedom

NASA Technical Reports Server (NTRS)

Maloney, Thomas M.; Frate, David T.

1993-01-01

Nickel-Hydrogen (Ni/H2) secondary batteries will be implemented as a power source for the Space Station Freedom as well as for other NASA missions. Consequently, characterization tests of Ni/H2 cells from Eagle-Picher, Whittaker-Yardney, and Hughes were completed at the NASA Lewis Research Center. Watt-hour efficiencies of each Ni/H2 cell were measured for regulated charge and discharge cycles as a function of temperature, charge rate, discharge rate, and state of charge. Temperatures ranged from -5 C to 30 C, charge rates ranged from C/10 to 1C, discharge rates ranged from C/10 to 2C, and states of charge ranged from 20 percent to 100 percent. Results from regression analyses and analyses of mean watt-hour efficiencies demonstrated that overall performance was best at temperatures between 10 C and 20 C while the discharge rate correlated most strongly with watt-hour efficiency. In general, the cell with back-to-back electrode arrangement, single stack, 26 percent KOH, and serrated zircar separator and the cell with a recirculating electrode arrangement, unit stack, 31 percent KOH, zircar separators performed best.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-01-01

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

Temporal Synchronization Analysis for Improving Regression Modeling of Fecal Indicator Bacteria Levels

EPA Science Inventory

Multiple linear regression models are often used to predict levels of fecal indicator bacteria (FIB) in recreational swimming waters based on independent variables (IVs) such as meteorologic, hydrodynamic, and water-quality measures. The IVs used for these analyses are traditiona...

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression

PubMed Central

Dipnall, Joanna F.

2016-01-01

Background Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. Methods The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009–2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. Results After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). Conclusion The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin. PMID:26848571

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression.

PubMed

Dipnall, Joanna F; Pasco, Julie A; Berk, Michael; Williams, Lana J; Dodd, Seetal; Jacka, Felice N; Meyer, Denny

2016-01-01

Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009-2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin.

Building information for systematic improvement of the prevention of hospital-acquired pressure ulcers with statistical process control charts and regression.

PubMed

Padula, William V; Mishra, Manish K; Weaver, Christopher D; Yilmaz, Taygan; Splaine, Mark E

2012-06-01

To demonstrate complementary results of regression and statistical process control (SPC) chart analyses for hospital-acquired pressure ulcers (HAPUs), and identify possible links between changes and opportunities for improvement between hospital microsystems and macrosystems. Ordinary least squares and panel data regression of retrospective hospital billing data, and SPC charts of prospective patient records for a US tertiary-care facility (2004-2007). A prospective cohort of hospital inpatients at risk for HAPUs was the study population. There were 337 HAPU incidences hospital wide among 43 844 inpatients. A probit regression model predicted the correlation of age, gender and length of stay on HAPU incidence (pseudo R(2)=0.096). Panel data analysis determined that for each additional day in the hospital, there was a 0.28% increase in the likelihood of HAPU incidence. A p-chart of HAPU incidence showed a mean incidence rate of 1.17% remaining in statistical control. A t-chart showed the average time between events for the last 25 HAPUs was 13.25 days. There was one 57-day period between two incidences during the observation period. A p-chart addressing Braden scale assessments showed that 40.5% of all patients were risk stratified for HAPUs upon admission. SPC charts complement standard regression analysis. SPC amplifies patient outcomes at the microsystem level and is useful for guiding quality improvement. Macrosystems should monitor effective quality improvement initiatives in microsystems and aid the spread of successful initiatives to other microsystems, followed by system-wide analysis with regression. Although HAPU incidence in this study is below the national mean, there is still room to improve HAPU incidence in this hospital setting since 0% incidence is theoretically achievable. Further assessment of pressure ulcer incidence could illustrate improvement in the quality of care and prevent HAPUs.

Statistical relations among earthquake magnitude, surface rupture length, and surface fault displacement

USGS Publications Warehouse

Bonilla, Manuel G.; Mark, Robert K.; Lienkaemper, James J.

1984-01-01

In order to refine correlations of surface-wave magnitude, fault rupture length at the ground surface, and fault displacement at the surface by including the uncertainties in these variables, the existing data were critically reviewed and a new data base was compiled. Earthquake magnitudes were redetermined as necessary to make them as consistent as possible with the Gutenberg methods and results, which make up much of the data base. Measurement errors were estimated for the three variables for 58 moderate to large shallow-focus earthquakes. Regression analyses were then made utilizing the estimated measurement errors.The regression analysis demonstrates that the relations among the variables magnitude, length, and displacement are stochastic in nature. The stochastic variance, introduced in part by incomplete surface expression of seismogenic faulting, variation in shear modulus, and regional factors, dominates the estimated measurement errors. Thus, it is appropriate to use ordinary least squares for the regression models, rather than regression models based upon an underlying deterministic relation in which the variance results primarily from measurement errors.Significant differences exist in correlations of certain combinations of length, displacement, and magnitude when events are grouped by fault type or by region, including attenuation regions delineated by Evernden and others.Estimates of the magnitude and the standard deviation of the magnitude of a prehistoric or future earthquake associated with a fault can be made by correlating Ms with the logarithms of rupture length, fault displacement, or the product of length and displacement.Fault rupture area could be reliably estimated for about 20 of the events in the data set. Regression of Ms on rupture area did not result in a marked improvement over regressions that did not involve rupture area. Because no subduction-zone earthquakes are included in this study, the reported results do not apply to such zones.

High HbA1c levels correlate with reduced plaque regression during statin treatment in patients with stable coronary artery disease: results of the coronary atherosclerosis study measuring effects of rosuvastatin using intravascular ultrasound in Japanese subjects (COSMOS).

PubMed

Daida, Hiroyuki; Takayama, Tadateru; Hiro, Takafumi; Yamagishi, Masakazu; Hirayama, Atsushi; Saito, Satoshi; Yamaguchi, Tetsu; Matsuzaki, Masunori

2012-07-25

The incidence of cardiac events is higher in patients with diabetes than in people without diabetes. The Coronary Atherosclerosis Study Measuring Effects of Rosuvastatin Using Intravascular Ultrasound in Japanese Subjects (COSMOS) demonstrated significant plaque regression in Japanese patients with chronic coronary disease after 76 weeks of rosuvastatin (2.5 mg once daily, up-titrated to a maximum of 20 mg/day to achieve LDL cholesterol <80 mg/dl). In this subanalysis of COSMOS, we examined the association between HbA1c and plaque regression in 40 patients with HbA1c ≥6.5% (high group) and 86 patients with HbA1c <6.5% (low group). In multivariate analyses, HbA1c and plaque volume at baseline were major determinants of plaque regression. LDL cholesterol decreased by 37% and 39% in the high and low groups, respectively, while HDL cholesterol increased by 16% and 22%, respectively. The reduction in plaque volume was significantly (p = 0.04) greater in the low group (from 71.0 ± 39.9 to 64.7 ± 34.7 mm(3)) than in the high group (from 74.3 ± 34.2 to 71.4 ± 32.3 mm(3)). Vessel volume increased in the high group but not in the low group (change from baseline: +4.2% vs -0.8%, p = 0.02). Change in plaque volume was significantly correlated with baseline HbA1c. Despite similar improvements in lipid levels, plaque regression was less pronounced in patients with high HbA1c levels compared with those with low levels. Tight glucose control during statin therapy may enhance plaque regression in patients with stable coronary disease. ClinicalTrials.gov, Identifier NCT00329160.

Random regression analyses using B-splines functions to model growth from birth to adult age in Canchim cattle.

PubMed

Baldi, F; Alencar, M M; Albuquerque, L G

2010-12-01

The objective of this work was to estimate covariance functions using random regression models on B-splines functions of animal age, for weights from birth to adult age in Canchim cattle. Data comprised 49,011 records on 2435 females. The model of analysis included fixed effects of contemporary groups, age of dam as quadratic covariable and the population mean trend taken into account by a cubic regression on orthogonal polynomials of animal age. Residual variances were modelled through a step function with four classes. The direct and maternal additive genetic effects, and animal and maternal permanent environmental effects were included as random effects in the model. A total of seventeen analyses, considering linear, quadratic and cubic B-splines functions and up to seven knots, were carried out. B-spline functions of the same order were considered for all random effects. Random regression models on B-splines functions were compared to a random regression model on Legendre polynomials and with a multitrait model. Results from different models of analyses were compared using the REML form of the Akaike Information criterion and Schwarz' Bayesian Information criterion. In addition, the variance components and genetic parameters estimated for each random regression model were also used as criteria to choose the most adequate model to describe the covariance structure of the data. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most adequate to describe the covariance structure of the data. Random regression models using B-spline functions as base functions fitted the data better than Legendre polynomials, especially at mature ages, but higher number of parameters need to be estimated with B-splines functions. © 2010 Blackwell Verlag GmbH.

Estimates of Flow Duration, Mean Flow, and Peak-Discharge Frequency Values for Kansas Stream Locations

USGS Publications Warehouse

Perry, Charles A.; Wolock, David M.; Artman, Joshua C.

2004-01-01

Streamflow statistics of flow duration and peak-discharge frequency were estimated for 4,771 individual locations on streams listed on the 1999 Kansas Surface Water Register. These statistics included the flow-duration values of 90, 75, 50, 25, and 10 percent, as well as the mean flow value. Peak-discharge frequency values were estimated for the 2-, 5-, 10-, 25-, 50-, and 100-year floods. Least-squares multiple regression techniques were used, along with Tobit analyses, to develop equations for estimating flow-duration values of 90, 75, 50, 25, and 10 percent and the mean flow for uncontrolled flow stream locations. The contributing-drainage areas of 149 U.S. Geological Survey streamflow-gaging stations in Kansas and parts of surrounding States that had flow uncontrolled by Federal reservoirs and used in the regression analyses ranged from 2.06 to 12,004 square miles. Logarithmic transformations of climatic and basin data were performed to yield the best linear relation for developing equations to compute flow durations and mean flow. In the regression analyses, the significant climatic and basin characteristics, in order of importance, were contributing-drainage area, mean annual precipitation, mean basin permeability, and mean basin slope. The analyses yielded a model standard error of prediction range of 0.43 logarithmic units for the 90-percent duration analysis to 0.15 logarithmic units for the 10-percent duration analysis. The model standard error of prediction was 0.14 logarithmic units for the mean flow. Regression equations used to estimate peak-discharge frequency values were obtained from a previous report, and estimates for the 2-, 5-, 10-, 25-, 50-, and 100-year floods were determined for this report. The regression equations and an interpolation procedure were used to compute flow durations, mean flow, and estimates of peak-discharge frequency for locations along uncontrolled flow streams on the 1999 Kansas Surface Water Register. Flow durations, mean flow, and peak-discharge frequency values determined at available gaging stations were used to interpolate the regression-estimated flows for the stream locations where available. Streamflow statistics for locations that had uncontrolled flow were interpolated using data from gaging stations weighted according to the drainage area and the bias between the regression-estimated and gaged flow information. On controlled reaches of Kansas streams, the streamflow statistics were interpolated between gaging stations using only gaged data weighted by drainage area.

Comparison of enzyme-linked immunosorbent assay and gas chromatography procedures for the detection of cyanazine and metolachlor in surface water samples

USGS Publications Warehouse

Schraer, S.M.; Shaw, D.R.; Boyette, M.; Coupe, R.H.; Thurman, E.M.

2000-01-01

Enzyme-linked immunosorbent assay (ELISA) data from surface water reconnaissance were compared to data from samples analyzed by gas chromatography for the pesticide residues cyanazine (2-[[4-chloro-6-(ethylamino)-l,3,5-triazin-2-yl]amino]-2-methylpropanenitrile ) and metolachlor (2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl)acetamide). When ELISA analyses were duplicated, cyanazine and metolachlor detection was found to have highly reproducible results; adjusted R2s were 0.97 and 0.94, respectively. When ELISA results for cyanazine were regressed against gas chromatography results, the models effectively predicted cyanazine concentrations from ELISA analyses (adjusted R2s ranging from 0.76 to 0.81). The intercepts and slopes for these models were not different from 0 and 1, respectively. This indicates that cyanazine analysis by ELISA is expected to give the same results as analysis by gas chromatography. However, regressing ELISA analyses for metolachlor against gas chromatography data provided more variable results (adjusted R2s ranged from 0.67 to 0.94). Regression models for metolachlor analyses had two of three intercepts that were not different from 0. Slopes for all metolachlor regression models were significantly different from 1. This indicates that as metolachlor concentrations increase, ELISA will over- or under-estimate metolachlor concentration, depending on the method of comparison. ELISA can be effectively used to detect cyanazine and metolachlor in surface water samples. However, when detections of metolachlor have significant consequences or implications it may be necessary to use other analytical methods.

Horses Auto-Recruit Their Lungs by Inspiratory Breath Holding Following Recovery from General Anaesthesia

PubMed Central

Mosing, Martina; Waldmann, Andreas D.; MacFarlane, Paul; Iff, Samuel; Auer, Ulrike; Bohm, Stephan H.; Bettschart-Wolfensberger, Regula; Bardell, David

2016-01-01

This study evaluated the breathing pattern and distribution of ventilation in horses prior to and following recovery from general anaesthesia using electrical impedance tomography (EIT). Six horses were anaesthetised for 6 hours in dorsal recumbency. Arterial blood gas and EIT measurements were performed 24 hours before (baseline) and 1, 2, 3, 4, 5 and 6 hours after horses stood following anaesthesia. At each time point 4 representative spontaneous breaths were analysed. The percentage of the total breath length during which impedance remained greater than 50% of the maximum inspiratory impedance change (breath holding), the fraction of total tidal ventilation within each of four stacked regions of interest (ROI) (distribution of ventilation) and the filling time and inflation period of seven ROI evenly distributed over the dorso-ventral height of the lungs were calculated. Mixed effects multi-linear regression and linear regression were used and significance was set at p<0.05. All horses demonstrated inspiratory breath holding until 5 hours after standing. No change from baseline was seen for the distribution of ventilation during inspiration. Filling time and inflation period were more rapid and shorter in ventral and slower and longer in most dorsal ROI compared to baseline, respectively. In a mixed effects multi-linear regression, breath holding was significantly correlated with PaCO2 in both the univariate and multivariate regression. Following recovery from anaesthesia, horses showed inspiratory breath holding during which gas redistributed from ventral into dorsal regions of the lungs. This suggests auto-recruitment of lung tissue which would have been dependent and likely atelectic during anaesthesia. PMID:27331910

Comparative multivariate analyses of transient otoacoustic emissions and distorsion products in normal and impaired hearing.

PubMed

Stamate, Mirela Cristina; Todor, Nicolae; Cosgarea, Marcel

2015-01-01

The clinical utility of otoacoustic emissions as a noninvasive objective test of cochlear function has been long studied. Both transient otoacoustic emissions and distorsion products can be used to identify hearing loss, but to what extent they can be used as predictors for hearing loss is still debated. Most studies agree that multivariate analyses have better test performances than univariate analyses. The aim of the study was to determine transient otoacoustic emissions and distorsion products performance in identifying normal and impaired hearing loss, using the pure tone audiogram as a gold standard procedure and different multivariate statistical approaches. The study included 105 adult subjects with normal hearing and hearing loss who underwent the same test battery: pure-tone audiometry, tympanometry, otoacoustic emission tests. We chose to use the logistic regression as a multivariate statistical technique. Three logistic regression models were developed to characterize the relations between different risk factors (age, sex, tinnitus, demographic features, cochlear status defined by otoacoustic emissions) and hearing status defined by pure-tone audiometry. The multivariate analyses allow the calculation of the logistic score, which is a combination of the inputs, weighted by coefficients, calculated within the analyses. The accuracy of each model was assessed using receiver operating characteristics curve analysis. We used the logistic score to generate receivers operating curves and to estimate the areas under the curves in order to compare different multivariate analyses. We compared the performance of each otoacoustic emission (transient, distorsion product) using three different multivariate analyses for each ear, when multi-frequency gold standards were used. We demonstrated that all multivariate analyses provided high values of the area under the curve proving the performance of the otoacoustic emissions. Each otoacoustic emission test presented high values of area under the curve, suggesting that implementing a multivariate approach to evaluate the performances of each otoacoustic emission test would serve to increase the accuracy in identifying the normal and impaired ears. We encountered the highest area under the curve value for the combined multivariate analysis suggesting that both otoacoustic emission tests should be used in assessing hearing status. Our multivariate analyses revealed that age is a constant predictor factor of the auditory status for both ears, but the presence of tinnitus was the most important predictor for the hearing level, only for the left ear. Age presented similar coefficients, but tinnitus coefficients, by their high value, produced the highest variations of the logistic scores, only for the left ear group, thus increasing the risk of hearing loss. We did not find gender differences between ears for any otoacoustic emission tests, but studies still debate this question as the results are contradictory. Neither gender, nor environment origin had any predictive value for the hearing status, according to the results of our study. Like any other audiological test, using otoacoustic emissions to identify hearing loss is not without error. Even when applying multivariate analysis, perfect test performance is never achieved. Although most studies demonstrated the benefit of using the multivariate analysis, it has not been incorporated into clinical decisions maybe because of the idiosyncratic nature of multivariate solutions or because of the lack of the validation studies.

Comparative multivariate analyses of transient otoacoustic emissions and distorsion products in normal and impaired hearing

PubMed Central

STAMATE, MIRELA CRISTINA; TODOR, NICOLAE; COSGAREA, MARCEL

2015-01-01

Background and aim The clinical utility of otoacoustic emissions as a noninvasive objective test of cochlear function has been long studied. Both transient otoacoustic emissions and distorsion products can be used to identify hearing loss, but to what extent they can be used as predictors for hearing loss is still debated. Most studies agree that multivariate analyses have better test performances than univariate analyses. The aim of the study was to determine transient otoacoustic emissions and distorsion products performance in identifying normal and impaired hearing loss, using the pure tone audiogram as a gold standard procedure and different multivariate statistical approaches. Methods The study included 105 adult subjects with normal hearing and hearing loss who underwent the same test battery: pure-tone audiometry, tympanometry, otoacoustic emission tests. We chose to use the logistic regression as a multivariate statistical technique. Three logistic regression models were developed to characterize the relations between different risk factors (age, sex, tinnitus, demographic features, cochlear status defined by otoacoustic emissions) and hearing status defined by pure-tone audiometry. The multivariate analyses allow the calculation of the logistic score, which is a combination of the inputs, weighted by coefficients, calculated within the analyses. The accuracy of each model was assessed using receiver operating characteristics curve analysis. We used the logistic score to generate receivers operating curves and to estimate the areas under the curves in order to compare different multivariate analyses. Results We compared the performance of each otoacoustic emission (transient, distorsion product) using three different multivariate analyses for each ear, when multi-frequency gold standards were used. We demonstrated that all multivariate analyses provided high values of the area under the curve proving the performance of the otoacoustic emissions. Each otoacoustic emission test presented high values of area under the curve, suggesting that implementing a multivariate approach to evaluate the performances of each otoacoustic emission test would serve to increase the accuracy in identifying the normal and impaired ears. We encountered the highest area under the curve value for the combined multivariate analysis suggesting that both otoacoustic emission tests should be used in assessing hearing status. Our multivariate analyses revealed that age is a constant predictor factor of the auditory status for both ears, but the presence of tinnitus was the most important predictor for the hearing level, only for the left ear. Age presented similar coefficients, but tinnitus coefficients, by their high value, produced the highest variations of the logistic scores, only for the left ear group, thus increasing the risk of hearing loss. We did not find gender differences between ears for any otoacoustic emission tests, but studies still debate this question as the results are contradictory. Neither gender, nor environment origin had any predictive value for the hearing status, according to the results of our study. Conclusion Like any other audiological test, using otoacoustic emissions to identify hearing loss is not without error. Even when applying multivariate analysis, perfect test performance is never achieved. Although most studies demonstrated the benefit of using the multivariate analysis, it has not been incorporated into clinical decisions maybe because of the idiosyncratic nature of multivariate solutions or because of the lack of the validation studies. PMID:26733749

Application of Partial Least Square (PLS) Regression to Determine Landscape-Scale Aquatic Resources Vulnerability in the Ozark Mountains

EPA Science Inventory

Partial least squares (PLS) analysis offers a number of advantages over the more traditionally used regression analyses applied in landscape ecology, particularly for determining the associations among multiple constituents of surface water and landscape configuration. Common dat...

Using a Guided Machine Learning Ensemble Model to Predict Discharge Disposition following Meningioma Resection.

PubMed

Muhlestein, Whitney E; Akagi, Dallin S; Kallos, Justiss A; Morone, Peter J; Weaver, Kyle D; Thompson, Reid C; Chambless, Lola B

2018-04-01

Objective  Machine learning (ML) algorithms are powerful tools for predicting patient outcomes. This study pilots a novel approach to algorithm selection and model creation using prediction of discharge disposition following meningioma resection as a proof of concept. Materials and Methods  A diversity of ML algorithms were trained on a single-institution database of meningioma patients to predict discharge disposition. Algorithms were ranked by predictive power and top performers were combined to create an ensemble model. The final ensemble was internally validated on never-before-seen data to demonstrate generalizability. The predictive power of the ensemble was compared with a logistic regression. Further analyses were performed to identify how important variables impact the ensemble. Results  Our ensemble model predicted disposition significantly better than a logistic regression (area under the curve of 0.78 and 0.71, respectively, p  = 0.01). Tumor size, presentation at the emergency department, body mass index, convexity location, and preoperative motor deficit most strongly influence the model, though the independent impact of individual variables is nuanced. Conclusion  Using a novel ML technique, we built a guided ML ensemble model that predicts discharge destination following meningioma resection with greater predictive power than a logistic regression, and that provides greater clinical insight than a univariate analysis. These techniques can be extended to predict many other patient outcomes of interest.

Overexpression of epithelial cell adhesion molecule protein is associated with favorable prognosis in an unselected cohort of ovarian cancer patients.

PubMed

Battista, Marco Johannes; Cotarelo, Cristina; Jakobi, Sina; Steetskamp, Joscha; Makris, Georgios; Sicking, Isabel; Weyer, Veronika; Schmidt, Marcus

2014-07-01

The aim of this study was to evaluate the prognostic influence of epithelial cell adhesion molecule (EpCAM) in an unselected cohort of ovarian cancer (OC) patients. Expression of EpCAM was determined by immunohistochemistry in an unselected cohort of 117 patients with OC. Univariable and multivariable Cox regression analyses adjusted for age, tumor stage, histological grading, histological subtype, postoperative tumor burden and completeness of chemotherapy were performed in order to determine the prognostic influence of EpCAM. The Kaplan-Meier method is used to estimate survival rates. Univariable Cox regression analysis showed that overexpression of EpCAM is associated with favorable prognosis in terms of progression-free survival (PFS) (p = 0.011) and disease-specific survival (DSS) (p = 0.003). In multivariable Cox regression analysis, overexpression of EpCAM retains its significance independent of established prognostic factors for longer PFS [hazard ratios (HR) 0.408, 95 % confidence interval (CI) 0.197-0.846, p = 0.003] but not for PFS (HR 0.666, 95 % CI 0.366-1.212, p = 0.183). Kaplan-Meier plots demonstrate an influence on 5-year PFS rates (0 vs. 27.6 %, p = 0.048) and DSS rates (11.8 vs. 54.0 %, p = 0.018). These findings support the hypothesis that the expression of EpCAM is associated with favorable prognosis in OC.

Association between cardiovascular risk factors and carotid intima-media thickness in prepubertal Brazilian children.

PubMed

Gazolla, Fernanda Mussi; Neves Bordallo, Maria Alice; Madeira, Isabel Rey; de Miranda Carvalho, Cecilia Noronha; Vieira Monteiro, Alexandra Maria; Pinheiro Rodrigues, Nádia Cristina; Borges, Marcos Antonio; Collett-Solberg, Paulo Ferrez; Muniz, Bruna Moreira; de Oliveira, Cecilia Lacroix; Pinheiro, Suellen Martins; de Queiroz Ribeiro, Rebeca Mathias

2015-05-01

Early exposure to cardiovascular risk factors creates a chronic inflammatory state that could damage the endothelium followed by thickening of the carotid intima-media. To investigate the association of cardiovascular risk factors and thickening of the carotid intima. Media in prepubertal children. In this cross-sectional study, carotid intima-media thickness (cIMT) and cardiovascular risk factors were assessed in 129 prepubertal children aged from 5 to 10 year. Association was assessed by simple and multivariate logistic regression analyses. In simple logistic regression analyses, body mass index (BMI) z-score, waist circumference, and systolic blood pressure (SBP) were positively associated with increased left, right, and average cIMT, whereas diastolic blood pressure was positively associated only with increased left and average cIMT (p<0.05). In multivariate logistic regression analyses increased left cIMT was positively associated to BMI z-score and SBP, and increased average cIMT was only positively associated to SBP (p<0.05). BMI z-score and SBP were the strongest risk factors for increased cIMT.

Multidisciplinary Design Optimization for Aeropropulsion Engines and Solid Modeling/Animation via the Integrated Forced Methods

NASA Technical Reports Server (NTRS)

2004-01-01

The grant closure report is organized in the following four chapters: Chapter describes the two research areas Design optimization and Solid mechanics. Ten journal publications are listed in the second chapter. Five highlights is the subject matter of chapter three. CHAPTER 1. The Design Optimization Test Bed CometBoards. CHAPTER 2. Solid Mechanics: Integrated Force Method of Analysis. CHAPTER 3. Five Highlights: Neural Network and Regression Methods Demonstrated in the Design Optimization of a Subsonic Aircraft. Neural Network and Regression Soft Model Extended for PX-300 Aircraft Engine. Engine with Regression and Neural Network Approximators Designed. Cascade Optimization Strategy with Neural network and Regression Approximations Demonstrated on a Preliminary Aircraft Engine Design. Neural Network and Regression Approximations Used in Aircraft Design.

Longitudinal evaluation of the importance of homework assignment completion for the academic performance of middle school students with ADHD.

PubMed

Langberg, Joshua M; Dvorsky, Melissa R; Molitor, Stephen J; Bourchtein, Elizaveta; Eddy, Laura D; Smith, Zoe; Schultz, Brandon K; Evans, Steven W

2016-04-01

The primary goal of this study was to longitudinally evaluate the homework assignment completion patterns of middle school age adolescents with ADHD, their associations with academic performance, and malleable predictors of homework assignment completion. Analyses were conducted on a sample of 104 middle school students comprehensively diagnosed with ADHD and followed for 18 months. Multiple teachers for each student provided information about the percentage of homework assignments turned in at five separate time points and school grades were collected quarterly. Results showed that agreement between teachers with respect to students assignment completion was high, with an intraclass correlation of .879 at baseline. Students with ADHD were turning in an average of 12% fewer assignments each academic quarter in comparison to teacher-reported classroom averages. Regression analyses revealed a robust association between the percentage of assignments turned in at baseline and school grades 18 months later, even after controlling for baseline grades, achievement (reading and math), intelligence, family income, and race. Cross-lag analyses demonstrated that the association between assignment completion and grades was reciprocal, with assignment completion negatively impacting grades and low grades in turn being associated with decreased future homework completion. Parent ratings of homework materials management abilities at baseline significantly predicted the percentage of assignments turned in as reported by teachers 18 months later. These findings demonstrate that homework assignment completion problems are persistent across time and an important intervention target for adolescents with ADHD. Copyright © 2015 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

The Antivascular Actions of Mild Intensity Ultrasound on a Murine Neoplasm

NASA Astrophysics Data System (ADS)

Wood, Andrew K. W.; Bunte, Ralph M.; Ansaloni, Sara; Lee, William M.-F.; Sehgal, Chandra M.

2006-05-01

This study was aimed at determining whether mild intensity ultrasound affected the fragile and leaky angiogenic blood vessels in a tumor. In 27 mice (C3HV/HeN strain) a subcutaneous melanoma (K173522) was insonated with continuous physiotherapy ultrasound (1 MHz; spatial-average-temporal-average = 2.3 W cm-2). Analyses of contrast enhanced power Doppler observations showed that insonation significantly increased the avascular area in the neoplasm. A linear regression analysis demonstrated that each min of insonation lead to a 25% reduction in tumor vascularity. The predominant acute effect of insonation was an apparently irreparable dilation of the tumor capillaries; liquefactive necrosis of neoplastic cells, related to a secondary ischemia, was a delayed effect.

Intrinsic and extrinsic motivation for smoking cessation.

PubMed

Curry, S; Wagner, E H; Grothaus, L C

1990-06-01

An intrinsic-extrinsic model of motivation for smoking cessation was evaluated with 2 samples (ns = 1.217 and 151) of smokers who requested self-help materials for smoking cessation. Exploratory and confirmatory principal components analysis on a 36-item Reasons for Quitting (RFQ) scale supported the intrinsic-extrinsic motivation distinction. A 4-factor model, with 2 intrinsic dimensions (concerns about health and desire for self-control) and 2 extrinsic dimensions (immediate reinforcement and social influence), was defined by 20 of the 36 RFQ items. The 20-item measure demonstrated moderate to high levels of internal consistency and convergent and discriminant validity. Logistic regression analyses indicated that smokers with higher levels of intrinsic relative to extrinsic motivation were more likely to achieve abstinence from smoking.

Patient-provider relationship predicts mental and physical health indicators for HIV-positive men who have sex with men.

PubMed

Bankoff, Sarah M; McCullough, Mary B; Pantalone, David W

2013-06-01

We used secondary data analysis to examine associations among aspects of patient-provider relationships and mental and physical health indicators. Positive patient perceptions of patient-provider relationships were associated with fewer mental health symptoms in this outpatient sample of HIV-positive men who have sex with men (N = 171). Regression analyses revealed the role of anxiety and depression in explaining associations between two aspects of patient-provider relationships (i.e. quality of information offered and provider interactional style) and health-related quality of life. The findings demonstrated the importance of patient-provider relationships to improving physical health and functioning and maintaining engagement in care, among HIV-positive men who have sex with men.

Heterogeneous Risk Perceptions: The Case of Poultry Meat Purchase Intentions in Finland

PubMed Central

Heikkilä, Jaakko; Pouta, Eija; Forsman-Hugg, Sari; Mäkelä, Johanna

2013-01-01

This study focused on the heterogeneity of consumer reactions, measured through poultry meat purchase intentions, when facing three cases of risk. The heterogeneity was analysed by latent class logistic regression that included all three risk cases. Approximately 60% of the respondents belonged to the group of production risk avoiders, in which the intention to purchase risk food was significantly lower than in the second group of risk neutrals. In addition to socio-demographic variables, the purchase intentions were statistically associated with several attitude-based variables. We highlighted some policy implications of the heterogeneity. Overall, the study demonstrated that risk matters to consumers, not all risk is equal, and consumer types react somewhat differently to different types of risk. PMID:24157513

A Statistical Analysis of the Economic Drivers of Battery Energy Storage in Commercial Buildings: Preprint

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

Long, Matthew; Simpkins, Travis; Cutler, Dylan

There is significant interest in using battery energy storage systems (BESS) to reduce peak demand charges, and therefore the life cycle cost of electricity, in commercial buildings. This paper explores the drivers of economic viability of BESS in commercial buildings through statistical analysis. A sample population of buildings was generated, a techno-economic optimization model was used to size and dispatch the BESS, and the resulting optimal BESS sizes were analyzed for relevant predictor variables. Explanatory regression analyses were used to demonstrate that peak demand charges are the most significant predictor of an economically viable battery, and that the shape ofmore » the load profile is the most significant predictor of the size of the battery.« less

A Statistical Analysis of the Economic Drivers of Battery Energy Storage in Commercial Buildings

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

Long, Matthew; Simpkins, Travis; Cutler, Dylan

There is significant interest in using battery energy storage systems (BESS) to reduce peak demand charges, and therefore the life cycle cost of electricity, in commercial buildings. This paper explores the drivers of economic viability of BESS in commercial buildings through statistical analysis. A sample population of buildings was generated, a techno-economic optimization model was used to size and dispatch the BESS, and the resulting optimal BESS sizes were analyzed for relevant predictor variables. Explanatory regression analyses were used to demonstrate that peak demand charges are the most significant predictor of an economically viable battery, and that the shape ofmore » the load profile is the most significant predictor of the size of the battery.« less

Inverse expression of survivin and reprimo correlates with poor patient prognosis in gastric cancer

PubMed Central

Cerda-Opazo, Paulina; Valenzuela-Valderrama, Manuel; Wichmann, Ignacio; Rodríguez, Andrés; Contreras-Reyes, Daniel; Fernández, Elmer A.; Carrasco-Aviño, Gonzalo; Corvalán, Alejandro H.; Quest, Andrew F.G.

2018-01-01

BACKGROUND The objective of the study was to determine the relationship between Survivin and Reprimo transcript/protein expression levels, and gastric cancer outcome. METHODS In silico correlations between an agnostic set of twelve p53-dependent apoptosis and cell-cycle genes were explored in the gastric adenocarcinoma TCGA database, using cBioPortal. Findings were validated by regression analysis of RNAseq data. Separate regression analyses were performed to assess the impact of p53 status on Survivin and Reprimo. Quantitative reverse-transcription PCR (RT-qPCR) and immunohistochemistry confirmed in silico findings on fresh-frozen and paraffin-embedded gastric cancer tissues, respectively. Wild-type (AGS, SNU-1) and mutated p53 (NCI-N87) cell lines transfected with pEGFP-Survivin or pCMV6-Reprimo were evaluated by RT-qPCR and Western blotting. Kaplan-Meier method and Long-Rank test were used to assess differences in patient outcome. RESULTS cBioPortal analysis revealed an inverse correlation between Survivin and Reprimo expression (Pearson’s r= −0.3, Spearman’s ρ= −0.55). RNAseq analyses confirmed these findings (Spearman’s ρ= −0.37, p<4.2e-09) and revealed p53 dependence in linear regression models (p<0.05). mRNA and protein levels validated these observations in clinical samples (p<0.001). In vitro analysis in cell lines demonstrated that increasing Survivin reduced Reprimo, while increasing Reprimo reduced Survivin expression, but only did so in p53 wild-type gastric cells (p<0.05). Survivin-positive but Reprimo-negative patients displayed shorter overall survival rates (p=0.047, Long Rank Test) (HR=0.32; 95%IC: 0.11-0.97; p=0.044). CONCLUSIONS TCGA RNAseq data analysis, evaluation of clinical samples and studies in cell lines identified an inverse relationship between Survivin and Reprimo. Elevated Survivin and reduced Reprimo protein expression correlated with poor patient prognosis in gastric cancer. PMID:29560115

Inverse expression of survivin and reprimo correlates with poor patient prognosis in gastric cancer.

PubMed

Cerda-Opazo, Paulina; Valenzuela-Valderrama, Manuel; Wichmann, Ignacio; Rodríguez, Andrés; Contreras-Reyes, Daniel; Fernández, Elmer A; Carrasco-Aviño, Gonzalo; Corvalán, Alejandro H; Quest, Andrew F G

2018-02-27

The objective of the study was to determine the relationship between Survivin and Reprimo transcript/protein expression levels, and gastric cancer outcome. In silico correlations between an agnostic set of twelve p53-dependent apoptosis and cell-cycle genes were explored in the gastric adenocarcinoma TCGA database, using cBioPortal. Findings were validated by regression analysis of RNAseq data. Separate regression analyses were performed to assess the impact of p53 status on Survivin and Reprimo. Quantitative reverse-transcription PCR (RT-qPCR) and immunohistochemistry confirmed in silico findings on fresh-frozen and paraffin-embedded gastric cancer tissues, respectively. Wild-type (AGS, SNU-1) and mutated p53 (NCI-N87) cell lines transfected with pEGFP-Survivin or pCMV6-Reprimo were evaluated by RT-qPCR and Western blotting. Kaplan-Meier method and Long-Rank test were used to assess differences in patient outcome. cBioPortal analysis revealed an inverse correlation between Survivin and Reprimo expression (Pearson's r= -0.3, Spearman's ρ= -0.55). RNAseq analyses confirmed these findings (Spearman's ρ= -0.37, p<4.2e-09) and revealed p53 dependence in linear regression models (p<0.05). mRNA and protein levels validated these observations in clinical samples (p<0.001). In vitro analysis in cell lines demonstrated that increasing Survivin reduced Reprimo, while increasing Reprimo reduced Survivin expression, but only did so in p53 wild-type gastric cells (p<0.05). Survivin-positive but Reprimo-negative patients displayed shorter overall survival rates (p=0.047, Long Rank Test) (HR=0.32; 95%IC: 0.11-0.97; p=0.044). TCGA RNAseq data analysis, evaluation of clinical samples and studies in cell lines identified an inverse relationship between Survivin and Reprimo. Elevated Survivin and reduced Reprimo protein expression correlated with poor patient prognosis in gastric cancer.

Comparison of Xenon-Enhanced Area-Detector CT and Krypton Ventilation SPECT/CT for Assessment of Pulmonary Functional Loss and Disease Severity in Smokers.

PubMed

Ohno, Yoshiharu; Fujisawa, Yasuko; Takenaka, Daisuke; Kaminaga, Shigeo; Seki, Shinichiro; Sugihara, Naoki; Yoshikawa, Takeshi

2018-02-01

The objective of this study was to compare the capability of xenon-enhanced area-detector CT (ADCT) performed with a subtraction technique and coregistered 81m Kr-ventilation SPECT/CT for the assessment of pulmonary functional loss and disease severity in smokers. Forty-six consecutive smokers (32 men and 14 women; mean age, 67.0 years) underwent prospective unenhanced and xenon-enhanced ADCT, 81m Kr-ventilation SPECT/CT, and pulmonary function tests. Disease severity was evaluated according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification. CT-based functional lung volume (FLV), the percentage of wall area to total airway area (WA%), and ventilated FLV on xenon-enhanced ADCT and SPECT/CT were calculated for each smoker. All indexes were correlated with percentage of forced expiratory volume in 1 second (%FEV 1 ) using step-wise regression analyses, and univariate and multivariate logistic regression analyses were performed. In addition, the diagnostic accuracy of the proposed model was compared with that of each radiologic index by means of McNemar analysis. Multivariate logistic regression showed that %FEV 1 was significantly affected (r = 0.77, r 2 = 0.59) by two factors: the first factor, ventilated FLV on xenon-enhanced ADCT (p < 0.0001); and the second factor, WA% (p = 0.004). Univariate logistic regression analyses indicated that all indexes significantly affected GOLD classification (p < 0.05). Multivariate logistic regression analyses revealed that ventilated FLV on xenon-enhanced ADCT and CT-based FLV significantly influenced GOLD classification (p < 0.0001). The diagnostic accuracy of the proposed model was significantly higher than that of ventilated FLV on SPECT/CT (p = 0.03) and WA% (p = 0.008). Xenon-enhanced ADCT is more effective than 81m Kr-ventilation SPECT/CT for the assessment of pulmonary functional loss and disease severity.

Application of Partial Least Squares (PLS) Regression to Determine Landscape-Scale Aquatic Resource Vulnerability in the Ozark Mountains

EPA Science Inventory

Partial least squares (PLS) analysis offers a number of advantages over the more traditionally used regression analyses applied in landscape ecology to study the associations among constituents of surface water and landscapes. Common data problems in ecological studies include: s...

Infantile hemangioma-like vascular lesion in a 26-year-old woman after abortion.

PubMed

Lu, Yang; Wang, Shu Jun; Li, Xin; Hu, Li; Zhang, Wen Jie; Li, Wei

2014-01-01

A 26-year-old woman (G2P1A1) presented with a 5-week history of multiple red marks on her body after a therapeutic abortion. A physical examination found 15 palpable red marks on her head, neck, chest, arms and legs. Proliferating endothelial cells, which expressed CD31, CD34, von Willebrand factor, but not Glut-1 and merosin, were observed in the lesional area by histopathological analyses. Histocompatibility antigen typing of 2 lesions was identical to a sample from peripheral blood. Accelerated regression was observed in 2 lesions treated by intralesional injection of betamethasone, while spontaneous regression was observed within 9 months in the remaining lesions without any treatment. Rapid growth, spontaneous regression and histological analyses in this case support the diagnosis of 'infantile hemangioma-like vascular lesion'.

Identifying individual changes in performance with composite quality indicators while accounting for regression to the mean.

PubMed

Gajewski, Byron J; Dunton, Nancy

2013-04-01

Almost a decade ago Morton and Torgerson indicated that perceived medical benefits could be due to "regression to the mean." Despite this caution, the regression to the mean "effects on the identification of changes in institutional performance do not seem to have been considered previously in any depth" (Jones and Spiegelhalter). As a response, Jones and Spiegelhalter provide a methodology to adjust for regression to the mean when modeling recent changes in institutional performance for one-variable quality indicators. Therefore, in our view, Jones and Spiegelhalter provide a breakthrough methodology for performance measures. At the same time, in the interests of parsimony, it is useful to aggregate individual quality indicators into a composite score. Our question is, can we develop and demonstrate a methodology that extends the "regression to the mean" literature to allow for composite quality indicators? Using a latent variable modeling approach, we extend the methodology to the composite indicator case. We demonstrate the approach on 4 indicators collected by the National Database of Nursing Quality Indicators. A simulation study further demonstrates its "proof of concept."

Heaping-Induced Bias in Regression-Discontinuity Designs. NBER Working Paper No. 17408

ERIC Educational Resources Information Center

Barreca, Alan I.; Lindo, Jason M.; Waddell, Glen R.

2011-01-01

This study uses Monte Carlo simulations to demonstrate that regression-discontinuity designs arrive at biased estimates when attributes related to outcomes predict heaping in the running variable. After showing that our usual diagnostics are poorly suited to identifying this type of problem, we provide alternatives. We also demonstrate how the…

Marriage Advantages in Perinatal Health: Evidence of Marriage Selection or Marriage Protection?

PubMed Central

Kane, Jennifer B.

2015-01-01

Marriage is a social tie associated with health advantages for adults and their children, as lower rates of preterm birth and low birth weight are observed among married women. This study tests two competing hypotheses explaining these marriage advantages—marriage protection versus marriage selection—using a sample of recent births to single, cohabiting, and married women from the National Survey of Family Growth, 2006–10. Propensity score matching and fixed effects regression results demonstrate support for marriage selection, as a rich set of early life selection factors account for all of the cohabiting-married disparity and part of the single-married disparity. Subsequent analyses demonstrate prenatal smoking mediates the adjusted single-married disparity in birth weight, lending some support for the marriage protection perspective. Study findings sharpen our understanding of why and how marriage matters for child well-being, and provide insight into preconception and prenatal factors describing intergenerational transmissions of inequality via birth weight. PMID:26778858

Association of school performance indicators with implementation of the healthy kids, smart kids programme: case study.

PubMed

Nansel, Tonja R; Huang, Terry T K; Rovner, Alisha J; Sanders-Butler, Yvonne

2010-01-01

The purpose of the present analysis was to examine secular trends in school performance indicators in relationship to the implementation of a programme targeting the school food and physical activity environment. Data on available school performance indicators were obtained; retrospective analyses were conducted to assess trends in indicators in association with programme implementation; each outcome was regressed v. year, beginning with the year prior to programme implementation. The Healthy Kids, Smart Kids programme, a grass-roots effort to enhance the school food and physical activity environment in the Browns Mill Elementary School in Georgia. Data included publicly available school records from the years 1995 to 2006. The number of nurse, counselling and disciplinary referrals per 100 students demonstrated a downward trend, while standardized test scores demonstrated an upward trend beginning in the year of programme implementation. School year was a significant predictor of all indicators. Promoting nutrition and physical activity within the school environment may be a promising approach for enhancing both student health and educational outcomes.

The scope and control of attention as separate aspects of working memory.

PubMed

Shipstead, Zach; Redick, Thomas S; Hicks, Kenny L; Engle, Randall W

2012-01-01

The present study examines two varieties of working memory (WM) capacity task: visual arrays (i.e., a measure of the amount of information that can be maintained in working memory) and complex span (i.e., a task that taps WM-related attentional control). Using previously collected data sets we employ confirmatory factor analysis to demonstrate that visual arrays and complex span tasks load on separate, but correlated, factors. A subsequent series of structural equation models and regression analyses demonstrate that these factors contribute both common and unique variance to the prediction of general fluid intelligence (Gf). However, while visual arrays does contribute uniquely to higher cognition, its overall correlation to Gf is largely mediated by variance associated with the complex span factor. Thus we argue that visual arrays performance is not strictly driven by a limited-capacity storage system (e.g., the focus of attention; Cowan, 2001), but may also rely on control processes such as selective attention and controlled memory search.

Bootstrap Enhanced Penalized Regression for Variable Selection with Neuroimaging Data.

PubMed

Abram, Samantha V; Helwig, Nathaniel E; Moodie, Craig A; DeYoung, Colin G; MacDonald, Angus W; Waller, Niels G

2016-01-01

Recent advances in fMRI research highlight the use of multivariate methods for examining whole-brain connectivity. Complementary data-driven methods are needed for determining the subset of predictors related to individual differences. Although commonly used for this purpose, ordinary least squares (OLS) regression may not be ideal due to multi-collinearity and over-fitting issues. Penalized regression is a promising and underutilized alternative to OLS regression. In this paper, we propose a nonparametric bootstrap quantile (QNT) approach for variable selection with neuroimaging data. We use real and simulated data, as well as annotated R code, to demonstrate the benefits of our proposed method. Our results illustrate the practical potential of our proposed bootstrap QNT approach. Our real data example demonstrates how our method can be used to relate individual differences in neural network connectivity with an externalizing personality measure. Also, our simulation results reveal that the QNT method is effective under a variety of data conditions. Penalized regression yields more stable estimates and sparser models than OLS regression in situations with large numbers of highly correlated neural predictors. Our results demonstrate that penalized regression is a promising method for examining associations between neural predictors and clinically relevant traits or behaviors. These findings have important implications for the growing field of functional connectivity research, where multivariate methods produce numerous, highly correlated brain networks.

Bootstrap Enhanced Penalized Regression for Variable Selection with Neuroimaging Data

PubMed Central

Abram, Samantha V.; Helwig, Nathaniel E.; Moodie, Craig A.; DeYoung, Colin G.; MacDonald, Angus W.; Waller, Niels G.

2016-01-01

Recent advances in fMRI research highlight the use of multivariate methods for examining whole-brain connectivity. Complementary data-driven methods are needed for determining the subset of predictors related to individual differences. Although commonly used for this purpose, ordinary least squares (OLS) regression may not be ideal due to multi-collinearity and over-fitting issues. Penalized regression is a promising and underutilized alternative to OLS regression. In this paper, we propose a nonparametric bootstrap quantile (QNT) approach for variable selection with neuroimaging data. We use real and simulated data, as well as annotated R code, to demonstrate the benefits of our proposed method. Our results illustrate the practical potential of our proposed bootstrap QNT approach. Our real data example demonstrates how our method can be used to relate individual differences in neural network connectivity with an externalizing personality measure. Also, our simulation results reveal that the QNT method is effective under a variety of data conditions. Penalized regression yields more stable estimates and sparser models than OLS regression in situations with large numbers of highly correlated neural predictors. Our results demonstrate that penalized regression is a promising method for examining associations between neural predictors and clinically relevant traits or behaviors. These findings have important implications for the growing field of functional connectivity research, where multivariate methods produce numerous, highly correlated brain networks. PMID:27516732

Stepwise group sparse regression (SGSR): gene-set-based pharmacogenomic predictive models with stepwise selection of functional priors.

PubMed

Jang, In Sock; Dienstmann, Rodrigo; Margolin, Adam A; Guinney, Justin

2015-01-01

Complex mechanisms involving genomic aberrations in numerous proteins and pathways are believed to be a key cause of many diseases such as cancer. With recent advances in genomics, elucidating the molecular basis of cancer at a patient level is now feasible, and has led to personalized treatment strategies whereby a patient is treated according to his or her genomic profile. However, there is growing recognition that existing treatment modalities are overly simplistic, and do not fully account for the deep genomic complexity associated with sensitivity or resistance to cancer therapies. To overcome these limitations, large-scale pharmacogenomic screens of cancer cell lines--in conjunction with modern statistical learning approaches--have been used to explore the genetic underpinnings of drug response. While these analyses have demonstrated the ability to infer genetic predictors of compound sensitivity, to date most modeling approaches have been data-driven, i.e. they do not explicitly incorporate domain-specific knowledge (priors) in the process of learning a model. While a purely data-driven approach offers an unbiased perspective of the data--and may yield unexpected or novel insights--this strategy introduces challenges for both model interpretability and accuracy. In this study, we propose a novel prior-incorporated sparse regression model in which the choice of informative predictor sets is carried out by knowledge-driven priors (gene sets) in a stepwise fashion. Under regularization in a linear regression model, our algorithm is able to incorporate prior biological knowledge across the predictive variables thereby improving the interpretability of the final model with no loss--and often an improvement--in predictive performance. We evaluate the performance of our algorithm compared to well-known regularization methods such as LASSO, Ridge and Elastic net regression in the Cancer Cell Line Encyclopedia (CCLE) and Genomics of Drug Sensitivity in Cancer (Sanger) pharmacogenomics datasets, demonstrating that incorporation of the biological priors selected by our model confers improved predictability and interpretability, despite much fewer predictors, over existing state-of-the-art methods.

Addressing the identification problem in age-period-cohort analysis: a tutorial on the use of partial least squares and principal components analysis.

PubMed

Tu, Yu-Kang; Krämer, Nicole; Lee, Wen-Chung

2012-07-01

In the analysis of trends in health outcomes, an ongoing issue is how to separate and estimate the effects of age, period, and cohort. As these 3 variables are perfectly collinear by definition, regression coefficients in a general linear model are not unique. In this tutorial, we review why identification is a problem, and how this problem may be tackled using partial least squares and principal components regression analyses. Both methods produce regression coefficients that fulfill the same collinearity constraint as the variables age, period, and cohort. We show that, because the constraint imposed by partial least squares and principal components regression is inherent in the mathematical relation among the 3 variables, this leads to more interpretable results. We use one dataset from a Taiwanese health-screening program to illustrate how to use partial least squares regression to analyze the trends in body heights with 3 continuous variables for age, period, and cohort. We then use another dataset of hepatocellular carcinoma mortality rates for Taiwanese men to illustrate how to use partial least squares regression to analyze tables with aggregated data. We use the second dataset to show the relation between the intrinsic estimator, a recently proposed method for the age-period-cohort analysis, and partial least squares regression. We also show that the inclusion of all indicator variables provides a more consistent approach. R code for our analyses is provided in the eAppendix.

Recall of "The Real Cost" Anti-Smoking Campaign Is Specifically Associated With Endorsement of Campaign-Targeted Beliefs.

PubMed

Kranzler, Elissa C; Gibson, Laura A; Hornik, Robert C

2017-10-01

Though previous research suggests the FDA's "The Real Cost" anti-smoking campaign has reduced smoking initiation, the theorized pathway of effects (through targeted beliefs) has not been evaluated. This study assesses the relationship between recall of campaign television advertisements and ad-specific anti-smoking beliefs. Respondents in a nationally representative survey of nonsmoking youths age 13-17 (n = 4,831) reported exposure to four The Real Cost advertisements and a fake ad, smoking-relevant beliefs, and nonsmoking intentions. Analyses separately predicted each targeted belief from specific ad recall, adjusting for potential confounders and survey weights. Parallel analyses with non-targeted beliefs showed smaller effects, strengthening claims of campaign effects. Recall of four campaign ads (but not the fake ad) significantly predicted endorsement of the ad-targeted belief (Mean β = .13). Two-sided sign tests indicated stronger ad recall associations with the targeted belief relative to the non-targeted belief (p < .05). Logistic regression analyses indicated that respondents who endorsed campaign-targeted beliefs were more likely to have no intention to smoke (p < .01). This study is the first to demonstrate a relationship between recall of ads from The Real Cost campaign and the theorized pathway of effects (through targeted beliefs). These analyses also provide a methodological template for showing campaign effects despite limitations of available data.

What Would I Know About Mercy? Faith and Optimistic Expectancies Among African Americans

PubMed Central

Mattis, Jacqueline S.; Powell, Wizdom; Grayman, Nyasha A.; Murray, Yohance; Cole-Lewis, Yasmin C.; Goodwill, Janelle R.

2017-01-01

A small body of research has begun to explore the association between faith and optimism among African Americans. However, missing from the extant work is an examination of the extent to which traditional indices of religious commitment work together with beliefs about God to shape optimism. The present study examines the utility of indices of social location, religious commitment (i.e., early and current religious service attendance, subjective religiosity), belief about the quality of one’s relationship with God (i.e., a belief that one is connected to a loving God), and beliefs about being the recipient of divine forgiveness for predicting dispositional optimism among a sample of community residing African American adults (N = 241). Age, subjective religiosity, and organizational religiosity were positively related to optimism in bivariate analyses. Hierarchical regression analyses demonstrated a significant association between age, subjective religiosity, and optimism; however, those associations were eliminated once relationship with God and belief in one’s forgiveness by God were entered into the model. Only belief in God’s love predicted optimism in multivariate analyses. Serial mediation analyses revealed that beliefs about the quality of one’s relationship with God and belief in divine forgiveness fully mediated the relationship between subjective religiosity and optimism, but that the relationship is driven largely by relationship with God. Implications of these findings are discussed. PMID:29057016

Application of Regulatory Focus Theory to Search Advertising

PubMed Central

Mowle, Elyse N.; Georgia, Emily J.; Doss, Brian D.; Updegraff, John A.

2015-01-01

Purpose The purpose of this paper is to test the utility of regulatory focus theory principles in a real-world setting; specifically, Internet hosted text advertisements. Effect of compatibility of the ad text with the regulatory focus of the consumer was examined. Design/methodology/approach Advertisements were created using Google AdWords. Data were collected for the number of views and clicks each ad received. Effect of regulatory fit was measured using logistic regression. Findings Logistic regression analyses demonstrated that there was a strong main effect for keyword, such that users were almost six times as likely to click on a promotion advertisement as a prevention advertisement, as well as a main effect for compatibility, such that users were twice as likely to click on an advertisement with content that was consistent with their keyword. Finally, there was a strong interaction of these two variables, such that the effect of consistent advertisements was stronger for promotion searches than for prevention searches. Research limitations/implications The effect of ad compatibility had medium to large effect sizes, suggesting that individuals’ state may have more influence on advertising response than do individuals’ traits (e.g. personality traits). Measurement of regulatory fit was limited by the constraints of Google AdWords. Practical implications The results of this study provide a possible framework for ad creation for Internet advertisers. Originality/value This paper is the first study to demonstrate the utility of regulatory focus theory in online advertising. PMID:26430293

Logistic regression for circular data

NASA Astrophysics Data System (ADS)

Al-Daffaie, Kadhem; Khan, Shahjahan

2017-05-01

This paper considers the relationship between a binary response and a circular predictor. It develops the logistic regression model by employing the linear-circular regression approach. The maximum likelihood method is used to estimate the parameters. The Newton-Raphson numerical method is used to find the estimated values of the parameters. A data set from weather records of Toowoomba city is analysed by the proposed methods. Moreover, a simulation study is considered. The R software is used for all computations and simulations.

Estimates of Median Flows for Streams on the 1999 Kansas Surface Water Register

USGS Publications Warehouse

Perry, Charles A.; Wolock, David M.; Artman, Joshua C.

2004-01-01

The Kansas State Legislature, by enacting Kansas Statute KSA 82a?2001 et. seq., mandated the criteria for determining which Kansas stream segments would be subject to classification by the State. One criterion for the selection as a classified stream segment is based on the statistic of median flow being equal to or greater than 1 cubic foot per second. As specified by KSA 82a?2001 et. seq., median flows were determined from U.S. Geological Survey streamflow-gaging-station data by using the most-recent 10 years of gaged data (KSA) for each streamflow-gaging station. Median flows also were determined by using gaged data from the entire period of record (all-available hydrology, AAH). Least-squares multiple regression techniques were used, along with Tobit analyses, to develop equations for estimating median flows for uncontrolled stream segments. The drainage area of the gaging stations on uncontrolled stream segments used in the regression analyses ranged from 2.06 to 12,004 square miles. A logarithmic transformation of the data was needed to develop the best linear relation for computing median flows. In the regression analyses, the significant climatic and basin characteristics, in order of importance, were drainage area, mean annual precipitation, mean basin permeability, and mean basin slope. Tobit analyses of KSA data yielded a model standard error of prediction of 0.285 logarithmic units, and the best equations using Tobit analyses of AAH data had a model standard error of prediction of 0.250 logarithmic units. These regression equations and an interpolation procedure were used to compute median flows for the uncontrolled stream segments on the 1999 Kansas Surface Water Register. Measured median flows from gaging stations were incorporated into the regression-estimated median flows along the stream segments where available. The segments that were uncontrolled were interpolated using gaged data weighted according to the drainage area and the bias between the regression-estimated and gaged flow information. On controlled segments of Kansas streams, the median flow information was interpolated between gaging stations using only gaged data weighted by drainage area. Of the 2,232 total stream segments on the Kansas Surface Water Register, 34.5 percent of the segments had an estimated median streamflow of less than 1 cubic foot per second when the KSA analysis was used. When the AAH analysis was used, 36.2 percent of the segments had an estimated median streamflow of less than 1 cubic foot per second. This report supercedes U.S. Geological Survey Water-Resources Investigations Report 02?4292.

The occupational safety and health scorecard--a business case example for strategic management.

PubMed

Köper, Birgit; Möller, Klaus; Zwetsloot, Gerard

2009-12-01

Human resources and health issues are crucial in terms of corporate competitiveness. However, systematic, continuous and strategically aligned occupational safety and health (OSH) management is scarcely applied in companies. One major reason for this could be the lack of generally accepted and standardised OSH control methods. Our objective was thus to conceptualize a method by which qualitative factors such as human resources and OSH aspects contribute to the performance or value-added layer of an organization. We developed a business case based on the well-known and accepted Balanced Scorecard approach, which we adapted and applied to the management of OSH issues. The concept was implemented in the course of a comprehensive case study at a German automobile manufacturer. We gathered health as well as finance data in order to test which health-related indicators had an impact on financial performance. The demonstration of, and reporting on, how the promotion of workplace health contributes strategically to the organization is crucial for both health and human resource managers. Based on multivariate regression analyses, our main finding was that the Balanced Scorecard approach is an adequate means to control OSH issues in terms of strategic health management. Our analyses demonstrated that health-related interventions contribute significantly to performance aspects such as quality, productivity, absenteeism, and cost reduction. Therefore, the financial impact of health-related aspects / interventions could be demonstrated by means of the OSH scorecard. The availability and quality of health data within the context of overall corporate performance data needs to be improved in order to bridge OSH-related and performance issues of an organization.

Advanced Statistics for Exotic Animal Practitioners.

PubMed

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.

The association of serum prolactin concentration with inflammatory biomarkers - cross-sectional findings from the population-based Study of Health in Pomerania.

PubMed

Friedrich, Nele; Schneider, Harald J; Spielhagen, Christin; Markus, Marcello Ricardo Paulista; Haring, Robin; Grabe, Hans J; Buchfelder, Michael; Wallaschofski, Henri; Nauck, Matthias

2011-10-01

Prolactin (PRL) is involved in immune regulation and may contribute to an atherogenic phenotype. Previous results on the association of PRL with inflammatory biomarkers have been conflicting and limited by small patient studies. Therefore, we used data from a large population-based sample to assess the cross-sectional associations between serum PRL concentration and high-sensitivity C-reactive protein (hsCRP), fibrinogen, interleukin-6 (IL-6), and white blood cell (WBC) count. From the population-based Study of Health in Pomerania (SHIP), a total of 3744 subjects were available for the present analyses. PRL and inflammatory biomarkers were measured. Linear and logistic regression models adjusted for age, sex, body-mass-index, total cholesterol and glucose were analysed. Multivariable linear regression models revealed a positive association of PRL with WBC. Multivariable logistic regression analyses showed a significant association of PRL with increased IL-6 in non-smokers [highest vs lowest quintile: odds ratio 1·69 (95% confidence interval 1·10-2·58), P = 0·02] and smokers [OR 2·06 (95%-CI 1·10-3·89), P = 0·02]. Similar results were found for WBC in non-smokers [highest vs lowest quintile: OR 2·09 (95%-CI 1·21-3·61), P = 0·01)] but not in smokers. Linear and logistic regression analyses revealed no significant associations of PRL with hsCRP or fibrinogen. Serum PRL concentrations are associated with inflammatory biomarkers including IL-6 and WBC, but not hsCRP or fibrinogen. The suggested role of PRL in inflammation needs further investigation in future prospective studies. © 2011 Blackwell Publishing Ltd.

Using Marginal Structural Modeling to Estimate the Cumulative Impact of an Unconditional Tax Credit on Self-Rated Health.

PubMed

Pega, Frank; Blakely, Tony; Glymour, M Maria; Carter, Kristie N; Kawachi, Ichiro

2016-02-15

In previous studies, researchers estimated short-term relationships between financial credits and health outcomes using conventional regression analyses, but they did not account for time-varying confounders affected by prior treatment (CAPTs) or the credits' cumulative impacts over time. In this study, we examined the association between total number of years of receiving New Zealand's Family Tax Credit (FTC) and self-rated health (SRH) in 6,900 working-age parents using 7 waves of New Zealand longitudinal data (2002-2009). We conducted conventional linear regression analyses, both unadjusted and adjusted for time-invariant and time-varying confounders measured at baseline, and fitted marginal structural models (MSMs) that more fully adjusted for confounders, including CAPTs. Of all participants, 5.1%-6.8% received the FTC for 1-3 years and 1.8%-3.6% for 4-7 years. In unadjusted and adjusted conventional regression analyses, each additional year of receiving the FTC was associated with 0.033 (95% confidence interval (CI): -0.047, -0.019) and 0.026 (95% CI: -0.041, -0.010) units worse SRH (on a 5-unit scale). In the MSMs, the average causal treatment effect also reflected a small decrease in SRH (unstabilized weights: β = -0.039 unit, 95% CI: -0.058, -0.020; stabilized weights: β = -0.031 unit, 95% CI: -0.050, -0.007). Cumulatively receiving the FTC marginally reduced SRH. Conventional regression analyses and MSMs produced similar estimates, suggesting little bias from CAPTs. © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Adult attachment security and college student substance use.

PubMed

Kassel, Jon D; Wardle, Margaret; Roberts, John E

2007-06-01

Previous research has demonstrated strong links between quality of adult attachment styles and various forms of psychological distress. A burgeoning literature further points to a relationship between insecure attachment and drug use, particularly alcohol consumption. In the present study, we expanded upon the existing literature by examining the relationship between adult attachment style and use of cigarettes, alcohol, and marijuana in a sample of 212 college students. Moreover, based on our previous work [Hankin, B.L., Kassel, J.D., and Abela, J.R.Z. (2005). Adult attachment dimensions and specificity of emotional distress symptoms: prospective investigations of cognitive risk and interpersonal stress generation as mediating mechanisms. Personality and Social Psychology Bulletin, 31, 136-151.], we proposed a conceptual model positing that adult attachment style influences both frequency of drug use and stress-motivated drug use through its impact on dysfunctional attitudes and self-esteem. Initial correlational analyses indicated significant (positive) associations between anxious attachment (tapping neediness and fear of abandonment) and both drug use frequency and stress-motivated drug use. Simultaneous regression analyses revealed that, for drug use frequency, the influence of anxious attachment operated primarily through its effect on dysfunctional attitudes and self-esteem. Regarding drug use attributable to negative affect reduction, anxious attachment demonstrated direct, independent effects on both cigarette smoking and alcohol use. These findings highlight the potential importance of adult attachment styles as a risk factor for drug use among college students.

Neuropsychiatry and White Matter Microstructure in Huntington's Disease.

PubMed

Gregory, Sarah; Scahill, Rachael I; Seunarine, Kiran K; Stopford, Cheryl; Zhang, Hui; Zhang, Jiaying; Orth, Michael; Durr, Alexandra; Roos, Raymund A C; Langbehn, Douglas R; Long, Jeffrey D; Johnson, Hans; Rees, Geraint; Tabrizi, Sarah J; Craufurd, David

2015-01-01

Neuropsychiatric symptoms in Huntington's disease (HD) are often evident prior to clinical diagnosis. Apathy is highly correlated with disease progression, while depression and irritability occur at different stages of the disease, both before and after clinical onset. Little is understood about the neural bases of these neuropsychiatric symptoms and to what extent those neural bases are analogous to neuropsychiatric disorders in the general population. We used Diffusion Tensor Imaging (DTI) to investigate structural connectivity between brain regions and any putative microstructural changes associated with depression, apathy and irritability in HD. DTI data were collected from 39 premanifest and 45 early-HD participants in the Track-HD study and analysed using whole-brain Tract-Based Spatial Statistics. We used regression analyses to identify white matter tracts whose structural integrity (as measured by fractional anisotropy, FA) was correlated with HADS-depression, PBA-apathy or PBA-irritability scores in gene-carriers and related to cumulative probability to onset (CPO). For those with the highest CPO, we found significant correlations between depression scores and reduced FA in the splenium of the corpus callosum. In contrast, those with lowest CPO demonstrated significant correlations between irritability scores and widespread FA reductions. There was no significant relationship between apathy and FA throughout the whole brain. We demonstrate that white matter changes associated with both depression and irritability in HD occur at different stages of disease progression concomitant with their clinical presentation.

Health related social exclusion in Europe: a multilevel study of the role of welfare generosity

PubMed Central

2013-01-01

Introduction The aim of this paper was to investigate the association between health, social position, social participation and the welfare state. Extending recent research on the social consequences of poor health, we asked whether and how welfare generosity is related to the risk of social exclusion associated with combinations of poor health, low education and economic inactivity. Methods Our analyses are based on data from the European Social Survey, round 3 (2006/7), comprising between 21,205 and 21,397 individuals, aged 25–59 years, within 21 European welfare states. The analyses were conducted by means of multilevel logistic regression analysis in STATA 12. Results The results demonstrated that the risk of non-participation in social networks decreased as welfare generosity increased. The risk of social exclusion, i.e. non-participation in social networks among disadvantaged groups, seldom differed from the overall association, and in absolute terms it was invariably smaller in more generous welfare state contexts. Conclusions The results showed that there were no indications of higher levels of non-participation among disadvantaged groups in more generous welfare states. On the contrary, resources made available by the welfare state seemed to matter to all individuals in terms of overall lower levels of non-participation. As such, these results demonstrate the importance of linking health related social exclusion to the social policy context. PMID:24073744

Health related social exclusion in Europe: a multilevel study of the role of welfare generosity.

PubMed

Saltkjel, Therese; Dahl, Espen; van der Wel, Kjetil A

2013-09-28

The aim of this paper was to investigate the association between health, social position, social participation and the welfare state. Extending recent research on the social consequences of poor health, we asked whether and how welfare generosity is related to the risk of social exclusion associated with combinations of poor health, low education and economic inactivity. Our analyses are based on data from the European Social Survey, round 3 (2006/7), comprising between 21,205 and 21,397 individuals, aged 25-59 years, within 21 European welfare states. The analyses were conducted by means of multilevel logistic regression analysis in STATA 12. The results demonstrated that the risk of non-participation in social networks decreased as welfare generosity increased. The risk of social exclusion, i.e. non-participation in social networks among disadvantaged groups, seldom differed from the overall association, and in absolute terms it was invariably smaller in more generous welfare state contexts. The results showed that there were no indications of higher levels of non-participation among disadvantaged groups in more generous welfare states. On the contrary, resources made available by the welfare state seemed to matter to all individuals in terms of overall lower levels of non-participation. As such, these results demonstrate the importance of linking health related social exclusion to the social policy context.

Impact of Exposure to Childhood Maltreatment on Transitions to Alcohol Dependence in Women and Men.

PubMed

Oberleitner, Lindsay M S; Smith, Philip H; Weinberger, Andrea H; Mazure, Carolyn M; McKee, Sherry A

2015-11-01

Childhood maltreatment decreases age of first use and speeds the transition from first use to dependence (i.e., telescoping) for alcohol use, however, it is currently unknown whether this influence is the same for men and women. Analyses were conducted with the National Epidemiologic Survey on Alcohol and Related Conditions (n = 34,653). Outcome variables included age of alcohol initiation and time to onset of Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition alcohol dependence. Predictor variables included gender and childhood maltreatment. Linear and Poisson regression analyses were conducted. Results demonstrated that in regard to age of drinking initiation, individuals who experienced childhood maltreatment initiated 1 year earlier than those without maltreatment, however, there was no interaction of this relationship with gender. Regarding the time to dependence, it was found that women who experienced childhood maltreatment demonstrated telescoping (shorter time between onset and dependence) compared to women without maltreatment and men (both with and without maltreatment). Women with a history of childhood maltreatment are particularly vulnerable to an accelerated time from initiation of alcohol use until dependence, a pattern indicative of increased negative alcohol-related outcomes. Findings highlight the need for development of gender-specific prevention efforts and behavioral treatments to aid in early intervention of problematic alcohol use in women. © The Author(s) 2015.

Does Wartime Captivity Affect Late-life Mental Health? A Study of Vietnam-era Repatriated Prisoners of War

PubMed Central

Park, Crystal L.; Kaiser, Anica Pless; Spiro, Avron; King, Daniel W.; King, Lynda A.

2012-01-01

Our earlier study of U.S. prisoners of war in Vietnam (King et al., 2011) examined personal and military demographics and aspects of the stressful experience of wartime imprisonment as they related to psychological well-being shortly after homecoming in 1973. Research with repatriated prisoners of war (RPWs) from other military eras suggests that the severity of captivity stressors might predict long-term distress. However, the extent to which effects of the captivity experience persisted for Vietnam-era RPWs is unknown. The present study extended our previous analyses by examining the associations of demographic factors, captivity stressors, and repatriation mental health with subsequent symptoms of posttraumatic stress disorder (PTSD), anxiety, and depressive symptoms (measured nearly 30 years later) in a sample of 292 Vietnam-era RPWs. Results indicated that although most of the men in our sample were within normal limits on anxiety and depressive symptoms, a substantial minority reported experiencing clinically significant levels. Levels of PTSD symptoms were generally low, with only a modest proportion demonstrating elevations. Multiple regression analyses showed that age at capture and posttraumatic stress symptoms at repatriation predicted all three long-term mental health outcomes. In addition, physical torture predicted long-term PTSD symptoms. Findings highlight the potential long-term effects of wartime captivity, and also suggest that most Vietnam-era RPWs demonstrate remarkable resilience to extraordinarily stressful life experiences. PMID:22984347

Testing Mediation Using Multiple Regression and Structural Equation Modeling Analyses in Secondary Data

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…

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…

Dietary magnesium and potassium intakes and circulating magnesium are associated with heel bone ultrasound attenuation and osteoporotic fracture risk in the EPIC-Norfolk cohort study.

PubMed

Hayhoe, Richard P G; Lentjes, Marleen A H; Luben, Robert N; Khaw, Kay-Tee; Welch, Ailsa A

2015-08-01

In our aging population, maintenance of bone health is critical to reduce the risk of osteoporosis and potentially debilitating consequences of fractures in older individuals. Among modifiable lifestyle and dietary factors, dietary magnesium and potassium intakes are postulated to influence bone quality and osteoporosis, principally via calcium-dependent alteration of bone structure and turnover. We investigated the influence of dietary magnesium and potassium intakes, as well as circulating magnesium, on bone density status and fracture risk in an adult population in the United Kingdom. A random subset of 4000 individuals from the European Prospective Investigation into Cancer and Nutrition-Norfolk cohort of 25,639 men and women with baseline data was used for bone density cross-sectional analyses and combined with fracture cases (n = 1502) for fracture case-cohort longitudinal analyses (mean follow-up 13.4 y). Relevant biological, lifestyle, and dietary covariates were used in multivariate regression analyses to determine associations between dietary magnesium and potassium intakes and calcaneal broadband ultrasound attenuation (BUA), as well as in Prentice-weighted Cox regression to determine associated risk of fracture. Separate analyses, excluding dietary covariates, investigated associations of BUA and fractures with serum magnesium concentration. Statistically significant positive trends in calcaneal BUA for women (n = 1360) but not men (n = 968) were apparent across increasing quintiles of magnesium plus potassium (Mg+K) z score intake (P = 0.03) or potassium intake alone (P = 0.04). Reduced hip fracture risk in both men (n = 1958) and women (n = 2755) was evident for individuals in specific Mg+K z score intake quintiles compared with the lowest. Statistically significant trends in fracture risk in men across serum magnesium concentration groups were apparent for spine fractures (P = 0.02) and total hip, spine, and wrist fractures (P = 0.02). None of these individual statistically significant associations remained after adjustment for multiple testing. These findings enhance the limited literature studying the association of magnesium and potassium with bone density and demonstrate that further investigation is warranted into the mechanisms involved and the potential protective role against osteoporosis. © 2015 American Society for Nutrition.

Aspiration Thrombectomy and Drug-Eluting Stent Implantation Decrease the Occurrence of Angina Pectoris One Year After Acute Myocardial Infarction.

PubMed

Lee, Wei-Chieh; Fang, Chih-Yuan; Chen, Huang-Chung; Hsueh, Shu-Kai; Chen, Chien-Jen; Yang, Cheng-Hsu; Yip, Hon-Kan; Hang, Chi-Ling; Wu, Chiung-Jen; Fang, Hsiu-Yu

2016-04-01

Angina pectoris is a treatable symptom that is associated with mortality and decreased quality of life. Angina eradication is a primary care goal of care after an acute myocardial infarction (AMI). Our aim was to evaluate factors influencing angina pectoris 1 year after an AMI.From January 2005 to December 2013, 1547 patient received primary percutaneous intervention in our hospital for an acute ST-segment elevation myocardial infarction (MI). Of these patients, 1336 patients did not experience post-MI angina during a 1-year follow-up, and 211 patients did. Univariate and multivariate logistic regression analyses were performed to identify the factors influencing angina pectoris 1 year after an AMI. Propensity score matched analyses were performed for subgroups analyses.The average age of the patients was 61.08 ± 12.77 years, with a range of 25 to 97 years, and 82.9% of the patients were male. During 1-year follow-up, 13.6% of the patients experienced post-MI angina. There was a longer chest pain-to-reperfusion time in the post-MI angina group (P = 0.01), as well as a higher fasting sugar level, glycohemoglobin (HbA1C), serum creatinine, troponin-I and creatine kinase MB (CK-MB). The post-MI angina group also had a higher prevalence of multiple-vessel disease. Manual thrombectomy, and distal protective device and intracoronary glycoprotein IIb/IIIa inhibitor injection were used frequently in the no post-MI angina group. Antiplatelet agents and post-MI medication usage were similar between the 2 groups. Multivariate logistic regression analyses demonstrated that prior MI was a positive independent predictor of occurrence of post-MI angina. Manual thrombectomy use and drug-eluting stent implantation were negative independent predictors of post-MI angina. Higher troponin-I and longer chest pain-to-reperfusion time exhibited a trend toward predicting post-MI angina.Prior MIs were strong, independent predictors of post-MI angina. Manual thrombectomy and drug-eluting stent implantation could decrease the occurrence of angina pectoris 1 year after an AMI, decrease long-term healthy costs, and increase post-MI quality of life.

Aspiration Thrombectomy and Drug-Eluting Stent Implantation Decrease the Occurrence of Angina Pectoris One Year After Acute Myocardial Infarction

PubMed Central

Lee, Wei-Chieh; Fang, Chih-Yuan; Chen, Huang-Chung; Hsueh, Shu-Kai; Chen, Chien-Jen; Yang, Cheng-Hsu; Yip, Hon-Kan; Hang, Chi-Ling; Wu, Chiung-Jen; Fang, Hsiu-Yu

2016-01-01

Abstract Angina pectoris is a treatable symptom that is associated with mortality and decreased quality of life. Angina eradication is a primary care goal of care after an acute myocardial infarction (AMI). Our aim was to evaluate factors influencing angina pectoris 1 year after an AMI. From January 2005 to December 2013, 1547 patient received primary percutaneous intervention in our hospital for an acute ST-segment elevation myocardial infarction (MI). Of these patients, 1336 patients did not experience post-MI angina during a 1-year follow-up, and 211 patients did. Univariate and multivariate logistic regression analyses were performed to identify the factors influencing angina pectoris 1 year after an AMI. Propensity score matched analyses were performed for subgroups analyses. The average age of the patients was 61.08 ± 12.77 years, with a range of 25 to 97 years, and 82.9% of the patients were male. During 1-year follow-up, 13.6% of the patients experienced post-MI angina. There was a longer chest pain-to-reperfusion time in the post-MI angina group (P = 0.01), as well as a higher fasting sugar level, glycohemoglobin (HbA1C), serum creatinine, troponin-I and creatine kinase MB (CK-MB). The post-MI angina group also had a higher prevalence of multiple-vessel disease. Manual thrombectomy, and distal protective device and intracoronary glycoprotein IIb/IIIa inhibitor injection were used frequently in the no post-MI angina group. Antiplatelet agents and post-MI medication usage were similar between the 2 groups. Multivariate logistic regression analyses demonstrated that prior MI was a positive independent predictor of occurrence of post-MI angina. Manual thrombectomy use and drug-eluting stent implantation were negative independent predictors of post-MI angina. Higher troponin-I and longer chest pain-to-reperfusion time exhibited a trend toward predicting post-MI angina. Prior MIs were strong, independent predictors of post-MI angina. Manual thrombectomy and drug-eluting stent implantation could decrease the occurrence of angina pectoris 1 year after an AMI, decrease long-term healthy costs, and increase post-MI quality of life. PMID:27124029

Selecting risk factors: a comparison of discriminant analysis, logistic regression and Cox's regression model using data from the Tromsø Heart Study.

PubMed

Brenn, T; Arnesen, E

1985-01-01

For comparative evaluation, discriminant analysis, logistic regression and Cox's model were used to select risk factors for total and coronary deaths among 6595 men aged 20-49 followed for 9 years. Groups with mortality between 5 and 93 per 1000 were considered. Discriminant analysis selected variable sets only marginally different from the logistic and Cox methods which always selected the same sets. A time-saving option, offered for both the logistic and Cox selection, showed no advantage compared with discriminant analysis. Analysing more than 3800 subjects, the logistic and Cox methods consumed, respectively, 80 and 10 times more computer time than discriminant analysis. When including the same set of variables in non-stepwise analyses, all methods estimated coefficients that in most cases were almost identical. In conclusion, discriminant analysis is advocated for preliminary or stepwise analysis, otherwise Cox's method should be used.

Hypnotism as a Function of Trance State Effects, Expectancy, and Suggestibility: An Italian Replication.

PubMed

Pekala, Ronald J; Baglio, Francesca; Cabinio, Monia; Lipari, Susanna; Baglio, Gisella; Mendozzi, Laura; Cecconi, Pietro; Pugnetti, Luigi; Sciaky, Riccardo

2017-01-01

Previous research using stepwise regression analyses found self-reported hypnotic depth (srHD) to be a function of suggestibility, trance state effects, and expectancy. This study sought to replicate and expand that research using a general state measure of hypnotic responsivity, the Phenomenology of Consciousness Inventory: Hypnotic Assessment Procedure (PCI-HAP). Ninety-five participants completed an Italian translation of the PCI-HAP, with srHD scores predicted from the PCI-HAP assessment items. The regression analysis replicated the previous research results. Additionally, stepwise regression analyses were able to predict the srHD score equally well using only the PCI dimension scores. These results not only replicated prior research but suggest how this methodology to assess hypnotic responsivity, when combined with more traditional neurophysiological and cognitive-behavioral methodologies, may allow for a more comprehensive understanding of that enigma called hypnosis.

Satisfaction and adherence in patients with iron overload receiving iron chelation therapy as assessed by a newly developed patient instrument.

PubMed

Rofail, Diana; Abetz, Linda; Viala, Muriel; Gait, Claire; Baladi, Jean-Francois; Payne, Krista

2009-01-01

This study assesses satisfaction with iron chelation therapy (ICT) based on a reliable and valid instrument, and explores the relationship between satisfaction and adherence to ICT. Patients in the USA and UK completed a new "Satisfaction with ICT" (SICT) instrument consisting of 28 items, three pertaining to adherence. Simple and multivariate regression analyses assessed the relationship between satisfaction with different aspects of ICT and adherence. First assessments of the SICT instrument indicate its validity and reliability. Recommended thresholds for internal consistency, convergent validity, discriminant validity, and floor and ceiling effects were met. A number of variables were identified in the simple linear regression analyses as significant predictors of "never thinking about stopping ICT," a proxy for adherence. These significant variables were entered into the multivariate model to assess the combined factor effects, explaining 42% of the total variance of "never thinking about stopping ICT." A significant and positive relationship was demonstrated between "never thinking about stopping ICT" and age (P = 0.04), Perceived Effectiveness of ICT (P = 0.003), low Burden of ICT (P = 0.002), and low Side Effects of ICT (P = 0.01). The SICT is a reliable and valid instrument which will be useful in ICT clinical trials. Furthermore, the administration of ICT by slow subcutaneous infusion negatively impacts on satisfaction with ICT which was shown to be a determinant of adherence. This points to the need for new more convenient and less burdensome oral iron chelators to increase adherence, and ultimately to improve patient outcomes.

Chronic care management for patients with COPD: a critical review of available evidence.

PubMed

Lemmens, Karin M M; Lemmens, Lidwien C; Boom, José H C; Drewes, Hanneke W; Meeuwissen, Jolanda A C; Steuten, Lotte M G; Vrijhoef, Hubertus J M; Baan, Caroline A

2013-10-01

Clinical diversity and methodological heterogeneity exists between studies on chronic care management. This study aimed to examine the effectiveness of chronic care management in chronic obstructive pulmonary disease (COPD) while taking heterogeneity into account, enabling the understanding of and the decision making about such programmes. Three investigated sources of heterogeneity were study quality, length of follow-up, and number of intervention components. We performed a review of previously published reviews and meta-analyses on COPD chronic care management. Their primary studies that were analyzed as statistical, clinical and methodological heterogeneity were present. Meta-regression analyses were performed to explain the variances among the primary studies. Generally, the included reviews showed positive results on quality of life and hospitalizations. Inconclusive effects were found on emergency department visits and no effects on mortality. Pooled effects on hospitalizations, emergency department visits and quality of life of primary studies did not reach significant improvement. No effects were found on mortality. Meta-regression showed that the number of components of chronic care management programmes explained present heterogeneity for hospitalizations and emergency department visits. Four components showed significant effects on hospitalizations, whereas two components had significant effects on emergency department visits. Methodological study quality and length of follow-up did not significantly explain heterogeneity. This study demonstrated that COPD chronic care management has the potential to improve outcomes of care; heterogeneity in outcomes was explained. Further research is needed to elucidate the diversity between COPD chronic care management studies in terms of the effects measured and strengthen the support for chronic care management. © 2011 John Wiley & Sons Ltd.

Proposing a Tentative Cut Point for the Compulsive Sexual Behavior Inventory

PubMed Central

Storholm, Erik David; Fisher, Dennis G.; Napper, Lucy E.; Reynolds, Grace L.

2015-01-01

Bivariate analyses were utilized in order to identify the relations between scores on the Compulsive Sexual Behavior Inventory (CSBI) and self-report of risky sexual behavior and drug abuse among 482 racially and ethnically diverse men and women. CSBI scores were associated with both risky sexual behavior and drug abuse among a diverse non-clinical sample, thereby providing evidence of criterion-related validity. The variables that demonstrated a high association with the CSBI were subsequently entered into a multiple regression model. Four variables (number of sexual partners in the last 30 days, self-report of trading drugs for sex, having paid for sex, and perceived chance of acquiring HIV) were retained as variables with good model fit. Receiver operating characteristic (ROC) curve analyses were conducted in order to determine the optimal tentative cut point for the CSBI. The four variables retained in the multiple regression model were utilized as exploratory gold standards in order to construct ROC curves. The ROC curves were then compared to one another in order to determine the point that maximized both sensitivity and specificity in the identification of compulsive sexual behavior with the CSBI scale. The current findings suggest that a tentative cut point of 40 may prove clinically useful in discriminating between persons who exhibit compulsive sexual behavior and those who do not. Because of the association between compulsive sexual behavior and HIV, STIs, and drug abuse, it is paramount that a psychometrically sound measure of compulsive sexual behavior is made available to all healthcare professionals working in disease prevention and other areas. PMID:21203814

Could yoga practice improve treatment-related side effects and quality of life for women with breast cancer? A systematic review and meta-analysis.

PubMed

Pan, Yuanqing; Yang, Kehu; Wang, Yuliang; Zhang, Laiping; Liang, Haiqing

2017-04-01

To determine if yoga as a complementary and alternative therapy was associated with enhanced health and treatment-related side effects in patients with breast cancer. This systematic review examines whether yoga practice provides any measurable benefit, both physically and psychologically, for women with breast cancer. PubMed, EMBASE and the Cochrane Library for randomized controlled trials (RCTs) throughout June 2013. We evaluated the quality of the included studies by the Cochrane Handbook 5.2 standards and analyzed the data using the Stata software, version 10.0. Meta-regression and subgroup analysis were also performed to identify additional predictors of outcome and to assess heterogeneity. Sixteen RCTs with a total of 930 participants were included. Comparing yoga groups to control groups, there was a statistically significant difference in overall health-related quality of life, depression, anxiety and gastrointestinal symptoms. Meta-regression analyses revealed that the duration of yoga practice and type of control group partly explained the heterogeneity. Subgroup analyses revealed that yoga had a positive effect on anxiety only when it had been practiced for longer than 3 months. Only the wait-list control group showed an effect of yoga on physical well-being. The current evidence demonstrates that yoga practice could be effective in enhancing health and managing some treatment-related side effects for patients recovering from breast cancer. In future clinical studies, clinicians should consider the patient's wishes along with the current best evidence of the effects of yoga practice in their clinical decision-making. © 2015 Wiley Publishing Asia Pty Ltd.

Maxillary hypoplasia in the cleft patient: contribution of orthodontic dental space closure to orthognathic surgery.

PubMed

Lee, Justine C; Slack, Ginger C; Walker, Ryann; Graves, Lindsay; Yen, Sandra; Woo, Jessica; Ambaram, Rishal; Martz, Martin G; Kawamoto, Henry K; Bradley, James P

2014-02-01

Cleft lip and palate surgery in the developing child is known to be associated with maxillary hypoplasia. However, the effects of nonsurgical manipulations on maxillary growth have not been well investigated. The authors present the contribution of orthodontic dental space closure with canine substitution to maxillary hypoplasia and the need for orthognathic surgery. Cleft lip/palate and cleft palate patients older than 15 years of age were reviewed for dental anomalies, orthodontic canine substitution, and Le Fort I advancement. Skeletal relationships of the maxilla to the skull base (SNA), mandible (ANB), and facial height were determined on lateral cephalograms. Logistic regression analyses were performed to estimate odds ratios. Ninety-five patients were reviewed (mean age, 18.1 years). In 65 patients with congenitally missing teeth, 55 percent with patent dental spaces required Le Fort I advancement. In contrast, 89 percent who underwent canine substitution required Le Fort I advancement (p = 0.004). Canine substitution is associated with a statistically significant increase in maxillary retrognathia when compared with dental space preservation on lateral cephalograms (mean SNA, 75.2 and 79.0, respectively; p = 0.006). Adjusting for missing dentition, logistic regression analyses demonstrated that canine substitution is an independent predictor for orthognathic surgery (OR, 6.47) and maxillary retrusion defined by SNA < 78 (OR, 8.100). The coordination of orthodontia and surgery is essential to cleft care. The authors report a strong association between orthodontic cleft closure using canine substitution with maxillary hypoplasia and subsequent Le Fort I advancement, and suggest systematic criteria for management of cleft-related dental agenesis. Therapeutic, III.

Subclinical hypothyroidism and diabetes as risk factors for postoperative stiff shoulder.

PubMed

Blonna, Davide; Fissore, Francesca; Bellato, Enrico; La Malfa, Marco; Calò, Michel; Bonasia, Davide Edoardo; Rossi, Roberto; Castoldi, Filippo

2017-07-01

Postoperative stiffness can be a disabling condition after arthroscopic shoulder surgery. The purpose of this study was to analyse the potential contribution of subclinical forms of hypothyroidism and diabetes in the development of postoperative shoulder stiffness. A prospective study was conducted on 65 consecutive patients scheduled for arthroscopic subacromial decompression or rotator cuff tear repair. Patients with preoperative stiffness were excluded. Preoperative measurements of free thyroxine, free triiodothyronine, thyroid-stimulating hormone and fasting glycaemia were taken in all patients to detect subclinical forms of diabetes and hypothyroidism. A follow-up was planned at 30, 60, 90 and 180 days after surgery. According to range of motion measurements, postoperative stiffness was classified as severe or moderate at follow-up. Univariate and logistic regression analyses were performed for the assessment of risk factors for stiffness. The overall incidence of postoperative stiffness was 29 % (19/65) in our cohort. Considering only the arthroscopic rotator cuff repairs, this incidence was 23 % (7/31). A new diagnosis of subclinical forms of diabetes or hypothyroidism was made in five cases. All five of these cases developed postoperative stiffness. The logistic regression analysis demonstrated that hypothyroidism was a risk factor for severe stiffness (RR = 25; p = 0.001) and that diabetes was a risk factor for moderate stiffness (RR = 5.7; p = 0.03). The postoperative stiffness in the majority of patients can be predicted by a careful analysis of past medical history and by detecting subclinical forms of hypothyroidism and diabetes. Prognostic study, Level II.

Impact of thoracic epidural analgesia on blood loss in radical retropubic prostatectomy.

PubMed

Baumunk, Daniel; Strang, Christof Maria; Kropf, Siegfried; Schäfer, Michael; Schrader, Mark; Weikert, Steffen; Cash, Hannes; Breckwoldt, Jan; Miller, Kurt; Hachenberg, Thomas; Schostak, Martin

2014-01-01

Radical retropubic prostatectomy (RRP) is associated with an increased risk of intraoperative blood loss and the necessity of transfusions. This prospective randomised clinical study evaluates the influence of thoracic epidural analgesia (TEA) on blood loss in RRP. 235 patients were randomised: TEA in group 1 (n = 116; general anaesthesia + TEA) comprised continuous administration of 0.25% bupivacaine, while group 2 (n = 119; general anaesthesia alone) received intravenous analgesia with fentanyl (intubation: 2 µg/kg; maintenance: 0.1-0.3 mg). A restrictive infusion regimen (<1,000 ml until specimen removal) was administered in both groups. Blood loss, infusion rates and anaesthesiological parameters were recorded and analysed using regression models and analyses of variance. Haemoglobin difference between the pre- and the first postoperative day (group 1: 3.35 ± 1.16 g/dl; group 2: 3.56 ± 1.42 g/dl; p = 0.19), overall blood loss (group 1: 665 ± 431.5 ml; group 2: 705 ± 881 ml; p = 0.73) and transfusion rates (0.4% intraoperatively; 2.55% postoperatively; p = 1.0) did not show group differences. In regression analysis blood loss was influenced by preoperative haemoglobin levels (p < 0.0001), patients' weight (p = 0.018) and duration of the operation (p = 0.017). This study did not demonstrate a direct impact of TEA on intraoperative blood loss and transfusion rates in RRP. Further randomised clinical trials are needed to evaluate an impact of the different anaesthetic procedures presented alone or in combination on blood loss. 2014 S. Karger AG, Basel.

Proposing a tentative cut point for the Compulsive Sexual Behavior Inventory.

PubMed

Storholm, Erik David; Fisher, Dennis G; Napper, Lucy E; Reynolds, Grace L; Halkitis, Perry N

2011-12-01

Bivariate analyses were utilized in order to identify the relations between scores on the Compulsive Sexual Behavior Inventory (CSBI) and self-report of risky sexual behavior and drug abuse among 482 racially and ethnically diverse men and women. CSBI scores were associated with both risky sexual behavior and drug abuse among a diverse non-clinical sample, thereby providing evidence of criterion-related validity. The variables that demonstrated a high association with the CSBI were subsequently entered into a multiple regression model. Four variables (number of sexual partners in the last 30 days, self-report of trading drugs for sex, having paid for sex, and perceived chance of acquiring HIV) were retained as variables with good model fit. Receiver operating characteristic (ROC) curve analyses were conducted in order to determine the optimal tentative cut point for the CSBI. The four variables retained in the multiple regression model were utilized as exploratory gold standards in order to construct ROC curves. The ROC curves were then compared to one another in order to determine the point that maximized both sensitivity and specificity in the identification of compulsive sexual behavior with the CSBI scale. The current findings suggest that a tentative cut point of 40 may prove clinically useful in discriminating between persons who exhibit compulsive sexual behavior and those who do not. Because of the association between compulsive sexual behavior and HIV, STIs, and drug abuse, it is paramount that a psychometrically sound measure of compulsive sexual behavior is made available to all healthcare professionals working in disease prevention and other areas.

Glutamatergic system abnormalities in posttraumatic stress disorder.

PubMed

Nishi, Daisuke; Hashimoto, Kenji; Noguchi, Hiroko; Hamazaki, Kei; Hamazaki, Tomohito; Matsuoka, Yutaka

2015-12-01

Accumulating evidence suggests involvement of the glutamatergic system in the biological mechanisms of posttraumatic stress disorder (PTSD), but few studies have demonstrated an association between glutamatergic system abnormalities and PTSD diagnosis or severity. We aimed to examine whether abnormalities in serum glutamate and in the glutamine/glutamate ratio were associated with PTSD diagnosis and severity in severely injured patients at risk for PTSD and major depressive disorder (MDD). This is a nested case-control study in TPOP (Tachikawa project for prevention of posttraumatic stress disorder with polyunsaturated fatty acid) trial. Diagnosis and severity of PTSD were assessed 3 months after the accidents using the Clinician-Administered PTSD Scale. The associations of glutamate levels and the glutamine/glutamate ratio with diagnosis and severity of PTSD and MDD were investigated by univariate and multiple linear regression analyses. Ninety-seven of 110 participants (88 %) completed assessments at 3 months. Serum glutamate levels were significantly higher for participants with full or partial PTSD than for participants without PTSD (p = 0.049) and for participants with MDD than for participants without MDD (p = 0.048). Multiple linear regression analyses showed serum glutamate levels were significantly positively associated with PTSD severity (p = 0.02) and MDD severity (p = 0.03). The glutamine/glutamate ratio was also significantly inversely associated with PTSD severity (p = 0.03), but not with MDD severity (p = 0.07). These findings suggest that the glutamatergic system may play a major role in the pathogenesis of PTSD and the need for new treatments targeting the glutamatergic system to be developed for PTSD.

Quality of life outcomes in patients living with stoma.

PubMed

Anaraki, Fakhrialsadat; Vafaie, Mohamad; Behboo, Roobic; Maghsoodi, Nakisa; Esmaeilpour, Sahar; Safaee, Azadeh

2012-09-01

Despite efforts to maintain the intestinal tissue and treat gastrointestinal disease, a large number of patients undergo ostomy surgery each year. Using stoma reduces the patient's quality of life (QOL) greatly. Although there are approximately 3000 patients in Iran; there is little information about the impact of stoma on their QOL. The study aims to evaluate QOL of stoma patients using a special measurement tool. This survey was a cross-sectional study that was conducted on 102 random samples of stoma patients. The City of Hope Quality of Life-Ostomy Questionnaire was used for collecting demographic and clinical information and evaluating QOL. Univariate and multiple regression analyses were performed to identify predictors of QOL. The mean score for the overall QOL for stoma patients was 7.48 ± 0.9. 70% of patients were dissatisfied with sexual activities. More than half of them reported feelings of depression following stoma surgery. Univariate analysis indicated that factors such as the type of ostomy (temporary/permanent), the underlying disease that had led to the stoma, depression, problem with location of ostomy, and change in clothing style had significant effects on overall QOL and its subscales (P < 0.05). The results of the regression analyses showed that only depression and problem with the location of ostomy were statistically significant in predicting patients' QOL and its subscales (P < 0.05). The findings demonstrated that living with stoma influences the overall aspect of QOL. Education for the patients and their families is important for improving the stoma patients' QOL. Sexual and psychological consultation may also improve patients' QOL.

Complete immunization coverage and its determinants among children in Malaysia: findings from the National Health and Morbidity Survey (NHMS) 2016.

PubMed

Lim, K K; Chan, Y Y; Noor Ani, A; Rohani, J; Siti Norfadhilah, Z A; Santhi, M R

2017-12-01

The success of the Expanded Program on Immunization among children will greatly reduce the burden of illness and disability from vaccine preventable diseases. The aim of the study was to evaluate the complete immunization coverage and its determinants among children aged 12-23 months in Malaysia. Cross-sectional study. Data on immunization were extracted from the 2016 National Health and Morbidity Survey. Complete immunization coverage was classified as received all recommended primary vaccine doses by the age of 12 months and verified by vaccination cards, and incompletely immunized if they received partially recommended vaccine dose or not received any recommended vaccine dose or had no vaccination card. The multiple logistic regression analyses were conducted to determine the sociodemographic factors associated with complete immunization coverage. The overall complete immunization coverage among children (verified by cards) was 86.4% (n = 8920, 95% confidence interval: 85.4-87.4). Multivariable logistic regression analyses model revealed that factors significantly associated with complete immunization coverage were ethnicity, occupation of the mother, head of household's education level, and head of household's occupation. While sex, citizenship, household income, mother's age, and marital status were not significantly associated with complete immunization coverage. According to the World Health Organization criteria, the present study demonstrated that the immunization coverage of 86.4% is still unsatisfactory. Thus, the current intervention program should be enhanced in order to achieve the 95% coverage for all antigens in the national vaccination program. Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Explorative spatial analysis of traffic accident statistics and road mortality among the provinces of Turkey.

PubMed

Erdogan, Saffet

2009-10-01

The aim of the study is to describe the inter-province differences in traffic accidents and mortality on roads of Turkey. Two different risk indicators were used to evaluate the road safety performance of the provinces in Turkey. These indicators are the ratios between the number of persons killed in road traffic accidents (1) and the number of accidents (2) (nominators) and their exposure to traffic risk (denominator). Population and the number of registered motor vehicles in the provinces were used as denominators individually. Spatial analyses were performed to the mean annual rate of deaths and to the number of fatal accidents that were calculated for the period of 2001-2006. Empirical Bayes smoothing was used to remove background noise from the raw death and accident rates because of the sparsely populated provinces and small number of accident and death rates of provinces. Global and local spatial autocorrelation analyses were performed to show whether the provinces with high rates of deaths-accidents show clustering or are located closer by chance. The spatial distribution of provinces with high rates of deaths and accidents was nonrandom and detected as clustered with significance of P<0.05 with spatial autocorrelation analyses. Regions with high concentration of fatal accidents and deaths were located in the provinces that contain the roads connecting the Istanbul, Ankara, and Antalya provinces. Accident and death rates were also modeled with some independent variables such as number of motor vehicles, length of roads, and so forth using geographically weighted regression analysis with forward step-wise elimination. The level of statistical significance was taken as P<0.05. Large differences were found between the rates of deaths and accidents according to denominators in the provinces. The geographically weighted regression analyses did significantly better predictions for both accident rates and death rates than did ordinary least regressions, as indicated by adjusted R(2) values. Geographically weighted regression provided values of 0.89-0.99 adjusted R(2) for death and accident rates, compared with 0.88-0.95, respectively, by ordinary least regressions. Geographically weighted regression has the potential to reveal local patterns in the spatial distribution of rates, which would be ignored by the ordinary least regression approach. The application of spatial analysis and modeling of accident statistics and death rates at provincial level in Turkey will help to identification of provinces with outstandingly high accident and death rates. This could help more efficient road safety management in Turkey.

Forest Type and Above Ground Biomass Estimation Based on Sentinel-2A and WorldView-2 Data Evaluation of Predictor nd Data Suitability

NASA Astrophysics Data System (ADS)

Fritz, Andreas; Enßle, Fabian; Zhang, Xiaoli; Koch, Barbara

2016-08-01

The present study analyses the two earth observation sensors regarding their capability of modelling forest above ground biomass and forest density. Our research is carried out at two different demonstration sites. The first is located in south-western Germany (region Karlsruhe) and the second is located in southern China in Jiangle County (Province Fujian). A set of spectral and spatial predictors are computed from both, Sentinel-2A and WorldView-2 data. Window sizes in the range of 3*3 pixels to 21*21 pixels are computed in order to cover the full range of the canopy sizes of mature forest stands. Textural predictors of first and second order (grey-level-co-occurrence matrix) are calculated and are further used within a feature selection procedure. Additionally common spectral predictors from WorldView-2 and Sentinel-2A data such as all relevant spectral bands and NDVI are integrated in the analyses. To examine the most important predictors, a predictor selection algorithm is applied to the data, whereas the entire predictor set of more than 1000 predictors is used to find most important ones. Out of the original set only the most important predictors are then further analysed. Predictor selection is done with the Boruta package in R (Kursa and Rudnicki (2010)), whereas regression is computed with random forest. Prior the classification and regression a tuning of parameters is done by a repetitive model selection (100 runs), based on the .632 bootstrapping. Both are implemented in the caret R pack- age (Kuhn et al. (2016)). To account for the variability in the data set 100 independent runs are performed. Within each run 80 percent of the data is used for training and the 20 percent are used for an independent validation. With the subset of original predictors mapping of above ground biomass is performed.

Elevated blood pressure, race/ethnicity, and C-reactive protein levels in children and adolescents.

PubMed

Lande, Marc B; Pearson, Thomas A; Vermilion, Roger P; Auinger, Peggy; Fernandez, Isabel D

2008-12-01

Adult hypertension is independently associated with elevated C-reactive protein levels, after controlling for obesity and other cardiovascular risk factors. The objective of this study was to determine, with a nationally representative sample of children, whether the relationship between elevated blood pressure and C-reactive protein levels may be evident before adulthood. Cross-sectional data for children 8 to 17 years of age who participated in the National Health and Nutrition Examination Survey between 1999 and 2004 were analyzed. Bivariate analyses compared children with C-reactive protein levels of >3 mg/L versus or=95th percentile and 1.3% had diastolic blood pressure of >or=95th percentile. Children with C-reactive protein levels of >3 mg/L had higher systolic blood pressure, compared with children with C-reactive protein levels of or=95th percentile was independently associated with C-reactive protein levels in boys but not girls. Subset analyses according to race/ethnicity demonstrated that the independent association of elevated systolic blood pressure with C-reactive protein levels was largely limited to black boys. These data indicate that there is interplay between race/ethnicity, elevated systolic blood pressure, obesity, and inflammation in children, a finding that has potential implications for disparities in cardiovascular disease later in life.

Correlation between the complex PSA/total PSA ratio and the free PSA/total PSA ratio, sensitivity and specificity of both markers for the diagnosis of prostate cancer.

PubMed

Pérez-Lanzac-Lorca, A; Barco-Sánchez, A; Romero, E; Martinez-Peinado, A; López-Elorza, F; Sanchez-Sanchez, E; Alvarez-Ossorio-Fernandez, J L; Castiñeiras-Fernández, J

2013-09-01

To compare the behaviour of the PSAcomplex/PSAtotal percentage (PSAc%) against the PSA free/PSA total (PSAl%) and analyse both markers for their usefulness in diagnosing prostate cancer. We measured total PSA (PSAt), free PSA (PSAl), complex PSA (PSAc), PSAl% and PSAc% levels in 158 patients. Of these, 98 (62%) were biopsied for presenting PSAt≥3 ng/dl and PSAl%<20, PSAt>10, suspicious rectal examination or suspicious ultrasound node. We performed linear regression and Passing-Bablok regression analyses. The ROC curves were calculated to study the sensitivity and specificity of PSAl% and PSAc% and were compared to each other. The prostate cancer diagnoses were analysed by PSAl% and PSAc% by applying the χ(2) test. The correlation coefficient (r) was good (0.7447, P<.0001), and the index of determination (r(2)) was 0,5. The result of the Passing-Bablok analysis was a slope of 1.658 (1.452 to 1.897) and an intersection of 2.044 (-0,936 to 5.393). The optimal cutoff for PSAl% (≤14.7854) showed a sensitivity of 89.29% [95% CI, 0,642-0,823] and a specificity of 54.29% (95% CI, 0,642-0,823). The optimal cutoff for PSAc% (>89.7796) had a sensitivity of 71.43% (95% CI, 0,616-0,802) and a specificity of 71.43% (95% CI, 0,616-0,802). There were no significant differences when comparing the areas under the curve of both markers (P=.59). The PPV of PSAl% was less than that of PSAc% (45.7% vs. 71%). There was a good correlation between PSAl% and PSAc%. PSAc% has demonstrated greater specificity and efficacy than PSAl% in the diagnosis of prostate cancer. Copyright © 2012 AEU. Published by Elsevier Espana. All rights reserved.

Workplace gender composition and psychological distress: the importance of the psychosocial work environment.

PubMed

Elwér, Sofia; Johansson, Klara; Hammarström, Anne

2014-03-10

Health consequences of the gender segregated labour market have previously been demonstrated in the light of gender composition of occupations and workplaces, with somewhat mixed results. Associations between the gender composition and health status have been suggested to be shaped by the psychosocial work environment. The present study aims to analyse how workplace gender composition is related to psychological distress and to explore the importance of the psychosocial work environment for psychological distress at workplaces with different gender compositions. The study population consisted of participants from the Northern Swedish Cohort with a registered workplace in 2007 when the participants were 42 years old (N=795). Questionnaire data were supplemented with register data on the gender composition of the participants' workplaces divided into three groups: workplaces with more women, mixed workplaces, and workplaces with more men. Associations between psychological distress and gender composition were analysed with multivariate logistic regression analysis adjusting for socioeconomic position, previous psychological distress, psychosocial work environment factors and gender. Logistic regression analyses (including interaction terms for gender composition and each work environment factor) were also used to assess differential associations between psychosocial work factor and psychological distress according to gender composition. Working at workplaces with a mixed gender composition was related to a higher likelihood of psychological distress compared to workplaces with more men, after adjustments for socioeconomic position, psychological distress at age 21, psychosocial work environment factors and gender. Psychosocial work environment factors did not explain the association between gender composition and psychological distress. The association between gender composition and psychological distress cannot be explained by differences in the perception of the psychosocial work environment and thus the work environment hypothesis is not supported. Workplaces with a mixed gender composition needs further research attention to explain the negative development of psychological distress during working life for both women and men at these workplaces.

Workplace gender composition and psychological distress: the importance of the psychosocial work environment

PubMed Central

2014-01-01

Background Health consequences of the gender segregated labour market have previously been demonstrated in the light of gender composition of occupations and workplaces, with somewhat mixed results. Associations between the gender composition and health status have been suggested to be shaped by the psychosocial work environment. The present study aims to analyse how workplace gender composition is related to psychological distress and to explore the importance of the psychosocial work environment for psychological distress at workplaces with different gender compositions. Methods The study population consisted of participants from the Northern Swedish Cohort with a registered workplace in 2007 when the participants were 42 years old (N = 795). Questionnaire data were supplemented with register data on the gender composition of the participants’ workplaces divided into three groups: workplaces with more women, mixed workplaces, and workplaces with more men. Associations between psychological distress and gender composition were analysed with multivariate logistic regression analysis adjusting for socioeconomic position, previous psychological distress, psychosocial work environment factors and gender. Logistic regression analyses (including interaction terms for gender composition and each work environment factor) were also used to assess differential associations between psychosocial work factor and psychological distress according to gender composition. Results Working at workplaces with a mixed gender composition was related to a higher likelihood of psychological distress compared to workplaces with more men, after adjustments for socioeconomic position, psychological distress at age 21, psychosocial work environment factors and gender. Psychosocial work environment factors did not explain the association between gender composition and psychological distress. Conclusions The association between gender composition and psychological distress cannot be explained by differences in the perception of the psychosocial work environment and thus the work environment hypothesis is not supported. Workplaces with a mixed gender composition needs further research attention to explain the negative development of psychological distress during working life for both women and men at these workplaces. PMID:24612791

Accounting for standard errors of vision-specific latent trait in regression models.

PubMed

Wong, Wan Ling; Li, Xiang; Li, Jialiang; Wong, Tien Yin; Cheng, Ching-Yu; Lamoureux, Ecosse L

2014-07-11

To demonstrate the effectiveness of Hierarchical Bayesian (HB) approach in a modeling framework for association effects that accounts for SEs of vision-specific latent traits assessed using Rasch analysis. A systematic literature review was conducted in four major ophthalmic journals to evaluate Rasch analysis performed on vision-specific instruments. The HB approach was used to synthesize the Rasch model and multiple linear regression model for the assessment of the association effects related to vision-specific latent traits. The effectiveness of this novel HB one-stage "joint-analysis" approach allows all model parameters to be estimated simultaneously and was compared with the frequently used two-stage "separate-analysis" approach in our simulation study (Rasch analysis followed by traditional statistical analyses without adjustment for SE of latent trait). Sixty-six reviewed articles performed evaluation and validation of vision-specific instruments using Rasch analysis, and 86.4% (n = 57) performed further statistical analyses on the Rasch-scaled data using traditional statistical methods; none took into consideration SEs of the estimated Rasch-scaled scores. The two models on real data differed for effect size estimations and the identification of "independent risk factors." Simulation results showed that our proposed HB one-stage "joint-analysis" approach produces greater accuracy (average of 5-fold decrease in bias) with comparable power and precision in estimation of associations when compared with the frequently used two-stage "separate-analysis" procedure despite accounting for greater uncertainty due to the latent trait. Patient-reported data, using Rasch analysis techniques, do not take into account the SE of latent trait in association analyses. The HB one-stage "joint-analysis" is a better approach, producing accurate effect size estimations and information about the independent association of exposure variables with vision-specific latent traits. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

The link between vascular deterioration and branched chain amino acids in a population with high glycated haemoglobin: the SABPA study.

PubMed

Mels, C M; Schutte, A E; Schutte, R; Huisman, H W; Smith, W; Fourie, C M; Kruger, R; van Rooyen, J M; Malan, N T; Malan, L

2013-12-01

Globally the prevalence of non-communicable diseases, such as hypertension and type 2 diabetes, are escalating. Metabolomic studies indicated that circulating branched chain amino acids (BCAAs) are associated with insulin resistance, coronary artery disease and increased risk for cardiovascular events. We aimed to extend the current understanding of the cardiovascular risk associated with BCAAs. We explored whether BCAAs are related to markers of cardiovascular disease in a bi-ethnic population and whether this relationship was influenced by chronic hyperglycaemia. We included 200 African and 209 Caucasian participants, and determined their ambulatory blood pressure and carotid intima-media thickness (cIMT). We analysed blood samples for glycated haemoglobin (HbA1c) and BCAAs. Participants were stratified into two groups according to their HbA1c value using the median cut-off value of 5.6%. Ambulatory BP, cIMT and BCAAs were significantly higher (all p < 0.001) in the high HbA1c group. Single regression analyses indicated significant positive associations of ambulatory blood pressure and cIMT with BCAAs (all p < 0.05) in both the groups. These associations between ambulatory systolic blood pressure (SBP) (r = 0.16, p = 0.035) and cIMT (r = 0.22, p = 0.004) with BCAAs remained in the high HbA1c group after adjusting for age, gender, ethnicity and body mass index (BMI) and were confirmed in multiple regression analyses (ambulatory SBP: R (2) = 0.17, β = 0.21, p = 0.005 and cIMT: R (2) = 0.30, β = 0.19, p = 0.003). Our results demonstrate that BCAAs are independently related to ambulatory BP and cIMT in individuals with high HbA1c levels and suggest that potential cardiovascular deterioration accompany the rise in BCAAs in conditions of hyperglycaemia.

Prognosis Related to Metastatic Burden Measured by 18F-Fluorocholine PET/CT in Castrate Resistant Prostate Cancer

PubMed Central

Kwee, Sandi A.; Lim, John; Watanabe, Alex; Kromer-Baker, Kathleen; Coel, Marc N.

2015-01-01

This study investigates the prognostic significance of metabolically active tumor volume (MATV) measurements applied to fluorine-18 fluorocholine (FC) PET/CT in castrate-resistant prostate cancer (CRPC). Methods FC PET/CT imaging was performed in 30 patients with CRPC. Metastatic disease was quantified on the basis of maximum standardized uptake value (SUVmax), MATV, and total lesion activity (TLA = MATV × mean SUV). Tumor burden indices derived from whole-body summation of PET tumor volume measurements (ie. net MATV and net TLA) were evaluated as variables in Cox regression and Kaplan-Meier survival analyses. Results Net MATV ranged from 0.12 cm3 to 1543.9 cm3 (median 52.6 cm3). Net TLA ranged from 0.40g to 6688.7g (median 225.1g). PSA level at the time of PET correlated significantly with net MATV (Pearson r = 0.65, p = 0.0001) and net TLA (r = 0.60, p = 0.0005) but not highest lesional SUVmax of each scan. Survivors were followed for a median 23 months (range 6 – 38 months). On Cox regression analyses, overall survival was significantly associated with net MATV (p = 0.0068), net TLA (p = 0.0072), and highest lesion SUVmax (p = 0.0173), and borderline associated with PSA level (p = 0.0458). Only net MATV and net TLA remained significant in univariate-adjusted survival analyses. Kaplan-Meier analysis demonstrated significant differences in survival between groups stratified by median net MATV (log-rank P = 0.0371), net TLA (log-rank P = 0.0371), and highest lesion SUVmax (log-rank P = 0.0223). Conclusions Metastatic prostate cancer detected by FC PET/CT can be quantified based on volumetric measurements of tumor metabolic activity. The prognostic value of FC PET/CT may stem from this capacity to assess whole-body tumor burden. With further clinical validation, FC PET-based indices of global disease activity and mortality risk could prove useful in patient-individualized treatment of CRPC. PMID:24676753

Summer microhabitat use of fluvial bull trout in Eastern Oregon streams

USGS Publications Warehouse

Al-Chokhachy, R.; Budy, P.

2007-01-01

The management and recovery of populations of bull trout Salvelinus confluentus requires a comprehensive understanding of habitat use across different systems, life stages, and life history forms. To address these needs, we collected microhabitat use and availability data in three fluvial populations of bull trout in eastern Oregon. We evaluated diel differences in microhabitat use, the consistency of microhabitat use across systems and size-classes based on preference, and our ability to predict bull trout microhabitat use. Diel comparisons suggested bull trout continue to use deeper microhabitats with cover but shift into significantly slower habitats during nighttime periods; however, we observed no discrete differences in substrate use patterns across diel periods. Across life stages, we found that both juvenile and adult bull trout used slow-velocity microhabitats with cover, but the use of specific types varied. Both logistic regression and habitat preference analyses suggested that adult bull trout used deeper habitats than juveniles. Habitat preference analyses suggested that bull trout habitat use was consistent across all three systems, as chi-square tests rejected the null hypotheses that microhabitats were used in proportion to those available (P < 0.0001). Validation analyses indicated that the logistic regression models (juvenile and adult) were effective at predicting bull trout absence across all tests (specificity values = 100%); however, our ability to accurately predict bull trout absence was limited (sensitivity values = 0% across all tests). Our results highlight the limitations of the models used to predict microhabitat use for fish species like bull trout, which occur at naturally low densities. However, our results also demonstrate that bull trout microhabitat use patterns are generally consistent across systems, a pattern that parallels observations at both similar and larger scales and across life history forms. Thus, our results, in combination with previous bull trout habitat studies, provide managers with benchmarks for restoration in highly degraded systems.

Segregation analysis of prostate cancer in France: evidence for autosomal dominant inheritance and residual brother-brother dependence.

PubMed

Valeri, A; Briollais, L; Azzouzi, R; Fournier, G; Mangin, P; Berthon, P; Cussenot, O; Demenais, F

2003-03-01

Four segregation analyses concerning prostate cancer (CaP), three conducted in the United States and one in Northern Europe, have shown evidence for a dominant major gene but with different parameter estimates. A recent segregation analysis of Australian pedigrees has found a better fit of a two-locus model than single-locus models. This model included a dominantly inherited increased risk that was greater at younger ages and a recessively inherited or X-linked increased risk that was greater at older ages. Recent linkage analyses have led to the detection of at least 8 CaP predisposing genes, suggesting a complex inheritance and genetic heterogeneity. To assess the nature of familial aggregation of prostate cancer in France, segregation analysis was conducted in 691 families ascertained through 691 CaP patients, recruited from three French hospitals and unselected with respect to age at diagnosis, clinical stage or family history. This mode of family inclusion, without any particular selection of the probands, is unique, as probands from all previous analyses were selected according to various criteria. Segregation analysis was carried out using the logistic hazard regressive model, as incorporated in the REGRESS program, which can accommodate a major gene effect, residual familial dependences of any origin (genetic and/or environmental), and covariates, while including survival analysis concepts. Segregation analysis showed evidence for the segregation of an autosomal dominant gene (allele frequency of 0.03%) with an additional brother-brother dependence. The estimated cumulative risks of prostate cancer by age 85 years, among subjects with the at-risk genotype, were 86% in the fathers' generation and 99% in the probands' generation. This study supports the model of Mendelian transmission of a rare autosomal dominant gene with high penetrance, and demonstrates that additional genetic and/or common sibling environmental factors are involved to account for the familial clustering of CaP.

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…

Some Insults are Easier to Detect: The Embodied Insult Detection Effect

PubMed Central

Wellsby, Michele; Siakaluk, Paul D.; Pexman, Penny M.; Owen, William J.

2010-01-01

In the present research we examined the effects of bodily experience on processing of insults in a series of semantic categorization tasks we call insult detection tasks (i.e., participants decided whether presented stimuli were insults or not). Two types of insults were used: more embodied insults (e.g., asswipe, ugly), and less embodied insults (e.g., cheapskate, twit), as well as non-insults. In Experiments 1 and 2 the non-insults did not form a single, coherent category (e.g., airbase, polka), whereas in Experiment 3 all the non-insults were compliments (e.g., eyeful, honest). Regardless of type of non-insult used, we observed facilitatory embodied insult effects such that more embodied insults were responded to faster and recalled more often than less embodied insults. In Experiment 4 we used a larger set of insults as stimuli, which allowed hierarchical multiple regression analyses. These analyses revealed that bodily experience ratings accounted for a significant amount of unique response latency, response error, and recall variability for responses to insults, even with several other predictor variables (e.g., frequency, offensiveness, imageability) included in the analyses: responses were faster and more accurate, and there was greater recall for relatively more embodied insults. These results demonstrate that conceptual knowledge of insults is grounded in knowledge gained through bodily experience. PMID:21738511

Acute myeloid and chronic lymphoid leukaemias and exposure to low-level benzene among petroleum workers

PubMed Central

Rushton, L; Schnatter, A R; Tang, G; Glass, D C

2014-01-01

Background: High benzene exposure causes acute myeloid leukaemia (AML). Three petroleum case–control studies identified 60 cases (241 matched controls) for AML and 80 cases (345 matched controls) for chronic lymphoid leukaemia (CLL). Methods: Cases were classified and scored regarding uncertainty by two haematologists using available diagnostic information. Blinded quantitative benzene exposure assessment used work histories and exposure measurements adjusted for era-specific circumstances. Statistical analyses included conditional logistic regression and penalised smoothing splines. Results: Benzene exposures were much lower than previous studies. Categorical analyses showed increased ORs for AML with several exposure metrics, although patterns were unclear; neither continuous exposure metrics nor spline analyses gave increased risks. ORs were highest in terminal workers, particularly for Tanker Drivers. No relationship was found between benzene exposure and risk of CLL, although the Australian study showed increased risks in refinery workers. Conclusion: Overall, this study does not persuasively demonstrate a risk between benzene and AML. A previously reported strong relationship between myelodysplastic syndrome (MDS) (potentially previously reported as AML) at our study's low benzene levels suggests that MDS may be the more relevant health risk for lower exposure. Higher CLL risks in refinery workers may be due to more diverse exposures than benzene alone. PMID:24357793

Retooling CalEnviroScreen: Cumulative Pollution Burden and Race-Based Environmental Health Vulnerabilities in California.

PubMed

Liévanos, Raoul S

2018-04-16

The California Community Environmental Health Screening Tool (CalEnviroScreen) advances research and policy pertaining to environmental health vulnerability. However, CalEnviroScreen departs from its historical foundations and comparable screening tools by no longer considering racial status as an indicator of environmental health vulnerability and predictor of cumulative pollution burden. This study used conceptual frameworks and analytical techniques from environmental health and inequality literature to address the limitations of CalEnviroScreen, especially its inattention to race-based environmental health vulnerabilities. It developed an adjusted measure of cumulative pollution burden from the CalEnviroScreen 2.0 data that facilitates multivariate analyses of the effect of neighborhood racial composition on cumulative pollution burden, net of other indicators of population vulnerability, traffic density, industrial zoning, and local and regional clustering of pollution burden. Principal component analyses produced three new measures of population vulnerability, including Latina/o cumulative disadvantage that represents the spatial concentration of Latinas/os, economic disadvantage, limited English-speaking ability, and health vulnerability. Spatial error regression analyses demonstrated that concentrations of Latinas/os, followed by Latina/o cumulative disadvantage, are the strongest demographic determinants of adjusted cumulative pollution burden. Findings have implications for research and policy pertaining to cumulative impacts and race-based environmental health vulnerabilities within and beyond California.

The paddle move commonly used in magic tricks as a means for analysing the perceptual limits of combined motion trajectories.

PubMed

Hergovich, Andreas; Gröbl, Kristian; Carbon, Claus-Christian

2011-01-01

Following Gustav Kuhn's inspiring technique of using magicians' acts as a source of insight into cognitive sciences, we used the 'paddle move' for testing the psychophysics of combined movement trajectories. The paddle move is a standard technique in magic consisting of a combined rotating and tilting movement. Careful control of the mutual speed parameters of the two movements makes it possible to inhibit the perception of the rotation, letting the 'magic' effect emerge--a sudden change of the tilted object. By using 3-D animated computer graphics we analysed the interaction of different angular speeds and the object shape/size parameters in evoking this motion disappearance effect. An angular speed of 540 degrees s(-1) (1.5 rev. s(-1)) sufficed to inhibit the perception of the rotary movement with the smallest object showing the strongest effect. 90.7% of the 172 participants were not able to perceive the rotary movement at an angular speed of 1125 degrees s(-1) (3.125 rev. s(-1)). Further analysis by multiple linear regression revealed major influences on the effectiveness of the magic trick of object height and object area, demonstrating the applicability of analysing key factors of magic tricks to reveal limits of the perceptual system.

Family functioning mediates adaptation in caregivers of individuals with Rett syndrome.

PubMed

Lamb, Amanda E; Biesecker, Barbara B; Umstead, Kendall L; Muratori, Michelle; Biesecker, Leslie G; Erby, Lori H

2016-11-01

The objective of this study was to investigate factors related to family functioning and adaptation in caregivers of individuals with Rett syndrome (RS). A cross-sectional quantitative survey explored the relationships between demographics, parental self-efficacy, coping methods, family functioning and adaptation. A forward-backward, step-wise model selection procedure was used to evaluate variables associated with both family functioning and adaptation. Analyses also explored family functioning as a mediator of the relationship between other variables and adaptation. Bivariate analyses (N=400) revealed that greater parental self-efficacy, a greater proportion of problem-focused coping, and a lesser proportion of emotion-focused coping were associated with more effective family functioning. In addition, these key variables were significantly associated with greater adaptation, as was family functioning, while controlling for confounders. Finally, regression analyses suggest family functioning as a mediator of the relationships between three variables (parental self-efficacy, problem-focused coping, and emotion-focused coping) with adaptation. This study demonstrates the potentially predictive roles of expectations and coping methods and the mediator role of family functioning in adaptation among caregivers of individuals with RS, a chronic developmental disorder. A potential target for intervention is strengthening of caregiver competence in the parenting role to enhance caregiver adaptation. Published by Elsevier Ireland Ltd.

Does Educational Status Impact Adult Mortality in Denmark? A Twin Approach

PubMed Central

Madsen, Mia; Andersen, Anne-Marie Nybo; Christensen, Kaare; Andersen, Per Kragh; Osler, Merete

2010-01-01

To disentangle an independent effect of educational status on mortality risk from direct and indirect selection mechanisms, the authors used a discordant twin pair design, which allowed them to isolate the effect of education by means of adjustment for genetic and environmental confounding per design. The study is based on data from the Danish Twin Registry and Statistics Denmark. Using Cox regression, they estimated hazard ratios for mortality according to the highest attained education among 5,260 monozygotic and 11,088 dizygotic same-sex twin pairs born during 1921–1950 and followed during 1980–2008. Both standard cohort and intrapair analyses were conducted separately for zygosity, gender, and birth cohort. Educational differences in mortality were demonstrated in the standard cohort analyses but attenuated in the intrapair analyses in all subgroups but men born during 1921–1935, and no effect modification by zygosity was observed. Hence, the results are most compatible with an effect of early family environment in explaining the educational inequality in mortality. However, large educational differences were still reflected in mortality risk differences within twin pairs, thus supporting some degree of independent effect of education. In addition, the effect of education may be more pronounced in older cohorts of Danish men. PMID:20530466

Retooling CalEnviroScreen: Cumulative Pollution Burden and Race-Based Environmental Health Vulnerabilities in California

PubMed Central

2018-01-01

The California Community Environmental Health Screening Tool (CalEnviroScreen) advances research and policy pertaining to environmental health vulnerability. However, CalEnviroScreen departs from its historical foundations and comparable screening tools by no longer considering racial status as an indicator of environmental health vulnerability and predictor of cumulative pollution burden. This study used conceptual frameworks and analytical techniques from environmental health and inequality literature to address the limitations of CalEnviroScreen, especially its inattention to race-based environmental health vulnerabilities. It developed an adjusted measure of cumulative pollution burden from the CalEnviroScreen 2.0 data that facilitates multivariate analyses of the effect of neighborhood racial composition on cumulative pollution burden, net of other indicators of population vulnerability, traffic density, industrial zoning, and local and regional clustering of pollution burden. Principal component analyses produced three new measures of population vulnerability, including Latina/o cumulative disadvantage that represents the spatial concentration of Latinas/os, economic disadvantage, limited English-speaking ability, and health vulnerability. Spatial error regression analyses demonstrated that concentrations of Latinas/os, followed by Latina/o cumulative disadvantage, are the strongest demographic determinants of adjusted cumulative pollution burden. Findings have implications for research and policy pertaining to cumulative impacts and race-based environmental health vulnerabilities within and beyond California. PMID:29659481

Genetic parameters for growth characteristics of free-range chickens under univariate random regression models.

PubMed

Rovadoscki, Gregori A; Petrini, Juliana; Ramirez-Diaz, Johanna; Pertile, Simone F N; Pertille, Fábio; Salvian, Mayara; Iung, Laiza H S; Rodriguez, Mary Ana P; Zampar, Aline; Gaya, Leila G; Carvalho, Rachel S B; Coelho, Antonio A D; Savino, Vicente J M; Coutinho, Luiz L; Mourão, Gerson B

2016-09-01

Repeated measures from the same individual have been analyzed by using repeatability and finite dimension models under univariate or multivariate analyses. However, in the last decade, the use of random regression models for genetic studies with longitudinal data have become more common. Thus, the aim of this research was to estimate genetic parameters for body weight of four experimental chicken lines by using univariate random regression models. Body weight data from hatching to 84 days of age (n = 34,730) from four experimental free-range chicken lines (7P, Caipirão da ESALQ, Caipirinha da ESALQ and Carijó Barbado) were used. The analysis model included the fixed effects of contemporary group (gender and rearing system), fixed regression coefficients for age at measurement, and random regression coefficients for permanent environmental effects and additive genetic effects. Heterogeneous variances for residual effects were considered, and one residual variance was assigned for each of six subclasses of age at measurement. Random regression curves were modeled by using Legendre polynomials of the second and third orders, with the best model chosen based on the Akaike Information Criterion, Bayesian Information Criterion, and restricted maximum likelihood. Multivariate analyses under the same animal mixed model were also performed for the validation of the random regression models. The Legendre polynomials of second order were better for describing the growth curves of the lines studied. Moderate to high heritabilities (h(2) = 0.15 to 0.98) were estimated for body weight between one and 84 days of age, suggesting that selection for body weight at all ages can be used as a selection criteria. Genetic correlations among body weight records obtained through multivariate analyses ranged from 0.18 to 0.96, 0.12 to 0.89, 0.06 to 0.96, and 0.28 to 0.96 in 7P, Caipirão da ESALQ, Caipirinha da ESALQ, and Carijó Barbado chicken lines, respectively. Results indicate that genetic gain for body weight can be achieved by selection. Also, selection for body weight at 42 days of age can be maintained as a selection criterion. © 2016 Poultry Science Association Inc.

The theory of reasoned action and intention to seek cancer information.

PubMed

Ross, Levi; Kohler, Connie L; Grimley, Diane M; Anderson-Lewis, Charkarra

2007-01-01

To evaluate the applicability of the theory of reasoned action to explain men's intentions to seek prostate cancer information. Three hundred randomly selected African American men participated in telephone interviews. Correlational and regression analyses were conducted to examine relationships among measures. All relationships were significant in regression analyses. Attitudes and subjective norm were significantly related to intentions. Indirect measures of beliefs derived from elicitation research were associated with direct measures of attitude and subjective norms. The data are sufficiently clear to support the applicability of the theory for this behavioral domain with African American men and suggest several important areas for future research.

An Investigation of the Relations Between Student Knowledge, Personal Contact, and Attitudes Toward Individuals with Schizophrenia

PubMed Central

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

Virtual reality and neuropsychological assessment: The reliability of a virtual kitchen to assess daily-life activities in victims of traumatic brain injury.

PubMed

Besnard, Jeremy; Richard, Paul; Banville, Frederic; Nolin, Pierre; Aubin, Ghislaine; Le Gall, Didier; Richard, Isabelle; Allain, Phillippe

2016-01-01

Traumatic brain injury (TBI) causes impairments affecting instrumental activities of daily living (IADL). However, few studies have considered virtual reality as an ecologically valid tool for the assessment of IADL in patients who have sustained a TBI. The main objective of the present study was to examine the use of the Nonimmersive Virtual Coffee Task (NI-VCT) for IADL assessment in patients with TBI. We analyzed the performance of 19 adults suffering from TBI and 19 healthy controls (HCs) in the real and virtual tasks of making coffee with a coffee machine, as well as in global IQ and executive functions. Patients performed worse than HCs on both real and virtual tasks and on all tests of executive functions. Correlation analyses revealed that NI-VCT scores were related to scores on the real task. Moreover, regression analyses demonstrated that performance on NI-VCT matched real-task performance. Our results support the idea that the virtual kitchen is a valid tool for IADL assessment in patients who have sustained a TBI.

Intimate Partner Violence in the Canadian Armed Forces: The Role of Family Stress and Its Impact on Well-Being.

PubMed

Skomorovsky, Alla; Hujaleh, Filsan; Wolejszo, Stefan

2015-07-01

Unique demands of military life (e.g., deployment) can have a significant impact on family life. Although most families cope effectively with military life stressors, some may have difficulty adjusting, experiencing marital conflicts, and violence. Evidence suggests that unmanaged occupational demands may create family stress by interfering with efforts to fulfill family duties. This study examined the effects of work-family conflict and marital satisfaction on intimate violence experienced by Canadian Armed Forces members, and the impact of such violence on their psychological well-being (N = 525). Regression analyses showed that both work-family conflict and marital satisfaction were unique and significant predictors of emotional and physical violence experienced by Canadian Armed Forces members. Moreover, bootstrapping analyses demonstrated that marital satisfaction partially mediated the relationship between work-family and family-work conflicts and intimate partner violence. The results point to the importance of examining the interrelationship between family stress and occupational stressors when exploring interpersonal violence and its psychological impact on military personnel. Reprint & Copyright © 2015 Association of Military Surgeons of the U.S.

Housing Status and HIV Risk Behaviors among Transgender Women in Los Angeles

PubMed Central

Fletcher, Jesse B.; Kisler, Kimberly A.; Reback, Cathy J.

2014-01-01

Due to social stigma, lack of social support, and minimal legal employment opportunities, transgender women (transwomen) face elevated rates of unstable housing. This study examined the association between housing status and HIV risk behaviors among 517 transwomen encountered through street outreach. Seven variables (including sociodemographics, HIV status, housing status, and sexual partner type) were used to estimate partial associations during multivariable analyses; housing status was coded trichotomously (housed, marginally housed, and homeless) for these analyses. Results demonstrated that homeless and marginally housed transwomen engaged in significantly higher rates of illicit drug use than housed transwomen; however, marginally housed and housed transwomen engaged in significantly higher rates of illegal hormone injections than homeless transwomen. Rates of sex work were high in the sample as a whole, though sex with an exchange partner was most common among the marginally housed transwomen. Multivariate logistic regression revealed that unstable housing moderated the association between HIV status and engagement in unprotected serodiscordant anal intercourse. The marginally housed transwomen exhibited the greatest risk profile for HIV acquisition or transmission. PMID:25190499

Development of a Highly Automated and Multiplexed Targeted Proteome Pipeline and Assay for 112 Rat Brain Synaptic Proteins

PubMed Central

Colangelo, Christopher M.; Ivosev, Gordana; Chung, Lisa; Abbott, Thomas; Shifman, Mark; Sakaue, Fumika; Cox, David; Kitchen, Rob R.; Burton, Lyle; Tate, Stephen A; Gulcicek, Erol; Bonner, Ron; Rinehart, Jesse; Nairn, Angus C.; Williams, Kenneth R.

2015-01-01

We present a comprehensive workflow for large scale (>1000 transitions/run) label-free LC-MRM proteome assays. Innovations include automated MRM transition selection, intelligent retention time scheduling (xMRM) that improves Signal/Noise by >2-fold, and automatic peak modeling. Improvements to data analysis include a novel Q/C metric, Normalized Group Area Ratio (NGAR), MLR normalization, weighted regression analysis, and data dissemination through the Yale Protein Expression Database. As a proof of principle we developed a robust 90 minute LC-MRM assay for Mouse/Rat Post-Synaptic Density (PSD) fractions which resulted in the routine quantification of 337 peptides from 112 proteins based on 15 observations per protein. Parallel analyses with stable isotope dilution peptide standards (SIS), demonstrate very high correlation in retention time (1.0) and protein fold change (0.94) between the label-free and SIS analyses. Overall, our first method achieved a technical CV of 11.4% with >97.5% of the 1697 transitions being quantified without user intervention, resulting in a highly efficient, robust, and single injection LC-MRM assay. PMID:25476245

Media exposure and dimensions of anxiety sensitivity: differential associations with PTSD symptom clusters.

PubMed

Collimore, Kelsey C; McCabe, Randi E; Carleton, R Nicholas; Asmundson, Gordon J G

2008-08-01

The present investigation examined the impact of anxiety sensitivity (AS) and media exposure on posttraumatic stress disorder (PTSD) symptoms. Reactions from 143 undergraduate students in Hamilton, Ontario were assessed in the Fall of 2003 to gather information on anxiety, media coverage, and PTSD symptoms related to exposure to a remote traumatic event (September 11th). Regression analyses revealed that the Anxiety Sensitivity Index (ASI; [Peterson, R. A., & Reiss, S. (1992). Anxiety Sensitivity Index manual, 2nd ed. Worthington, Ohio: International Diagnostic Systems]) and State-Trait Anxiety Inventory trait form (STAI-T; [Spielberger, C. D., Gorsuch, R. L., & Lushene, R. E. (1970). State-trait anxiety inventory. Palo Alto, California: Consulting Psychologists Press]) total scores were significant predictors of PTSD symptoms in general. The ASI total score was also a significant predictor of hyperarousal and avoidance symptoms. Subsequent analyses further demonstrated differential relationships based on subscales and symptom clusters. Specifically, media exposure and trait anxiety predicted hyperarousal and re-experiencing symptoms, whereas the ASI fear of somatic sensations subscale significantly predicted avoidance and overall PTSD symptoms. Implications and directions for future research are discussed.

Mathematical Ecology Analysis of Geographical Distribution of Soybean-Nodulating Bradyrhizobia in Japan

PubMed Central

Saeki, Yuichi; Shiro, Sokichi; Tajima, Toshiyuki; Yamamoto, Akihiro; Sameshima-Saito, Reiko; Sato, Takashi; Yamakawa, Takeo

2013-01-01

We characterized the relationship between the genetic diversity of indigenous soybean-nodulating bradyrhizobia from weakly acidic soils in Japan and their geographical distribution in an ecological study of indigenous soybean rhizobia. We isolated bradyrhizobia from three kinds of Rj-genotype soybeans. Their genetic diversity and community structure were analyzed by PCR-RFLP analysis of the 16S–23S rRNA gene internal transcribed spacer (ITS) region with 11 Bradyrhizobium USDA strains as references. We used data from the present study and previous studies to carry out mathematical ecological analyses, multidimensional scaling analysis with the Bray-Curtis index, polar ordination analysis, and multiple regression analyses to characterize the relationship between soybean-nodulating bradyrhizobial community structures and their geographical distribution. The mathematical ecological approaches used in this study demonstrated the presence of ecological niches and suggested the geographical distribution of soybean-nodulating bradyrhizobia to be a function of latitude and the related climate, with clusters in the order Bj123, Bj110, Bj6, and Be76 from north to south in Japan. PMID:24240318

Computational toxicology: Its essential role in reducing drug attrition.

PubMed

Naven, R T; Louise-May, S

2015-12-01

Predictive toxicology plays a critical role in reducing the failure rate of new drugs in pharmaceutical research and development. Despite recent gains in our understanding of drug-induced toxicity, however, it is urgent that the utility and limitations of our current predictive tools be determined in order to identify gaps in our understanding of mechanistic and chemical toxicology. Using recently published computational regression analyses of in vitro and in vivo toxicology data, it will be demonstrated that significant gaps remain in early safety screening paradigms. More strategic analyses of these data sets will allow for a better understanding of their domain of applicability and help identify those compounds that cause significant in vivo toxicity but which are currently mis-predicted by in silico and in vitro models. These 'outliers' and falsely predicted compounds are metaphorical lighthouses that shine light on existing toxicological knowledge gaps, and it is essential that these compounds are investigated if attrition is to be reduced significantly in the future. As such, the modern computational toxicologist is more productively engaged in understanding these gaps and driving investigative toxicology towards addressing them. © The Author(s) 2015.

Terrorism, distress, and drinking: vulnerability and protective factors.

PubMed

Richman, Judith A; Rospenda, Kathleen M; Cloninger, Lea

2009-12-01

Research has demonstrated effects of 9/11 on distress and drinking outcomes in individuals directly affected and indirectly affected across the United States. Fewer studies have addressed vulnerability and protective factors shown to moderate the effects of stress exposure. We report findings from a Midwestern workplace cohort study. Respondents to a 6 wave longitudinal mail survey completed questionnaires prior to September 11, 2001 and again in 2003 and 2005. Regression analyses encompassed measures of terrorism-related beliefs and fears, workplace stressors (sexual harassment, generalized abuse and low decision latitude), marital and parental status, and perceived social support in 2003, and distress and deleterious drinking outcomes in 2005. Analyses showed that terrorism-related fears significantly interacted with workplace stressors and interpersonal social relationships in predicting distress, drinking or both, controlling for pre-9/11 distress and drinking. Gender differences were also found. This article suggests that certain individuals may be at heightened risk for distressful reactions to and/or deleterious drinking resulting from terrorism-related issues and fears due to additional risk factors involving workplace stressors and inadequate interpersonal bonds. However, limitations of the study were noted and future research was recommended.

Self-Regulatory Strategies as Correlates of Physical Activity Behavior in Persons With Multiple Sclerosis.

PubMed

Cederberg, Katie L; Balto, Julia M; Motl, Robert W

2018-05-01

To examine self-regulation strategies as correlates of physical activity in persons with multiple sclerosis (MS). Cross-sectional, or survey, study. University-based research laboratory. Convenience sample of persons with MS (N=68). Not applicable. Exercise Self-Efficacy Scale (EXSE), 12-item Physical Activity Self-Regulation Scale (PASR-12), and Godin Leisure-Time Exercise Questionnaire (GLTEQ). Correlation analyses indicated that GLTEQ scores were positively and significantly associated with overall self-regulation (r=.43), self-monitoring (r=.45), goal-setting (r=.27), reinforcement (r=.30), time management (r=.41), and relapse prevention (r=.53) PASR-12 scores. Regression analyses indicated that relapse prevention (B=5.01; SE B=1.74; β=.51) and self-monitoring (B=3.65; SE B=1.71; β=.33) were unique predictors of physical activity behavior, and relapse prevention demonstrated a significant association with physical activity behavior that was accounted for by EXSE. Our results indicate that self-regulatory strategies, particularly relapse prevention, may be important correlates of physical activity behavior that can inform the design of future behavioral interventions in MS. Published by Elsevier Inc.

Sexual revictimization among Iraq and Afghanistan war era veterans.

PubMed

Schry, Amie R; Beckham, Jean C; The Va Mid-Atlantic Mirecc Workgroup; Calhoun, Patrick S

2016-06-30

Research in both civilian and military populations has demonstrated that females who experience childhood sexual abuse (CSA) are more likely to experience sexual assault in adulthood than females who did not experience CSA. Among veteran samples, however, little research has examined previous sexual assault as a risk factor of military sexual assault and post-military sexual assault, and very little research has examined revictimization in male veterans. The purpose of this study was to examine risk of sexual revictimization in a sample of veterans who served during the wars in Iraq and Afghanistan. A sample of 3106 veterans (80.4% male) completed a measure of lifetime exposure to traumatic events, including sexual abuse and sexual assault. Logistic regression analyses were used to examine previous sexual abuse/assault as predictors of later sexual assault; analyses were conducted separately for males and females. In general, previous sexual abuse/assault was associated with later sexual assault in both male and female veterans. These findings have important assessment and treatment implications for clinicians working with veterans. Published by Elsevier Ireland Ltd.

Self-care and depression in patients with chronic heart failure.

PubMed

Holzapfel, Nicole; Löwe, Bernd; Wild, Beate; Schellberg, Dieter; Zugck, Christian; Remppis, Andrew; Katus, Hugo A; Haass, Markus; Rauch, Bernhard; Jünger, Jana; Herzog, Wolfgang; Müller-Tasch, Thomas

2009-01-01

Although chronic heart failure (CHF) is often complicated by comorbid depression and poor self-care, little is known about their specific association in patients with CHF. To investigate self-care behavior among patients with CHF with different degrees of depression severity. A total of 287 patients with documented CHF, New York Heart Association functional class II to IV, completed the European Heart Failure Self-Care Behavior Scale. The Structured Clinical Interview for DSM (SCID) IV served as the criterion standard for the presence of a depressive disorder. Analyses of covariance and linear regression analyses revealed that patients with CHF with minor depression reported significantly lower levels of self-care than patients with major depression (P = .003) and nondepressed patients (P = .014). In addition to minor depression, age (P < or = .001), multimorbidity (P = .01), left ventricular ejection fraction (P = .001), and family status (P = .01) were determinants of self-care. Our results demonstrate that patients with CHF with minor depression and not major depression are at higher risk for poor self-care and its resulting consequences, such as symptom deterioration and frequent hospitalization.

Childhood Cancer in Context: Sociodemographic Factors, Stress, and Psychological Distress Among Mothers and Children.

PubMed

Bemis, Heather; Yarboi, Janet; Gerhardt, Cynthia A; Vannatta, Kathryn; Desjardins, Leandra; Murphy, Lexa K; Rodriguez, Erin M; Compas, Bruce E

2015-09-01

To examine associations between sociodemographic factors (single parenthood, family income, education level, race), stress, and psychological distress among pediatric cancer patients and their mothers. Participants completed measures assessing sociodemographic variables, depressive symptoms, posttraumatic stress symptoms, general stress, and cancer-related stress within the first year of the child's (ages 5-17 years) cancer diagnosis or relapse. Mothers (N = 318) provided self-reports and parent report of their children; children aged 10-17 years (N = 151) completed self-reports. Each sociodemographic variable demonstrated unique associations with mothers' and children's stress and distress in bivariate analyses. A cumulative sociodemographic risk measure was positively correlated with all stress and distress variables. In regression analyses predicting mothers' and children's distress, independent and cumulative sociodemographic measures were no longer significant when accounting for levels of stress. Findings highlight the need to consider the ecological context of pediatric cancer, particularly the impact of sociodemographic disadvantage on stress and distress in this population. © The Author 2015. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Trauma-Related Dissociation Is Linked With Maladaptive Personality Functioning

PubMed Central

Granieri, Antonella; Guglielmucci, Fanny; Costanzo, Antonino; Caretti, Vincenzo; Schimmenti, Adriano

2018-01-01

Background: Extensive research has demonstrated the positive associations among the exposure to traumatic experiences, the levels of dissociation, and the severity of psychiatric symptoms in adults. However, it has been hypothesized in clinical literature that an excessive activation of the dissociative processes following multiple traumatic experiences may jeopardize the psychological and behavioral functioning of the individuals, fostering higher levels of maladaptive personality functioning. Methods: The study involved 322 adult volunteers from Italy. Participants completed measures on traumatic experiences, dissociation, and maladaptive personality traits. Results: The number of traumatic experiences reported by participants were positively associated with dissociation scores and maladaptive personality scores. Mediation analyses showed that dissociation acted as a partial mediator in the relationship between traumatic experiences and overall maladaptive personality functioning. Regression curve analyses showed that the positive association between maladaptive personality functioning and dissociation was stronger among participants with higher exposure to traumatic experiences. Conclusion: Exposure to multiple traumatic experiences may increase the risk for an excessive activation of the dissociative processes, which in turn may generate severe impairments in multiple domains of personality functioning. PMID:29887807

Childhood Cancer in Context: Sociodemographic Factors, Stress, and Psychological Distress Among Mothers and Children

PubMed Central

Yarboi, Janet; Gerhardt, Cynthia A.; Vannatta, Kathryn; Desjardins, Leandra; Murphy, Lexa K.; Rodriguez, Erin M.; Compas, Bruce E.

2015-01-01

Objective To examine associations between sociodemographic factors (single parenthood, family income, education level, race), stress, and psychological distress among pediatric cancer patients and their mothers. Methods Participants completed measures assessing sociodemographic variables, depressive symptoms, posttraumatic stress symptoms, general stress, and cancer-related stress within the first year of the child’s (ages 5–17 years) cancer diagnosis or relapse. Mothers (N = 318) provided self-reports and parent report of their children; children aged 10–17 years (N = 151) completed self-reports. Results Each sociodemographic variable demonstrated unique associations with mothers’ and children’s stress and distress in bivariate analyses. A cumulative sociodemographic risk measure was positively correlated with all stress and distress variables. In regression analyses predicting mothers’ and children’s distress, independent and cumulative sociodemographic measures were no longer significant when accounting for levels of stress. Conclusions Findings highlight the need to consider the ecological context of pediatric cancer, particularly the impact of sociodemographic disadvantage on stress and distress in this population. PMID:25840446

Development of Super-Ensemble techniques for ocean analyses: the Mediterranean Sea case

NASA Astrophysics Data System (ADS)

Pistoia, Jenny; Pinardi, Nadia; Oddo, Paolo; Collins, Matthew; Korres, Gerasimos; Drillet, Yann

2017-04-01

Short-term ocean analyses for Sea Surface Temperature SST in the Mediterranean Sea can be improved by a statistical post-processing technique, called super-ensemble. This technique consists in a multi-linear regression algorithm applied to a Multi-Physics Multi-Model Super-Ensemble (MMSE) dataset, a collection of different operational forecasting analyses together with ad-hoc simulations produced by modifying selected numerical model parameterizations. A new linear regression algorithm based on Empirical Orthogonal Function filtering techniques is capable to prevent overfitting problems, even if best performances are achieved when we add correlation to the super-ensemble structure using a simple spatial filter applied after the linear regression. Our outcomes show that super-ensemble performances depend on the selection of an unbiased operator and the length of the learning period, but the quality of the generating MMSE dataset has the largest impact on the MMSE analysis Root Mean Square Error (RMSE) evaluated with respect to observed satellite SST. Lower RMSE analysis estimates result from the following choices: 15 days training period, an overconfident MMSE dataset (a subset with the higher quality ensemble members), and the least square algorithm being filtered a posteriori.

Obese individuals with more components of the metabolic syndrome and/or prediabetes demonstrate decreased activation of reward-related brain centers in response to food cues in both the fed and fasting states: A preliminary fMRI study

PubMed Central

Farr, Olivia M.; Mantzoros, Christos S.

2016-01-01

It remains unknown whether obese individuals with more components of the metabolic syndrome and/or prediabetes demonstrate altered activation of brain centers in response to food cues. We examined obese prediabetics (n=26) vs. obese nondiabetics (n=11) using fMRI. We also performed regression analyses on the basis of the number of MetS components per subject. Obese individuals with prediabetes have decreased activation of the reward-related putamen in the fasting state and decreased activation of the salience- and reward-related insula after eating. Obese individuals with more components of MetS demonstrate decreased activation of the putamen while fasting. All these activations remain significant when corrected for BMI, waist circumference (WC), HbA1c and gender. Decreased activation in reward-related brain areas between obese individuals is more pronounced in subjects with prediabetes and MetS. Prospective studies are needed to quantify their contributions to the development of prediabetes/MetS and to study whether these conditions may predispose to the exacerbation of obesity and the development of comorbidities over time. PMID:28017966

Factors associated with the income distribution of full-time physicians: a quantile regression approach.

PubMed

Shih, Ya-Chen Tina; Konrad, Thomas R

2007-10-01

Physician income is generally high, but quite variable; hence, physicians have divergent perspectives regarding health policy initiatives and market reforms that could affect their incomes. We investigated factors underlying the distribution of income within the physician population. Full-time physicians (N=10,777) from the restricted version of the 1996-1997 Community Tracking Study Physician Survey (CTS-PS), 1996 Area Resource File, and 1996 health maintenance organization penetration data. We conducted separate analyses for primary care physicians (PCPs) and specialists. We employed least square and quantile regression models to examine factors associated with physician incomes at the mean and at various points of the income distribution, respectively. We accounted for the complex survey design for the CTS-PS data using appropriate weighted procedures and explored endogeneity using an instrumental variables method. We detected widespread and subtle effects of many variables on physician incomes at different points (10th, 25th, 75th, and 90th percentiles) in the distribution that were undetected when employing regression estimations focusing on only the means or medians. Our findings show that the effects of managed care penetration are demonstrable at the mean of specialist incomes, but are more pronounced at higher levels. Conversely, a gender gap in earnings occurs at all levels of income of both PCPs and specialists, but is more pronounced at lower income levels. The quantile regression technique offers an analytical tool to evaluate policy effects beyond the means. A longitudinal application of this approach may enable health policy makers to identify winners and losers among segments of the physician workforce and assess how market dynamics and health policy initiatives affect the overall physician income distribution over various time intervals.

Duration of Mechanical Ventilation in the Emergency Department.

PubMed

Angotti, Lauren B; Richards, Jeremy B; Fisher, Daniel F; Sankoff, Jeffrey D; Seigel, Todd A; Al Ashry, Haitham S; Wilcox, Susan R

2017-08-01

Due to hospital crowding, mechanically ventilated patients are increasingly spending hours boarding in emergency departments (ED) before intensive care unit (ICU) admission. This study aims to evaluate the association between time ventilated in the ED and in-hospital mortality, duration of mechanical ventilation, ICU and hospital length of stay (LOS). This was a multi-center, prospective, observational study of patients ventilated in the ED, conducted at three academic Level I Trauma Centers from July 2011 to March 2013. All consecutive adult patients on invasive mechanical ventilation were eligible for enrollment. We performed a Cox regression to assess for a mortality effect for mechanically ventilated patients with each hour of increasing LOS in the ED and multivariable regression analyses to assess for independently significant contributors to in-hospital mortality. Our primary outcome was in-hospital mortality, with secondary outcomes of ventilator days, ICU LOS and hospital LOS. We further commented on use of lung protective ventilation and frequency of ventilator changes made in this cohort. We enrolled 535 patients, of whom 525 met all inclusion criteria. Altered mental status without respiratory pathology was the most common reason for intubation, followed by trauma and respiratory failure. Using iterated Cox regression, a mortality effect occurred at ED time of mechanical ventilation > 7 hours, and the longer ED stay was also associated with a longer total duration of intubation. However, adjusted multivariable regression analysis demonstrated only older age and admission to the neurosciences ICU as independently associated with increased mortality. Of interest, only 23.8% of patients ventilated in the ED for over seven hours had changes made to their ventilator. In a prospective observational study of patients mechanically ventilated in the ED, there was a significant mortality benefit to expedited transfer of patients into an appropriate ICU setting.

A new improved graphical and quantitative method for detecting bias in meta-analysis.

PubMed

Furuya-Kanamori, Luis; Barendregt, Jan J; Doi, Suhail A R

2018-04-04

Detection of publication and related biases remains suboptimal and threatens the validity and interpretation of meta-analytical findings. When bias is present, it usually differentially affects small and large studies manifesting as an association between precision and effect size and therefore visual asymmetry of conventional funnel plots. This asymmetry can be quantified and Egger's regression is, by far, the most widely used statistical measure for quantifying funnel plot asymmetry. However, concerns have been raised about both the visual appearance of funnel plots and the sensitivity of Egger's regression to detect such asymmetry, particularly when the number of studies is small. In this article, we propose a new graphical method, the Doi plot, to visualize asymmetry and also a new measure, the LFK index, to detect and quantify asymmetry of study effects in Doi plots. We demonstrate that the visual representation of asymmetry was better for the Doi plot when compared with the funnel plot. We also show that the diagnostic accuracy of the LFK index in discriminating between asymmetry due to simulated publication bias versus chance or no asymmetry was also better with the LFK index which had areas under the receiver operating characteristic curve of 0.74-0.88 with simulations of meta-analyses with five, 10, 15, and 20 studies. The Egger's regression result had lower areas under the receiver operating characteristic curve values of 0.58-0.75 across the same simulations. The LFK index also had a higher sensitivity (71.3-72.1%) than the Egger's regression result (18.5-43.0%). We conclude that the methods proposed in this article can markedly improve the ability of researchers to detect bias in meta-analysis.

Factors Associated with the Income Distribution of Full-Time Physicians: A Quantile Regression Approach

PubMed Central

Shih, Ya-Chen Tina; Konrad, Thomas R

2007-01-01

Objective Physician income is generally high, but quite variable; hence, physicians have divergent perspectives regarding health policy initiatives and market reforms that could affect their incomes. We investigated factors underlying the distribution of income within the physician population. Data Sources Full-time physicians (N=10,777) from the restricted version of the 1996–1997 Community Tracking Study Physician Survey (CTS-PS), 1996 Area Resource File, and 1996 health maintenance organization penetration data. Study Design We conducted separate analyses for primary care physicians (PCPs) and specialists. We employed least square and quantile regression models to examine factors associated with physician incomes at the mean and at various points of the income distribution, respectively. We accounted for the complex survey design for the CTS-PS data using appropriate weighted procedures and explored endogeneity using an instrumental variables method. Principal Findings We detected widespread and subtle effects of many variables on physician incomes at different points (10th, 25th, 75th, and 90th percentiles) in the distribution that were undetected when employing regression estimations focusing on only the means or medians. Our findings show that the effects of managed care penetration are demonstrable at the mean of specialist incomes, but are more pronounced at higher levels. Conversely, a gender gap in earnings occurs at all levels of income of both PCPs and specialists, but is more pronounced at lower income levels. Conclusions The quantile regression technique offers an analytical tool to evaluate policy effects beyond the means. A longitudinal application of this approach may enable health policy makers to identify winners and losers among segments of the physician workforce and assess how market dynamics and health policy initiatives affect the overall physician income distribution over various time intervals. PMID:17850525

Financial ties and concordance between results and conclusions in meta-analyses: retrospective cohort study.

PubMed

Yank, Veronica; Rennie, Drummond; Bero, Lisa A

2007-12-08

To determine whether financial ties to one drug company are associated with favourable results or conclusions in meta-analyses on antihypertensive drugs. Retrospective cohort study. Meta-analyses published up to December 2004 that were not duplicates and evaluated the effects of antihypertensive drugs compared with any comparator on clinical end points in adults. Financial ties were categorised as one drug company compared with all others. The main outcomes were the results and conclusions of meta-analyses, with both outcomes separately categorised as being favourable or not favourable towards the study drug. We also collected data on characteristics of meta-analyses that the literature suggested might be associated with favourable results or conclusions. 124 meta-analyses were included in the study, 49 (40%) of which had financial ties to one drug company. On univariate logistic regression analyses, meta-analyses of better methodological quality were more likely to have favourable results (odds ratio 1.16, 95% confidence interval 1.07 to 1.27). Although financial ties to one drug company were not associated with favourable results, such ties constituted the only characteristic significantly associated with favourable conclusions (4.09, 1.30 to 12.83). When controlling for other characteristics of meta-analyses in multiple logistic regression analyses, meta-analyses that had financial ties to one drug company remained more likely to report favourable conclusions (5.11, 1.54 to 16.92). Meta-analyses on antihypertensive drugs and with financial ties to one drug company are not associated with favourable results but are associated with favourable conclusions.

Effects of a westernized lifestyle on the association between fasting serum nonesterified fatty acids and insulin secretion in Japanese men.

PubMed

Kamei, Nozomu; Yamane, Kiminori; Nakanishi, Shuhei; Ishida, Kazufumi; Ohtaki, Megu; Okubo, Masamichi; Kohno, Nobuoki

2005-06-01

The effects of the prolonged elevation of nonesterified fatty acid (NEFA) levels on insulin secretion have been controversial and thought to be sex-specific. To investigate the association between a westernized lifestyle and the effects of NEFA on insulin secretion in Japanese men, we examined 67 nondiabetic Japanese-American men and 220 nondiabetic native Japanese men who underwent a 75-g oral glucose tolerance test (OGTT). Most Japanese Americans we surveyed are genetically identical to Japanese living in Japan, but their lifestyle is more westernized. Sets of multiple regression analyses were performed to evaluate the relationship between the sum of the immunoreactive insulin (IRI) levels during the OGTT ((Sigma)IRI) and clinical parameters. Japanese Americans had higher levels of fasting IRI, (Sigma)IRI, and a higher insulin resistance index (homeostasis model assessment for insulin resistance [HOMA-IR]) than native Japanese, whereas there were no significant differences in fasting NEFA and triglyceride levels. A multiple regression analysis adjusted for age, fasting triglycerides, and body mass index (BMI) demonstrated that the fasting NEFA level was an independent determinant of the (Sigma)IRI only in Japanese-American men ( P = .001), but not in native Japanese men ( P = .054). Even when HOMA-IR was included in models instead of BMI, the NEFA level was a significant variable of (Sigma)IRI only in Japanese Americans ( P < .001), and not in native Japanese ( P = .098). In addition, a multiple regression analysis adjusted for age, fasting triglycerides, and BMI demonstrated that the fasting NEFA level was the only independent determinant of (Sigma)C-peptide in Japanese-American men ( P = .041). In conclusion, NEFA seems to be associated with insulin secretion independent of obesity or HOMA-IR. A westernized lifestyle may increase the effects of serum fasting NEFA levels on total insulin secretion after a glucose load in Japanese men.

Does substance misuse moderate the relationship between criminal thinking and recidivism?

PubMed Central

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

Spatial analysis of alcohol-related motor vehicle crash injuries in southeastern Michigan.

PubMed

Meliker, Jaymie R; Maio, Ronald F; Zimmerman, Marc A; Kim, Hyungjin Myra; Smith, Sarah C; Wilson, Mark L

2004-11-01

Temporal, behavioral and social risk factors that affect injuries resulting from alcohol-related motor vehicle crashes have been characterized in previous research. Much less is known about spatial patterns and environmental associations of alcohol-related motor vehicle crashes. The aim of this study was to evaluate geographic patterns of alcohol-related motor vehicle crashes and to determine if locations of alcohol outlets are associated with those crashes. In addition, we sought to demonstrate the value of integrating spatial and traditional statistical techniques in the analysis of this preventable public health risk. The study design was a cross-sectional analysis of individual-level blood alcohol content, traffic report information, census block group data, and alcohol distribution outlets. Besag and Newell's spatial analysis and traditional logistic regression both indicated that areas of low population density had more alcohol-related motor vehicle crashes than expected (P < 0.05). There was no significant association between alcohol outlets and alcohol-related motor vehicle crashes using distance analyses, logistic regression, and Chi-square. Differences in environmental or behavioral factors characteristic of areas of low population density may be responsible for the higher proportion of alcohol-related crashes occurring in these areas.

Analysis of Feature Intervisibility and Cumulative Visibility Using GIS, Bayesian and Spatial Statistics: A Study from the Mandara Mountains, Northern Cameroon

PubMed Central

Wright, David K.; MacEachern, Scott; Lee, Jaeyong

2014-01-01

The locations of diy-geδ-bay (DGB) sites in the Mandara Mountains, northern Cameroon are hypothesized to occur as a function of their ability to see and be seen from points on the surrounding landscape. A series of geostatistical, two-way and Bayesian logistic regression analyses were performed to test two hypotheses related to the intervisibility of the sites to one another and their visual prominence on the landscape. We determine that the intervisibility of the sites to one another is highly statistically significant when compared to 10 stratified-random permutations of DGB sites. Bayesian logistic regression additionally demonstrates that the visibility of the sites to points on the surrounding landscape is statistically significant. The location of sites appears to have also been selected on the basis of lower slope than random permutations of sites. Using statistical measures, many of which are not commonly employed in archaeological research, to evaluate aspects of visibility on the landscape, we conclude that the placement of DGB sites improved their conspicuousness for enhanced ritual, social cooperation and/or competition purposes. PMID:25383883

Total bone calcium in normal women: effect of age and menopause status

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

Gallagher, J.C.; Goldgar, D.; Moy, A.

1987-12-01

Bone density in different regions of the skeleton was measured in 392 normal women aged 20-80 years by dual photon absorpiometry. In premenopausal women, aged 25-50 years, multiple regression analysis of regional bone density on age, height, and weight showed a small significant decrease in total bone density (less than 0.01) but no significant change in other regions of the skeleton. In postmenopausal women there were highly significant decreases in all regions of the skeleton (p less than 0.001), and bone density in these areas decreased as a logarithmic function of years since menopause. Based on multiple regression analyses, themore » decrease in spine density and total bone calcium was 2.5-3.0 times greater in the 25 years after menopause than the 25 years before menopause. The largest change, however, occurred in the first five years after menopause. During this time the estimated annual change in spine density and total bone calcium was about 10 times greater than that in the premenopausal period. These results demonstrate the important effect of the menopause in determining bone mass in later life.« less

The population ecology of male gametophytes: the link between pollination and seed production.

PubMed

Harder, Lawrence D; Aizen, Marcelo A; Richards, Shane A

2016-05-01

The fate of male gametophytes after pollen reaches stigmas links pollination to ovule fertilisation, governing subsequent siring success and seed production. Although male gametophyte performance primarily involves cellular processes, an ecological analogy may expose insights into the nature and implications of male gametophyte success. We elaborate this analogy theoretically and present empirical examples that illustrate associated insights. Specifically, we consider pollen loads on stigmas as localised populations subject to density-independent mortality and density-dependent processes as they traverse complex stylar environments. Different combinations of the timing of pollen-tube access to limiting stylar resources (simultaneous or sequential), the tube distribution among resources (repulsed or random) and the timing of density-independent mortality relative to competition (before or after) create signature relations of mean pollen-tube success and its variation among pistils to pollen receipt. Using novel nonlinear regression analyses (two-moment regression), we illustrate contrasting relations for two species, demonstrating that variety in these relations is a feature of reproductive diversity among angiosperms, rather than merely a theoretical curiosity. Thus, the details of male gametophyte ecology should shape sporophyte reproductive success and hence the dynamics and structure of angiosperm populations. © 2016 John Wiley & Sons Ltd/CNRS.

A flexible count data regression model for risk analysis.

PubMed

Guikema, Seth D; Coffelt, Jeremy P; Goffelt, Jeremy P

2008-02-01

In many cases, risk and reliability analyses involve estimating the probabilities of discrete events such as hardware failures and occurrences of disease or death. There is often additional information in the form of explanatory variables that can be used to help estimate the likelihood of different numbers of events in the future through the use of an appropriate regression model, such as a generalized linear model. However, existing generalized linear models (GLM) are limited in their ability to handle the types of variance structures often encountered in using count data in risk and reliability analysis. In particular, standard models cannot handle both underdispersed data (variance less than the mean) and overdispersed data (variance greater than the mean) in a single coherent modeling framework. This article presents a new GLM based on a reformulation of the Conway-Maxwell Poisson (COM) distribution that is useful for both underdispersed and overdispersed count data and demonstrates this model by applying it to the assessment of electric power system reliability. The results show that the proposed COM GLM can provide as good of fits to data as the commonly used existing models for overdispered data sets while outperforming these commonly used models for underdispersed data sets.

Birth weight and neonatal adiposity prediction using fractional limb volume obtained with 3D ultrasound.

PubMed

O'Connor, Clare; O'Higgins, Amy; Doolan, Anne; Segurado, Ricardo; Stuart, Bernard; Turner, Michael J; Kennelly, Máireád M

2014-01-01

The objective of this investigation was to study fetal thigh volume throughout gestation and explore its correlation with birth weight and neonatal body composition. This novel technique may improve birth weight prediction and lead to improved detection rates for fetal growth restriction. Fractional thigh volume (TVol) using 3D ultrasound, fetal biometry and soft tissue thickness were studied longitudinally in 42 mother-infant pairs. The percentages of neonatal body fat, fat mass and fat-free mass were determined using air displacement plethysmography. Correlation and linear regression analyses were performed. Linear regression analysis showed an association between TVol and birth weight. TVol at 33 weeks was also associated with neonatal fat-free mass. There was no correlation between TVol and neonatal fat mass. Abdominal circumference, estimated fetal weight (EFW) and EFW centile showed consistent correlations with birth weight. Thigh volume demonstrated an additional independent contribution to birth weight prediction when added to the EFW centile from the 38-week scan (p = 0.03). Fractional TVol performed at 33 weeks gestation is correlated with birth weight and neonatal lean body mass. This screening test may highlight those at risk of fetal growth restriction or macrosomia.

Sex discrimination from the acetabulum in a twentieth-century skeletal sample from France using digital photogrammetry.

PubMed

Macaluso, P J

2011-02-01

Digital photogrammetric methods were used to collect diameter, area, and perimeter data of the acetabulum for a twentieth-century skeletal sample from France (Georges Olivier Collection, Musée de l'Homme, Paris) consisting of 46 males and 36 females. The measurements were then subjected to both discriminant function and logistic regression analyses in order to develop osteometric standards for sex assessment. Univariate discriminant functions and logistic regression equations yielded overall correct classification accuracy rates for both the left and the right acetabula ranging from 84.1% to 89.6%. The multivariate models developed in this study did not provide increased accuracy over those using only a single variable. Classification sex bias ratios ranged between 1.1% and 7.3% for the majority of models. The results of this study, therefore, demonstrate that metric analysis of acetabular size provides a highly accurate, and easily replicable, method of discriminating sex in this documented skeletal collection. The results further suggest that the addition of area and perimeter data derived from digital images may provide a more effective method of sex assessment than that offered by traditional linear measurements alone. Copyright © 2010 Elsevier GmbH. All rights reserved.

Serum Iron Level Is Associated with Time to Antibiotics in Cystic Fibrosis.

PubMed

Gifford, Alex H; Dorman, Dana B; Moulton, Lisa A; Helm, Jennifer E; Griffin, Mary M; MacKenzie, Todd A

2015-12-01

Serum levels of hepcidin-25, a peptide hormone that reduces blood iron content, are elevated when patients with cystic fibrosis (CF) develop pulmonary exacerbation (PEx). Because hepcidin-25 is unavailable as a clinical laboratory test, we questioned whether a one-time serum iron level was associated with the subsequent number of days until PEx, as defined by the need to receive systemic antibiotics (ABX) for health deterioration. Clinical, biochemical, and microbiological parameters were simultaneously checked in 54 adults with CF. Charts were reviewed to determine when they first experienced a PEx after these parameters were assessed. Time to ABX was compared in subgroups with and without specific attributes. Multivariate linear regression was used to identify parameters that significantly explained variation in time to ABX. In univariate analyses, time to ABX was significantly shorter in subjects with Aspergillus-positive sputum cultures and CF-related diabetes. Multivariate linear regression models demonstrated that shorter time to ABX was associated with younger age, lower serum iron level, and Aspergillus sputum culture positivity. Serum iron, age, and Aspergillus sputum culture positivity are factors associated with shorter time to subsequent PEx in CF adults. © 2015 Wiley Periodicals, Inc.

Expression of Fas, FasL, caspase-8 and other factors of the extrinsic apoptotic pathway during the onset of interdigital tissue elimination.

PubMed

Svandova, E Budisova; Vesela, B; Lesot, H; Poliard, A; Matalova, E

2017-04-01

Elimination of the interdigital web is considered to be the classical model for assessing apoptosis. So far, most of the molecules described in the process have been connected to the intrinsic (mitochondrial) pathway. The extrinsic (receptor mediated) apoptotic pathway has been rather neglected, although it is important in development, immunomodulation and cancer therapy. This work aimed to investigate factors of the extrinsic apoptotic machinery during interdigital regression with a focus on three crucial initiators: Fas, Fas ligand and caspase-8. Immunofluorescent analysis of mouse forelimb histological sections revealed abundant expression of these molecules prior to digit separation. Subsequent PCR Array analyses indicated the expression of several markers engaged in the extrinsic pathway. Between embryonic days 11 and 13, statistically significant increases in the expression of Fas and caspase-8 were observed, along with other molecules involved in the extrinsic apoptotic pathway such as Dapk1, Traf3, Tnsf12, Tnfrsf1A and Ripk1. These results demonstrate for the first time the presence of extrinsic apoptotic components in mouse limb development and indicate novel candidates in the molecular network accompanying the regression of interdigital tissue during digitalisation.

Polarimetry based partial least square classification of ex vivo healthy and basal cell carcinoma human skin tissues.

PubMed

Ahmad, Iftikhar; Ahmad, Manzoor; Khan, Karim; Ikram, Masroor

2016-06-01

Optical polarimetry was employed for assessment of ex vivo healthy and basal cell carcinoma (BCC) tissue samples from human skin. Polarimetric analyses revealed that depolarization and retardance for healthy tissue group were significantly higher (p<0.001) compared to BCC tissue group. Histopathology indicated that these differences partially arise from BCC-related characteristic changes in tissue morphology. Wilks lambda statistics demonstrated the potential of all investigated polarimetric properties for computer assisted classification of the two tissue groups. Based on differences in polarimetric properties, partial least square (PLS) regression classified the samples with 100% accuracy, sensitivity and specificity. These findings indicate that optical polarimetry together with PLS statistics hold promise for automated pathology classification. Copyright © 2016 Elsevier B.V. All rights reserved.

Service with a smile: do emotional intelligence, gender, and autonomy moderate the emotional labor process?

PubMed

Johnson, Hazel-Anne M; Spector, Paul E

2007-10-01

This survey study of 176 participants from eight customer service organizations investigated how individual factors moderate the impact of emotional labor strategies on employee well-being. Hierarchical regression analyses indicated that gender and autonomy were significant moderators of the relationships between emotional labor strategies and the personal outcomes of emotional exhaustion, affective well-being, and job satisfaction. Females were more likely to experience negative consequences when engaging in surface acting. Autonomy served to alleviate negative outcomes for individuals who used emotional labor strategies often. Contrary to our hypotheses, emotional intelligence did not moderate the relationship between the emotional labor strategies and personal outcomes. Results demonstrated how the emotional labor process can influence employee well-being. (c) 2007 APA, all rights reserved.

A Network Method of Measuring Affiliation-based Peer Influence: Assessing the Influences of Teammates’ Smoking on Adolescent Smoking

PubMed Central

Fujimoto, Kayo; Unger, Jennifer B.; Valente, Thomas W.

2011-01-01

Using a network analytic framework, this study introduces a new method to measure peer influence based on adolescents’ affiliations or two-mode social network data. Exposure based on affiliations is referred to as the “affiliation exposure model.” This study demonstrates the methodology using data on young adolescent smoking being influenced by joint participation in school-based organized sports activities with smokers. The analytic sample consisted of 1260 American adolescents from age 10 to 13 in middle schools, and the results of the longitudinal regression analyses showed that adolescents were more likely to smoke as they were increasingly exposed to teammates who smoke. This study illustrates the importance of peer influence via affiliation through team sports. PMID:22313152

Dancing with the Muses: dissociation and flow.

PubMed

Thomson, Paula; Jaque, S Victoria

2012-01-01

This study investigated dissociative psychological processes and flow (dispositional and state) in a group of professional and pre-professional dancers (n=74). In this study, high scores for global (Mdn=4.14) and autotelic (Mdn=4.50) flow suggest that dancing was inherently integrating and rewarding, although 17.6% of the dancers were identified as possibly having clinical levels of dissociation (Dissociative Experiences Scale-Taxon cutoff score≥20). The results of the multivariate analysis of variance indicated that subjects with high levels of dissociation had significantly lower levels of global flow (p<.05). Stepwise linear regression analyses demonstrated that dispositional flow negatively predicted the dissociative constructs of depersonalization and taxon (p<.05) but did not significantly predict the variance in absorption/imagination (p>.05). As hypothesized, dissociation and flow seem to operate as different mental processes.

Remediation for Students With Mathematics Difficulties: An Intervention Study in Middle Schools.

PubMed

Moser Opitz, Elisabeth; Freesemann, Okka; Prediger, Susanne; Grob, Urs; Matull, Ina; Hußmann, Stephan

As empirical studies have consistently shown, low achievement in mathematics at the secondary level can often be traced to deficits in the understanding of certain basic arithmetic concepts taught in primary school. The present intervention study in middle schools evaluated whether such learning deficits can be reduced effectively and whether the type of instruction influences students' progress. The sample consisted of 123 students in 34 classes, split among one control group and two intervention groups: (a) small group instruction and (b) independent work partially integrated into regular classrooms. Over a period of 14 weeks, students were taught basic concepts, such as place value and basic operations. In addition, they practiced fact retrieval and counting (in groups). Multilevel regression analyses demonstrated that the interventions can be used to reduce given deficits.

Substance Use and Sexual Risk Within the Context of Gender Inequality in South Africa

PubMed Central

Wechsberg, Wendee M.; Luseno, Winnie; Riehman, Kara; Karg, Rhonda; Browne, Felicia; Parry, Charles

2011-01-01

This study examines substance use and sexual risk within the context of gender inequality among 163 women from an urban region of South Africa who were participating in a 2004–2006 study funded by the National Institute of Alcohol Abuse and Alcoholism. Items assessed patterns of substance use, gender inequality, risk communication, and psychological distress. Multivariate logistic regression analyses revealed that economic dependence on a main partner and traditional beliefs about a woman’s right to refuse sex were associated with substance use prior to or during sex with that partner. The findings demonstrate that substance abuse prior to sex may reinforce traditional beliefs and that women with more progressive beliefs about gender ideology seem better able to control their substance use in risky environments. PMID:18649238

Substance use and sexual risk within the context of gender inequality in South Africa.

PubMed

Wechsberg, Wendee M; Luseno, Winnie; Riehman, Kara; Karg, Rhonda; Browne, Felicia; Parry, Charles

2008-07-01

This study examines substance use and sexual risk within the context of gender inequality among 163 women from an urban region of South Africa who were participating in a 2004-2006 study funded by the National Institute of Alcohol Abuse and Alcoholism. Items assessed patterns of substance use, gender inequality, risk communication, and psychological distress. Multivariate logistic regression analyses revealed that economic dependence on a main partner and traditional beliefs about a woman's right to refuse sex were associated with substance use prior to or during sex with that partner. The findings demonstrate that substance abuse prior to sex may reinforce traditional beliefs and that women with more progressive beliefs about gender ideology seem better able to control their substance use in risky environments.

Partial Least Square Analyses of Landscape and Surface Water Biota Associations in the Savannah River Basin

EPA Science Inventory

Ecologists are often faced with problem of small sample size, correlated and large number of predictors, and high noise-to-signal relationships. This necessitates excluding important variables from the model when applying standard multiple or multivariate regression analyses. In ...

Systematic Review and Meta-Analysis: Dose-Response Relationship of Selective Serotonin Reuptake Inhibitors in Major Depressive Disorder.

PubMed

Jakubovski, Ewgeni; Varigonda, Anjali L; Freemantle, Nicholas; Taylor, Matthew J; Bloch, Michael H

2016-02-01

Previous studies suggested that the treatment response to selective serotonin reuptake inhibitors (SSRIs) in major depressive disorder follows a flat response curve within the therapeutic dose range. The present study was designed to clarify the relationship between dosage and treatment response in major depressive disorder. The authors searched PubMed for randomized placebo-controlled trials examining the efficacy of SSRIs for treating adults with major depressive disorder. Trials were also required to assess improvement in depression severity at multiple time points. Additional data were collected on treatment response and all-cause and side effect-related discontinuation. All medication doses were transformed into imipramine-equivalent doses. The longitudinal data were analyzed with a mixed-regression model. Endpoint and tolerability analyses were analyzed using meta-regression and stratified subgroup analysis by predefined SSRI dose categories in order to assess the effect of SSRI dosing on the efficacy and tolerability of SSRIs for major depressive disorder. Forty studies involving 10,039 participants were included. Longitudinal modeling (dose-by-time interaction=0.0007, 95% CI=0.0001-0.0013) and endpoint analysis (meta-regression: β=0.00053, 95% CI=0.00018-0.00088, z=2.98) demonstrated a small but statistically significant positive association between SSRI dose and efficacy. Higher doses of SSRIs were associated with an increased likelihood of dropouts due to side effects (meta-regression: β=0.00207, 95% CI=0.00071-0.00342, z=2.98) and decreased likelihood of all-cause dropout (meta-regression: β=-0.00093, 95% CI=-0.00165 to -0.00021, z=-2.54). Higher doses of SSRIs appear slightly more effective in major depressive disorder. This benefit appears to plateau at around 250 mg of imipramine equivalents (50 mg of fluoxetine). The slightly increased benefits of SSRIs at higher doses are somewhat offset by decreased tolerability at high doses.

Association Between Dietary Intake and Function in Amyotrophic Lateral Sclerosis.

PubMed

Nieves, Jeri W; Gennings, Chris; Factor-Litvak, Pam; Hupf, Jonathan; Singleton, Jessica; Sharf, Valerie; Oskarsson, Björn; Fernandes Filho, J Americo M; Sorenson, Eric J; D'Amico, Emanuele; Goetz, Ray; Mitsumoto, Hiroshi

2016-12-01

There is growing interest in the role of nutrition in the pathogenesis and progression of amyotrophic lateral sclerosis (ALS). To evaluate the associations between nutrients, individually and in groups, and ALS function and respiratory function at diagnosis. A cross-sectional baseline analysis of the Amyotrophic Lateral Sclerosis Multicenter Cohort Study of Oxidative Stress study was conducted from March 14, 2008, to February 27, 2013, at 16 ALS clinics throughout the United States among 302 patients with ALS symptom duration of 18 months or less. Nutrient intake, measured using a modified Block Food Frequency Questionnaire (FFQ). Amyotrophic lateral sclerosis function, measured using the ALS Functional Rating Scale-Revised (ALSFRS-R), and respiratory function, measured using percentage of predicted forced vital capacity (FVC). Baseline data were available on 302 patients with ALS (median age, 63.2 years [interquartile range, 55.5-68.0 years]; 178 men and 124 women). Regression analysis of nutrients found that higher intakes of antioxidants and carotenes from vegetables were associated with higher ALSFRS-R scores or percentage FVC. Empirically weighted indices using the weighted quantile sum regression method of "good" micronutrients and "good" food groups were positively associated with ALSFRS-R scores (β [SE], 2.7 [0.69] and 2.9 [0.9], respectively) and percentage FVC (β [SE], 12.1 [2.8] and 11.5 [3.4], respectively) (all P < .001). Positive and significant associations with ALSFRS-R scores (β [SE], 1.5 [0.61]; P = .02) and percentage FVC (β [SE], 5.2 [2.2]; P = .02) for selected vitamins were found in exploratory analyses. Antioxidants, carotenes, fruits, and vegetables were associated with higher ALS function at baseline by regression of nutrient indices and weighted quantile sum regression analysis. We also demonstrated the usefulness of the weighted quantile sum regression method in the evaluation of diet. Those responsible for nutritional care of the patient with ALS should consider promoting fruit and vegetable intake since they are high in antioxidants and carotenes.

Differences in Causal Estimates from Longitudinal Analyses of Residualized versus Simple Gain Scores: Contrasting Controls for Selection and Regression Artifacts

ERIC Educational Resources Information Center

Larzelere, Robert E.; Ferrer, Emilio; Kuhn, Brett R.; Danelia, Ketevan

2010-01-01

This study estimates the causal effects of six corrective actions for children's problem behaviors, comparing four types of longitudinal analyses that correct for pre-existing differences in a cohort of 1,464 4- and 5-year-olds from Canadian National Longitudinal Survey of Children and Youth (NLSCY) data. Analyses of residualized gain scores found…

Identification of Sexually Abused Female Adolescents at Risk for Suicidal Ideations: A Classification and Regression Tree Analysis

ERIC Educational Resources Information Center

Brabant, Marie-Eve; Hebert, Martine; Chagnon, Francois

2013-01-01

This study explored the clinical profiles of 77 female teenager survivors of sexual abuse and examined the association of abuse-related and personal variables with suicidal ideations. Analyses revealed that 64% of participants experienced suicidal ideations. Findings from classification and regression tree analysis indicated that depression,…

miR-199a-5p regulates HIF-1α and OSGIN2 and its expression is correlated to soft-tissue sarcoma patients' outcome

PubMed Central

Keßler, Jacqueline; Rot, Swetlana; Bache, Matthias; Kappler, Matthias; Würl, Peter; Vordermark, Dirk; Taubert, Helge; Greither, Thomas

2016-01-01

Soft tissue sarcomas are a heterogeneous group of malignant neoplasms of mesenchymal origin. Partly due to hypoxia, an aggressive and radioresistant phenotype frequently develops, resulting in poorer patient outcome. microRNAs (miRNAs) are tiny, non-coding regulators of gene expression and in situations of cellular stress situations may predict clinical progression and patient outcome. In the present study, hypoxia-associated miR-199a-5p expression in 96 soft tissue sarcoma samples was analysed by reverse transcription-quantitative polymerase chain reaction and associations between miR-199a-5p expression and patient clinicopathological characteristics and survival were measured. Additionally, luciferase reporter assays analyzed the post-transcriptional regulation of hypoxia-associated genes hypoxia-inducible factor 1α (HIF-1α), oxidative stress induced growth inhibitor 2 (OSGIN2) and vascular endothelial growth factor (VEGF) by miR-199a-5p. Survival analyses indicated that low expression of miR-199a-5p was significantly correlated with poorer tumor-specific survival (univariate Cox's-Regression analyses; relative risk=1.92, P=0.029). Furthermore, it was demonstrated that the 3′UTR of HIF-1α and OSGIN2 genes were regulated by miR-199a-5p in-vitro, although the 3′UTR of VEGF was not. To the best of our knowledge, this is the first report demonstrating the regulation of the 3′untranslated region of the OSGIN2 gene by miR-199a-5p and a significant correlation between low miR-199a-5p expression and a poor outcome of patients with soft tissue sarcoma. PMID:28101243

Partner's influences and other correlates of prenatal alcohol use.

PubMed

van der Wulp, Nickie Y; Hoving, Ciska; de Vries, Hein

2015-04-01

To investigate the influence of partners on alcohol consumption in pregnant women within the context of other factors. A Dutch nationwide online cross-sectional study among 158 pregnant women and their partners was conducted. To identify correlates of prenatal alcohol use, including perceived and reported partner norm (i.e. partner's belief regarding acceptability of prenatal alcohol use), partner modeling (i.e. partner's alcohol use during the woman's pregnancy) and partner support (i.e. partner's help in abstaining from alcohol during pregnancy), independent sample T-tests and Chi square tests were conducted. Correlation analyses tested the relationship between perceived and reported partner influence. Multivariate logistic hierarchical regression analyses tested the independent impact of partner's perceived and reported influence next to other correlates from the I-Change Model. Pregnant women who consumed alcohol perceived a weaker partner norm (p < 0.001) and less partner modeling (p < 0.05), with the partner reporting a weaker norm (p < 0.001), more drinking days per week (p < 0.05) and weaker support (p < 0.05). Perceived and reported partner norm, modeling and support were positively related (respectively p < 0.01, p < 0.01 and p < 0.05). The multivariate analyses demonstrated that pregnant women with a higher education who perceived lower severity of harm due to prenatal alcohol use and a weaker partner norm were more likely to use alcohol (R(2) = 0.42). This study demonstrated that perceived partner norm was the most critical of the constructs of perceived and reported partner influences in explaining prenatal alcohol use.

Secure Logistic Regression Based on Homomorphic Encryption: Design and Evaluation

PubMed Central

Song, Yongsoo; Wang, Shuang; Xia, Yuhou; Jiang, Xiaoqian

2018-01-01

Background Learning a model without accessing raw data has been an intriguing idea to security and machine learning researchers for years. In an ideal setting, we want to encrypt sensitive data to store them on a commercial cloud and run certain analyses without ever decrypting the data to preserve privacy. Homomorphic encryption technique is a promising candidate for secure data outsourcing, but it is a very challenging task to support real-world machine learning tasks. Existing frameworks can only handle simplified cases with low-degree polynomials such as linear means classifier and linear discriminative analysis. Objective The goal of this study is to provide a practical support to the mainstream learning models (eg, logistic regression). Methods We adapted a novel homomorphic encryption scheme optimized for real numbers computation. We devised (1) the least squares approximation of the logistic function for accuracy and efficiency (ie, reduce computation cost) and (2) new packing and parallelization techniques. Results Using real-world datasets, we evaluated the performance of our model and demonstrated its feasibility in speed and memory consumption. For example, it took approximately 116 minutes to obtain the training model from the homomorphically encrypted Edinburgh dataset. In addition, it gives fairly accurate predictions on the testing dataset. Conclusions We present the first homomorphically encrypted logistic regression outsourcing model based on the critical observation that the precision loss of classification models is sufficiently small so that the decision plan stays still. PMID:29666041

A robust and efficient stepwise regression method for building sparse polynomial chaos expansions

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

Abraham, Simon, E-mail: Simon.Abraham@ulb.ac.be; Raisee, Mehrdad; Ghorbaniasl, Ghader

2017-03-01

Polynomial Chaos (PC) expansions are widely used in various engineering fields for quantifying uncertainties arising from uncertain parameters. The computational cost of classical PC solution schemes is unaffordable as the number of deterministic simulations to be calculated grows dramatically with the number of stochastic dimension. This considerably restricts the practical use of PC at the industrial level. A common approach to address such problems is to make use of sparse PC expansions. This paper presents a non-intrusive regression-based method for building sparse PC expansions. The most important PC contributions are detected sequentially through an automatic search procedure. The variable selectionmore » criterion is based on efficient tools relevant to probabilistic method. Two benchmark analytical functions are used to validate the proposed algorithm. The computational efficiency of the method is then illustrated by a more realistic CFD application, consisting of the non-deterministic flow around a transonic airfoil subject to geometrical uncertainties. To assess the performance of the developed methodology, a detailed comparison is made with the well established LAR-based selection technique. The results show that the developed sparse regression technique is able to identify the most significant PC contributions describing the problem. Moreover, the most important stochastic features are captured at a reduced computational cost compared to the LAR method. The results also demonstrate the superior robustness of the method by repeating the analyses using random experimental designs.« less

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

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.

[How medical students perform academically by admission types?].

PubMed

Kim, Se-Hoon; Lee, Keumho; Hur, Yera; Kim, Ji-Ha

2013-09-01

Despite the importance of selecting students whom are capable for medical education and to become a good doctor, not enough studies have been done in the category. This study focused on analysing the medical students' academic performance (grade point average, GPA) differences, flunk and dropout rates by admission types. From 2004 to 2010, we gathered 369 Konyang University College of Medicine's students admission data and analyzed the differences between admission method and academic achievement, differences in failure and dropout rates. Analysis of variance (ANOVA), ordinary least square, and logistic regression were used. The rolling students showed higher academic achievement from year 1 to 3 than regular students (p < 0.01). Using admission type variable as control variable in multiple regression model similar results were shown. But unlike the results of ANOVA, GPA differences by admission types were shown not only in lower academic years but also in year 6 (p < 0.01). From the regression analysis of flunk and dropout rate by admission types, regular admission type students showed higher drop out rate than the rolling ones which demonstrates admission types gives significant effect on flunk or dropout rates in medical students (p < 0.01). The rolling admissions type students tend to show lower flunk rate and dropout rates and perform better academically. This implies selecting students primarily by Korean College Scholastic Ability Test does not guarantee their academic success in medical education. Thus we suggest a more in-depth comprehensive method of selecting students that are appropriate to individual medical school's educational goal.

The Predictive Effects of Protection Motivation Theory on Intention and Behaviour of Physical Activity in Patients with Type 2 Diabetes.

PubMed

Ali Morowatisharifabad, Mohammad; Abdolkarimi, Mahdi; Asadpour, Mohammad; Fathollahi, Mahmood Sheikh; Balaee, Parisa

2018-04-15

Theory-based education tailored to target behaviour and group can be effective in promoting physical activity. The purpose of this study was to examine the predictive power of Protection Motivation Theory on intent and behaviour of Physical Activity in Patients with Type 2 Diabetes. This descriptive study was conducted on 250 patients in Rafsanjan, Iran. To examine the scores of protection motivation theory structures, a researcher-made questionnaire was used. Its validity and reliability were confirmed. The level of physical activity was also measured by the International Short - form Physical Activity Inventory. Its validity and reliability were also approved. Data were analysed by statistical tests including correlation coefficient, chi-square, logistic regression and linear regression. The results revealed that there was a significant correlation between all the protection motivation theory constructs and the intention to do physical activity. The results showed that the Theory structures were able to predict 60% of the variance of physical activity intention. The results of logistic regression demonstrated that increase in the score of physical activity intent and self - efficacy increased the chance of higher level of physical activity by 3.4 and 1.5 times, respectively OR = (3.39, 1.54). Considering the ability of protection motivation theory structures to explain the physical activity behaviour, interventional designs are suggested based on the structures of this theory, especially to improve self -efficacy as the most powerful factor in predicting physical activity intention and behaviour.

Advantages of the net benefit regression framework for economic evaluations of interventions in the workplace: a case study of the cost-effectiveness of a collaborative mental health care program for people receiving short-term disability benefits for psychiatric disorders.

PubMed

Hoch, Jeffrey S; Dewa, Carolyn S

2014-04-01

Economic evaluations commonly accompany trials of new treatments or interventions; however, regression methods and their corresponding advantages for the analysis of cost-effectiveness data are not well known. To illustrate regression-based economic evaluation, we present a case study investigating the cost-effectiveness of a collaborative mental health care program for people receiving short-term disability benefits for psychiatric disorders. We implement net benefit regression to illustrate its strengths and limitations. Net benefit regression offers a simple option for cost-effectiveness analyses of person-level data. By placing economic evaluation in a regression framework, regression-based techniques can facilitate the analysis and provide simple solutions to commonly encountered challenges. Economic evaluations of person-level data (eg, from a clinical trial) should use net benefit regression to facilitate analysis and enhance results.

Variance Estimation Using Replication Methods in Structural Equation Modeling with Complex Sample Data

ERIC Educational Resources Information Center

Stapleton, Laura M.

2008-01-01

This article discusses replication sampling variance estimation techniques that are often applied in analyses using data from complex sampling designs: jackknife repeated replication, balanced repeated replication, and bootstrapping. These techniques are used with traditional analyses such as regression, but are currently not used with structural…

Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia

NASA Astrophysics Data System (ADS)

Pradhan, Biswajeet

2010-05-01

This paper presents the results of the cross-validation of a multivariate logistic regression model using remote sensing data and GIS for landslide hazard analysis on the Penang, Cameron, and Selangor areas in Malaysia. Landslide locations in the study areas were identified by interpreting aerial photographs and satellite images, supported by field surveys. SPOT 5 and Landsat TM satellite imagery were used to map landcover and vegetation index, respectively. Maps of topography, soil type, lineaments and land cover were constructed from the spatial datasets. Ten factors which influence landslide occurrence, i.e., slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, soil type, landcover, rainfall precipitation, and normalized difference vegetation index (ndvi), were extracted from the spatial database and the logistic regression coefficient of each factor was computed. Then the landslide hazard was analysed using the multivariate logistic regression coefficients derived not only from the data for the respective area but also using the logistic regression coefficients calculated from each of the other two areas (nine hazard maps in all) as a cross-validation of the model. For verification of the model, the results of the analyses were then compared with the field-verified landslide locations. Among the three cases of the application of logistic regression coefficient in the same study area, the case of Selangor based on the Selangor logistic regression coefficients showed the highest accuracy (94%), where as Penang based on the Penang coefficients showed the lowest accuracy (86%). Similarly, among the six cases from the cross application of logistic regression coefficient in other two areas, the case of Selangor based on logistic coefficient of Cameron showed highest (90%) prediction accuracy where as the case of Penang based on the Selangor logistic regression coefficients showed the lowest accuracy (79%). Qualitatively, the cross application model yields reasonable results which can be used for preliminary landslide hazard mapping.

High HbA1c levels correlate with reduced plaque regression during statin treatment in patients with stable coronary artery disease: Results of the coronary atherosclerosis study measuring effects of rosuvastatin using intravascular ultrasound in Japanese subjects (COSMOS)

PubMed Central

2012-01-01

Background The incidence of cardiac events is higher in patients with diabetes than in people without diabetes. The Coronary Atherosclerosis Study Measuring Effects of Rosuvastatin Using Intravascular Ultrasound in Japanese Subjects (COSMOS) demonstrated significant plaque regression in Japanese patients with chronic coronary disease after 76 weeks of rosuvastatin (2.5 mg once daily, up-titrated to a maximum of 20 mg/day to achieve LDL cholesterol <80 mg/dl). Methods In this subanalysis of COSMOS, we examined the association between HbA1c and plaque regression in 40 patients with HbA1c ≥6.5% (high group) and 86 patients with HbA1c <6.5% (low group). Results In multivariate analyses, HbA1c and plaque volume at baseline were major determinants of plaque regression. LDL cholesterol decreased by 37% and 39% in the high and low groups, respectively, while HDL cholesterol increased by 16% and 22%, respectively. The reduction in plaque volume was significantly (p = 0.04) greater in the low group (from 71.0 ± 39.9 to 64.7 ± 34.7 mm3) than in the high group (from 74.3 ± 34.2 to 71.4 ± 32.3 mm3). Vessel volume increased in the high group but not in the low group (change from baseline: +4.2% vs −0.8%, p = 0.02). Change in plaque volume was significantly correlated with baseline HbA1c. Conclusions Despite similar improvements in lipid levels, plaque regression was less pronounced in patients with high HbA1c levels compared with those with low levels. Tight glucose control during statin therapy may enhance plaque regression in patients with stable coronary disease. Trial registration ClinicalTrials.gov, Identifier NCT00329160 PMID:22831708

Logistic Regression in the Identification of Hazards in Construction

NASA Astrophysics Data System (ADS)

Drozd, Wojciech

2017-10-01

The construction site and its elements create circumstances that are conducive to the formation of risks to safety during the execution of works. Analysis indicates the critical importance of these factors in the set of characteristics that describe the causes of accidents in the construction industry. This article attempts to analyse the characteristics related to the construction site, in order to indicate their importance in defining the circumstances of accidents at work. The study includes sites inspected in 2014 - 2016 by the employees of the District Labour Inspectorate in Krakow (Poland). The analysed set of detailed (disaggregated) data includes both quantitative and qualitative characteristics. The substantive task focused on classification modelling in the identification of hazards in construction and identifying those of the analysed characteristics that are important in an accident. In terms of methodology, resource data analysis using statistical classifiers, in the form of logistic regression, was the method used.

Parental employment status and adolescents' health: the role of financial situation, parent-adolescent relationship and adolescents' resilience.

PubMed

Bacikova-Sleskova, Maria; Benka, Jozef; Orosova, Olga

2015-01-01

The paper deals with parental employment status and its relationship to adolescents' self-reported health. It studies the role of the financial situation, parent-adolescent relationship and adolescent resilience in the relationship between parental employment status and adolescents' self-rated health, vitality and mental health. Multiple regression analyses were used to analyse questionnaire data obtained from 2799 adolescents (mean age 14.3) in 2006. The results show a negative association of the father's, but not mother's unemployment or non-employment with adolescents' health. Regression analyses showed that neither financial strain nor a poor parent-adolescent relationship or a low score in resilience accounted for the relationship between the father's unemployment or non-employment and poorer adolescent health. Furthermore, resilience did not work as a buffer against the negative impact of fathers' unemployment on adolescents' health.

Applications of MIDAS regression in analysing trends in water quality

NASA Astrophysics Data System (ADS)

Penev, Spiridon; Leonte, Daniela; Lazarov, Zdravetz; Mann, Rob A.

2014-04-01

We discuss novel statistical methods in analysing trends in water quality. Such analysis uses complex data sets of different classes of variables, including water quality, hydrological and meteorological. We analyse the effect of rainfall and flow on trends in water quality utilising a flexible model called Mixed Data Sampling (MIDAS). This model arises because of the mixed frequency in the data collection. Typically, water quality variables are sampled fortnightly, whereas the rain data is sampled daily. The advantage of using MIDAS regression is in the flexible and parsimonious modelling of the influence of the rain and flow on trends in water quality variables. We discuss the model and its implementation on a data set from the Shoalhaven Supply System and Catchments in the state of New South Wales, Australia. Information criteria indicate that MIDAS modelling improves upon simplistic approaches that do not utilise the mixed data sampling nature of the data.

Normalization Regression Estimation With Application to a Nonorthogonal, Nonrecursive Model of School Learning.

ERIC Educational Resources Information Center

Bulcock, J. W.; And Others

Advantages of normalization regression estimation over ridge regression estimation are demonstrated by reference to Bloom's model of school learning. Theoretical concern centered on the structure of scholastic achievement at grade 10 in Canadian high schools. Data on 886 students were randomly sampled from the Carnegie Human Resources Data Bank.…

CO2 flux determination by closed-chamber methods can be seriously biased by inappropriate application of linear regression

NASA Astrophysics Data System (ADS)

Kutzbach, L.; Schneider, J.; Sachs, T.; Giebels, M.; Nykänen, H.; Shurpali, N. J.; Martikainen, P. J.; Alm, J.; Wilmking, M.

2007-07-01

Closed (non-steady state) chambers are widely used for quantifying carbon dioxide (CO2) fluxes between soils or low-stature canopies and the atmosphere. It is well recognised that covering a soil or vegetation by a closed chamber inherently disturbs the natural CO2 fluxes by altering the concentration gradients between the soil, the vegetation and the overlying air. Thus, the driving factors of CO2 fluxes are not constant during the closed chamber experiment, and no linear increase or decrease of CO2 concentration over time within the chamber headspace can be expected. Nevertheless, linear regression has been applied for calculating CO2 fluxes in many recent, partly influential, studies. This approach was justified by keeping the closure time short and assuming the concentration change over time to be in the linear range. Here, we test if the application of linear regression is really appropriate for estimating CO2 fluxes using closed chambers over short closure times and if the application of nonlinear regression is necessary. We developed a nonlinear exponential regression model from diffusion and photosynthesis theory. This exponential model was tested with four different datasets of CO2 flux measurements (total number: 1764) conducted at three peatland sites in Finland and a tundra site in Siberia. The flux measurements were performed using transparent chambers on vegetated surfaces and opaque chambers on bare peat surfaces. Thorough analyses of residuals demonstrated that linear regression was frequently not appropriate for the determination of CO2 fluxes by closed-chamber methods, even if closure times were kept short. The developed exponential model was well suited for nonlinear regression of the concentration over time c(t) evolution in the chamber headspace and estimation of the initial CO2 fluxes at closure time for the majority of experiments. CO2 flux estimates by linear regression can be as low as 40% of the flux estimates of exponential regression for closure times of only two minutes and even lower for longer closure times. The degree of underestimation increased with increasing CO2 flux strength and is dependent on soil and vegetation conditions which can disturb not only the quantitative but also the qualitative evaluation of CO2 flux dynamics. The underestimation effect by linear regression was observed to be different for CO2 uptake and release situations which can lead to stronger bias in the daily, seasonal and annual CO2 balances than in the individual fluxes. To avoid serious bias of CO2 flux estimates based on closed chamber experiments, we suggest further tests using published datasets and recommend the use of nonlinear regression models for future closed chamber studies.

Direct-on-Filter α-Quartz Estimation in Respirable Coal Mine Dust Using Transmission Fourier Transform Infrared Spectrometry and Partial Least Squares Regression

PubMed Central

Miller, Arthur L.; Weakley, Andrew Todd; Griffiths, Peter R.; Cauda, Emanuele G.; Bayman, Sean

2017-01-01

In order to help reduce silicosis in miners, the National Institute for Occupational Health and Safety (NIOSH) is developing field-portable methods for measuring airborne respirable crystalline silica (RCS), specifically the polymorph α-quartz, in mine dusts. In this study we demonstrate the feasibility of end-of-shift measurement of α-quartz using a direct-on-filter (DoF) method to analyze coal mine dust samples deposited onto polyvinyl chloride filters. The DoF method is potentially amenable for on-site analyses, but deviates from the current regulatory determination of RCS for coal mines by eliminating two sample preparation steps: ashing the sampling filter and redepositing the ash prior to quantification by Fourier transform infrared (FT-IR) spectrometry. In this study, the FT-IR spectra of 66 coal dust samples from active mines were used, and the RCS was quantified by using: (1) an ordinary least squares (OLS) calibration approach that utilizes standard silica material as done in the Mine Safety and Health Administration's P7 method; and (2) a partial least squares (PLS) regression approach. Both were capable of accounting for kaolinite, which can confound the IR analysis of silica. The OLS method utilized analytical standards for silica calibration and kaolin correction, resulting in a good linear correlation with P7 results and minimal bias but with the accuracy limited by the presence of kaolinite. The PLS approach also produced predictions well-correlated to the P7 method, as well as better accuracy in RCS prediction, and no bias due to variable kaolinite mass. Besides decreased sensitivity to mineral or substrate confounders, PLS has the advantage that the analyst is not required to correct for the presence of kaolinite or background interferences related to the substrate, making the method potentially viable for automated RCS prediction in the field. This study demonstrated the efficacy of FT-IR transmission spectrometry for silica determination in coal mine dusts, using both OLS and PLS analyses, when kaolinite was present. PMID:27645724

Direct-on-Filter α-Quartz Estimation in Respirable Coal Mine Dust Using Transmission Fourier Transform Infrared Spectrometry and Partial Least Squares Regression.

PubMed

Miller, Arthur L; Weakley, Andrew Todd; Griffiths, Peter R; Cauda, Emanuele G; Bayman, Sean

2017-05-01

In order to help reduce silicosis in miners, the National Institute for Occupational Health and Safety (NIOSH) is developing field-portable methods for measuring airborne respirable crystalline silica (RCS), specifically the polymorph α-quartz, in mine dusts. In this study we demonstrate the feasibility of end-of-shift measurement of α-quartz using a direct-on-filter (DoF) method to analyze coal mine dust samples deposited onto polyvinyl chloride filters. The DoF method is potentially amenable for on-site analyses, but deviates from the current regulatory determination of RCS for coal mines by eliminating two sample preparation steps: ashing the sampling filter and redepositing the ash prior to quantification by Fourier transform infrared (FT-IR) spectrometry. In this study, the FT-IR spectra of 66 coal dust samples from active mines were used, and the RCS was quantified by using: (1) an ordinary least squares (OLS) calibration approach that utilizes standard silica material as done in the Mine Safety and Health Administration's P7 method; and (2) a partial least squares (PLS) regression approach. Both were capable of accounting for kaolinite, which can confound the IR analysis of silica. The OLS method utilized analytical standards for silica calibration and kaolin correction, resulting in a good linear correlation with P7 results and minimal bias but with the accuracy limited by the presence of kaolinite. The PLS approach also produced predictions well-correlated to the P7 method, as well as better accuracy in RCS prediction, and no bias due to variable kaolinite mass. Besides decreased sensitivity to mineral or substrate confounders, PLS has the advantage that the analyst is not required to correct for the presence of kaolinite or background interferences related to the substrate, making the method potentially viable for automated RCS prediction in the field. This study demonstrated the efficacy of FT-IR transmission spectrometry for silica determination in coal mine dusts, using both OLS and PLS analyses, when kaolinite was present.

Convergence of self-reports and coworker reports of counterproductive work behavior: a cross-sectional multi-source survey among health care workers.

PubMed

de Jonge, Jan; Peeters, Maria C W

2009-05-01

Most studies of counterproductive work behavior (CWB) are criticized for overreliance on single-source self-reports. This study attempts to triangulate on behaviors and perceptions of the work environment by linking job incumbent self-report with coworker report of the job incumbent's behaviors. Theoretical framework is the Demand-Induced Strain Compensation (DISC) Model, which proposes in general that specific job resources should match specific job demands to reduce deviant behavioral outcomes such as CWB. To test the extent to which job incumbent self-report and coworker report of CWB in health care work converge, and the extent to which job incumbent-reported work-related antecedents (i.e., job demands and job resources) similarly predict both self-reported and coworker-reported behaviors (in line with DISC theory). A cross-sectional survey with anonymous questionnaires was conducted, using data from two different sources (self-reports and coworker reports). A large organization for residential elderly care in the Northern urban area in The Netherlands. Self-report and coworker questionnaires were distributed to 123 health care workers, of which 73 people returned the self-report questionnaire (59% response rate). In addition, 66 out of 123 coworker questionnaires were returned (54% coworker response rate). In total 54 surveys of job incumbents and coworkers could be matched. Next to descriptive statistics, t-test, and correlations, hierarchical regression analyses were conducted using SPSS 15.0 for Windows. Correlations and a t-test demonstrated significant convergence between job incumbent and coworker reports of CWB. Hierarchical regression analyses showed that both job incumbent and coworker data consistently demonstrated CWB to be related to its work-related antecedents. Specifically, findings showed that both physical and emotional job resources moderated the relation between physical job demands and CWB. The current findings provide stronger evidence that (multi-source measured) CWB is associated with job demands and job resources than has been provided in the past. Moreover, the present study implies that DISC theory has the potential of making a profound contribution to our understanding of counterproductive working behaviors in health care work. Future longitudinal studies should investigate this kind of relations more intensely.

Regression methods for spatially correlated data: an example using beetle attacks in a seed orchard

Treesearch

Preisler Haiganoush; Nancy G. Rappaport; David L. Wood

1997-01-01

We present a statistical procedure for studying the simultaneous effects of observed covariates and unmeasured spatial variables on responses of interest. The procedure uses regression type analyses that can be used with existing statistical software packages. An example using the rate of twig beetle attacks on Douglas-fir trees in a seed orchard illustrates the...

How Variables Uncorrelated with the Dependent Variable Can Actually Make Excellent Predictors: The Important Suppressor Variable Case.

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…

Per capita community-level effects of an invasive grass, Microstegium vimineum, on vegetation in mesic forests in northern Mississippi (USA)

Treesearch

J. Stephen Brewer

2010-01-01

Quantifying per capita impacts of invasive species on resident communities requires integrating regression analyses with experiments under natural conditions. Using multivariate and univariate approaches, I regressed the abundance of 105 resident species of groundcover plants and tree seedlings against the abundance and height of an invasive grass, Microstegium...

Two-Year versus One-Year Head Start Program Impact: Addressing Selection Bias by Comparing Regression Modeling with Propensity Score Analysis

ERIC Educational Resources Information Center

Leow, Christine; Wen, Xiaoli; Korfmacher, Jon

2015-01-01

This article compares regression modeling and propensity score analysis as different types of statistical techniques used in addressing selection bias when estimating the impact of two-year versus one-year Head Start on children's school readiness. The analyses were based on the national Head Start secondary dataset. After controlling for…

The Impact of Being Labeled as a Persistently Lowest Achieving School: Regression Discontinuity Evidence on Consequential School Labeling

ERIC Educational Resources Information Center

Saw, Guan; Schneider, Barbara; Frank, Kenneth; Chen, I-Chien; Keesler, Venessa; Martineau, Joseph

2017-01-01

Since the No Child Left Behind Act was enacted, grading and labeling of schools as low performing have been increasingly used as means to incentivize failing schools to raise student achievement. Using statewide high school data from Michigan, our regression discontinuity analyses show that the bottom 5% of schools identified as persistently…

Regression Analyses on the Butterfly Ballot Effect: A Statistical Perspective of the US 2000 Election

ERIC Educational Resources Information Center

Wu, Dane W.

2002-01-01

The year 2000 US presidential election between Al Gore and George Bush has been the most intriguing and controversial one in American history. The state of Florida was the trigger for the controversy, mainly, due to the use of the misleading "butterfly ballot". Using prediction (or confidence) intervals for least squares regression lines…

Erosion and soil displacement related to timber harvesting in northwestern California, U.S.A.

Treesearch

R.M. Rice; D.J. Furbish

1984-01-01

The relationship between measures of site disturbance and erosion resulting from timber harvest was studied by regression analyses. None of the 12 regression models developed and tested yielded a coefficient of determination (R2) greater than 0.60. The results indicated that the poor fits to the data were due, in part, to unexplained qualitative...

"Erosion and soil displacement related to timber harvesting in northwestern California, U.S.A."

Treesearch

R. M. Rice; D. J. Furbish

1984-01-01

The relationship between measures of site disturbance and erosion resulting from timber harvest was studied by regression analyses. None of the 12 regression models developed and tested yielded a coefficient of determination (R 2) greater than 0.60. The results indicated that the poor fits to the data were due, in part, to unexplained qualitative differences in...

Regressive Imagery in Creative Problem-Solving: Comparing Verbal Protocols of Expert and Novice Visual Artists and Computer Programmers

ERIC Educational Resources Information Center

Kozbelt, Aaron; Dexter, Scott; Dolese, Melissa; Meredith, Daniel; Ostrofsky, Justin

2015-01-01

We applied computer-based text analyses of regressive imagery to verbal protocols of individuals engaged in creative problem-solving in two domains: visual art (23 experts, 23 novices) and computer programming (14 experts, 14 novices). Percentages of words involving primary process and secondary process thought, plus emotion-related words, were…

A classical regression framework for mediation analysis: fitting one model to estimate mediation effects.

PubMed

Saunders, Christina T; Blume, Jeffrey D

2017-10-26

Mediation analysis explores the degree to which an exposure's effect on an outcome is diverted through a mediating variable. We describe a classical regression framework for conducting mediation analyses in which estimates of causal mediation effects and their variance are obtained from the fit of a single regression model. The vector of changes in exposure pathway coefficients, which we named the essential mediation components (EMCs), is used to estimate standard causal mediation effects. Because these effects are often simple functions of the EMCs, an analytical expression for their model-based variance follows directly. Given this formula, it is instructive to revisit the performance of routinely used variance approximations (e.g., delta method and resampling methods). Requiring the fit of only one model reduces the computation time required for complex mediation analyses and permits the use of a rich suite of regression tools that are not easily implemented on a system of three equations, as would be required in the Baron-Kenny framework. Using data from the BRAIN-ICU study, we provide examples to illustrate the advantages of this framework and compare it with the existing approaches. © The Author 2017. Published by Oxford University Press.

Procedures for adjusting regional regression models of urban-runoff quality using local data

USGS Publications Warehouse

Hoos, A.B.; Sisolak, J.K.

1993-01-01

Statistical operations termed model-adjustment procedures (MAP?s) can be used to incorporate local data into existing regression models to improve the prediction of urban-runoff quality. Each MAP is a form of regression analysis in which the local data base is used as a calibration data set. Regression coefficients are determined from the local data base, and the resulting `adjusted? regression models can then be used to predict storm-runoff quality at unmonitored sites. The response variable in the regression analyses is the observed load or mean concentration of a constituent in storm runoff for a single storm. The set of explanatory variables used in the regression analyses is different for each MAP, but always includes the predicted value of load or mean concentration from a regional regression model. The four MAP?s examined in this study were: single-factor regression against the regional model prediction, P, (termed MAP-lF-P), regression against P,, (termed MAP-R-P), regression against P, and additional local variables (termed MAP-R-P+nV), and a weighted combination of P, and a local-regression prediction (termed MAP-W). The procedures were tested by means of split-sample analysis, using data from three cities included in the Nationwide Urban Runoff Program: Denver, Colorado; Bellevue, Washington; and Knoxville, Tennessee. The MAP that provided the greatest predictive accuracy for the verification data set differed among the three test data bases and among model types (MAP-W for Denver and Knoxville, MAP-lF-P and MAP-R-P for Bellevue load models, and MAP-R-P+nV for Bellevue concentration models) and, in many cases, was not clearly indicated by the values of standard error of estimate for the calibration data set. A scheme to guide MAP selection, based on exploratory data analysis of the calibration data set, is presented and tested. The MAP?s were tested for sensitivity to the size of a calibration data set. As expected, predictive accuracy of all MAP?s for the verification data set decreased as the calibration data-set size decreased, but predictive accuracy was not as sensitive for the MAP?s as it was for the local regression models.

An automated ranking platform for machine learning regression models for meat spoilage prediction using multi-spectral imaging and metabolic profiling.

PubMed

Estelles-Lopez, Lucia; Ropodi, Athina; Pavlidis, Dimitris; Fotopoulou, Jenny; Gkousari, Christina; Peyrodie, Audrey; Panagou, Efstathios; Nychas, George-John; Mohareb, Fady

2017-09-01

Over the past decade, analytical approaches based on vibrational spectroscopy, hyperspectral/multispectral imagining and biomimetic sensors started gaining popularity as rapid and efficient methods for assessing food quality, safety and authentication; as a sensible alternative to the expensive and time-consuming conventional microbiological techniques. Due to the multi-dimensional nature of the data generated from such analyses, the output needs to be coupled with a suitable statistical approach or machine-learning algorithms before the results can be interpreted. Choosing the optimum pattern recognition or machine learning approach for a given analytical platform is often challenging and involves a comparative analysis between various algorithms in order to achieve the best possible prediction accuracy. In this work, "MeatReg", a web-based application is presented, able to automate the procedure of identifying the best machine learning method for comparing data from several analytical techniques, to predict the counts of microorganisms responsible of meat spoilage regardless of the packaging system applied. In particularly up to 7 regression methods were applied and these are ordinary least squares regression, stepwise linear regression, partial least square regression, principal component regression, support vector regression, random forest and k-nearest neighbours. MeatReg" was tested with minced beef samples stored under aerobic and modified atmosphere packaging and analysed with electronic nose, HPLC, FT-IR, GC-MS and Multispectral imaging instrument. Population of total viable count, lactic acid bacteria, pseudomonads, Enterobacteriaceae and B. thermosphacta, were predicted. As a result, recommendations of which analytical platforms are suitable to predict each type of bacteria and which machine learning methods to use in each case were obtained. The developed system is accessible via the link: www.sorfml.com. Copyright © 2017 Elsevier Ltd. All rights reserved.

Increased prevalence of low back pain among physiotherapy students compared to medical students.

PubMed

Falavigna, Asdrubal; Teles, Alisson Roberto; Mazzocchin, Thaís; de Braga, Gustavo Lisbôa; Kleber, Fabrício Diniz; Barreto, Felipe; Santin, Juliana Tosetto; Barazzetti, Daniel; Lazzaretti, Lucas; Steiner, Bruna; Beckenkamp, Natália Laste

2011-03-01

Some studies have demonstrated that physiotherapists have a high prevalence of low back pain (LBP). The association between physiotherapy students, who are potentially exposed to the same LBP occupational risks as graduates, and LBP has never been demonstrated. The objective of the study is to evaluate the association between undergraduate physiotherapy study and LBP. The study design includes a cross-sectional study. A questionnaire-based study was carried out with physiotherapy and medical students. LBP was measured as lifetime, 1-year and point prevalence. Bivariate and multivariate analyses were performed to find the factors associated with LBP. Bivariate analyses were also performed to assess differences between LBP characteristics in the two courses. 77.9% of the students had LBP at some point in their lives, 66.8% in the last year and 14.4% of them reported they were suffering from LBP at the moment of answering the questionnaire. Physiotherapy students reported a higher prevalence of LBP when compared with the medical students in all measures. In the logistic regression model, physiotherapy students (A-OR 2.51; 95% CI 1.35-4.67; p = 0.003), and being exposed to the undergraduate study for more than four semesters (A-OR 2.55; 95% CI 1.43-4.55; p = 0.001) were independently associated with LBP. There were no differences between the courses concerning pain intensity and disability. As it was a cross-sectional study, we were not able to observe accurately if there is an increasing incidence of LBP during the course. Also, we did not intend to identify which activities in the course were associated with the development of LBP. This study clearly demonstrated an association between undergraduate physiotherapy study and LBP. The length of course exposure is also associated with LBP.

Tools to Support Interpreting Multiple Regression in the Face of Multicollinearity

PubMed Central

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.

PubMed

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.

Ureteral stents increase risk of postoperative acute kidney injury following colorectal surgery.

PubMed

Hassinger, Taryn E; Mehaffey, J Hunter; Mullen, Matthew G; Michaels, Alex D; Elwood, Nathan R; Levi, Shoshana T; Hedrick, Traci L; Friel, Charles M

2018-07-01

Ureteral stents are commonly placed before colorectal resection to assist in identification of ureters and prevent injury. Acute kidney injury (AKI) is a common cause of morbidity and increased cost following colorectal surgery. Although previously associated with reflex anuria, prophylactic stents have not been found to increase AKI. We sought to determine the impact of ureteral stents on the incidence of AKI following colorectal surgery. All patients undergoing colon or rectal resection at a single institution between 2005 and 2015 were reviewed using American College of Surgeons National Surgical Quality Improvement Program dataset. AKI was defined as a rise in serum creatinine to ≥ 1.5 times the preoperative value. Univariate and multivariate regression analyses were performed to identify independent predictors of AKI. 2910 patients underwent colorectal resection. Prophylactic ureteral stents were placed in 129 patients (4.6%). Postoperative AKI occurred in 335 (11.5%) patients during their hospitalization. The stent group demonstrated increased AKI incidence (32.6% vs. 10.5%; p < 0.0001) with bilateral having a higher rate than unilateral stents. Hospital costs were higher in the stent group ($23,629 vs. $16,091; p < 0.0001), and patients with bilateral stents had the highest costs. Multivariable logistic regression identified predictors of AKI after colorectal surgery including age, procedure duration, and ureteral stent placement. Prophylactic ureteral stents independently increased AKI risk when placed prior to colorectal surgery. These data demonstrate increased morbidity and hospital costs related to usage of stents in colorectal surgery, indicating that placement should be limited to patients with highest potential benefit.

Sexual possibility situations and sexual behaviors among young adolescents: the moderating role of protective factors.

PubMed

DiLorio, Colleen; Dudley, William N; Soet, Johanna E; McCarty, Frances

2004-12-01

To examine sexual possibility situations (SPS) and protective practices associated with involvement in intimate sexual behaviors and the initiation of sexual intercourse among young adolescents and to determine if protective factors moderate the relationship between SPS and sexual behaviors. Data for these analyses were obtained from the baseline assessment for adolescents conducted as part of an HIV prevention study called "Keepin' it R.E.A.L.!" The study was conducted with a community-based organization (CBO) in an urban area serving a predominantly African-American population. In addition to items assessing SPS, intimate sexual behaviors, and initiation of sexual intercourse, adolescents provided information on the following protective factors: educational goals, self-concept, future time perspective, orientation to health, self-efficacy, outcome expectations, parenting, communication, values, and prosocial activities. Background personal information, including age and gender, was also collected. The analyses were conducted on data from 491 predominantly African-American adolescents, 61% of whom were boys. Variables were combined to form SPS and protective indices that were used in the first set of regression analyses. In a second set of analyses, the indices were unbundled and individual variables were entered into regression analyses. Both SPS and protective indices explained significant portions of variance in intimate sexual behaviors, and the SPS index explained a significant portion of variance in the initiation of sexual intercourse. The regression analysis using the unbundled SPS and protective factors revealed the following statistically significant predictors for intimate sexual behaviors: age, gender, time alone with groups of peers, time alone with a member of the opposite sex, behavior self-concept, popularity self-concept, self-efficacy for abstinence, outcome expectations for abstinence, parental control, personal values, and parental values. A similar regression analysis revealed that age, time alone with a member of the opposite sex, and personal values were significant predictors of initiation of sexual intercourse. These results provide evidence for the important role of protective factors in explaining early involvement in sexual behaviors and show that protective factors extend beyond personal characteristics to include both familial and peer factors.

Power, effects, confidence, and significance: an investigation of statistical practices in nursing research.

PubMed

Gaskin, Cadeyrn J; Happell, Brenda

2014-05-01

To (a) assess the statistical power of nursing research to detect small, medium, and large effect sizes; (b) estimate the experiment-wise Type I error rate in these studies; and (c) assess the extent to which (i) a priori power analyses, (ii) effect sizes (and interpretations thereof), and (iii) confidence intervals were reported. Statistical review. Papers published in the 2011 volumes of the 10 highest ranked nursing journals, based on their 5-year impact factors. Papers were assessed for statistical power, control of experiment-wise Type I error, reporting of a priori power analyses, reporting and interpretation of effect sizes, and reporting of confidence intervals. The analyses were based on 333 papers, from which 10,337 inferential statistics were identified. The median power to detect small, medium, and large effect sizes was .40 (interquartile range [IQR]=.24-.71), .98 (IQR=.85-1.00), and 1.00 (IQR=1.00-1.00), respectively. The median experiment-wise Type I error rate was .54 (IQR=.26-.80). A priori power analyses were reported in 28% of papers. Effect sizes were routinely reported for Spearman's rank correlations (100% of papers in which this test was used), Poisson regressions (100%), odds ratios (100%), Kendall's tau correlations (100%), Pearson's correlations (99%), logistic regressions (98%), structural equation modelling/confirmatory factor analyses/path analyses (97%), and linear regressions (83%), but were reported less often for two-proportion z tests (50%), analyses of variance/analyses of covariance/multivariate analyses of variance (18%), t tests (8%), Wilcoxon's tests (8%), Chi-squared tests (8%), and Fisher's exact tests (7%), and not reported for sign tests, Friedman's tests, McNemar's tests, multi-level models, and Kruskal-Wallis tests. Effect sizes were infrequently interpreted. Confidence intervals were reported in 28% of papers. The use, reporting, and interpretation of inferential statistics in nursing research need substantial improvement. Most importantly, researchers should abandon the misleading practice of interpreting the results from inferential tests based solely on whether they are statistically significant (or not) and, instead, focus on reporting and interpreting effect sizes, confidence intervals, and significance levels. Nursing researchers also need to conduct and report a priori power analyses, and to address the issue of Type I experiment-wise error inflation in their studies. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Re-examining the link between prenatal maternal anxiety and child emotional difficulties, using a sibling design.

PubMed

Bekkhus, Mona; Lee, Yunsung; Nordhagen, Rannveig; Magnus, Per; Samuelsen, Sven O; Borge, Anne I H

2018-02-01

Prenatal exposure to maternal anxiety has been associated with child emotional difficulties in a number of epidemiological studies. One key concern, however, is that this link is vulnerable to confounding by pleiotropic genes or environmental family factors. Data on 82 383 mothers and children from the population-based Mother and Child Cohort Study and data on 21 980 siblings were used in this study. Mothers filled out questionnaires for each unique pregnancy, for infant difficulties at 6 months and for emotional difficulties at 36 months. The link between prenatal maternal anxiety and child difficulties were examined using logistic regression analyses and multiple linear regression analyses for the full study sample and the sibling sample. In the conventional full-cohort analyses, prenatal exposure to maternal anxiety was associated with child difficulties at both 6 months [odds ratio (OR) = 2.1 (1.94-2.27)] and 36 months [OR = 2.72 (2.47-2.99)]. The findings were essentially the same whether we examined difficulties at 6 months or at 36 months. However, these associations were no longer present once we controlled for potential social and genetic confounders in the sibling comparison analyses, either at 6 months [OR = 1.32 (0.91-1.90)] or at 36 months [OR = 1.28 (0.63-2.60)]. Findings from multiple regression analyses with continuous measures were essentially the same. Our finding lends little support for there being an independent prenatal effect on child emotional difficulties; rather, our findings suggest that the link between prenatal maternal anxiety and child difficulties could be confounded by pleiotropic genes or environmental family factors. © The Author 2017; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association

Factor complexity of crash occurrence: An empirical demonstration using boosted regression trees.

PubMed

Chung, Yi-Shih

2013-12-01

Factor complexity is a characteristic of traffic crashes. This paper proposes a novel method, namely boosted regression trees (BRT), to investigate the complex and nonlinear relationships in high-variance traffic crash data. The Taiwanese 2004-2005 single-vehicle motorcycle crash data are used to demonstrate the utility of BRT. Traditional logistic regression and classification and regression tree (CART) models are also used to compare their estimation results and external validities. Both the in-sample cross-validation and out-of-sample validation results show that an increase in tree complexity provides improved, although declining, classification performance, indicating a limited factor complexity of single-vehicle motorcycle crashes. The effects of crucial variables including geographical, time, and sociodemographic factors explain some fatal crashes. Relatively unique fatal crashes are better approximated by interactive terms, especially combinations of behavioral factors. BRT models generally provide improved transferability than conventional logistic regression and CART models. This study also discusses the implications of the results for devising safety policies. Copyright © 2012 Elsevier Ltd. All rights reserved.

Survival Data and Regression Models

NASA Astrophysics Data System (ADS)

Grégoire, G.

2014-12-01

We start this chapter by introducing some basic elements for the analysis of censored survival data. Then we focus on right censored data and develop two types of regression models. The first one concerns the so-called accelerated failure time models (AFT), which are parametric models where a function of a parameter depends linearly on the covariables. The second one is a semiparametric model, where the covariables enter in a multiplicative form in the expression of the hazard rate function. The main statistical tool for analysing these regression models is the maximum likelihood methodology and, in spite we recall some essential results about the ML theory, we refer to the chapter "Logistic Regression" for a more detailed presentation.

On the equivalence of case-crossover and time series methods in environmental epidemiology.

PubMed

Lu, Yun; Zeger, Scott L

2007-04-01

The case-crossover design was introduced in epidemiology 15 years ago as a method for studying the effects of a risk factor on a health event using only cases. The idea is to compare a case's exposure immediately prior to or during the case-defining event with that same person's exposure at otherwise similar "reference" times. An alternative approach to the analysis of daily exposure and case-only data is time series analysis. Here, log-linear regression models express the expected total number of events on each day as a function of the exposure level and potential confounding variables. In time series analyses of air pollution, smooth functions of time and weather are the main confounders. Time series and case-crossover methods are often viewed as competing methods. In this paper, we show that case-crossover using conditional logistic regression is a special case of time series analysis when there is a common exposure such as in air pollution studies. This equivalence provides computational convenience for case-crossover analyses and a better understanding of time series models. Time series log-linear regression accounts for overdispersion of the Poisson variance, while case-crossover analyses typically do not. This equivalence also permits model checking for case-crossover data using standard log-linear model diagnostics.

Has Adult Sleep Duration Declined Over the Last 50+ Years?

PubMed Central

Youngstedt, Shawn D.; Goff, Eric E.; Reynolds, Alex M.; Kripke, Daniel F.; Irwin, Michael R.; Bootzin, Richard R.; Khan, Nidha; Jean-Louis, Girardin

2015-01-01

Summary The common assumption that population sleep duration has declined in the past few decades has not been supported by recent reviews, which have been limited to self-reported data. The aim of this review was to assess whether there has been a reduction in objectively recorded sleep duration over the last 50+ years. The literature was searched for studies published from 1960–2013, which assessed objective sleep duration (TST) in healthy normal-sleeping adults. The search found 168 studies that met inclusion criteria, with 257 data points representing 6,052 individuals ages 18–88 years. Data were assessed by comparing the regression lines of age vs. TST in studies conducted between 1960–1989 vs. 1990–2013. Weighted regression analyses assessed the association of year of study with age-adjusted TST across all data points. Regression analyses also assessed the association of year of study with TST separately for 10-year age categories (e.g., ages 18–27 years), and separately for polysomnographic and actigraphic data, and for studies involving a fixed sleep schedule and participants’ customary sleep schedules. Analyses revealed no significant association of sleep duration with study year. The results are consistent with recent reviews of subjective data, which have challenged the notion of a modern epidemic of insufficient sleep. PMID:26478985

The Use of Linear Instrumental Variables Methods in Health Services Research and Health Economics: A Cautionary Note

PubMed Central

Terza, Joseph V; Bradford, W David; Dismuke, Clara E

2008-01-01

Objective To investigate potential bias in the use of the conventional linear instrumental variables (IV) method for the estimation of causal effects in inherently nonlinear regression settings. Data Sources Smoking Supplement to the 1979 National Health Interview Survey, National Longitudinal Alcohol Epidemiologic Survey, and simulated data. Study Design Potential bias from the use of the linear IV method in nonlinear models is assessed via simulation studies and real world data analyses in two commonly encountered regression setting: (1) models with a nonnegative outcome (e.g., a count) and a continuous endogenous regressor; and (2) models with a binary outcome and a binary endogenous regressor. Principle Findings The simulation analyses show that substantial bias in the estimation of causal effects can result from applying the conventional IV method in inherently nonlinear regression settings. Moreover, the bias is not attenuated as the sample size increases. This point is further illustrated in the survey data analyses in which IV-based estimates of the relevant causal effects diverge substantially from those obtained with appropriate nonlinear estimation methods. Conclusions We offer this research as a cautionary note to those who would opt for the use of linear specifications in inherently nonlinear settings involving endogeneity. PMID:18546544

Factors Affecting Female Teachers' Attitudes toward Help-Seeking or Help-Avoidance in Coping with Behavioral Problems

ERIC Educational Resources Information Center

Inbar-Furst, Hagit; Gumpel, Thomas P.

2015-01-01

Questionnaires were given to 392 elementary school teachers to examine help-seeking or help-avoidance in dealing with classroom behavioral problems. Scale validity was examined through a series of exploratory and confirmatory factor analyses. Using a series of multivariate regression analyses and structural equation modeling, we identified…

Recycling and Ambivalence: Quantitative and Qualitative Analyses of Household Recycling among Young Adults

ERIC Educational Resources Information Center

Ojala, Maria

2008-01-01

Theories about ambivalence, as well as quantitative and qualitative empirical approaches, are applied to obtain an understanding of recycling among young adults. A questionnaire was mailed to 422 Swedish young people. Regression analyses showed that a mix of negative emotions (worry) and positive emotions (hope and joy) about the environmental…

Alcohol and tobacco use and cognitive-motivational variables in school settings: effects on academic performance in Spanish adolescents.

PubMed

Inglés, Cándido J; Torregrosa, María S; Rodríguez-Marín, Jesús; García del Castillo, José A; Gázquez, José J; García-Fernández, José M; Delgado, Beatriz

2013-01-01

The aim of the present study was to analyze: (a) the relationship between alcohol and tobacco use and academic performance, and (b) the predictive role of psycho-educational factors and alcohol and tobacco abuse on academic performance in a sample of 352 Spanish adolescents from grades 8 to 10 of Compulsory Secondary Education. The Self-Description Questionnaire-II, the Sydney Attribution Scale, and the Achievement Goal Tendencies Questionnaire were administered in order to analyze cognitive-motivational variables. Alcohol and tobacco abuse, sex, and grade retention were also measured using self-reported questions. Academic performance was measured by school records. Frequency analyses and logistic regression analyses were used. Frequency analyses revealed that students who abuse of tobacco and alcohol show a higher rate of poor academic performance. Logistic regression analyses showed that health behaviours, and educational and cognitive-motivational variables exert a different effect on academic performance depending on the academic area analyzed. These results point out that not only academic, but also health variables should be address to improve academic performance in adolescence.

Adverse birth factors predict cognitive ability, but not hand preference.

PubMed

Nicholls, Michael E R; Johnston, David W; Shields, Michael A

2012-09-01

There is a persistent theory that birth stress and subsequent brain pathology play an important role in the manifestation of left-handedness. Evidence for this theory, however, is mixed and studies are often beset with problems related to small sample sizes and unreliable health reports. TO avoid these issues, this study used a sample of approximately 10,000 children from the British Cohort Study. The study contains objective birth-health reports and comprehensive measures of socioeconomic status, handedness, cognitive ability, and behavioral/health issues. Regression analyses showed that variables associated with birth stress affected cognitive/behavioral/health outcomes of the child. Despite this, these same factors did not affect the direction or degree of hand preference. We have therefore demonstrated a dissociation whereby adverse birth factors affect the brain's cognitive ability, but not handedness, and by implication, cerebral lateralization. The study also demonstrated a link between left-handedness and reduced levels of cognitive ability. This link cannot be due a generalized birth-stress mechanism and may be caused by specific mechanisms related to changes in cerebral dominance.

Predicting water filter and bottled water use in Appalachia: a community-scale case study.

PubMed

Levêque, Jonas G; Burns, Robert C

2017-06-01

A questionnaire survey was conducted in order to assess residents' perceptions of water quality for drinking and recreational purposes in a mid-sized city in northcentral West Virginia. Two logistic regression analyses were conducted in order to investigate the factors that influence bottle use and filter use. Results show that 37% of respondents primarily use bottled water and that 58% use a household filter when drinking from the tap. Respondents with lower levels of environmental concern, education levels, and lower organoleptic perceptions were most likely to perceive health risks from tap water consumption, and were most likely to use bottled water. Income, age, and organoleptic perceptions were predictors of water filter use among respondents. Clean water for recreational purposes was not found to be significant with either of these models. Our results demonstrate that bottle use and filter use are explained differently. We argue that more education and better communication about local tap water quality would decrease the use of bottled water. We demonstrate that household filters could be used as an alternative to bottled water.

Species composition and morphologic variation of Porites in the Gulf of California

NASA Astrophysics Data System (ADS)

López-Pérez, R. A.

2013-09-01

Morphometric analysis of corallite calices confirmed that from the late Miocene to the Recent, four species of Porites have inhabited the Gulf of California: the extinct Porites carrizensis, the locally extirpated Porites lobata and the extant Porites sverdrupi and Porites panamensis. Furthermore, large-scale spatial and temporal phenotypic plasticity was observed in the dominant species P. panamensis. Canonical discriminant analysis and ANOVA demonstrated that the calice structures of P. panamensis experienced size reduction between the late Pleistocene and Recent. Similarly, PERMANOVA, regression and correlation analyses demonstrated that across the 800 km north to south in the gulf, P. panamensis populations displayed a similar reduction in calice structures. Based on correlation analysis with environmental data, these large spatial changes are likely related to changes in nutrient concentration and sea surface temperature. As such, the large-scale spatial and temporal phenotypic variation recorded in populations of P. panamensis in the Gulf of California is likely related to optimization of corallite performance (energy acquisition) within various environmental scenarios. These findings may have relevance to modern conservation efforts within this ecological dominant genus.

Association of school performance indicators with implementation of the Healthy Kids, Smart Kids program: case study

PubMed Central

Nansel, Tonja R.; Huang, Terry T.K.; Rovner, Alisha J.; Sanders-Butler, Yvonne

2009-01-01

Objective: The purpose of this analysis was to examine secular trends in school performance indicators in relationship to the implementation of a program targeting the school food and physical activity environment. Design: Data on available school performance indicators were obtained; retrospective analyses were conducted to assess trends in indicators in association with program implementation; each outcome was regressed on year, beginning with the year prior to program implementation. Setting: The Healthy Kids, Smart Kids program was a grass-roots effort to enhance the school food and physical activity environment in the Browns Mill Elementary School in Georgia. Subjects: Data included publicly available school records from the years 1995 to 2006. Results: The number of nurse, counseling, and disciplinary referrals per 100 students demonstrated a downward trend, while standardized test scores demonstrated an upward trend beginning the year of program implementation. School year was a significant predictor of all indicators. Conclusions: Promoting nutrition and physical activity within the school environment may be a promising approach for enhancing both student health and educational outcomes. PMID:19454125

Electronic Health Record (EHR) Organizational Change: Explaining Resistance Through Profession, Organizational Experience, and EHR Communication Quality.

PubMed

Barrett, Ashley K

2018-04-01

The American Recovery and Reinvestment Act passed by the U.S. government in 2009 mandates that all healthcare organizations adopt a certified electronic health record (EHR) system by 2015. Failure to comply will result in Medicare reimbursement penalties, which steadily increase with each year of delinquency. There are several repercussions of this seemingly top-down, rule-bound organizational change-one of which is employee resistance. Given the penalties for violating EHR meaningful use standards are ongoing, resistance to this mandate presents a serious issue for healthcare organizations. This study surveyed 345 employees in one healthcare organization that recently implemented an EHR. Analysis of variance results offer theoretical and pragmatic contributions by demonstrating physicians, nurses, and employees with more experience in their organization are the most resistant to EHR change. The job characteristics model is used to explain these findings. Hierarchical regression analyses also demonstrate the quality of communication surrounding EHR implementation-from both formal and informal sources-is negatively associated with EHR resistance and positively associated with perceived EHR implementation success and EHR's perceived relative advantage.

Methods for estimating annual exceedance-probability discharges and largest recorded floods for unregulated streams in rural Missouri

USGS Publications Warehouse

Southard, Rodney E.; Veilleux, Andrea G.

2014-01-01

Regression analysis techniques were used to develop a set of equations for rural ungaged stream sites for estimating discharges with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. Basin and climatic characteristics were computed using geographic information software and digital geospatial data. A total of 35 characteristics were computed for use in preliminary statewide and regional regression analyses. Annual exceedance-probability discharge estimates were computed for 278 streamgages by using the expected moments algorithm to fit a log-Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data from water year 1844 to 2012. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized multiple Grubbs-Beck test was used to detect potentially influential low floods. Annual peak flows less than a minimum recordable discharge at a streamgage were incorporated into the at-site station analyses. An updated regional skew coefficient was determined for the State of Missouri using Bayesian weighted least-squares/generalized least squares regression analyses. At-site skew estimates for 108 long-term streamgages with 30 or more years of record and the 35 basin characteristics defined for this study were used to estimate the regional variability in skew. However, a constant generalized-skew value of -0.30 and a mean square error of 0.14 were determined in this study. Previous flood studies indicated that the distinct physical features of the three physiographic provinces have a pronounced effect on the magnitude of flood peaks. Trends in the magnitudes of the residuals from preliminary statewide regression analyses from previous studies confirmed that regional analyses in this study were similar and related to three primary physiographic provinces. The final regional regression analyses resulted in three sets of equations. For Regions 1 and 2, the basin characteristics of drainage area and basin shape factor were statistically significant. For Region 3, because of the small amount of data from streamgages, only drainage area was statistically significant. Average standard errors of prediction ranged from 28.7 to 38.4 percent for flood region 1, 24.1 to 43.5 percent for flood region 2, and 25.8 to 30.5 percent for region 3. The regional regression equations are only applicable to stream sites in Missouri with flows not significantly affected by regulation, channelization, backwater, diversion, or urbanization. Basins with about 5 percent or less impervious area were considered to be rural. Applicability of the equations are limited to the basin characteristic values that range from 0.11 to 8,212.38 square miles (mi2) and basin shape from 2.25 to 26.59 for Region 1, 0.17 to 4,008.92 mi2 and basin shape 2.04 to 26.89 for Region 2, and 2.12 to 2,177.58 mi2 for Region 3. Annual peak data from streamgages were used to qualitatively assess the largest floods recorded at streamgages in Missouri since the 1915 water year. Based on existing streamgage data, the 1983 flood event was the largest flood event on record since 1915. The next five largest flood events, in descending order, took place in 1993, 1973, 2008, 1994 and 1915. Since 1915, five of six of the largest floods on record occurred from 1973 to 2012.

Maternal sensitivity, infant limbic structure volume and functional connectivity: a preliminary study

PubMed Central

Rifkin-Graboi, A; Kong, L; Sim, L W; Sanmugam, S; Broekman, B F P; Chen, H; Wong, E; Kwek, K; Saw, S-M; Chong, Y-S; Gluckman, P D; Fortier, M V; Pederson, D; Meaney, M J; Qiu, A

2015-01-01

Mechanisms underlying the profound parental effects on cognitive, emotional and social development in humans remain poorly understood. Studies with nonhuman models suggest variations in parental care affect the limbic system, influential to learning, autobiography and emotional regulation. In some research, nonoptimal care relates to decreases in neurogenesis, although other work suggests early-postnatal social adversity accelerates the maturation of limbic structures associated with emotional learning. We explored whether maternal sensitivity predicts human limbic system development and functional connectivity patterns in a small sample of human infants. When infants were 6 months of age, 20 mother–infant dyads attended a laboratory-based observational session and the infants underwent neuroimaging at the same age. After considering age at imaging, household income and postnatal maternal anxiety, regression analyses demonstrated significant indirect associations between maternal sensitivity and bilateral hippocampal volume at six months, with the majority of associations between sensitivity and the amygdala demonstrating similar indirect, but not significant results. Moreover, functional analyses revealed direct associations between maternal sensitivity and connectivity between the hippocampus and areas important for emotional regulation and socio-emotional functioning. Sensitivity additionally predicted indirect associations between limbic structures and regions related to autobiographical memory. Our volumetric results are consistent with research indicating accelerated limbic development in response to early social adversity, and in combination with our functional results, if replicated in a larger sample, may suggest that subtle, but important, variations in maternal care influence neuroanatomical trajectories important to future cognitive and emotional functioning. PMID:26506054

Need for recovery across work careers: the impact of work, health and personal characteristics.

PubMed

Gommans, F G; Jansen, N W H; Stynen, D; de Grip, A; Kant, Ij

2015-04-01

Employees experiencing a high need for recovery (NFR) are at risk of long-term adverse effects in both their health and labour participation. So far, the determinants of NFR across age categories remain unknown. The aim of this study is to investigate the determinants of the NFR among employees in three age categories (30-44, 45-54 and 55-65 years), for men and women separately. The study was based on data from the prospective Maastricht Cohort Study. Wave T3 (May 1999) was chosen as article baseline (n = 7,900). The follow-up period of 20 months included five follow-up waves. Cox regression analyses were performed to investigate the determinants, which originated from the work environment, health and lifestyle and personal domain of employees, of NFR across age categories over time. Cross-sectional results demonstrated substantial differences in mean scores and proportion of cases of NFR across age categories. Longitudinal analyses demonstrated risk factors in the multifactorial aetiology of NFR that played a role in all age categories, but also showed several age-specific risk factors, e.g. low decision latitude appeared to be a risk factor only in the oldest age category. Although selection effects may have occurred, this study shows that the risk factors for a high NFR were different among the age categories. To prevent and reduce a high NFR among employees, it is important to develop preventive measures that target age-specific risk factors.

Neuropsychiatry and White Matter Microstructure in Huntington’s Disease

PubMed Central

Gregory, Sarah; Scahill, Rachael I.; Seunarine, Kiran K.; Stopford, Cheryl; Zhang, Hui; Zhang, Jiaying; Orth, Michael; Durr, Alexandra; Roos, Raymund A.C.; Langbehn, Douglas R.; Long, Jeffrey D.; Johnson, Hans; Rees, Geraint; Tabrizi, Sarah J.; Craufurd, David

2015-01-01

Abstract Background: Neuropsychiatric symptoms in Huntington’s disease (HD) are often evident prior to clinical diagnosis. Apathy is highly correlated with disease progression, while depression and irritability occur at different stages of the disease, both before and after clinical onset. Little is understood about the neural bases of these neuropsychiatric symptoms and to what extent those neural bases are analogous to neuropsychiatric disorders in the general population. Objective: We used Diffusion Tensor Imaging (DTI) to investigate structural connectivity between brain regions and any putative microstructural changes associated with depression, apathy and irritability in HD. Methods: DTI data were collected from 39 premanifest and 45 early-HD participants in the Track-HD study and analysed using whole-brain Tract-Based Spatial Statistics. We used regression analyses to identify white matter tracts whose structural integrity (as measured by fractional anisotropy, FA) was correlated with HADS-depression, PBA-apathy or PBA-irritability scores in gene-carriers and related to cumulative probability to onset (CPO). Results: For those with the highest CPO, we found significant correlations between depression scores and reduced FA in the splenium of the corpus callosum. In contrast, those with lowest CPO demonstrated significant correlations between irritability scores and widespread FA reductions. There was no significant relationship between apathy and FA throughout the whole brain. Conclusions: We demonstrate that white matter changes associated with both depression and irritability in HD occur at different stages of disease progression concomitant with their clinical presentation. PMID:26443926

The association between cognitive impairment and community service use patterns in older people living in Australia.

PubMed

Vecchio, Nerina; Fitzgerald, Janna A; Radford, Katrina; Fisher, Ron

2016-05-01

Family plays a vital role in supporting individuals with dementia to reside in the community, thus delaying institutionalisation. Existing research indicates that the burden of care-giving is particularly high for those caring for a person with dementia. Yet, little is known about the uptake of community services by people with a diagnosis of dementia. Therefore, this study aims to better understand the relationship between cognitive impairment and the receipt of community care services. In order to examine the relationship, secondary data collected across Queensland, Australia, from 59,352 home-care clients aged 65 and over during 2007-2008 are analysed. This cross-sectional study uses regression analyses to estimate the relationship between cognitive impairment and service mix, while controlling for socio-demographic characteristics. The dependent variables include formal services, informal care and total home-care service hours during a 12-month period. The findings of this study demonstrate that cognitive impairment is associated with accessing more hours of respite and day centre care but fewer hours of other formal care services. Additionally, the likelihood of support from an informal caregiver increases when a client becomes cognitively impaired. Therefore, this study demonstrates that there is an increased need for respite programmes to support informal caregivers in the future, as the population of people living with dementia increases. These findings support the need for investigations of new and innovative respite models in the future. © 2015 John Wiley & Sons Ltd.

Bullying as a Stressor in Mid-Adolescent Girls and Boys-Associations with Perceived Stress, Recurrent Pain, and Salivary Cortisol.

PubMed

Östberg, Viveca; Låftman, Sara B; Modin, Bitte; Lindfors, Petra

2018-02-20

Bullying involves repeated exposure to negative actions while also invoking a power asymmetry between the involved parties. From a stress perspective, being bullied can be seen as a severe and chronic stressor, and an everyday social-evaluative threat, coupled with a shortage of effective social resources for dealing with this particular stressor. The aim of this study was to investigate whether exposure to bullying among mid-adolescent girls and boys is associated with subjective and objective stress-related outcomes in terms of perceived stress, recurrent pain, and salivary cortisol. The data came from the School Stress and Support Study (TriSSS) including students in grades 8-9 in two schools in Stockholm, Sweden, in 2010 (study sample n = 392; cortisol subsample n = 198). Bullying was self-reported and measured by multiple items. The statistical analyses included binary logistic and linear (OLS) regression. Being bullied was associated with greater perceived stress and an increased risk of recurrent pain, among both boys and girls. Also, bullied students had lower cortisol output (AUC G ) and lower cortisol awakening response (CAR G ) as compared to those who were not bullied. Gender-stratified analyses demonstrated that these associations were statistically significant for boys but not for girls. In conclusion, this study demonstrated that being bullied was related to both subjective and objective stress markers among mid-adolescent girls and boys, pointing to the necessity of continuously working against bullying.

Heterogeneity in drug abuse among juvenile offenders: is mixture regression more informative than standard regression?

PubMed

Montgomery, Katherine L; Vaughn, Michael G; Thompson, Sanna J; Howard, Matthew O

2013-11-01

Research on juvenile offenders has largely treated this population as a homogeneous group. However, recent findings suggest that this at-risk population may be considerably more heterogeneous than previously believed. This study compared mixture regression analyses with standard regression techniques in an effort to explain how known factors such as distress, trauma, and personality are associated with drug abuse among juvenile offenders. Researchers recruited 728 juvenile offenders from Missouri juvenile correctional facilities for participation in this study. Researchers investigated past-year substance use in relation to the following variables: demographic characteristics (gender, ethnicity, age, familial use of public assistance), antisocial behavior, and mental illness symptoms (psychopathic traits, psychiatric distress, and prior trauma). Results indicated that standard and mixed regression approaches identified significant variables related to past-year substance use among this population; however, the mixture regression methods provided greater specificity in results. Mixture regression analytic methods may help policy makers and practitioners better understand and intervene with the substance-related subgroups of juvenile offenders.

Effect of ethnicity and sex on the growth of the axial and appendicular skeleton of children living in a developing country.

PubMed

Nyati, Lukhanyo H; Norris, Shane A; Cameron, Noel; Pettifor, John M

2006-05-01

Bones in the axial and appendicular skeletons exhibit heterogeneous growth patterns between different ethnic and sex groups. However, the influence of this differential growth on the expression of bone mineral content is not yet established. The aims of the present study were to investigate: 1) whether there are ethnic and sex differences in axial and appendicular dimensions of South African children; and 2) whether regional segment length is a better predictor of bone mass than stature. Anthropometric measurements of stature, weight, sitting height, and limb lengths were taken on 368 black and white, male and female 9-year-old children. DXA (dual-energy x-ray absorptiometry) scans of the distal ulna, distal radius, and hip and lumbar spine were also obtained. Analyses of covariance were performed to assess differences in limb lengths, adjusted for differences in stature. Multiple regression analyses were used to assess significant predictors of site-specific bone mass. Stature-adjusted means of limb lengths show that black boys have longer legs and humeri but shorter trunks than white boys. In addition, black children have longer forearms than white children, and girls have longer thighs than boys. The regression analysis demonstrated that site-specific bone mass was more strongly associated with regional segment length than stature, but this had little effect on the overall pattern of ethnic and sex differences. In conclusion, there is a differential effect of ethnicity and sex on the growth of the axial and appendicular skeletons, and regional segment length is a better predictor of site-specific bone mass than stature. Copyright 2005 Wiley-Liss, Inc.

Contemporary meta-analysis of short-term probiotic consumption on gastrointestinal transit.

PubMed

Miller, Larry E; Zimmermann, Angela K; Ouwehand, Arthur C

2016-06-07

To determine the efficacy of probiotic supplementation on intestinal transit time (ITT) in adults and to identify factors that influence these outcomes. We conducted a systematic review of randomized controlled trials of probiotic supplementation that measured ITT in adults. Study quality was assessed using the Jadad scale. A random effects meta-analysis was performed with standardized mean difference (SMD) of ITT between probiotic and control groups as the primary outcome. Meta-regression and subgroup analyses examined the impact of moderator variables on SMD of ITT. A total of 15 clinical trials with 17 treatment effects representing 675 subjects were included in this analysis. Probiotic supplementation was moderately efficacious in decreasing ITT compared to control, with an SMD of 0.38 (95%CI: 0.23-0.53, P < 0.001). Subgroup analyses demonstrated statistically greater reductions in ITT with probiotics in subjects with vs without constipation (SMD: 0.57 vs 0.22, P < 0.01) and in studies with high vs low study quality (SMD: 0.45 vs 0.00, P = 0.01). Constipation (R (2) = 38%, P < 0.01), higher study quality (R (2) = 31%, P = 0.01), older age (R (2) = 27%, P = 0.02), higher percentage of female subjects (R (2) = 26%, P = 0.02), and fewer probiotic strains (R (2) = 20%, P < 0.05) were predictive of decreased ITT with probiotics in meta-regression. Medium to large treatment effects were identified with B. lactis HN019 (SMD: 0.67, P < 0.001) and B. lactis DN-173 010 (SMD: 0.54, P < 0.01) while other probiotic strains yielded negligible reductions in ITT relative to control. Probiotic supplementation is moderately efficacious for reducing ITT in adults. Probiotics were most efficacious in constipated subjects, when evaluated in high-quality studies, and with certain probiotic strains.

Risk factors for anaemia among HIV infected children attending HIV care and treatment clinic at Muhimbili National Hospital in Dar es Salaam, Tanzania.

PubMed

Makubi, Abel N; Mugus, Ferdinand; Magesa, Pius M; Roberts, David; Quaresh, Amrana

2012-01-01

There is paucity of data describing the risk factors for anaemia among HIV infected children in Tanzania. This cross sectional study aimed at determining the contributing factors for anaemia among HIV-infected children attending Muhimbili National Hospital in Dar es Salaam. Both univariate and multivariate logistic regression analyses were performed to identify possible factors associated with anaemia in HIV-infected children. In this study a total of 75 (44%) patients among 167 recruited HIV children aged 6 months to 59 months were found to be anaemic (Hg<11 g/dl). Multivariate logistic regression demonstrated that not being on HAART (OR 3.40, 95%CI (1.20-9.60), having CD4% <25% (OR 2.30, 95%CI (1.20-34.60), having a history of tuberculosis (TB) (OR 3.23, 95%CI (1.10-9.70) and having hookworm infestation (OR 5.97, 95%CI (1.92-18.4) were independent risk factors for anaemia among HIV infected children. The analyses also showed that being HIV positive for ≥ 2.5 years resulted into a low risk of severe anaemia compared to being HIV positive for < 2.5 years. Taking multivitamins (OR 0.07, 95%, CI (0.020-0.30) and antihelminthics (OR 0.27, 95%CI (0.10-0.74) were also protective against anaemia in children. Similar factors (with exception of using antihelmintics) were associated with severe anaemia. In conclusion the factors associated with anaemia in HIV infected children were multifactorial in nature. Efforts to correct anaemia in HIV infected children should include use of HAART and treatment of infections such as TB and hookworms.

Morphometric traits capture the climatically driven species turnover of 10 spruce taxa across China.

PubMed

Li, He; Wang, GuoHong; Zhang, Yun; Zhang, WeiKang

2016-02-01

This study explored the relative roles of climate and phylogenetic background in driving morphometric trait variation in 10 spruce taxa in China. The study further addressed the hypothesis that these variations are consistent with species turnover on climatic gradients. Nine morphometric traits of leaves, seed cones, and seeds for the 10 studied spruce taxa were measured at 504 sites. These data were analyzed in combination with species DNA sequences from NCBI GenBank. We detected the effects of phylogeny and climate through trait-variation-based K statistics and phylogenetic eigenvector regression (PVR) analyses. Multivariate analyses were performed to detect trait variation along climatic gradients with species replacement. The estimated K-values for the nine studied morphometric traits ranged from 0.19 to 0.68, and the studied environmental variables explained 39-83% of the total trait variation. Trait variation tended to be determined largely by a temperature gradient varying from wet-cool climates to dry-warm summers and, additionally, by a moisture gradient. As the climate became wetter and cooler, spruce species tended to be replaced by other spruces with smaller needle leaves and seeds but larger cones and seed scales. A regression analysis showed that spruce species tended to be successively replaced by other species, along the gradient, although the trends observed within species were not necessarily consistent with the overall trend. The climatically driven replacement of the spruces in question could be well indicated by the between-species variation in morphometric traits that carry lower phylogenetic signal. Between-species variation in these traits is driven primarily by climatic factors. These species demonstrate a narrower ecological amplitude in temperature but wider ranges on the moisture gradient.

Vitamin D status and falls, frailty, and fractures among postmenopausal Japanese women living in Hawaii.

PubMed

Pramyothin, P; Techasurungkul, S; Lin, J; Wang, H; Shah, A; Ross, P D; Puapong, R; Wasnich, R D

2009-11-01

Vitamin D status and its relationship to physical performance, falls, and fractures in 495 postmenopausal women of Japanese ancestry in Hawaii were investigated. The mean 25-hydroxyvitamin D (25-OHD) was 31.94 ng/mL. No significant association of 25-OHD was demonstrated with most outcomes, possibly due to higher 25-OHD levels in this population. In this study, we investigated vitamin D status and its relationship to physical performance, muscle strength, falls, and fractures in postmenopausal Japanese females living in Hawaii. Of 510 community-dwelling women who participated in the eighth examination of the Hawaii Osteoporosis Study, 495 were included in these analyses. Multivariate regression models were used to evaluate the relationship of 25-OHD (D(3) and total) to eight performance-based measurements, 12 activities of daily living (ADLs), and muscle strength (grip, triceps, and quadriceps). Logistic regression analyses were performed to evaluate the relationship of 25-OHD to falls, vertebral fractures, and non-vertebral fractures. The mean total 25-OHD was 31.94 +/- 9.46 ng/mL; 44% of subjects had values <30 ng/mL, while none had values <10-12 ng/mL. There was little evidence of seasonal variation. Among performance-based measures, ADLs, and strength tests, only quadriceps strength was significantly associated with total 25-OHD (p = 0.0063) and 25-OHD(3) (p = 0.0001). No significant association of 25-OHD was found with vertebral or non-vertebral fractures, or incidence of one or more falls. Lack of serum 25-OHD relationship with falls and fractures or most physical performance measures in this study may be related to the low prevalence of very low 25-OHD levels in this population.

The contributing role of physical education in youth's daily physical activity and sedentary behavior.

PubMed

Chen, Senlin; Kim, Youngwon; Gao, Zan

2014-02-04

School physical education (PE) is considered as an effective channel for youth to accumulate moderate-to-vigorous physical activity (MVPA) and reduce sedentary time. The purpose of this study was to determine the contributing role of PE in daily MVPA and sedentary time among youth. The study recruited 67 sixth grade children (29 boys; Mean age = 11.75) from two suburban schools at a U.S. Midwest state, 48 of whom contributed ≥10 hours of physical activity (PA) data per day were included for analysis. An objective monitoring tool (i.e., Sensewear armband monitor) was used to capture the participants' MVPA and sedentary time for 7-14 days. Pearson product-moment correlation analysis (r), multi-level regression analyses, and analysis of variance were conducted for data analysis. MVPA and sedentary time in PE showed significant positive associations with daily MVPA and sedentary time, respectively (r = 0.35, p < 0.01; r = 0.55, p < 0.01). Regression analyses revealed that one minute increase in MVPA and sedentary behavior in PE was associated with 2.04 minutes and 5.30 minutes increases in daily MVPA and sedentary behavior, respectively, after controlling for sex and BMI. The participants demonstrated a significantly higher level of MVPA (p = .05) but similar sedentary time (p = 0.61) on PE days than on non-PE days. Boys had significantly more daily MVPA (p < .01) and less sedentary time (p < .01) than girls; while higher BMI was associated with more sedentary time (p < .01). PE displayed a positive contribution to increasing daily MVPA and decreasing daily sedentary time among youth. Active participation in PE classes increases the chance to be more active and less sedentary beyond PE among youth.

Measures of Heart Rate Variability in Individuals With Somatic Symptom Disorder.

PubMed

Huang, Wei-Lieh; Liao, Shih-Cheng; Yang, Cheryl C H; Kuo, Terry B J; Chen, Tzu-Ting; Chen, I-Ming; Gau, Susan Shur-Fen

2017-01-01

Little is known about autonomic nervous system activity in individuals with somatic symptom disorder (SSD) as defined by DSM-V criteria. The aims of this study were to investigate whether individuals with SSD differ from healthy controls in heart rate variability (HRV) measures of autonomic nervous system activity and whether sex has a moderating effect on this association. We recruited 168 individuals with SSD (35.1% men) and 106 healthy controls (27.4% men). Demographics, HRV, and psychological factors were measured using the Patient Health Questionnaire-15, Health Anxiety Questionnaire, Beck Depression Inventory-II (BDI-II), and Beck Anxiety Inventory. Multiple regression analysis was used to examine the association of SSD with HRV, adjusting for demographic and psychological measures. Individuals with SSD had lower levels of total-power HRV and low-frequency HRV, but no differences in high-frequency (HF)-HRV were found. HRV differences between SSD and controls varied by sex and age (triple interaction TP-HRV β = -0.222, p < .001; low-frequency HRV β = -0.332, p < .001; and HF-HRV β = -0.167, p = .006). Whole-sample multiple regression analyses revealed significant sex differences in the magnitudes of the association between BDI-II with HF-HRV (β of sex*BDI-II: 0.761, p = .005) and analyses stratified by sex indicated that HF-HRV was significantly correlated with depression in men with SSD (r = -0.491, p < .001) but not in women with SSD (r = 0.057, p = .558). These results suggest that patients with SSD demonstrate different patterns of HRV and the patterns of association between HRV indices and psychological factors vary between men and women.

Epilepsy and adverse quality of life in surgically resected meningioma.

PubMed

Tanti, M J; Marson, A G; Jenkinson, M D

2017-09-01

Meningiomas are common intracranial tumors, and despite surgery or therapy with anti-epileptic drugs (AEDs), many patients suffer from seizures. Epilepsy has a significant impact on quality of life (QoL) in non-tumor populations, but the impact of epilepsy on QoL in patients with meningioma is unknown. Our aim was to evaluate the impact of epilepsy on QoL in patients that have undergone resection of a benign meningioma. We recruited meningioma patients without epilepsy (n=109), meningioma patients with epilepsy (n=56), and epilepsy patients without meningioma (n=64). QoL was measured with the Short Form 36 version 2 (SF-36), the Functional Assessment of Cancer Therapy (FACT-BR), and the Liverpool Adverse Events Profile (LAEP). Regression analyses identified significant determinants of QoL. Patients with meningioma and epilepsy had poorer QoL scores than meningioma patients without epilepsy in all measures. In FACT-BR, this difference was significant. Multiple regression analyses demonstrated that current AED use had a greater impact on QoL scores than recent seizures. Other variables associated with impaired QoL included depression, unemployment, and meningioma attributed symptoms. Epilepsy has a negative impact on quality of life in patients with benign meningioma. AED use is correlated with impaired QoL and raised LAEP scores, suggesting that AEDs and adverse effects may have led to impaired QoL in our meningioma patients with epilepsy. The severity of epilepsy in our meningioma population was comparatively mild; therefore, a more conservative approach to AED therapy may be indicated in an attempt to minimize adverse effects. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Hospital outpatient perceptions of the physical environment of waiting areas: the role of patient characteristics on atmospherics in one academic medical center.

PubMed

Tsai, Chun-Yen; Wang, Mu-Chia; Liao, Wei-Tsen; Lu, Jui-Heng; Sun, Pi-Hung; Lin, Blossom Yen-Ju; Breen, Gerald-Mark

2007-12-05

This study examines hospital outpatient perceptions of the physical environment of the outpatient waiting areas in one medical center. The relationship of patient characteristics and their perceptions and needs for the outpatient waiting areas are also examined. The examined medical center consists of five main buildings which house seventeen primary waiting areas for the outpatient clinics of nine medical specialties: 1) Internal Medicine; 2) Surgery; 3) Ophthalmology; 4) Obstetrics-Gynecology and Pediatrics; 5) Chinese Medicine; 6) Otolaryngology; 7) Orthopedics; 8) Family Medicine; and 9) Dermatology. A 15-item structured questionnaire was developed to rate patient satisfaction covering the four dimensions of the physical environments of the outpatient waiting areas: 1) visual environment; 2) hearing environment; 3) body contact environment; and 4) cleanliness. The survey was conducted between November 28, 2005 and December 8, 2005. A total of 680 outpatients responded. Descriptive, univariate, and multiple regression analyses were applied in this study. All of the 15 items were ranked as relatively high with a range from 3.362 to 4.010, with a neutral score of 3. Using a principal component analysis' summated scores of four constructed dimensions of patient satisfaction with the physical environments (i.e. visual environment, hearing environment, body contact environment, and cleanliness), multiple regression analyses revealed that patient satisfaction with the physical environment of outpatient waiting areas was associated with gender, age, visiting frequency, and visiting time. Patients' socio-demographics and context backgrounds demonstrated to have effects on their satisfaction with the physical environment of outpatient waiting areas. In addition to noticing the overall rankings for less satisfactory items, what should receive further attention is the consideration of the patients' personal characteristics when redesigning more comfortable and customized physical environments of waiting areas.

Open versus robotic-assisted transabdominal preperitoneal (R-TAPP) inguinal hernia repair: a multicenter matched analysis of clinical outcomes.

PubMed

Gamagami, R; Dickens, E; Gonzalez, A; D'Amico, L; Richardson, C; Rabaza, J; Kolachalam, R

2018-04-26

To compare the perioperative outcomes of initial, consecutive robotic-assisted transabdominal preperitoneal (R-TAPP) inguinal hernia repair (IHR) cases with consecutive open cases completed by the same surgeons. Multicenter, retrospective, comparative study of perioperative results from open and robotic IHR using standard univariate and multivariate regression analyses for propensity score matched (1:1) cohorts. Seven general surgeons at six institutions contributed 602 consecutive open IHR and 652 consecutive R-TAPP IHR cases. Baseline patient characteristics in the unmatched groups were similar with the exception of previous abdominal surgery and all baseline characteristics were comparable in the matched cohorts. In matched analyses, postoperative complications prior to discharge were comparable. However, from post discharge through 30 days, fewer patients experienced complications in the R-TAPP group than in the open group [4.3% vs 7.7% (p = 0.047)]. The R-TAPP group had no reoperations post discharge through 30 days of follow-up compared with five patients (1.1%) in the open group (p = 0.062), respectively. Multivariate logistic regression analysis which demonstrated patient age > 65 years and the open approach were risk factors for complications within 30 days post discharge in the matched group [age > 65 years: odds ratio (OR) = 3.33 (95% CI 1.89, 5.87; p < 0.0001); open approach: OR = 1.89 (95% CI 1.05, 3.38; p = 0.031)]. In this matched analysis, R-TAPP provides similar postoperative complications prior to discharge and a lower rate of postoperative complications through 30 days compared to open repair. R-TAPP is a promising and reproducible approach, and may facilitate adoption of minimally invasive repairs of inguinal hernias.

Temporal trends in marijuana attitudes, availability and use in Colorado compared to non-medical marijuana states: 2003-11.

PubMed

Schuermeyer, Joseph; Salomonsen-Sautel, Stacy; Price, Rumi Kato; Balan, Sundari; Thurstone, Christian; Min, Sung-Joon; Sakai, Joseph T

2014-07-01

In 2009, policy changes were accompanied by a rapid increase in the number of medical marijuana cardholders in Colorado. Little published epidemiological work has tracked changes in the state around this time. Using the National Survey on Drug Use and Health, we tested for temporal changes in marijuana attitudes and marijuana-use-related outcomes in Colorado (2003-11) and differences within-year between Colorado and thirty-four non-medical-marijuana states (NMMS). Using regression analyses, we further tested whether patterns seen in Colorado prior to (2006-8) and during (2009-11) marijuana commercialization differed from patterns in NMMS while controlling for demographics. Within Colorado those reporting "great-risk" to using marijuana 1-2 times/week dropped significantly in all age groups studied between 2007-8 and 2010-11 (e.g. from 45% to 31% among those 26 years and older; p=0.0006). By 2010-11 past-year marijuana abuse/dependence had become more prevalent in Colorado for 12-17 year olds (5% in Colorado, 3% in NMMS; p=0.03) and 18-25 year olds (9% vs. 5%; p=0.02). Regressions demonstrated significantly greater reductions in perceived risk (12-17 year olds, p=0.005; those 26 years and older, p=0.01), and trend for difference in changes in availability among those 26 years and older and marijuana abuse/dependence among 12-17 year olds in Colorado compared to NMMS in more recent years (2009-11 vs. 2006-8). Our results show that commercialization of marijuana in Colorado has been associated with lower risk perception. Evidence is suggestive for marijuana abuse/dependence. Analyses including subsequent years 2012+ once available, will help determine whether such changes represent momentary vs. sustained effects. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Do health care workforce, population, and service provision significantly contribute to the total health expenditure? An econometric analysis of Serbia.

PubMed

Santric-Milicevic, M; Vasic, V; Terzic-Supic, Z

2016-08-15

In times of austerity, the availability of econometric health knowledge assists policy-makers in understanding and balancing health expenditure with health care plans within fiscal constraints. The objective of this study is to explore whether the health workforce supply of the public health care sector, population number, and utilization of inpatient care significantly contribute to total health expenditure. The dependent variable is the total health expenditure (THE) in Serbia from the years 2003 to 2011. The independent variables are the number of health workers employed in the public health care sector, population number, and inpatient care discharges per 100 population. The statistical analyses include the quadratic interpolation method, natural logarithm and differentiation, and multiple linear regression analyses. The level of significance is set at P < 0.05. The regression model captures 90 % of all variations of observed dependent variables (adjusted R square), and the model is significant (P < 0.001). Total health expenditure increased by 1.21 standard deviations, with an increase in health workforce growth rate by 1 standard deviation. Furthermore, this rate decreased by 1.12 standard deviations, with an increase in (negative) population growth rate by 1 standard deviation. Finally, the growth rate increased by 0.38 standard deviation, with an increase of the growth rate of inpatient care discharges per 100 population by 1 standard deviation (P < 0.001). Study results demonstrate that the government has been making an effort to control strongly health budget growth. Exploring causality relationships between health expenditure and health workforce is important for countries that are trying to consolidate their public health finances and achieve universal health coverage at the same time.

Neck Circumference, a Novel Indicator for Hyperuricemia

PubMed Central

Jiang, Jiajia; Cui, Jia; Yang, Xinghua; Wang, Anping; Mu, Yiming; Dong, Liguang; Wang, Shuyu; Gaisano, Herbert; Dou, Jingtao; He, Yan

2017-01-01

Background: Waist circumference has been correlated with the risk of hyperuricemia. Whether neck circumference is also associated with hyperuricemia has not been assessed. This study aimed to investigate whether neck circumference is associated with hyperuricemia. Methods: This study population from Beijing is part of the larger China-wide Risk Evaluation of Cancers in Chinese Diabetic Individuals: a lONgitudinal (REACTION) study. For this Beijing sub-center cross-sectional study, a total of 8971 subjects were recruited. Gender-specific multivariable-adjusted regression analyses were conducted to analyze the association of neck circumference and waist circumference with hyperuricemia and the association of neck circumference with serum uric acid levels in the non-hyperuricemia population. Results: After adjusting for confounding variables, regression analyses showed that neck circumference was positively associated with hyperuricemia [OR, 2.61 (1.86–3.67) for males and 3.27 (2.53–4.22) for females] in both genders; further, neck circumference was also positively associated with serum uric acid levels in non-hyperuricemia subjects [b, 2.58 (1.76–3.39) for males and 4.27 (3.70–4.84) for females] in both genders. Additionally, we demonstrated that neck circumference was similar to waist circumference in terms of the strength of association (OR, 3.03 for waist circumference vs. 2.61 for neck circumference in males, and 3.50 vs. 3.27 for females) with hyperuricemia and the ability to predict hyperuricemia (AUC, 0.63 for waist circumference vs. 0.61 for neck circumference in males, and 0.66 vs. 0.66 in females). Conclusion: Neck circumference is positively and independently associated with hyperuricemia in both genders and is also associated with serum uric acid levels in the non-hyperuricemia population. PMID:29238304

Organizational culture in cardiovascular care in Chinese hospitals: a descriptive cross-sectional study.

PubMed

Yin, Emily S; Downing, Nicholas S; Li, Xi; Singer, Sara J; Curry, Leslie A; Li, Jing; Krumholz, Harlan M; Jiang, Lixin

2015-12-21

Organizational learning, the process by which a group changes its behavior in response to newly acquired knowledge, is critical to outstanding organizational performance. In hospitals, strong organizational learning culture is linked with improved health outcomes for patients. This study characterizes the organizational learning culture of hospitals in China from the perspective of a cardiology service. Using a modified Abbreviated Learning Organization Survey (27 questions), we characterized organizational learning culture in a nationally representative sample of 162 Chinese hospitals, selecting 2 individuals involved with cardiovascular care at each hospital. Responses were analyzed at the hospital level by calculating the average of the two responses to each question. Responses were categorized as positive if they were 5+ on a 7-point scale or 4+ on a 5-point scale. Univariate and multiple regression analyses were used to assess the relationship between selected hospital characteristics and perceptions of organizational learning culture. Of the 324 participants invited to take the survey, 316 responded (98 % response rate). Perceptions of organizational learning culture varied among items, among domains, and both among and within hospitals. Overall, the median proportion of positive responses was 82 % (interquartile range = 59 % to 93 %). "Training," "Performance Monitoring," and "Leadership that Reinforces Learning" were characterized as the most favorable domains, while "Time for Reflection" was the least favorable. Multiple regression analyses showed that region was the only factor significantly correlated with overall positive response rate. This nationally representative survey demonstrated variation in hospital organizational learning culture among hospitals in China. The variation was not substantially explained by hospital characteristics. Organizational learning culture domains with lower positive response rates reveal important areas for improvement.

Association of serum anti-rotavirus immunoglobulin A antibody seropositivity and protection against severe rotavirus gastroenteritis: analysis of clinical trials of human rotavirus vaccine.

PubMed

Cheuvart, Brigitte; Neuzil, Kathleen M; Steele, A Duncan; Cunliffe, Nigel; Madhi, Shabir A; Karkada, Naveen; Han, Htay Htay; Vinals, Carla

2014-01-01

Clinical trials of the human rotavirus vaccine Rotarix™ (RV1) have demonstrated significant reductions in severe rotavirus gastroenteritis (RVGE) in children worldwide. However, no correlate of vaccine efficacy (VE) has yet been established. This paper presents 2 analyses which aimed to investigate whether serum anti-RV IgA measured by ELISA 1 or 2 mo post-vaccination can serve as a correlate of efficacy against RVGE: (1) In a large Phase III efficacy trial (Rota-037), the Prentice criteria for surrogate endpoints was applied to anti-RV IgA seropositivity 1 mo post-vaccination. These criteria determine whether a significant vaccine group effect can be predicted from the surrogate, namely seropositivity (anti-RV IgA concentration>20 U/mL); (2) Among other GSK-sponsored RV1 VE studies, 8 studies which assessed immunogenicity at 1 or 2 mo post-vaccination in all or a sub-cohort of enrolled subjects and had at least 10 RVGE episodes were included in a meta-analysis to measure the regression between clinical VE and VE predicted from immunogenicity (VE1). In Rota-037, anti-RV IgA seropositivity post-vaccination was associated with a lower incidence of any or severe RVGE, however, the proportion of vaccine group effect explained by seropositivity was only 43.6% and 32.7% respectively. This low proportion was due to the vaccine group effect observed in seronegative subjects. In the meta-analysis, the slope of the regression between clinical VE and VE1 was statistically significant. These two independent analyses support the hypothesis that post-vaccination anti-RV IgA seropositivity (antibody concentration ≥20 U/mL) may serve as a useful correlate of efficacy in clinical trials of RV1 vaccines.

First Trimester Prenatal Care Initiation Among Hispanic Women Along the U.S.-Mexico Border.

PubMed

Selchau, Katherine; Babuca, Maricela; Bower, Kara; Castro, Yara; Coakley, Eugenie; Flores, Araceli; Garcia, Jonah O; Reyes, Maria Lourdes F; Rojas, Yvonne; Rubin, Jason; Samuels, Deanne; Shattuck, Laura

2017-12-01

Background First trimester prenatal care (FTPNC) is associated with improved birth outcomes. U.S.-Mexico border Hispanic women have lower FTPNC than non-border or non-Hispanic women. This study aimed to identify (1) what demographic, knowledge and care-seeking factors influence FTPNC among Hispanic women in border counties served by five Healthy Start sites, and (2) what FTPNC barriers may be unique to this target population. Healthy Starts work to eliminate disparities in perinatal health in areas with high poverty and poor birth outcomes. Methods 403 Hispanic women of reproductive age in border communities of California, Arizona, New Mexico and Texas were surveyed on knowledge and behaviors related to prenatal care (PNC) and basic demographic information. Chi square analyses and logistic regressions were used to identify important relationships. Results Chi square analyses revealed that primiparous women were significantly less likely to start FTPNC than multiparous women (χ 2 = 6.8372, p = 0.0089). Women with accurate knowledge about FTPNC were more likely to obtain FTPNC (χ 2  = 29.280, p < .001) and more likely to have seen a doctor within the past year (χ 2  = 5.550, p = .018). Logistic regression confirmed that multiparity was associated with FTPNC and also that living in Texas was negatively associated with FTPNC (R 2  = 0.066, F(9,340) = 2.662, p = .005). Among 27 women with non-FTPNC, barriers included late pregnancy recognition (n = 19) and no medical insurance (n = 5). Conclusions This study supports research that first time pregnancies have lower FTPNC, and demonstrated a strong association between delayed PNC and late pregnancy recognition. Strengthened investments in preconception planning could improve FTPNC in this population.

Quality of Life Outcomes in Patients Living with Stoma

PubMed Central

Anaraki, Fakhrialsadat; Vafaie, Mohamad; Behboo, Roobic; Maghsoodi, Nakisa; Esmaeilpour, Sahar; Safaee, Azadeh

2012-01-01

Background: Despite efforts to maintain the intestinal tissue and treat gastrointestinal disease, a large number of patients undergo ostomy surgery each year. Using stoma reduces the patient's quality of life (QOL) greatly. Although there are approximately 3000 patients in Iran; there is little information about the impact of stoma on their QOL. Aims: The study aims to evaluate QOL of stoma patients using a special measurement tool. Settings and Design: This survey was a cross-sectional study that was conducted on 102 random samples of stoma patients. Materials and Methods: The City of Hope Quality of Life-Ostomy Questionnaire was used for collecting demographic and clinical information and evaluating QOL. Statistical Analysis Used: Univariate and multiple regression analyses were performed to identify predictors of QOL. Results: The mean score for the overall QOL for stoma patients was 7.48 ± 0.9. 70% of patients were dissatisfied with sexual activities. More than half of them reported feelings of depression following stoma surgery. Univariate analysis indicated that factors such as the type of ostomy (temporary/permanent), the underlying disease that had led to the stoma, depression, problem with location of ostomy, and change in clothing style had significant effects on overall QOL and its subscales (P < 0.05). The results of the regression analyses showed that only depression and problem with the location of ostomy were statistically significant in predicting patients’ QOL and its subscales (P < 0.05). Conclusions: The findings demonstrated that living with stoma influences the overall aspect of QOL. Education for the patients and their families is important for improving the stoma patients’ QOL. Sexual and psychological consultation may also improve patients’ QOL. PMID:23439841

A further examination of word frequency and age-of-acquisition effects in English lexical decision task performance: The role of frequency trajectory.

PubMed

Juhasz, Barbara J; Yap, Melvin J; Raoul, Akila; Kaye, Micaela

2018-04-23

Word frequency is an important predictor of lexical-decision task performance. The current study further examined the role of this variable by exploring the influence of frequency trajectory. Frequency trajectory is measured by how often a word occurs in childhood relative to adulthood. Past research on the role of this variable in word recognition has produced equivocal results. In the current study, words were selected based on their frequencies in Grade 1 (child frequency) and Grade 13 (college frequency). In Experiment 1, four frequency trajectory conditions were factorially examined in a lexical-decision task with English words: high-to-high (world), high-to-low (uncle), low-to-high (brain) and low-to-low (opera). an interaction between Grade 1 and college frequency demonstrated that words in the low-to-high condition were processed significantly faster and more accurately than words in the low-to-low condition, whereas the high-to-high and high-to-low conditions did not differ significantly. In Experiment 2, an advantage for words with an increasing frequency trajectory was also supported in regression analyses on both lexical decision and naming times for 3,039 items selected from the English Lexicon Project (Balota et al., 2007). This was replicated in Experiment 3, based on a regression analysis of 2,680 words from the British Lexicon Project (BLP; Keuleers, Lacey, Rastle, & Brysbaert, 2012). In all analyses, rated age-of-acquisition also significantly impacted word recognition. Together, the results suggest that the age at which a word is initially learned as well as its frequency trajectory across childhood impact performance in the lexical-decision task. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Drinking Patterns Across Spring, Summer, and Fall in 462 University Students.

PubMed

Schuckit, Marc A; Smith, Tom L; Clausen, Peyton; Skidmore, Jessica; Shafir, Alexandra; Kalmijn, Jelger

2016-04-01

Student heavy drinking and associated problems are common at most universities and fluctuate throughout the calendar year, with marked increases during celebrations. Most studies of student drinking are limited to the academic year itself, and relatively few focus specifically on special heavy drinking events. Even fewer studies include drinking during summer break and subsequent school return. In the context of an experimental protocol, beginning in January 2014, alcohol-related characteristics were evaluated 8 times over 55 weeks for 462 college freshmen, including periods that incorporated a campus festival, summer, and school return. Baseline predictors of drinking quantities over time included demography, substance use patterns, as well as environmental and attitudinal characteristics. Product-moment correlations evaluated relationships between baseline characteristics and subsequent quantities, and simultaneous entry regression analyses evaluated which characteristics most robustly predicted usual and maximum drinks over time. Maximum drinks per occasion increased 18% from the early spring (4/8/14 to 5/6/14) to the campus festival period (5/7/14 to 6/3/14), decreased 29% in the summer (7/8/14 to 8/5/14), and increased 31% on school return (10/7/14 to 11/4/14). The most robust predictors of higher quantities in regression analyses included items from each of the 3 major domains with the most consistent results seen for most baseline alcohol-related items and descriptive drinking norms (R(2) = 0.20 to 0.31). These data demonstrate important changes in students' drinking during the calendar year, including expected large increases during the month of a 1-day festival, large decreases over the summer, and resumption of relatively high quantities upon return to school. Copyright © 2016 by the Research Society on Alcoholism.

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

PubMed

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

2017-01-01

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

Development and validation of the Surgical Outcome Risk Tool (SORT)

PubMed Central

Protopapa, K L; Simpson, J C; Smith, N C E; Moonesinghe, S R

2014-01-01

Background Existing risk stratification tools have limitations and clinical experience suggests they are not used routinely. The aim of this study was to develop and validate a preoperative risk stratification tool to predict 30-day mortality after non-cardiac surgery in adults by analysis of data from the observational National Confidential Enquiry into Patient Outcome and Death (NCEPOD) Knowing the Risk study. Methods The data set was split into derivation and validation cohorts. Logistic regression was used to construct a model in the derivation cohort to create the Surgical Outcome Risk Tool (SORT), which was tested in the validation cohort. Results Prospective data for 19 097 cases in 326 hospitals were obtained from the NCEPOD study. Following exclusion of 2309, details of 16 788 patients were analysed (derivation cohort 11 219, validation cohort 5569). A model of 45 risk factors was refined on repeated regression analyses to develop a model comprising six variables: American Society of Anesthesiologists Physical Status (ASA-PS) grade, urgency of surgery (expedited, urgent, immediate), high-risk surgical specialty (gastrointestinal, thoracic, vascular), surgical severity (from minor to complex major), cancer and age 65 years or over. In the validation cohort, the SORT was well calibrated and demonstrated better discrimination than the ASA-PS and Surgical Risk Scale; areas under the receiver operating characteristic (ROC) curve were 0·91 (95 per cent c.i. 0·88 to 0·94), 0·87 (0·84 to 0·91) and 0·88 (0·84 to 0·92) respectively (P < 0·001). Conclusion The SORT allows rapid and simple data entry of six preoperative variables, and provides a percentage mortality risk for individuals undergoing surgery. PMID:25388883

Breeding value accuracy estimates for growth traits using random regression and multi-trait models in Nelore cattle.

PubMed

Boligon, A A; Baldi, F; Mercadante, M E Z; Lobo, R B; Pereira, R J; Albuquerque, L G

2011-06-28

We quantified the potential increase in accuracy of expected breeding value for weights of Nelore cattle, from birth to mature age, using multi-trait and random regression models on Legendre polynomials and B-spline functions. A total of 87,712 weight records from 8144 females were used, recorded every three months from birth to mature age from the Nelore Brazil Program. For random regression analyses, all female weight records from birth to eight years of age (data set I) were considered. From this general data set, a subset was created (data set II), which included only nine weight records: at birth, weaning, 365 and 550 days of age, and 2, 3, 4, 5, and 6 years of age. Data set II was analyzed using random regression and multi-trait models. The model of analysis included the contemporary group as fixed effects and age of dam as a linear and quadratic covariable. In the random regression analyses, average growth trends were modeled using a cubic regression on orthogonal polynomials of age. Residual variances were modeled by a step function with five classes. Legendre polynomials of fourth and sixth order were utilized to model the direct genetic and animal permanent environmental effects, respectively, while third-order Legendre polynomials were considered for maternal genetic and maternal permanent environmental effects. Quadratic polynomials were applied to model all random effects in random regression models on B-spline functions. Direct genetic and animal permanent environmental effects were modeled using three segments or five coefficients, and genetic maternal and maternal permanent environmental effects were modeled with one segment or three coefficients in the random regression models on B-spline functions. For both data sets (I and II), animals ranked differently according to expected breeding value obtained by random regression or multi-trait models. With random regression models, the highest gains in accuracy were obtained at ages with a low number of weight records. The results indicate that random regression models provide more accurate expected breeding values than the traditionally finite multi-trait models. Thus, higher genetic responses are expected for beef cattle growth traits by replacing a multi-trait model with random regression models for genetic evaluation. B-spline functions could be applied as an alternative to Legendre polynomials to model covariance functions for weights from birth to mature age.

Heterogeneous Effects of Fructose on Blood Lipids in Individuals With Type 2 Diabetes

PubMed Central

Sievenpiper, John L.; Carleton, Amanda J.; Chatha, Sheena; Jiang, Henry Y.; de Souza, Russell J.; Beyene, Joseph; Kendall, Cyril W.C.; Jenkins, David J.A.

2009-01-01

OBJECTIVE Because of blood lipid concerns, diabetes associations discourage fructose at high intakes. To quantify the effect of fructose on blood lipids in diabetes, we conducted a systematic review and meta-analysis of experimental clinical trials investigating the effect of isocaloric fructose exchange for carbohydrate on triglycerides, total cholesterol, LDL cholesterol, and HDL cholesterol in type 1 and 2 diabetes. RESEARCH DESIGN AND METHODS We searched MEDLINE, EMBASE, CINAHL, and the Cochrane Library for relevant trials of ≥7 days. Data were pooled by the generic inverse variance method and expressed as standardized mean differences with 95% CI. Heterogeneity was assessed by χ2 tests and quantified by I2. Meta-regression models identified dose threshold and independent predictors of effects. RESULTS Sixteen trials (236 subjects) met the eligibility criteria. Isocaloric fructose exchange for carbohydrate raised triglycerides and lowered total cholesterol under specific conditions without affecting LDL cholesterol or HDL cholesterol. A triglyceride-raising effect without heterogeneity was seen only in type 2 diabetes when the reference carbohydrate was starch (mean difference 0.24 [95% CI 0.05–0.44]), dose was >60 g/day (0.18 [0.00–0.37]), or follow-up was ≤4 weeks (0.18 [0.00–0.35]). Piecewise meta-regression confirmed a dose threshold of 60 g/day (R2 = 0.13)/10% energy (R2 = 0.36). A total cholesterol–lowering effect without heterogeneity was seen only in type 2 diabetes under the following conditions: no randomization and poor study quality (−0.19 [−0.34 to −0.05]), dietary fat >30% energy (−0.33 [−0.52 to −0.15]), or crystalline fructose (−0.28 [−0.47 to −0.09]). Multivariate meta-regression analyses were largely in agreement. CONCLUSIONS Pooled analyses demonstrated conditional triglyceride-raising and total cholesterol–lowering effects of isocaloric fructose exchange for carbohydrate in type 2 diabetes. Recommendations and large-scale future trials need to address the heterogeneity in the data. PMID:19592634

The analyses of risk factors for COPD in the Li ethnic group in Hainan, People's Republic of China.

PubMed

Ding, Yipeng; Xu, Junxu; Yao, Jinjian; Chen, Yu; He, Ping; Ouyang, Yanhong; Niu, Huan; Tian, Zhongjie; Sun, Pei

2015-01-01

To study the risk factors for chronic obstructive pulmonary disease (COPD) in Li population in Hainan province, People's Republic of China. Li people above 40 years of age from Hainan were chosen by stratified random cluster sampling between 2012 and 2014. All participants were interviewed with a home-visiting questionnaire, and spirometry was performed on all eligible participants. Patients with airflow limitation (forced expiratory volume in 1 second [FEV1]/forced vital capacity [FVC] <0.70) were further examined by postbronchodilator spirometry, and those with a postbronchodilator FEV1/FVC <0.70 was diagnosed with COPD. The information of physical condition and history, smoking intensity, smoking duration, second-hand smoking, education, job category, monthly household income, working years, residential environment, primary fuel for cooking and heating (biomass fuel including wood, crop residues, dung, and charcoal, or modern fuel such as natural gas, liquefied petroleum gas, electricity, and solar energy), ventilated kitchen, heating methods, air pollution, recurrent respiratory infections, family history of respiratory diseases, cough incentives, and allergies of COPD and non-COPD subjects was analyzed by univariate and multivariate logistic regression models to identify correlated risk factors for COPD. Out of the 5,463 Li participants, a total of 277 COPD cases were identified by spirometry, and 307 healthy subjects were randomly selected as controls. Univariate logistic regression analyses showed that older people (65 years and above), low body mass index (BMI), biomass smoke, 11-20 and >20 cigarettes/day, smoking for 40 years or more, second-hand smoking, recurrent respiratory infections, and induced cough were risk factors for COPD, whereas high BMI, high education level, and presence of ventilated kitchen were protective factors. Subsequent multivariate logistic regression model further demonstrated that aging, low BMI, biomass smoke, >20 cigarettes/day, and recurrent respiratory tract infections were high-risk factors for COPD in the Li population. The incidence of COPD has a strong correlation with age, BMI, biomass smoke, >20 cigarettes/day, and recurrent respiratory infections, suggesting they were high-risk factors for COPD in Li population.

Trends and spatial distribution of deaths of children aged 12-60 months in São Paulo, Brazil, 1980-98.

PubMed Central

Antunes, José Leopoldo Ferreira; Waldman, Eliseu Alves

2002-01-01

OBJECTIVE: To describe trends in the mortality of children aged 12-60 months and to perform spatial data analysis of its distribution at the inner city district level in São Paulo from 1980 to 1998. METHODS: Official mortality data were analysed in relation to the underlying causes of death. The population of children aged 12-60 months, disaggregated by sex and age, was estimated for each year. Educational levels, income, employment status, and other socioeconomic indices were also assessed. Statistical Package for Social Sciences software was used for the statistical processing of time series. The Cochrane-Orcutt procedure of generalized least squares regression analysis was used to estimate the regression parameters with control of first-order autocorrelation. Spatial data analysis employed the discrimination of death rates and socioeconomic indices at the inner city district level. For classifying area-level death rates the method of K-means cluster analysis was used. Spatial correlation between variables was analysed by the simultaneous autoregressive regression method. FINDINGS: There was a steady decline in death rates during the 1980s at an average rate of 3.08% per year, followed by a levelling off. Infectious diseases remained the major cause of mortality, accounting for 43.1% of deaths during the last three years of the study. Injuries accounted for 16.5% of deaths. Mortality rates at the area level clearly demonstrated inequity in the city's health profile: there was an increasing difference between the rich and the underprivileged social strata in this respect. CONCLUSION: The overall mortality rate among children aged 12-60 months dropped by almost 30% during the study period. Most of the decline happened during the 1980s. Many people still live in a state of deprivation in underserved areas. Time-series and spatial data analysis provided indications of potential value in the planning of social policies promoting well-being, through the identification of factors affecting child survival and the regions with the worst health profiles, to which programmes and resources should be preferentially directed. PMID:12077615

The analyses of risk factors for COPD in the Li ethnic group in Hainan, People’s Republic of China

PubMed Central

Ding, Yipeng; Xu, Junxu; Yao, Jinjian; Chen, Yu; He, Ping; Ouyang, Yanhong; Niu, Huan; Tian, Zhongjie; Sun, Pei

2015-01-01

Objective To study the risk factors for chronic obstructive pulmonary disease (COPD) in Li population in Hainan province, People’s Republic of China. Methods Li people above 40 years of age from Hainan were chosen by stratified random cluster sampling between 2012 and 2014. All participants were interviewed with a home-visiting questionnaire, and spirometry was performed on all eligible participants. Patients with airflow limitation (forced expiratory volume in 1 second [FEV1]/forced vital capacity [FVC] <0.70) were further examined by postbronchodilator spirometry, and those with a postbronchodilator FEV1/FVC <0.70 was diagnosed with COPD. The information of physical condition and history, smoking intensity, smoking duration, second-hand smoking, education, job category, monthly household income, working years, residential environment, primary fuel for cooking and heating (biomass fuel including wood, crop residues, dung, and charcoal, or modern fuel such as natural gas, liquefied petroleum gas, electricity, and solar energy), ventilated kitchen, heating methods, air pollution, recurrent respiratory infections, family history of respiratory diseases, cough incentives, and allergies of COPD and non-COPD subjects was analyzed by univariate and multivariate logistic regression models to identify correlated risk factors for COPD. Results Out of the 5,463 Li participants, a total of 277 COPD cases were identified by spirometry, and 307 healthy subjects were randomly selected as controls. Univariate logistic regression analyses showed that older people (65 years and above), low body mass index (BMI), biomass smoke, 11–20 and >20 cigarettes/day, smoking for 40 years or more, second-hand smoking, recurrent respiratory infections, and induced cough were risk factors for COPD, whereas high BMI, high education level, and presence of ventilated kitchen were protective factors. Subsequent multivariate logistic regression model further demonstrated that aging, low BMI, biomass smoke, >20 cigarettes/day, and recurrent respiratory tract infections were high-risk factors for COPD in the Li population. Conclusion The incidence of COPD has a strong correlation with age, BMI, biomass smoke, >20 cigarettes/day, and recurrent respiratory infections, suggesting they were high-risk factors for COPD in Li population. PMID:26664107

Web-based tools for modelling and analysis of multivariate data: California ozone pollution activity

PubMed Central

Dinov, Ivo D.; Christou, Nicolas

2014-01-01

This article presents a hands-on web-based activity motivated by the relation between human health and ozone pollution in California. This case study is based on multivariate data collected monthly at 20 locations in California between 1980 and 2006. Several strategies and tools for data interrogation and exploratory data analysis, model fitting and statistical inference on these data are presented. All components of this case study (data, tools, activity) are freely available online at: http://wiki.stat.ucla.edu/socr/index.php/SOCR_MotionCharts_CAOzoneData. Several types of exploratory (motion charts, box-and-whisker plots, spider charts) and quantitative (inference, regression, analysis of variance (ANOVA)) data analyses tools are demonstrated. Two specific human health related questions (temporal and geographic effects of ozone pollution) are discussed as motivational challenges. PMID:24465054

The Unique Effects of Parental Alcohol and Affective Disorders, Parenting, and Parental Negative Affect on Adolescent Maladjustment

PubMed Central

Haller, Moira; Chassin, Laurie

2010-01-01

Using a high-risk community sample, multiple regression analyses were conducted separately for mothers (N=416) and fathers (N= 346) to test the unique, prospective influence of parental negative affect on adolescent maladjustment (internalizing symptoms, externalizing symptoms, and negative emotionality) two years later over and above parental alcohol and affective disorders, major disruption in the family environment, and parenting. Adolescent sex was tested as a moderator. Results indicated that maternal (but not paternal) negative affect had a unique, prospective effect on adolescent internalizing symptoms in girls and negative emotionality in both sexes, but did not predict adolescent externalizing symptoms. Findings demonstrate that mothers’ negative affect may have unique effects on adolescent adjustment, separate from the effects of clinically significant parental psychopathology, parenting, and disruption in the family environment. PMID:23761947

The Unique Effects of Parental Alcohol and Affective Disorders, Parenting, and Parental Negative Affect on Adolescent Maladjustment.

PubMed

Haller, Moira; Chassin, Laurie

2011-07-01

Using a high-risk community sample, multiple regression analyses were conducted separately for mothers ( N =416) and fathers ( N = 346) to test the unique, prospective influence of parental negative affect on adolescent maladjustment (internalizing symptoms, externalizing symptoms, and negative emotionality) two years later over and above parental alcohol and affective disorders, major disruption in the family environment, and parenting. Adolescent sex was tested as a moderator. Results indicated that maternal (but not paternal) negative affect had a unique, prospective effect on adolescent internalizing symptoms in girls and negative emotionality in both sexes, but did not predict adolescent externalizing symptoms. Findings demonstrate that mothers' negative affect may have unique effects on adolescent adjustment, separate from the effects of clinically significant parental psychopathology, parenting, and disruption in the family environment.

Personality traits as risk factors of depression and anxiety among Japanese students.

PubMed

Matsudaira, Tomomi; Kitamura, Toshinori

2006-01-01

The aim of this study is to examine the effects of personality (temperament and character) on specific depression and specific anxiety. A total of 541 Japanese undergraduates were investigated by using the Temperament and Character Inventory (TCI) and the Hospital Anxiety and Depression (HAD) scale. Hierarchical multiple regression analyses demonstrated that specific depression was predicted by lower Reward-Dependence, Persistence, Self-Directedness, Cooperativeness, and Self-Transcendence; specific anxiety was predicted by higher Novelty-Seeking, Harm-Avoidance, Persistence, and Self-Transcendence, and lower Self-Directedness. Immaturity of Self-Directedness is a risk factor for negative affectivity. Immaturity of all character dimensions is a risk factor for specific depression. The relationship between Harm-Avoidance and depression in previous studies may be linked partly to somatic symptoms that were deliberately eliminated in the HAD scale.

Fear of Death in a Sample of Physicians

PubMed Central

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

Time Series Expression Analyses Using RNA-seq: A Statistical Approach

PubMed Central

Oh, Sunghee; Song, Seongho; Grabowski, Gregory; Zhao, Hongyu; Noonan, James P.

2013-01-01

RNA-seq is becoming the de facto standard approach for transcriptome analysis with ever-reducing cost. It has considerable advantages over conventional technologies (microarrays) because it allows for direct identification and quantification of transcripts. Many time series RNA-seq datasets have been collected to study the dynamic regulations of transcripts. However, statistically rigorous and computationally efficient methods are needed to explore the time-dependent changes of gene expression in biological systems. These methods should explicitly account for the dependencies of expression patterns across time points. Here, we discuss several methods that can be applied to model timecourse RNA-seq data, including statistical evolutionary trajectory index (SETI), autoregressive time-lagged regression (AR(1)), and hidden Markov model (HMM) approaches. We use three real datasets and simulation studies to demonstrate the utility of these dynamic methods in temporal analysis. PMID:23586021

Parents' work patterns and adolescent mental health.

PubMed

Dockery, Alfred; Li, Jianghong; Kendall, Garth

2009-02-01

Previous research demonstrates that non-standard work schedules undermine the stability of marriage and reduce family cohesiveness. Limited research has investigated the effects of parents working non-standard schedules on children's health and wellbeing and no published Australian studies have addressed this important issue. This paper contributes to bridging this knowledge gap by focusing on adolescents aged 15-20 years and by including sole parent families which have been omitted in previous research, using panel data from the Household, Income and Labour Dynamics in Australia Survey. Multilevel linear regression models are estimated to analyse the association between parental work schedules and hours of work and measures of adolescents' mental health derived from the SF-36 Health Survey. Evidence of negative impacts of parents working non-standard hours upon adolescent wellbeing is found to exist primarily within sole parent families.

Web-based tools for modelling and analysis of multivariate data: California ozone pollution activity.

PubMed

Dinov, Ivo D; Christou, Nicolas

2011-09-01

This article presents a hands-on web-based activity motivated by the relation between human health and ozone pollution in California. This case study is based on multivariate data collected monthly at 20 locations in California between 1980 and 2006. Several strategies and tools for data interrogation and exploratory data analysis, model fitting and statistical inference on these data are presented. All components of this case study (data, tools, activity) are freely available online at: http://wiki.stat.ucla.edu/socr/index.php/SOCR_MotionCharts_CAOzoneData. Several types of exploratory (motion charts, box-and-whisker plots, spider charts) and quantitative (inference, regression, analysis of variance (ANOVA)) data analyses tools are demonstrated. Two specific human health related questions (temporal and geographic effects of ozone pollution) are discussed as motivational challenges.

Methylation of DNA and chromatin as a mechanism of oncogenesis and therapeutic target in neuroblastoma.

PubMed

Ram Kumar, Ram Mohan; Schor, Nina Felice

2018-04-24

Neuroblastoma (NB), a developmental cancer, is often fatal, emphasizing the need to understand its pathogenesis and identify new therapeutic targets. The heterogeneous pathological and clinical phenotype of NB underscores the cryptic biological and genetic features of this tumor that result in outcomes ranging from rapid progression to spontaneous regression. Despite recent genome-wide mutation analyses, most primary NBs do not harbor driver mutations, implicating epigenetically-mediated gene regulatory mechanisms in the initiation and maintenance of NB. Aberrant epigenomic mechanisms, as demonstrated by global changes in DNA methylation signatures, acetylation, re-distribution of histone marks, and change in the chromatin architecture, are hypothesized to play a role in NB oncogenesis. This paper reviews the evidence for, putative mechanisms underlying, and prospects for therapeutic targeting of NB oncogenesis related to DNA methylation.

THE ROLE OF LOCATION IN EVALUATING RACIAL WAGE DISPARITY.

PubMed

Black, Dan A; Kolesnikova, Natalia; Sanders, Seth G; Taylor, Lowell J

2013-05-01

A standard object of empirical analysis in labor economics is a modified Mincer wage function in which an individual's log wage is specified to be a function of education, experience, and an indicator variable identifying race. We analyze this approach in a context in which individuals live and work in different locations (and thus face different housing prices and wages). Our model provides a justification for the traditional approach, but with the important caveat that the regression should include location-specific fixed effects. Empirical analyses of men in U.S. labor markets demonstrate that failure to condition on location causes us to (i) overstate the decline in black-white wage disparity over the past 60 years, and (ii) understate racial and ethnic wage gaps that remain after taking into account measured cognitive skill differences that emerge when workers are young.

Optimal design and experimental analyses of a new micro-vibration control payload-platform

NASA Astrophysics Data System (ADS)

Sun, Xiaoqing; Yang, Bintang; Zhao, Long; Sun, Xiaofen

2016-07-01

This paper presents a new payload-platform, for precision devices, which possesses the capability of isolating the complex space micro-vibration in low frequency range below 5 Hz. The novel payload-platform equipped with smart material actuators is investigated and designed through optimization strategy based on the minimum energy loss rate, for the aim of achieving high drive efficiency and reducing the effect of the magnetic circuit nonlinearity. Then, the dynamic model of the driving element is established by using the Lagrange method and the performance of the designed payload-platform is further discussed through the combination of the controlled auto regressive moving average (CARMA) model with modified generalized prediction control (MGPC) algorithm. Finally, an experimental prototype is developed and tested. The experimental results demonstrate that the payload-platform has an impressive potential of micro-vibration isolation.

Examining Postsecondary Education Predictors and Participation for Students With Learning Disabilities.

PubMed

Joshi, Gauri S; Bouck, Emily C

2017-01-01

Given the history of poor postschool outcomes for students with disabilities, researchers repeatedly sought to demonstrate the links between predictor variables and postschool outcomes for students with disabilities. This secondary data analysis used the National Longitudinal Transition Study-2 to examine the relationship between postsecondary education-related transition services and postsecondary education participation for students with learning disabilities. Logistic regression analyses indicated receiving core content area instruction in the general education classroom was positively related to postsecondary education participation. Frequency distributions indicated students with learning disabilities attended 2-year college at higher rates than other postsecondary education programs. The results suggest educators should consider inclusion in general education classroom for core content area instruction for students with learning disabilities with postsecondary education goals to the extent permitted by their least restrictive environment. © Hammill Institute on Disabilities 2015.

The "Generacion Diez" after-school program and Latino parent involvement with schools.

PubMed

Riggs, Nathaniel R; Medina, Carmen

2005-11-01

The current study examines associations between participation in after-school programs and change in Latino parent involvement with schools. Hierarchical linear regression analyses demonstrated that parents of children who had higher after-school program attendance rates were significantly more likely to report increases in the quality of relationships with their children's teachers, frequency of parent-teacher contact, and engagement with their children's schooling over a two-year period. However, greater home educator contacts were related to decreases in quality and quantity of parent-school involvement. A primary implication is that attendance in school-based after-school programs may draw parents into children's regular-day school context. Editors' Strategic Implications The authors illustrate the promising practice of using after-school programs to promote parent involvement and to help integrate the often disparate family and school contexts for Latino children.

A large-scale evaluation of the KiVa antibullying program: grades 4-6.

PubMed

Kärnä, Antti; Voeten, Marinus; Little, Todd D; Poskiparta, Elisa; Kaljonen, Anne; Salmivalli, Christina

2011-01-01

This study demonstrates the effectiveness of the KiVa antibullying program using a large sample of 8,237 youth from Grades 4-6 (10-12 years). Altogether, 78 schools were randomly assigned to intervention (39 schools, 4,207 students) and control conditions (39 schools, 4,030 students). Multilevel regression analyses revealed that after 9 months of implementation, the intervention had consistent beneficial effects on 7 of the 11 dependent variables, including self- and peer-reported victimization and self-reported bullying. The results indicate that the KiVa program is effective in reducing school bullying and victimization in Grades 4-6. Despite some evidence against school-based interventions, the results suggest that well-conceived school-based programs can reduce victimization. © 2011 The Authors. Child Development © 2011 Society for Research in Child Development, Inc.