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

Science.gov (United States)

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,…

The number of subjects per variable required in linear regression analyses.

Science.gov (United States)

Austin, Peter C; Steyerberg, Ewout W

2015-06-01

To determine the number of independent variables that can be included in a linear regression model. We used a series of Monte Carlo simulations to examine the impact of the number of subjects per variable (SPV) on the accuracy of estimated regression coefficients and standard errors, on the empirical coverage of estimated confidence intervals, and on the accuracy of the estimated R(2) of the fitted model. A minimum of approximately two SPV tended to result in estimation of regression coefficients with relative bias of less than 10%. Furthermore, with this minimum number of SPV, the standard errors of the regression coefficients were accurately estimated and estimated confidence intervals had approximately the advertised coverage rates. A much higher number of SPV were necessary to minimize bias in estimating the model R(2), although adjusted R(2) estimates behaved well. The bias in estimating the model R(2) statistic was inversely proportional to the magnitude of the proportion of variation explained by the population regression model. Linear regression models require only two SPV for adequate estimation of regression coefficients, standard errors, and confidence intervals. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

A Comparative Study of Classification and Regression Algorithms for Modelling Students' Academic Performance

Science.gov (United States)

Strecht, Pedro; Cruz, Luís; Soares, Carlos; Mendes-Moreira, João; Abreu, Rui

2015-01-01

Predicting the success or failure of a student in a course or program is a problem that has recently been addressed using data mining techniques. In this paper we evaluate some of the most popular classification and regression algorithms on this problem. We address two problems: prediction of approval/failure and prediction of grade. The former is…

Statistical and regression analyses of detected extrasolar systems

Czech Academy of Sciences Publication Activity Database

Pintr, Pavel; Peřinová, V.; Lukš, A.; Pathak, A.

2013-01-01

Roč. 75, č. 1 (2013), s. 37-45 ISSN 0032-0633 Institutional support: RVO:61389021 Keywords : Exoplanets * Kepler candidates * Regression analysis Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics Impact factor: 1.630, year: 2013 http://www.sciencedirect.com/science/article/pii/S0032063312003066

Reducing Inter-Laboratory Differences between Semen Analyses Using Z Score and Regression Transformations

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Esther Leushuis

2016-12-01

Full Text Available Background: Standardization of the semen analysis may improve reproducibility. We assessed variability between laboratories in semen analyses and evaluated whether a transformation using Z scores and regression statistics was able to reduce this variability. Materials and Methods: We performed a retrospective cohort study. We calculated between-laboratory coefficients of variation (CVB for sperm concentration and for morphology. Subsequently, we standardized the semen analysis results by calculating laboratory specific Z scores, and by using regression. We used analysis of variance for four semen parameters to assess systematic differences between laboratories before and after the transformations, both in the circulation samples and in the samples obtained in the prospective cohort study in the Netherlands between January 2002 and February 2004. Results: The mean CVB was 7% for sperm concentration (range 3 to 13% and 32% for sperm morphology (range 18 to 51%. The differences between the laboratories were statistically significant for all semen parameters (all P<0.001. Standardization using Z scores did not reduce the differences in semen analysis results between the laboratories (all P<0.001. Conclusion: There exists large between-laboratory variability for sperm morphology and small, but statistically significant, between-laboratory variation for sperm concentration. Standardization using Z scores does not eliminate between-laboratory variability.

Predicting Student Success on the Texas Chemistry STAAR Test: A Logistic Regression Analysis

Science.gov (United States)

Johnson, William L.; Johnson, Annabel M.; Johnson, Jared

2012-01-01

Background: The context is the new Texas STAAR end-of-course testing program. Purpose: The authors developed a logistic regression model to predict who would pass-or-fail the new Texas chemistry STAAR end-of-course exam. Setting: Robert E. Lee High School (5A) with an enrollment of 2700 students, Tyler, Texas. Date of the study was the 2011-2012…

Regression Analysis

CERN Document Server

Freund, Rudolf J; Sa, Ping

2006-01-01

The book provides complete coverage of the classical methods of statistical analysis. It is designed to give students an understanding of the purpose of statistical analyses, to allow the student to determine, at least to some degree, the correct type of statistical analyses to be performed in a given situation, and have some appreciation of what constitutes good experimental design

Emotional Issues and Peer Relations in Gifted Elementary Students: Regression Analysis of National Data

Science.gov (United States)

Wiley, Kristofor R.

2013-01-01

Many of the social and emotional needs that have historically been associated with gifted students have been questioned on the basis of recent empirical evidence. Research on the topic, however, is often limited by sample size, selection bias, or definition. This study addressed these limitations by applying linear regression methodology to data…

SOCR Analyses: Implementation and Demonstration of a New Graphical Statistics Educational Toolkit

Directory of Open Access Journals (Sweden)

Annie Chu

2009-04-01

Full Text Available The web-based, Java-written SOCR (Statistical Online Computational Resource toolshave been utilized in many undergraduate and graduate level statistics courses for sevenyears now (Dinov 2006; Dinov et al. 2008b. It has been proven that these resourcescan successfully improve students' learning (Dinov et al. 2008b. Being rst publishedonline in 2005, SOCR Analyses is a somewhat new component and it concentrate on datamodeling for both parametric and non-parametric data analyses with graphical modeldiagnostics. One of the main purposes of SOCR Analyses is to facilitate statistical learn-ing for high school and undergraduate students. As we have already implemented SOCRDistributions and Experiments, SOCR Analyses and Charts fulll the rest of a standardstatistics curricula. Currently, there are four core components of SOCR Analyses. Linearmodels included in SOCR Analyses are simple linear regression, multiple linear regression,one-way and two-way ANOVA. Tests for sample comparisons include t-test in the para-metric category. Some examples of SOCR Analyses' in the non-parametric category areWilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, Kolmogorov-Smirno testand Fligner-Killeen test. Hypothesis testing models include contingency table, Friedman'stest and Fisher's exact test. The last component of Analyses is a utility for computingsample sizes for normal distribution. In this article, we present the design framework,computational implementation and the utilization of SOCR Analyses.

Regression to Causality : Regression-style presentation influences causal attribution

DEFF Research Database (Denmark)

Bordacconi, Mats Joe; Larsen, Martin Vinæs

2014-01-01

of equivalent results presented as either regression models or as a test of two sample means. Our experiment shows that the subjects who were presented with results as estimates from a regression model were more inclined to interpret these results causally. Our experiment implies that scholars using regression...... models – one of the primary vehicles for analyzing statistical results in political science – encourage causal interpretation. Specifically, we demonstrate that presenting observational results in a regression model, rather than as a simple comparison of means, makes causal interpretation of the results...... more likely. Our experiment drew on a sample of 235 university students from three different social science degree programs (political science, sociology and economics), all of whom had received substantial training in statistics. The subjects were asked to compare and evaluate the validity...

Correlation and regression analyses of genetic effects for different types of cells in mammals under radiation and chemical treatment

International Nuclear Information System (INIS)

Slutskaya, N.G.; Mosseh, I.B.

2006-01-01

Data about genetic mutations under radiation and chemical treatment for different types of cells have been analyzed with correlation and regression analyses. Linear correlation between different genetic effects in sex cells and somatic cells have found. The results may be extrapolated on sex cells of human and mammals. (authors)

Analysing task design and students' responses to context-based problems through different analytical frameworks

Science.gov (United States)

Broman, Karolina; Bernholt, Sascha; Parchmann, Ilka

2015-05-01

Background:Context-based learning approaches are used to enhance students' interest in, and knowledge about, science. According to different empirical studies, students' interest is improved by applying these more non-conventional approaches, while effects on learning outcomes are less coherent. Hence, further insights are needed into the structure of context-based problems in comparison to traditional problems, and into students' problem-solving strategies. Therefore, a suitable framework is necessary, both for the analysis of tasks and strategies. Purpose:The aim of this paper is to explore traditional and context-based tasks as well as students' responses to exemplary tasks to identify a suitable framework for future design and analyses of context-based problems. The paper discusses different established frameworks and applies the Higher-Order Cognitive Skills/Lower-Order Cognitive Skills (HOCS/LOCS) taxonomy and the Model of Hierarchical Complexity in Chemistry (MHC-C) to analyse traditional tasks and students' responses. Sample:Upper secondary students (n=236) at the Natural Science Programme, i.e. possible future scientists, are investigated to explore learning outcomes when they solve chemistry tasks, both more conventional as well as context-based chemistry problems. Design and methods:A typical chemistry examination test has been analysed, first the test items in themselves (n=36), and thereafter 236 students' responses to one representative context-based problem. Content analysis using HOCS/LOCS and MHC-C frameworks has been applied to analyse both quantitative and qualitative data, allowing us to describe different problem-solving strategies. Results:The empirical results show that both frameworks are suitable to identify students' strategies, mainly focusing on recall of memorized facts when solving chemistry test items. Almost all test items were also assessing lower order thinking. The combination of frameworks with the chemistry syllabus has been

The number of subjects per variable required in linear regression analyses

NARCIS (Netherlands)

P.C. Austin (Peter); E.W. Steyerberg (Ewout)

2015-01-01

textabstractObjectives To determine the number of independent variables that can be included in a linear regression model. Study Design and Setting We used a series of Monte Carlo simulations to examine the impact of the number of subjects per variable (SPV) on the accuracy of estimated regression

Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies

OpenAIRE

Vatcheva, Kristina P.; Lee, MinJae; McCormick, Joseph B.; Rahbar, Mohammad H.

2016-01-01

The adverse impact of ignoring multicollinearity on findings and data interpretation in regression analysis is very well documented in the statistical literature. The failure to identify and report multicollinearity could result in misleading interpretations of the results. A review of epidemiological literature in PubMed from January 2004 to December 2013, illustrated the need for a greater attention to identifying and minimizing the effect of multicollinearity in analysis of data from epide...

Analyses of non-fatal accidents in an opencast mine by logistic regression model - a case study.

Science.gov (United States)

Onder, Seyhan; Mutlu, Mert

2017-09-01

Accidents cause major damage for both workers and enterprises in the mining industry. To reduce the number of occupational accidents, these incidents should be properly registered and carefully analysed. This study efficiently examines the Aegean Lignite Enterprise (ELI) of Turkish Coal Enterprises (TKI) in Soma between 2006 and 2011, and opencast coal mine occupational accident records were used for statistical analyses. A total of 231 occupational accidents were analysed for this study. The accident records were categorized into seven groups: area, reason, occupation, part of body, age, shift hour and lost days. The SPSS package program was used in this study for logistic regression analyses, which predicted the probability of accidents resulting in greater or less than 3 lost workdays for non-fatal injuries. Social facilities-area of surface installations, workshops and opencast mining areas are the areas with the highest probability for accidents with greater than 3 lost workdays for non-fatal injuries, while the reasons with the highest probability for these types of accidents are transporting and manual handling. Additionally, the model was tested for such reported accidents that occurred in 2012 for the ELI in Soma and estimated the probability of exposure to accidents with lost workdays correctly by 70%.

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

Science.gov (United States)

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.

Correlation, Regression and Path Analyses of Seed Yield Components in Crambe abyssinica, a Promising Industrial Oil Crop

OpenAIRE

Huang, Banglian; Yang, Yiming; Luo, Tingting; Wu, S.; Du, Xuezhu; Cai, Detian; Loo, van, E.N.; Huang Bangquan

2013-01-01

In the present study correlation, regression and path analyses were carried out to decide correlations among the agro- nomic traits and their contributions to seed yield per plant in Crambe abyssinica. Partial correlation analysis indicated that plant height (X1) was significantly correlated with branching height and the number of first branches (P <0.01); Branching height (X2) was significantly correlated with pod number of primary inflorescence (P <0.01) and number of secondary branch...

ENHANCED PREDICTION OF STUDENT DROPOUTS USING FUZZY INFERENCE SYSTEM AND LOGISTIC REGRESSION

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A. Saranya

2016-01-01

Full Text Available Predicting college and school dropouts is a major problem in educational system and has complicated challenge due to data imbalance and multi dimensionality, which can affect the low performance of students. In this paper, we have collected different database from various colleges, among these 500 best real attributes are identified in order to identify the factor that affecting dropout students using neural based classification algorithm and different mining technique are implemented for data processing. We also propose a Dropout Prediction Algorithm (DPA using fuzzy logic and Logistic Regression based inference system because the weighted average will improve the performance of whole system. We are experimented our proposed work with all other classification systems and documented as the best outcomes. The aggregated data is given to the decision trees for better dropout prediction. The accuracy of overall system 98.6% it shows the proposed work depicts efficient prediction.

Division I Student Athletes' Perceptions: How Well Does the Athletic Department Promote Student Athlete Development in an Urban-Serving University?

Science.gov (United States)

Vermillion, Mark

2014-01-01

The purpose of the research was to identify student athletes' perceptions of their athletic department regarding student development. Student athletes from a Division I athletic department were surveyed (n = 369) in order to monitor their development. Regression analyses, which included respondent's sport, gender, classification, reports of abuse,…

An Exploratory Study of Face-to-Face and Cyberbullying in Sixth Grade Students

Science.gov (United States)

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…

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

Directory of Open Access Journals (Sweden)

M. Guns

2012-06-01

Full Text Available 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.

Regression analysis with categorized regression calibrated exposure: some interesting findings

Directory of Open Access Journals (Sweden)

Hjartåker Anette

2006-07-01

Full Text Available Abstract Background Regression calibration as a method for handling measurement error is becoming increasingly well-known and used in epidemiologic research. However, the standard version of the method is not appropriate for exposure analyzed on a categorical (e.g. quintile scale, an approach commonly used in epidemiologic studies. A tempting solution could then be to use the predicted continuous exposure obtained through the regression calibration method and treat it as an approximation to the true exposure, that is, include the categorized calibrated exposure in the main regression analysis. Methods We use semi-analytical calculations and simulations to evaluate the performance of the proposed approach compared to the naive approach of not correcting for measurement error, in situations where analyses are performed on quintile scale and when incorporating the original scale into the categorical variables, respectively. We also present analyses of real data, containing measures of folate intake and depression, from the Norwegian Women and Cancer study (NOWAC. Results In cases where extra information is available through replicated measurements and not validation data, regression calibration does not maintain important qualities of the true exposure distribution, thus estimates of variance and percentiles can be severely biased. We show that the outlined approach maintains much, in some cases all, of the misclassification found in the observed exposure. For that reason, regression analysis with the corrected variable included on a categorical scale is still biased. In some cases the corrected estimates are analytically equal to those obtained by the naive approach. Regression calibration is however vastly superior to the naive method when applying the medians of each category in the analysis. Conclusion Regression calibration in its most well-known form is not appropriate for measurement error correction when the exposure is analyzed on a

[Application of negative binomial regression and modified Poisson regression in the research of risk factors for injury frequency].

Science.gov (United States)

Cao, Qingqing; Wu, Zhenqiang; Sun, Ying; Wang, Tiezhu; Han, Tengwei; Gu, Chaomei; Sun, Yehuan

2011-11-01

To Eexplore the application of negative binomial regression and modified Poisson regression analysis in analyzing the influential factors for injury frequency and the risk factors leading to the increase of injury frequency. 2917 primary and secondary school students were selected from Hefei by cluster random sampling method and surveyed by questionnaire. The data on the count event-based injuries used to fitted modified Poisson regression and negative binomial regression model. The risk factors incurring the increase of unintentional injury frequency for juvenile students was explored, so as to probe the efficiency of these two models in studying the influential factors for injury frequency. The Poisson model existed over-dispersion (P Poisson regression and negative binomial regression model, was fitted better. respectively. Both showed that male gender, younger age, father working outside of the hometown, the level of the guardian being above junior high school and smoking might be the results of higher injury frequencies. On a tendency of clustered frequency data on injury event, both the modified Poisson regression analysis and negative binomial regression analysis can be used. However, based on our data, the modified Poisson regression fitted better and this model could give a more accurate interpretation of relevant factors affecting the frequency of injury.

Genetic analyses of partial egg production in Japanese quail using multi-trait random regression models.

Science.gov (United States)

Karami, K; Zerehdaran, S; Barzanooni, B; Lotfi, E

2017-12-01

1. The aim of the present study was to estimate genetic parameters for average egg weight (EW) and egg number (EN) at different ages in Japanese quail using multi-trait random regression (MTRR) models. 2. A total of 8534 records from 900 quail, hatched between 2014 and 2015, were used in the study. Average weekly egg weights and egg numbers were measured from second until sixth week of egg production. 3. Nine random regression models were compared to identify the best order of the Legendre polynomials (LP). The most optimal model was identified by the Bayesian Information Criterion. A model with second order of LP for fixed effects, second order of LP for additive genetic effects and third order of LP for permanent environmental effects (MTRR23) was found to be the best. 4. According to the MTRR23 model, direct heritability for EW increased from 0.26 in the second week to 0.53 in the sixth week of egg production, whereas the ratio of permanent environment to phenotypic variance decreased from 0.48 to 0.1. Direct heritability for EN was low, whereas the ratio of permanent environment to phenotypic variance decreased from 0.57 to 0.15 during the production period. 5. For each trait, estimated genetic correlations among weeks of egg production were high (from 0.85 to 0.98). Genetic correlations between EW and EN were low and negative for the first two weeks, but they were low and positive for the rest of the egg production period. 6. In conclusion, random regression models can be used effectively for analysing egg production traits in Japanese quail. Response to selection for increased egg weight would be higher at older ages because of its higher heritability and such a breeding program would have no negative genetic impact on egg production.

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

Energy Technology Data Exchange (ETDEWEB)

Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd; Baharum, Adam [Pusat Pengajian Sains Matematik, Universiti Sains Malaysia, 11800 USM, Pulau Pinang, Malaysia amirul@unisel.edu.my, zalila@cs.usm.my, norlida@usm.my, adam@usm.my (Malaysia)

2015-10-22

Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test of the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

International Nuclear Information System (INIS)

Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd; Baharum, Adam

2015-01-01

Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test of the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake

The Role of Healthy Lifestyle in the Implementation of Regressing Suboptimal Health Status among College Students in China: A Nested Case-Control Study.

Science.gov (United States)

Chen, Jieyu; Xiang, Hongjie; Jiang, Pingping; Yu, Lin; Jing, Yuan; Li, Fei; Wu, Shengwei; Fu, Xiuqiong; Liu, Yanyan; Kwan, Hiuyee; Luo, Ren; Zhao, Xiaoshan; Sun, Xiaomin

2017-02-28

Suboptimal health status (SHS) is the intermediate health state between health and disease, it is medically undiagnosed and is also termed functional somatic syndrome. Although its clinical manifestations are complicated and various, SHS has not reached the disease status. Unhealthy lifestyle is associated with many chronic diseases and mortality. In accordance with the impact of lifestyle on health, it is intriguing to determine the association between unhealthy lifestyle and SHS risk. We conducted a nested case-control study among healthy Chinese college students from March 2012 to September 2013, which was nested in a prospective cohort of 5676 students. We performed 1:1 incidence density sampling with matched controls for birth year, sex, grade, specialty and individual character. SHS was evaluated using the medical examination report and Sub-health Measurement Scale V1.0 (SHMS V1.0). Exposure was defined as an unhealthy lifestyle per the frequency of six behavioral dimensions from the Health-promoting Lifestyle Profile (HPLP-II). We matched 543 cases of SHS (42.66%) in a cohort of 1273 students during the 1.5 years mean follow-up time with controls. A significant difference (t = 9.79, p lifestyle behavior with respect to behavioral dimensions significantly affected SHS likelihood. Further analyses revealed a marked increase (average increased 14.73 points) in lifestyle level among those SHS regression to health after 1.5 years, with respect to the HPLP-II behavioral dimensions, in addition to the total score (t = -15.34, p lifestyles, and the Int. J. Environ. Res. Public Health 2017, 14, 240 2 of 17 mitigation of modifiable lifestyle risk factors may lead to SHS regression. Increased efforts to modify unhealthy lifestyles are necessary to prevent SHS.

The Efficacy and Development of Students' Problem-Solving Strategies During Compulsory Schooling: Logfile Analyses.

Science.gov (United States)

Molnár, Gyöngyvér; Csapó, Benő

2018-01-01

The purpose of this study was to examine the role of exploration strategies students used in the first phase of problem solving. The sample for the study was drawn from 3 rd - to 12 th -grade students (aged 9-18) in Hungarian schools ( n = 4,371). Problems designed in the MicroDYN approach with different levels of complexity were administered to the students via the eDia online platform. Logfile analyses were performed to ascertain the impact of strategy use on the efficacy of problem solving. Students' exploration behavior was coded and clustered through Latent Class Analyses. Several theoretically effective strategies were identified, including the vary-one-thing-at-a-time (VOTAT) strategy and its sub-strategies. The results of the analyses indicate that the use of a theoretically effective strategy, which extract all information required to solve the problem, did not always lead to high performance. Conscious VOTAT strategy users proved to be the best problem solvers followed by non-conscious VOTAT strategy users and non-VOTAT strategy users. In the primary school sub-sample, six qualitatively different strategy class profiles were distinguished. The results shed new light on and provide a new interpretation of previous analyses of the processes involved in complex problem solving. They also highlight the importance of explicit enhancement of problem-solving skills and problem-solving strategies as a tool for knowledge acquisition in new contexts during and beyond school lessons.

The Efficacy and Development of Students' Problem-Solving Strategies During Compulsory Schooling: Logfile Analyses

Science.gov (United States)

Molnár, Gyöngyvér; Csapó, Benő

2018-01-01

The purpose of this study was to examine the role of exploration strategies students used in the first phase of problem solving. The sample for the study was drawn from 3rd- to 12th-grade students (aged 9–18) in Hungarian schools (n = 4,371). Problems designed in the MicroDYN approach with different levels of complexity were administered to the students via the eDia online platform. Logfile analyses were performed to ascertain the impact of strategy use on the efficacy of problem solving. Students' exploration behavior was coded and clustered through Latent Class Analyses. Several theoretically effective strategies were identified, including the vary-one-thing-at-a-time (VOTAT) strategy and its sub-strategies. The results of the analyses indicate that the use of a theoretically effective strategy, which extract all information required to solve the problem, did not always lead to high performance. Conscious VOTAT strategy users proved to be the best problem solvers followed by non-conscious VOTAT strategy users and non-VOTAT strategy users. In the primary school sub-sample, six qualitatively different strategy class profiles were distinguished. The results shed new light on and provide a new interpretation of previous analyses of the processes involved in complex problem solving. They also highlight the importance of explicit enhancement of problem-solving skills and problem-solving strategies as a tool for knowledge acquisition in new contexts during and beyond school lessons. PMID:29593606

Practicing Professional Values: Factors Influencing Involvement in Social Work Student Organizations

Science.gov (United States)

Martindale, Dorothy; Olate, René; Anderson, Keith A.

2017-01-01

One of the most promising avenues for the development of professional values is involvement in professional student organizations. A convenience sample of baccalaureate social work students (n = 482) was drawn from 15 institutions. Regression analyses revealed several predictors of involvement in social work student organizations, including…

Collaborative Learning with Web 2.0 Tools: Analysing Malaysian Students' Perceptions and Peer Interaction

Science.gov (United States)

Leow, Fui Theng; Neo, Mai

2015-01-01

Today, ICT, web resources and multimedia contents have become prevalent in Malaysian university classrooms; hence, the learning approaches need to be redesigned for enabling students to use these technologies in co-constructing new meaning. This study analyses student's perception and their peer interaction in the constructivist-collaborative…

Understanding the Greenhouse Effect by Embodiment - Analysing and Using Students' and Scientists' Conceptual Resources

Science.gov (United States)

Niebert, Kai; Gropengießer, Harald

2014-01-01

Over the last 20 years, science education studies have reported that there are very different understandings among students of science regarding the key aspects of climate change. We used the cognitive linguistic framework of experientialism to shed new light on this valuable pool of studies to identify the conceptual resources of understanding climate change. In our study, we interviewed 35 secondary school students on their understanding of the greenhouse effect and analysed the conceptions of climate scientists as drawn from textbooks and research reports. We analysed all data by metaphor analysis and qualitative content analysis to gain insight into students' and scientists' resources for understanding. In our analysis, we found that students and scientists refer to the same schemata to understand the greenhouse effect. We categorised their conceptions into three different principles the conceptions are based on: warming by more input, warming by less output, and warming by a new equilibrium. By interrelating students' and scientists' conceptions, we identified the students' learning demand: First, our students were afforded with experiences regarding the interactions of electromagnetic radiation and CO2. Second, our students reflected about the experience-based schemata they use as source domains for metaphorical understanding of the greenhouse effect. By uncovering the-mostly unconscious-deployed schemata, we gave students access to their source domains. We implemented these teaching guidelines in interventions and evaluated them in teaching experiments to develop evidence-based and theory-guided learning activities on the greenhouse effect.

Corporal Punishment and Student Outcomes in Rural Schools

Science.gov (United States)

Han, Seunghee

2014-01-01

This study examined the effects of corporal punishment on student outcomes in rural schools by analyzing 1,067 samples from the School Survey on Crime and Safety 2007-2008. Results of descriptive statistics and multivariate regression analyses indicated that schools with corporal punishment may decrease students' violent behaviors and…

Life Satisfaction and Violent Behaviors among Middle School Students

Science.gov (United States)

Valois, Robert F.; Paxton, Raheem J.; Zullig, Keith J.; Huebner, E. Scott

2006-01-01

We explored relationships between violent behaviors and perceived life satisfaction among 2,138 middle school students in a southern state using the CDC Middle School Youth Risk Behavior Survey (MSYRBS) and the Brief Multidimensional Student Life Satisfaction Scale (BMSLSS). Logistic regression analyses and multivariate models constructed…

Teacher Interviews, Student Interviews, and Classroom Observations in Combinatorics: Four Analyses

Science.gov (United States)

Caddle, Mary C.

2012-01-01

This research consists of teacher interviews, student interviews, and classroom observations, all based around the mathematical content area of combinatorics. Combinatorics is a part of discrete mathematics concerning the ordering and grouping of distinct elements. The data are used in four separate analyses. The first provides evidence that…

Deaf college students' mathematical skills relative to morphological knowledge, reading level, and language proficiency.

Science.gov (United States)

Kelly, Ronald R; Gaustad, Martha G

2007-01-01

This study of deaf college students examined specific relationships between their mathematics performance and their assessed skills in reading, language, and English morphology. Simple regression analyses showed that deaf college students' language proficiency scores, reading grade level, and morphological knowledge regarding word segmentation and meaning were all significantly correlated with both the ACT Mathematics Subtest and National Technical Institute for the Deaf (NTID) Mathematics Placement Test scores. Multiple regression analyses identified the best combination from among these potential independent predictors of students' performance on both the ACT and NTID mathematics tests. Additionally, the participating deaf students' grades in their college mathematics courses were significantly and positively associated with their reading grade level and their knowledge of morphological components of words.

Pennsylvania Academic Libraries and Student Retention and Graduation: A Preliminary Investigation with Confusing Results

Directory of Open Access Journals (Sweden)

Gregory A. Crawford

2014-11-01

Full Text Available This study examined the relationships between specific institutional financial variables and two library-related variables on graduation and retention rates for colleges and universities through correlations and multiple regression analysis. The analyses used data for Pennsylvania colleges and universities that were extracted from the Integrated Postsecondary Educational Data System (IPEDS and the Academic Libraries Survey (ALS.  All analyses were run using IBM SPSS software. The correlations showed that both library expenses per student and library use per student were significantly correlated with both graduation and retention rates. In contrast, the multiple regression results showed that neither library budgets nor library use had significant effects on either graduation rates or retention rates. As would be expected, instructional expenses per student had the highest correlation with both graduation and retention and also yielded the strongest coefficient in the resulting regression equations.

Regression Analysis and the Sociological Imagination

Science.gov (United States)

De Maio, Fernando

2014-01-01

Regression analysis is an important aspect of most introductory statistics courses in sociology but is often presented in contexts divorced from the central concerns that bring students into the discipline. Consequently, we present five lesson ideas that emerge from a regression analysis of income inequality and mortality in the USA and Canada.

Retention of community college students in online courses

Science.gov (United States)

Krajewski, Sarah

The issue of attrition in online courses at higher learning institutions remains a high priority in the United States. A recent rapid growth of online courses at community colleges has been instigated by student demand, as they meet the time constraints many nontraditional community college students have as a result of the need to work and care for dependents. Failure in an online course can cause students to become frustrated with the college experience, financially burdened, or to even give up and leave college. Attrition could be avoided by proper guidance of who is best suited for online courses. This study examined factors related to retention (i.e., course completion) and success (i.e., receiving a C or better) in an online biology course at a community college in the Midwest by operationalizing student characteristics (age, race, gender), student skills (whether or not the student met the criteria to be placed in an AFP course), and external factors (Pell recipient, full/part time status, first term) from the persistence model developed by Rovai. Internal factors from this model were not included in this study. Both univariate analyses and multivariate logistic regression were used to analyze the variables. Results suggest that race and Pell recipient were both predictive of course completion on univariate analyses. However, multivariate analyses showed that age, race, academic load and first term were predictive of completion and Pell recipient was no longer predictive. The univariate results for the C or better showed that age, race, Pell recipient, academic load, and meeting AFP criteria were predictive of success. Multivariate analyses showed that only age, race, and Pell recipient were significant predictors of success. Both regression models explained very little (<15%) of the variability within the outcome variables of retention and success. Therefore, although significant predictors were identified for course completion and retention, there are still

Analyses of Public Utility Building - Students Designs, Aimed at their Energy Efficiency Improvement

Science.gov (United States)

Wołoszyn, Marek Adam

2017-10-01

Public utility buildings are formally, structurally and functionally complex entities. Frequently, the process of their design involves the retroactive reconsideration of energy engineering issues, once a building concept has already been completed. At that stage, minor formal corrections are made along with the design of the external layer of the building in order to satisfy applicable standards. Architecture students do the same when designing assigned public utility buildings. In order to demonstrate energy-related defects of building designs developed by students, the conduct of analyses was proposed. The completed designs of public utility buildings were examined with regard to energy efficiency of the solutions they feature through the application of the following programs: Ecotect, Vasari, and in case of simpler analyses ArchiCad program extensions were sufficient.

Evaluating effects of developmental education for college students using a regression discontinuity design.

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Moss, Brian G; Yeaton, William H

2013-10-01

Annually, American colleges and universities provide developmental education (DE) to millions of underprepared students; however, evaluation estimates of DE benefits have been mixed. Using a prototypic exemplar of DE, our primary objective was to investigate the utility of a replicative evaluative framework for assessing program effectiveness. Within the context of the regression discontinuity (RD) design, this research examined the effectiveness of a DE program for five, sequential cohorts of first-time college students. Discontinuity estimates were generated for individual terms and cumulatively, across terms. Participants were 3,589 first-time community college students. DE program effects were measured by contrasting both college-level English grades and a dichotomous measure of pass/fail, for DE and non-DE students. Parametric and nonparametric estimates of overall effect were positive for continuous and dichotomous measures of achievement (grade and pass/fail). The variability of program effects over time was determined by tracking results within individual terms and cumulatively, across terms. Applying this replication strategy, DE's overall impact was modest (an effect size of approximately .20) but quite consistent, based on parametric and nonparametric estimation approaches. A meta-analysis of five RD results yielded virtually the same estimate as the overall, parametric findings. Subset analysis, though tentative, suggested that males benefited more than females, while academic gains were comparable for different ethnicities. The cumulative, within-study comparison, replication approach offers considerable potential for the evaluation of new and existing policies, particularly when effects are relatively small, as is often the case in applied settings.

and Multinomial Logistic Regression

African Journals Online (AJOL)

This work presented the results of an experimental comparison of two models: Multinomial Logistic Regression (MLR) and Artificial Neural Network (ANN) for classifying students based on their academic performance. The predictive accuracy for each model was measured by their average Classification Correct Rate (CCR).

Is Critical Thinking a Mediator Variable of Student Performance in School?

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Walter, Christel; Walter, Paul

2018-01-01

The study explores the influences of critical thinking and interests on students' performance at school. The tested students attended German grammar schools ("Gymnasien"). Separate regression analyses showed the expected moderate positive influences of critical thinking and interests on school performance. But analyzed simultaneously,…

Alcohol Use and Drinking Motives among Sanctioned and Nonsanctioned Students

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Doumas, Diana M.

2017-01-01

This study examined differences in the relationship of drinking motives to drinking behavior among sanctioned and nonsanctioned 1st-year students (N = 298). Results of hierarchical regression analyses indicated that for both sanctioned and nonsanctioned students, alcohol use was predicted by social and enhancement motives, and alcohol-related…

Analyses of Developmental Rate Isomorphy in Ectotherms: Introducing the Dirichlet Regression.

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David S Boukal

Full Text Available Temperature drives development in insects and other ectotherms because their metabolic rate and growth depends directly on thermal conditions. However, relative durations of successive ontogenetic stages often remain nearly constant across a substantial range of temperatures. This pattern, termed 'developmental rate isomorphy' (DRI in insects, appears to be widespread and reported departures from DRI are generally very small. We show that these conclusions may be due to the caveats hidden in the statistical methods currently used to study DRI. Because the DRI concept is inherently based on proportional data, we propose that Dirichlet regression applied to individual-level data is an appropriate statistical method to critically assess DRI. As a case study we analyze data on five aquatic and four terrestrial insect species. We find that results obtained by Dirichlet regression are consistent with DRI violation in at least eight of the studied species, although standard analysis detects significant departure from DRI in only four of them. Moreover, the departures from DRI detected by Dirichlet regression are consistently much larger than previously reported. The proposed framework can also be used to infer whether observed departures from DRI reflect life history adaptations to size- or stage-dependent effects of varying temperature. Our results indicate that the concept of DRI in insects and other ectotherms should be critically re-evaluated and put in a wider context, including the concept of 'equiproportional development' developed for copepods.

Item Response Theory Modeling and Categorical Regression Analyses of the Five-Factor Model Rating Form: A Study on Italian Community-Dwelling Adolescent Participants and Adult Participants.

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Fossati, Andrea; Widiger, Thomas A; Borroni, Serena; Maffei, Cesare; Somma, Antonella

2017-06-01

To extend the evidence on the reliability and construct validity of the Five-Factor Model Rating Form (FFMRF) in its self-report version, two independent samples of Italian participants, which were composed of 510 adolescent high school students and 457 community-dwelling adults, respectively, were administered the FFMRF in its Italian translation. Adolescent participants were also administered the Italian translation of the Borderline Personality Features Scale for Children-11 (BPFSC-11), whereas adult participants were administered the Italian translation of the Triarchic Psychopathy Measure (TriPM). Cronbach α values were consistent with previous findings; in both samples, average interitem r values indicated acceptable internal consistency for all FFMRF scales. A multidimensional graded item response theory model indicated that the majority of FFMRF items had adequate discrimination parameters; information indices supported the reliability of the FFMRF scales. Both categorical (i.e., item-level) and scale-level regression analyses suggested that the FFMRF scores may predict a nonnegligible amount of variance in the BPFSC-11 total score in adolescent participants, and in the TriPM scale scores in adult participants.

Beyond Depression and Suicide: The Mental Health of Transgender College Students

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Sara B. Oswalt

2017-02-01

Full Text Available Research studies examining the mental health of transgender individuals often focus on depression, anxiety, and suicidal ideation through the use of clinic samples. However, little is known about the emerging adult (18–26 years old transgender population and their mental health. The current study seeks to fill that gap by using a national dataset of college students (N = 547,727 to examine how transgender college students (n = 1143 differ from their cisgender peers regarding 12 different mental health conditions. Chi-square and regression analyses were conducted. Results demonstrate that transgender students have approximately twice the risk for most mental health conditions compared to female students. A notable exception is schizophrenia, in which transgender individuals have about seven times the risk compared to females. While these were significant findings, regression analyses indicate that being non-heterosexual is a greater predictor for mental health concerns. Implications for mental health practitioners at colleges and universities are discussed.

Deriving the Regression Line with Algebra

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Quintanilla, John A.

2017-01-01

Exploration with spreadsheets and reliance on previous skills can lead students to determine the line of best fit. To perform linear regression on a set of data, students in Algebra 2 (or, in principle, Algebra 1) do not have to settle for using the mysterious "black box" of their graphing calculators (or other classroom technologies).…

Comparison of Classical Linear Regression and Orthogonal Regression According to the Sum of Squares Perpendicular Distances

OpenAIRE

KELEŞ, Taliha; ALTUN, Murat

2016-01-01

Regression analysis is a statistical technique for investigating and modeling the relationship between variables. The purpose of this study was the trivial presentation of the equation for orthogonal regression (OR) and the comparison of classical linear regression (CLR) and OR techniques with respect to the sum of squared perpendicular distances. For that purpose, the analyses were shown by an example. It was found that the sum of squared perpendicular distances of OR is smaller. Thus, it wa...

Logistic regression models

CERN Document Server

Hilbe, Joseph M

2009-01-01

This book really does cover everything you ever wanted to know about logistic regression … with updates available on the author's website. Hilbe, a former national athletics champion, philosopher, and expert in astronomy, is a master at explaining statistical concepts and methods. Readers familiar with his other expository work will know what to expect-great clarity.The book provides considerable detail about all facets of logistic regression. No step of an argument is omitted so that the book will meet the needs of the reader who likes to see everything spelt out, while a person familiar with some of the topics has the option to skip "obvious" sections. The material has been thoroughly road-tested through classroom and web-based teaching. … The focus is on helping the reader to learn and understand logistic regression. The audience is not just students meeting the topic for the first time, but also experienced users. I believe the book really does meet the author's goal … .-Annette J. Dobson, Biometric...

Applied Regression Modeling A Business Approach

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Pardoe, Iain

2012-01-01

An applied and concise treatment of statistical regression techniques for business students and professionals who have little or no background in calculusRegression analysis is an invaluable statistical methodology in business settings and is vital to model the relationship between a response variable and one or more predictor variables, as well as the prediction of a response value given values of the predictors. In view of the inherent uncertainty of business processes, such as the volatility of consumer spending and the presence of market uncertainty, business professionals use regression a

Psychosocial predictors of breast self-examination behavior among female students: an application of the health belief model using logistic regression.

Science.gov (United States)

Didarloo, Alireza; Nabilou, Bahram; Khalkhali, Hamid Reza

2017-11-03

Breast cancer is a life-threatening condition affecting women around the world. The early detection of breast lumps using a breast self-examination (BSE) is important for the prevention and control of this disease. The aim of this study was to examine BSE behavior and its predictive factors among female university students using the Health Belief Model (HBM). This investigation was a cross-sectional survey carried out with 334 female students at Urmia University of Medical Sciences in the northwest of Iran. To collect the necessary data, researchers applied a valid and reliable three-part questionnaire. The data were analyzed using descriptive statistics and a chi-square test, in addition to multivariate logistic regression statistics in SPSS software version 16.0 (SPSS Inc., Chicago, IL, USA). The results indicated that 82 of the 334 participants (24.6%) reported practicing BSEs. Multivariate logistic regression analyses showed that high perceived severity [OR = 2.38, 95% CI = (1.02-5.54)], high perceived benefits [OR = 1.94, 95% CI = (1.09-3.46)], and high perceived self-efficacy [OR = 13.15, 95% CI = (3.64-47.51)] were better predictors of BSE behavior (P < 0.05) than low perceived severity, benefits, and self-efficacy. The findings also showed that a high level of knowledge compared to a low level of knowledge [OR = 5.51, 95% CI = (1.79-16.86)] and academic undergraduate and graduate degrees compared to doctoral degrees [OR = 2.90, 95% CI = (1.42-5.92)] of the participants were predictors of BSE performance (P < 0.05). The study revealed that the HBM constructs are able to predict BSE behavior. Among these constructs, self-efficacy was the most important predictor of the behavior. Interventions based on the constructs of perceived self-efficacy, benefits, and severity are recommended for increasing women's regular screening for breast cancer.

Improved Dietary Guidelines for Vitamin D: Application of Individual Participant Data (IPD)-Level Meta-Regression Analyses

Science.gov (United States)

Cashman, Kevin D.; Ritz, Christian; Kiely, Mairead

2017-01-01

Dietary Reference Values (DRVs) for vitamin D have a key role in the prevention of vitamin D deficiency. However, despite adopting similar risk assessment protocols, estimates from authoritative agencies over the last 6 years have been diverse. This may have arisen from diverse approaches to data analysis. Modelling strategies for pooling of individual subject data from cognate vitamin D randomized controlled trials (RCTs) are likely to provide the most appropriate DRV estimates. Thus, the objective of the present work was to undertake the first-ever individual participant data (IPD)-level meta-regression, which is increasingly recognized as best practice, from seven winter-based RCTs (with 882 participants ranging in age from 4 to 90 years) of the vitamin D intake–serum 25-hydroxyvitamin D (25(OH)D) dose-response. Our IPD-derived estimates of vitamin D intakes required to maintain 97.5% of 25(OH)D concentrations >25, 30, and 50 nmol/L across the population are 10, 13, and 26 µg/day, respectively. In contrast, standard meta-regression analyses with aggregate data (as used by several agencies in recent years) from the same RCTs estimated that a vitamin D intake requirement of 14 µg/day would maintain 97.5% of 25(OH)D >50 nmol/L. These first IPD-derived estimates offer improved dietary recommendations for vitamin D because the underpinning modeling captures the between-person variability in response of serum 25(OH)D to vitamin D intake. PMID:28481259

Improved Dietary Guidelines for Vitamin D: Application of Individual Participant Data (IPD-Level Meta-Regression Analyses

Directory of Open Access Journals (Sweden)

Kevin D. Cashman

2017-05-01

Full Text Available Dietary Reference Values (DRVs for vitamin D have a key role in the prevention of vitamin D deficiency. However, despite adopting similar risk assessment protocols, estimates from authoritative agencies over the last 6 years have been diverse. This may have arisen from diverse approaches to data analysis. Modelling strategies for pooling of individual subject data from cognate vitamin D randomized controlled trials (RCTs are likely to provide the most appropriate DRV estimates. Thus, the objective of the present work was to undertake the first-ever individual participant data (IPD-level meta-regression, which is increasingly recognized as best practice, from seven winter-based RCTs (with 882 participants ranging in age from 4 to 90 years of the vitamin D intake–serum 25-hydroxyvitamin D (25(OHD dose-response. Our IPD-derived estimates of vitamin D intakes required to maintain 97.5% of 25(OHD concentrations >25, 30, and 50 nmol/L across the population are 10, 13, and 26 µg/day, respectively. In contrast, standard meta-regression analyses with aggregate data (as used by several agencies in recent years from the same RCTs estimated that a vitamin D intake requirement of 14 µg/day would maintain 97.5% of 25(OHD >50 nmol/L. These first IPD-derived estimates offer improved dietary recommendations for vitamin D because the underpinning modeling captures the between-person variability in response of serum 25(OHD to vitamin D intake.

Predicting stress in pre-registration nursing students.

Science.gov (United States)

Pryjmachuk, Steven; Richards, David A

2007-02-01

To determine which variables from a pool of potential predictors predict General Health Questionnaire 'caseness' in pre-registration nursing students. Cross-sectional survey, utilizing self-report measures of sources of stress, stress (psychological distress) and coping, together with pertinent demographic measures such as sex, ethnicity, educational programme and nursing specialty being pursued, and age, social class and highest qualifications on entry to the programme. Questionnaire packs were distributed to all pre-registration nursing students (N=1,362) in a large English university. Completed packs were coded, entered into statistical software and subjected to a series of logistic regression analyses. Of the questionnaire packs 1,005 (74%) were returned, of which up to 973 were available for the regression analyses undertaken. Four logistic regression models were considered and, on the principle of parsimony, a single model was chosen for discussion. This model suggested that the key predictors of caseness in the population studied were self-report of pressure, whether or not respondents had children (specifically, whether these children were pre-school or school-age), scores on a 'personal problems' scale and the type of coping employed. The overall caseness rate among the population was around one-third. Since self-report and personal, rather than academic, concerns predict stress, personal teachers need to play a key role in supporting students through 'active listening', especially when students self-report high levels of stress and where personal/social problems are evident. The work-life balance of students, especially those with child-care responsibilities, should be a central tenet in curriculum design in nurse education (and, indeed, the education of other professional and occupational groups). There may be some benefit in offering stress management (coping skills) training to nursing students and, indeed, students of other disciplines.

Predicting South Korean University Students' Happiness through Social Support and Efficacy Beliefs

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Lee, Diane Sookyoung; Padilla, Amado M.

2016-01-01

This study investigated the adversity and coping experiences of 198 South Korean university students and takes a cultural lens in understanding how social and individual factors shape their happiness. Hierarchical linear regression analyses suggest that Korean students' perceptions of social support significantly predicted their happiness,…

Utilising "Low Tech" Analytical Frameworks to Analyse Dyslexic Caribbean Students' Classroom Narratives

Science.gov (United States)

Blackman, Stacey

2007-01-01

The cognitions of Caribbean students with dyslexia are explored as part of an embedded multiple case study approach to teaching and learning at two secondary schools on the island of Barbados. This exploration employed "low tech" approaches to analyse what pupils had said in interviews using a Miles and Huberman (1994) framework.…

Analysing inequalities in Germany a structured additive distributional regression approach

CERN Document Server

Silbersdorff, Alexander

2017-01-01

This book seeks new perspectives on the growing inequalities that our societies face, putting forward Structured Additive Distributional Regression as a means of statistical analysis that circumvents the common problem of analytical reduction to simple point estimators. This new approach allows the observed discrepancy between the individuals’ realities and the abstract representation of those realities to be explicitly taken into consideration using the arithmetic mean alone. In turn, the method is applied to the question of economic inequality in Germany.

The association between Colombian medical students' healthy personal habits and a positive attitude toward preventive counseling: cross-sectional analyses

Science.gov (United States)

Duperly, John; Lobelo, Felipe; Segura, Carolina; Sarmiento, Francisco; Herrera, Deisy; Sarmiento, Olga L; Frank, Erica

2009-01-01

Background Physician-delivered preventive counseling is important for the prevention and management of chronic diseases. Data from the U.S. indicates that medical students with healthy personal habits have a better attitude towards preventive counseling. However, this association and its correlates have not been addressed in rapidly urbanized settings where chronic disease prevention strategies constitute a top public health priority. This study examines the association between personal health practices and attitudes toward preventive counseling among first and fifth-year students from 8 medical schools in Bogotá, Colombia. Methods During 2006, a total of 661 first- and fifth-year medical students completed a culturally adapted Spanish version of the "Healthy Doctor = Healthy Patient" survey (response rate = 78%). Logistic regression analyses were used to assess the association between overall personal practices on physical activity, nutrition, weight control, smoking, alcohol use (main exposure variable) and student attitudes toward preventive counseling on these issues (main outcome variable), stratified by year of training and adjusting by gender and medical training-related factors (basic knowledge, perceived adequacy of training and perception of the school's promotion on each healthy habit). Results The median age and percentage of females for the first- and fifth-year students were 21 years and 59.5% and 25 years and 65%, respectively. After controlling for gender and medical training-related factors, consumption of ≥ 5 daily servings of fruits and/or vegetables, not being a smoker or binge drinker were associated with a positive attitude toward counseling on nutrition (OR = 4.71; CI = 1.6–14.1; p = 0.006 smoking (OR = 2.62; CI = 1.1–5.9; p = 0.022), and alcohol consumption (OR = 2.61; CI = 1.3–5.4; p = 0.009), respectively. Conclusion As for U.S. physician and medical students, a positive association was found between the personal health habits of

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

Science.gov (United States)

Haq, Muhammad Ahsan Ul

2016-12-01

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

Applied regression analysis a research tool

CERN Document Server

Pantula, Sastry; Dickey, David

1998-01-01

Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool. Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to...

The Role of Goal Importance in Predicting University Students' High Academic Performance

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Kyle, Vanessa A.; White, Katherine M.; Hyde, Melissa K.; Occhipinti, Stefano

2014-01-01

We examined goal importance, focusing on high, but not exclusive priority goals, in the theory of planned behaviour (TPB) to predict students' academic performance. At the beginning of semester, students in a psychology subject (N = 197) completed TPB and goal importance items for achieving a high grade. Regression analyses revealed partial…

A Simulation Investigation of Principal Component Regression.

Science.gov (United States)

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,…

An Excel Solver Exercise to Introduce Nonlinear Regression

Science.gov (United States)

Pinder, Jonathan P.

2013-01-01

Business students taking business analytics courses that have significant predictive modeling components, such as marketing research, data mining, forecasting, and advanced financial modeling, are introduced to nonlinear regression using application software that is a "black box" to the students. Thus, although correct models are…

Regression Analysis: Instructional Resource for Cost/Managerial Accounting

Science.gov (United States)

Stout, David E.

2015-01-01

This paper describes a classroom-tested instructional resource, grounded in principles of active learning and a constructivism, that embraces two primary objectives: "demystify" for accounting students technical material from statistics regarding ordinary least-squares (OLS) regression analysis--material that students may find obscure or…

Regression modeling of ground-water flow

Science.gov (United States)

Cooley, R.L.; Naff, R.L.

1985-01-01

Nonlinear multiple regression methods are developed to model and analyze groundwater flow systems. Complete descriptions of regression methodology as applied to groundwater flow models allow scientists and engineers engaged in flow modeling to apply the methods to a wide range of problems. Organization of the text proceeds from an introduction that discusses the general topic of groundwater flow modeling, to a review of basic statistics necessary to properly apply regression techniques, and then to the main topic: exposition and use of linear and nonlinear regression to model groundwater flow. Statistical procedures are given to analyze and use the regression models. A number of exercises and answers are included to exercise the student on nearly all the methods that are presented for modeling and statistical analysis. Three computer programs implement the more complex methods. These three are a general two-dimensional, steady-state regression model for flow in an anisotropic, heterogeneous porous medium, a program to calculate a measure of model nonlinearity with respect to the regression parameters, and a program to analyze model errors in computed dependent variables such as hydraulic head. (USGS)

Check-all-that-apply data analysed by Partial Least Squares regression

DEFF Research Database (Denmark)

Rinnan, Åsmund; Giacalone, Davide; Frøst, Michael Bom

2015-01-01

are analysed by multivariate techniques. CATA data can be analysed both by setting the CATA as the X and the Y. The former is the PLS-Discriminant Analysis (PLS-DA) version, while the latter is the ANOVA-PLS (A-PLS) version. We investigated the difference between these two approaches, concluding...

The Use of Nonparametric Kernel Regression Methods in Econometric Production Analysis

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard

and nonparametric estimations of production functions in order to evaluate the optimal firm size. The second paper discusses the use of parametric and nonparametric regression methods to estimate panel data regression models. The third paper analyses production risk, price uncertainty, and farmers' risk preferences...... within a nonparametric panel data regression framework. The fourth paper analyses the technical efficiency of dairy farms with environmental output using nonparametric kernel regression in a semiparametric stochastic frontier analysis. The results provided in this PhD thesis show that nonparametric......This PhD thesis addresses one of the fundamental problems in applied econometric analysis, namely the econometric estimation of regression functions. The conventional approach to regression analysis is the parametric approach, which requires the researcher to specify the form of the regression...

Student Motivation in Low-Stakes Assessment Contexts: An Exploratory Analysis in Engineering Mechanics

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Musekamp, Frank; Pearce, Jacob

2016-01-01

The goal of this paper is to examine the relationship of student motivation and achievement in low-stakes assessment contexts. Using Pearson product-moment correlations and hierarchical linear regression modelling to analyse data on 794 tertiary students who undertook a low-stakes engineering mechanics assessment (along with the questionnaire of…

Detecting overdispersion in count data: A zero-inflated Poisson regression analysis

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Afiqah Muhamad Jamil, Siti; Asrul Affendi Abdullah, M.; Kek, Sie Long; Nor, Maria Elena; Mohamed, Maryati; Ismail, Norradihah

2017-09-01

This study focusing on analysing count data of butterflies communities in Jasin, Melaka. In analysing count dependent variable, the Poisson regression model has been known as a benchmark model for regression analysis. Continuing from the previous literature that used Poisson regression analysis, this study comprising the used of zero-inflated Poisson (ZIP) regression analysis to gain acute precision on analysing the count data of butterfly communities in Jasin, Melaka. On the other hands, Poisson regression should be abandoned in the favour of count data models, which are capable of taking into account the extra zeros explicitly. By far, one of the most popular models include ZIP regression model. The data of butterfly communities which had been called as the number of subjects in this study had been taken in Jasin, Melaka and consisted of 131 number of subjects visits Jasin, Melaka. Since the researchers are considering the number of subjects, this data set consists of five families of butterfly and represent the five variables involve in the analysis which are the types of subjects. Besides, the analysis of ZIP used the SAS procedure of overdispersion in analysing zeros value and the main purpose of continuing the previous study is to compare which models would be better than when exists zero values for the observation of the count data. The analysis used AIC, BIC and Voung test of 5% level significance in order to achieve the objectives. The finding indicates that there is a presence of over-dispersion in analysing zero value. The ZIP regression model is better than Poisson regression model when zero values exist.

Spelling Ability in College Students Predicted by Decoding, Print Exposure, and Vocabulary

Science.gov (United States)

Ocal, Turkan; Ehri, Linnea

2017-01-01

This study examines students' exposure to print, vocabulary and decoding as predictors of spelling skills. Participants were 42 college students (Mean age 22.5, SD = 7.87; 31 females and 11 males). Hierarchical regression analyses showed that most of the variance in spelling was explained by vocabulary knowledge. When vocabulary was entered first…

Internal Accountability and District Achievement: How Superintendents Affect Student Learning

Science.gov (United States)

Hough, Kimberly L.

2014-01-01

This quantitative survey study was designed to determine whether superintendent accountability behaviors or agreement about accountability behaviors between superintendents and their subordinate central office administrators predicted district student achievement. Hierarchical multiple regression and analyses of covariance were employed,…

Metacognitive awareness and math anxiety in gifted students

Directory of Open Access Journals (Sweden)

Hakan Sarıcam

2015-12-01

Full Text Available The basic purpose of this study has been to examine the relationships between metacognitive awareness and maths anxiety in gifted students. The second aim was to compare with gifted and non-gifted students’ metacognitive awareness and maths anxiety levels. The participants were 300 (150 gifted, 150 non-gifted volunteer secondary school students in Turkey. The mean age of the participants was 12.56 years ranging from 12 to 13 years. For gathering data, the Maths Anxiety Scale for Elementary School Students and The Metacognitive Awareness Inventory for Children were used. For analysing the data, Spearman correlation analysis, the Mann Whitney U test, and linear regression analysis were used. According to the findings: firstly, gifted students’ metacognitive awareness scores were higher than those of non-gifted students. On the other hand, non-gifted students’ maths anxiety levels were higher than those of gifted students. Secondly, there was negative correlation between metacognitive awareness and math anxiety. Finally, the findings of linear regression analysis indicated that metacognitive awareness is explained by 48% total variance of maths anxiety in gifted students.

Alpins and thibos vectorial astigmatism analyses: proposal of a linear regression model between methods

Directory of Open Access Journals (Sweden)

Giuliano de Oliveira Freitas

2013-10-01

Full Text Available PURPOSE: To determine linear regression models between Alpins descriptive indices and Thibos astigmatic power vectors (APV, assessing the validity and strength of such correlations. METHODS: This case series prospectively assessed 62 eyes of 31 consecutive cataract patients with preoperative corneal astigmatism between 0.75 and 2.50 diopters in both eyes. Patients were randomly assorted among two phacoemulsification groups: one assigned to receive AcrySof®Toric intraocular lens (IOL in both eyes and another assigned to have AcrySof Natural IOL associated with limbal relaxing incisions, also in both eyes. All patients were reevaluated postoperatively at 6 months, when refractive astigmatism analysis was performed using both Alpins and Thibos methods. The ratio between Thibos postoperative APV and preoperative APV (APVratio and its linear regression to Alpins percentage of success of astigmatic surgery, percentage of astigmatism corrected and percentage of astigmatism reduction at the intended axis were assessed. RESULTS: Significant negative correlation between the ratio of post- and preoperative Thibos APVratio and Alpins percentage of success (%Success was found (Spearman's ρ=-0.93; linear regression is given by the following equation: %Success = (-APVratio + 1.00x100. CONCLUSION: The linear regression we found between APVratio and %Success permits a validated mathematical inference concerning the overall success of astigmatic surgery.

Prejudice against international students: the role of threat perceptions and authoritarian dispositions in U.S. students.

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Charles-Toussaint, Gifflene C; Crowson, H Michael

2010-01-01

International students provide a variety of benefits to higher education institutions within the United States (J. J. Lee, 2007; J. J. Lee & C. Rice, 2007). Despite these benefits, many international students experience prejudice and discrimination by American students. The purpose of the present study was to examine several potential predictors of prejudice against international students: perceptions of international students as symbolic and realistic threats, right-wing authoritarianism, and social dominance orientation. A simultaneous regression analysis that the authors based on 188 students at a Southwestern university revealed that perceptions of symbolic and realistic threats and social dominance orientation were each positive and significant predictors of prejudice. Mediation analyses suggested that the effects of right-wing authoritarianism on prejudice is fully mediated through perceived symbolic threat and partially mediated by realistic threat.

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

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

2013-10-01

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

College Students' Grief and Coping Strategies in Bereavement and Separation

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Nakajima, Naomi; Kodama, Kenichi

2013-01-01

The purposes of this study are to clarify the characteristics of college students' bereavement and separation and the relationship between coping strategies and grief reactions in bereavement and separation. 212 college students completed questionnaires. The results indicated that the majority of the respondents have experienced some bereavement or separation, in particular, separation from the lover. Multiple regression analyses showed that coping strategies such as "avoidance", "abandonment...

Predicting Student Success in a Major's Introductory Biology Course via Logistic Regression Analysis of Scientific Reasoning Ability and Mathematics Scores

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Thompson, E. David; Bowling, Bethany V.; Markle, Ross E.

2018-02-01

Studies over the last 30 years have considered various factors related to student success in introductory biology courses. While much of the available literature suggests that the best predictors of success in a college course are prior college grade point average (GPA) and class attendance, faculty often require a valuable predictor of success in those courses wherein the majority of students are in the first semester and have no previous record of college GPA or attendance. In this study, we evaluated the efficacy of the ACT Mathematics subject exam and Lawson's Classroom Test of Scientific Reasoning in predicting success in a major's introductory biology course. A logistic regression was utilized to determine the effectiveness of a combination of scientific reasoning (SR) scores and ACT math (ACT-M) scores to predict student success. In summary, we found that the model—with both SR and ACT-M as significant predictors—could be an effective predictor of student success and thus could potentially be useful in practical decision making for the course, such as directing students to support services at an early point in the semester.

Grades, Gender, and Encouragement: A Regression Discontinuity Analysis

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Owen, Ann L.

2010-01-01

The author employs a regression discontinuity design to provide direct evidence on the effects of grades earned in economics principles classes on the decision to major in economics and finds a differential effect for male and female students. Specifically, for female students, receiving an A for a final grade in the first economics class is…

Ideal Teacher Behaviors: Student Motivation and Self-Efficacy Predict Preferences

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Komarraju, Meera

2013-01-01

Differences in students' academic self-efficacy and motivation were examined in predicting preferred teacher traits. Undergraduates (261) completed the Teaching Behavior Checklist, Academic Self-Concept scale, and Academic Motivation scale. Hierarchical regression analyses indicated that academic self-efficacy and extrinsic motivation explained…

Regression analysis for the social sciences

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Gordon, Rachel A

2010-01-01

The book provides graduate students in the social sciences with the basic skills that they need to estimate, interpret, present, and publish basic regression models using contemporary standards. Key features of the book include: interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature. thorough integration of teaching statistical theory with teaching data processing and analysis. teaching of both SAS and Stata "side-by-side" and use of chapter exercises in which students practice programming and interpretation on the same data set and course exercises in which students can choose their own research questions and data set.

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

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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

The more total cognitive load is reduced by cues, the better retention and transfer of multimedia learning: A meta-analysis and two meta-regression analyses.

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Xie, Heping; Wang, Fuxing; Hao, Yanbin; Chen, Jiaxue; An, Jing; Wang, Yuxin; Liu, Huashan

2017-01-01

Cueing facilitates retention and transfer of multimedia learning. From the perspective of cognitive load theory (CLT), cueing has a positive effect on learning outcomes because of the reduction in total cognitive load and avoidance of cognitive overload. However, this has not been systematically evaluated. Moreover, what remains ambiguous is the direct relationship between the cue-related cognitive load and learning outcomes. A meta-analysis and two subsequent meta-regression analyses were conducted to explore these issues. Subjective total cognitive load (SCL) and scores on a retention test and transfer test were selected as dependent variables. Through a systematic literature search, 32 eligible articles encompassing 3,597 participants were included in the SCL-related meta-analysis. Among them, 25 articles containing 2,910 participants were included in the retention-related meta-analysis and the following retention-related meta-regression, while there were 29 articles containing 3,204 participants included in the transfer-related meta-analysis and the transfer-related meta-regression. The meta-analysis revealed a statistically significant cueing effect on subjective ratings of cognitive load (d = -0.11, 95% CI = [-0.19, -0.02], p < 0.05), retention performance (d = 0.27, 95% CI = [0.08, 0.46], p < 0.01), and transfer performance (d = 0.34, 95% CI = [0.12, 0.56], p < 0.01). The subsequent meta-regression analyses showed that dSCL for cueing significantly predicted dretention for cueing (β = -0.70, 95% CI = [-1.02, -0.38], p < 0.001), as well as dtransfer for cueing (β = -0.60, 95% CI = [-0.92, -0.28], p < 0.001). Thus in line with CLT, adding cues in multimedia materials can indeed reduce SCL and promote learning outcomes, and the more SCL is reduced by cues, the better retention and transfer of multimedia learning.

Predicting Word Reading Ability: A Quantile Regression Study

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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…

Ordinary Least Squares and Quantile Regression: An Inquiry-Based Learning Approach to a Comparison of Regression Methods

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Helmreich, James E.; Krog, K. Peter

2018-01-01

We present a short, inquiry-based learning course on concepts and methods underlying ordinary least squares (OLS), least absolute deviation (LAD), and quantile regression (QR). Students investigate squared, absolute, and weighted absolute distance functions (metrics) as location measures. Using differential calculus and properties of convex…

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

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

2013-01-01

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 fa...

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

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

2016-10-01

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

Students' approaches to medical school choice: relationship with students' characteristics and motivation.

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Wouters, Anouk; Croiset, Gerda; Schripsema, Nienke R; Cohen-Schotanus, Janke; Spaai, Gerard W G; Hulsman, Robert L; Kusurkar, Rashmi A

2017-06-12

The aim was to examine main reasons for students' medical school choice and their relationship with students' characteristics and motivation during the students' medical study. In this multisite cross-sectional study, all Year-1 and Year-4 students who had participated in a selection procedure in one of the three Dutch medical schools included in the study were invited to complete an online survey comprising personal data, their main reason for medical school choice and standard, validated questionnaires to measure their strength of motivation (Strength of Motivation for Medical School-Revised) and autonomous and controlled type of motivation (Academic Self-regulation Questionnaire). Four hundred seventy-eight students participated. We performed frequency analyses on the reasons for medical school choice and regression analyses and ANCOVAs to study their associations with students' characteristics and motivation during their medical study. Students indicated 'city' (Year-1: 24.7%, n=75 and Year-4: 36.0%, n=52) and 'selection procedure' (Year-1: 56.9%, n=173 and Year-4: 46.9%, n=68) as the main reasons for their medical school choice. The main reasons were associated with gender, age, being a first-generation university student, ethnic background and medical school, and no significant associations were found between the main reasons and the strength and type of motivation during the students' medical study. Most students had based their medical school choice on the selection procedure. If medical schools desire to achieve a good student-curriculum fit and attract a diverse student population aligning the selection procedure with the curriculum and taking into account various students' different approaches is important.

Bisphenol-A exposures and behavioural aberrations: median and linear spline and meta-regression analyses of 12 toxicity studies in rodents.

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Peluso, Marco E M; Munnia, Armelle; Ceppi, Marcello

2014-11-05

Exposures to bisphenol-A, a weak estrogenic chemical, largely used for the production of plastic containers, can affect the rodent behaviour. Thus, we examined the relationships between bisphenol-A and the anxiety-like behaviour, spatial skills, and aggressiveness, in 12 toxicity studies of rodent offspring from females orally exposed to bisphenol-A, while pregnant and/or lactating, by median and linear splines analyses. Subsequently, the meta-regression analysis was applied to quantify the behavioural changes. U-shaped, inverted U-shaped and J-shaped dose-response curves were found to describe the relationships between bisphenol-A with the behavioural outcomes. The occurrence of anxiogenic-like effects and spatial skill changes displayed U-shaped and inverted U-shaped curves, respectively, providing examples of effects that are observed at low-doses. Conversely, a J-dose-response relationship was observed for aggressiveness. When the proportion of rodents expressing certain traits or the time that they employed to manifest an attitude was analysed, the meta-regression indicated that a borderline significant increment of anxiogenic-like effects was present at low-doses regardless of sexes (β)=-0.8%, 95% C.I. -1.7/0.1, P=0.076, at ≤120 μg bisphenol-A. Whereas, only bisphenol-A-males exhibited a significant inhibition of spatial skills (β)=0.7%, 95% C.I. 0.2/1.2, P=0.004, at ≤100 μg/day. A significant increment of aggressiveness was observed in both the sexes (β)=67.9,C.I. 3.4, 172.5, P=0.038, at >4.0 μg. Then, bisphenol-A treatments significantly abrogated spatial learning and ability in males (Pbisphenol-A, e.g. ≤120 μg/day, were associated to behavioural aberrations in offspring. Copyright © 2014. Published by Elsevier Ireland Ltd.

Personality traits associated with intrinsic academic motivation in medical students.

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Tanaka, Masaaki; Mizuno, Kei; Fukuda, Sanae; Tajima, Seiki; Watanabe, Yasuyoshi

2009-04-01

Motivation is one of the most important psychological concepts in education and is related to academic outcomes in medical students. In this study, the relationships between personality traits and intrinsic academic motivation were examined in medical students. The study group consisted of 119 Year 2 medical students at Osaka City University Graduate School of Medicine. They completed questionnaires dealing with intrinsic academic motivation (the Intrinsic Motivation Scale toward Learning) and personality (the Temperament and Character Inventory [TCI]). On simple regression analyses, the TCI dimensions of persistence, self-directedness, co-operativeness and self-transcendence were positively associated with intrinsic academic motivation. On multiple regression analysis adjusted for age and gender, the TCI dimensions of persistence, self-directedness and self-transcendence were positively associated with intrinsic academic motivation. The temperament dimension of persistence and the character dimensions of self-directedness and self-transcendence are associated with intrinsic academic motivation in medical students.

Filipino students' reported parental socialization of academic achievement by socioeconomic group.

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Bernardo, Allan B I

2009-10-01

Academic achievement of students differs by socioeconomic group. Parents' socialization of academic achievement in their children was explored in self-reports of 241 students from two socioeconomic status (SES) groups in the Philippines, using a scale developed by Bempechat, et al. Students in the upper SES group had higher achievement than their peers in the middle SES group, but had lower scores on most dimensions of parental socialization of academic achievement. Regression analyses indicate that reported parental attempts to encourage more effort to achieve was associated with lower achievement in students with upper SES.

Regression analysis for the social sciences

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Gordon, Rachel A

2015-01-01

Provides graduate students in the social sciences with the basic skills they need to estimate, interpret, present, and publish basic regression models using contemporary standards. Key features of the book include: interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature. thorough integration of teaching statistical theory with teaching data processing and analysis. teaching of Stata and use of chapter exercises in which students practice programming and interpretation on the same data set. A separate set of exercises allows students to select a data set to apply the concepts learned in each chapter to a research question of interest to them, all updated for this edition.

South and North: DIF Analyses of University-Student Responses to the Emotional Skills and Competence Questionnaire

Directory of Open Access Journals (Sweden)

Bo Molander

2011-12-01

Full Text Available In a study of the Emotional Skills and Competence Questionnaire instrument (ESCQ; Takšić, 1998 three samples of university students from Balkan countries (Croatia, Serbia, and Slovenia were contrasted with two samples of university students from Nordic countries (Finland and Sweden. In total, 1978 students participated. Effects of country and gender were obtained from the ESCQ total scores, as well as from the subscale scores. The subsequent analyses of item bias, that is, differential item functioning (DIF, revealed a number of DIF items in pair wise comparisons of the samples, thus creating doubts about the fairness in comparing mean scores. Further analyses of the DIF items showed, however, that most of the item curve functions were uniform, and that effect sizes were low. It was also shown that the number of DIF items depended on which countries were compared. Spearman correlations between measures of number of DIF items and cultural values as measured by World Value Survey data were very high. Implications of these findings for future cross-cultural studies of the ESCQ instrument are discussed.

A Health Assessment Survey of Veteran Students: Utilizing a Community College-Veterans Affairs Medical Center Partnership.

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Misra-Hebert, Anita D; Santurri, Laura; DeChant, Richard; Watts, Brook; Sehgal, Ashwini R; Aron, David C

2015-10-01

To assess health status among student veterans at a community college utilizing a partnership between a Veterans Affairs Medical Center and a community college. Student veterans at Cuyahoga Community College in Cleveland, Ohio, in January to April 2013. A health assessment survey was sent to 978 veteran students. Descriptive analyses to assess prevalence of clinical diagnoses and health behaviors were performed. Logistic regression analyses were performed to assess for independent predictors of functional limitations. 204 students participated in the survey (21% response rate). Self-reported depression and unhealthy behaviors were high. Physical and emotional limitations (45% and 35%, respectively), and pain interfering with work (42%) were reported. Logistic regression analyses confirmed the independent association of self-reported depression with functional limitation (odds ratio [OR] = 3.3, 95% confidence interval [CI] 1.4-7.8, p statistic 0.72) and of post-traumatic stress disorder with pain interfering with work (OR 3.9, CI 1.1-13.6, p statistic 0.75). A health assessment survey identified priority areas to inform targeted health promotion for student veterans at a community college. A partnership between a Veterans Affairs Medical Center and a community college can be utilized to help understand the health needs of veteran students. Reprint & Copyright © 2015 Association of Military Surgeons of the U.S.

Probability of Corporal Punishment: Lack of Resources and Vulnerable Students

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Han, Seunghee

2011-01-01

The author examined corporal punishment practices in the United States based on data from 362 public school principals where corporal punishment is available. Results from multiple regression analyses show that schools with multiple student violence prevention programs and teacher training programs had fewer possibilities of use corporal…

Troubled Spirits: Prevalence and Predictors of Religious and Spiritual Concerns among University Students and Counseling Center Clients

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Johnson, Chad V.; Hayes, Jeffrey A.

2003-01-01

The authors conducted a study of 5,472 university students to identify the prevalence and predictors of religious and spiritual concerns. Approximately 25% of the sample reported considerable distress related to such concerns. Logistic regression analyses revealed that students with considerable distress related to religious or spiritual concerns…

Who Will Win?: Predicting the Presidential Election Using Linear Regression

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Lamb, John H.

2007-01-01

This article outlines a linear regression activity that engages learners, uses technology, and fosters cooperation. Students generated least-squares linear regression equations using TI-83 Plus[TM] graphing calculators, Microsoft[C] Excel, and paper-and-pencil calculations using derived normal equations to predict the 2004 presidential election.…

Classification and regression tree (CART) analyses of genomic signatures reveal sets of tetramers that discriminate temperature optima of archaea and bacteria

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Dyer, Betsey D.; Kahn, Michael J.; LeBlanc, Mark D.

2008-01-01

Classification and regression tree (CART) analysis was applied to genome-wide tetranucleotide frequencies (genomic signatures) of 195 archaea and bacteria. Although genomic signatures have typically been used to classify evolutionary divergence, in this study, convergent evolution was the focus. Temperature optima for most of the organisms examined could be distinguished by CART analyses of tetranucleotide frequencies. This suggests that pervasive (nonlinear) qualities of genomes may reflect certain environmental conditions (such as temperature) in which those genomes evolved. The predominant use of GAGA and AGGA as the discriminating tetramers in CART models suggests that purine-loading and codon biases of thermophiles may explain some of the results. PMID:19054742

Teaching the Concept of Breakdown Point in Simple Linear Regression.

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Chan, Wai-Sum

2001-01-01

Most introductory textbooks on simple linear regression analysis mention the fact that extreme data points have a great influence on ordinary least-squares regression estimation; however, not many textbooks provide a rigorous mathematical explanation of this phenomenon. Suggests a way to fill this gap by teaching students the concept of breakdown…

An Investigation of Students' Personality Traits and Attitudes toward Science

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Hong, Zuway-R.; Lin, Huann-shyang

2011-05-01

The purposes of this study were to validate an instrument of attitudes toward science and to investigate grade level, type of school, and gender differences in Taiwan's students' personality traits and attitudes toward science as well as predictors of attitudes toward science. Nine hundred and twenty-two elementary students and 1,954 secondary students completed the School Student Questionnaire in 2008. Factor analyses, correlation analyses, ANOVAs, and regressions were used to compare the similarities and differences among male and female students in different grade levels. The findings were as follows: female students had higher interest in science and made more contributions in teams than their male counterparts across all grade levels. As students advanced through school, student scores on the personality trait scales of Conscientiousness and Openness sharply declined; students' scores on Neuroticism dramatically increased. Elementary school and academic high school students had significantly higher total scores on interest in science than those of vocational high and junior high school students. Scores on the scales measuring the traits of Agreeableness, Extraversion, and Conscientiousness were the most significant predictors of students' attitudes toward science. Implications of these findings for classroom instruction are discussed.

Psychological Adaptation, Marital Satisfaction, and Academic Self-Efficacy of International Students

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Bulgan, Gökçe; Çiftçi, Ayse

2017-01-01

The authors investigated marital satisfaction and academic self-efficacy in relation to psychological adaptation (i.e., psychological well-being, life satisfaction) in a sample of 198 married international students. Results of multiple regression analyses indicated that marital satisfaction and academic self-efficacy accounted for 45.9% of…

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

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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…

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.

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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.

A Correlation of Community College Math Readiness and Student Success

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Brown, Jayna Nicole

Although traditional college students are more prepared for college-level math based on college admissions tests, little data have been collected on nontraditional adult learners. The purpose of this study was to investigate relationships between math placement tests and community college students' success in math courses and persistence to degree or certificate completion. Guided by Tinto's theory of departure and student retention, the research questions addressed relationships and predictability of math Computer-adaptive Placement Assessment and Support System (COMPASS) test scores and students' performance in math courses, persistence in college, and degree completion. After conducting correlation and regression analyses, no significant relationships were identified between COMPASS Math test scores and students' performance (n = 234) in math courses, persistence in college, or degree completion. However, independent t test and chi-squared analyses of the achievements of college students who tested into Basic Math (n = 138) vs. Introduction to Algebra (n = 96) yielded statistically significant differences in persistence (p = .039), degree completion (p college students' math competencies and degree achievement.

Augmenting Data with Published Results in Bayesian Linear Regression

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de Leeuw, Christiaan; Klugkist, Irene

2012-01-01

In most research, linear regression analyses are performed without taking into account published results (i.e., reported summary statistics) of similar previous studies. Although the prior density in Bayesian linear regression could accommodate such prior knowledge, formal models for doing so are absent from the literature. The goal of this…

Learning climate and feedback as predictors of dental students' self-determined motivation: The mediating role of basic psychological needs satisfaction.

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Orsini, C; Binnie, V; Wilson, S; Villegas, M J

2018-05-01

The aim of this study was to test the mediating role of the satisfaction of dental students' basic psychological needs of autonomy, competence and relatedness on the association between learning climate, feedback and student motivation. The latter was based on the self-determination theory's concepts of differentiation of autonomous motivation, controlled motivation and amotivation. A cross-sectional correlational study was conducted where 924 students completed self-reported questionnaires measuring motivation, perception of the learning climate, feedback and basic psychological needs satisfaction. Descriptive statistics, Cronbach's alpha scores and bivariate correlations were computed. Mediation of basic needs on each predictor-outcome association was tested based on a series of regression analyses. Finally, all variables were integrated into one structural equation model, controlling for the effects of age, gender and year of study. Cronbach's alpha scores were acceptable (.655 to .905). Correlation analyses showed positive and significant associations between both an autonomy-supportive learning climate and the quantity and quality of feedback received, and students' autonomous motivation, which decreased and became negative when correlated with controlled motivation and amotivation, respectively. Regression analyses revealed that these associations were indirect and mediated by how these predictors satisfied students' basic psychological needs. These results were corroborated by the structural equation analysis, in which data fit the model well and regression paths were in the expected direction. An autonomy-supportive learning climate and the quantity and quality of feedback were positive predictors of students' autonomous motivation and negative predictors of amotivation. However, this was an indirect association mediated by the satisfaction of students' basic psychological needs. Consequently, supporting students' needs of autonomy, competence and

Acculturative Stress, Parental and Professor Attachment, and College Adjustment in Asian International Students

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Han, Suejung; Pistole, M. Carole; Caldwell, Jarred M.

2017-01-01

This study examined parental and professor attachment as buffers against acculturative stress and as predictors of college adjustment of 210 Asian international students (AISs). Moderated hierarchical regression analyses revealed that acculturative stress negatively and secure parental and professor attachment positively predicted academic…

The Effects of Home-School Dissonance on African American Male High School Students

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Brown-Wright, Lynda; Tyler, Kenneth Maurice

2010-01-01

The current study examined associations between home-school dissonance and several academic and psychological variables among 80 African American male high school students. Regression analyses revealed that home-school dissonance significantly predicted multiple academic and psychological variables, including amotivation, academic cheating,…

Better Autologistic Regression

Directory of Open Access Journals (Sweden)

Mark A. Wolters

2017-11-01

Full Text Available Autologistic regression is an important probability model for dichotomous random variables observed along with covariate information. It has been used in various fields for analyzing binary data possessing spatial or network structure. The model can be viewed as an extension of the autologistic model (also known as the Ising model, quadratic exponential binary distribution, or Boltzmann machine to include covariates. It can also be viewed as an extension of logistic regression to handle responses that are not independent. Not all authors use exactly the same form of the autologistic regression model. Variations of the model differ in two respects. First, the variable coding—the two numbers used to represent the two possible states of the variables—might differ. Common coding choices are (zero, one and (minus one, plus one. Second, the model might appear in either of two algebraic forms: a standard form, or a recently proposed centered form. Little attention has been paid to the effect of these differences, and the literature shows ambiguity about their importance. It is shown here that changes to either coding or centering in fact produce distinct, non-nested probability models. Theoretical results, numerical studies, and analysis of an ecological data set all show that the differences among the models can be large and practically significant. Understanding the nature of the differences and making appropriate modeling choices can lead to significantly improved autologistic regression analyses. The results strongly suggest that the standard model with plus/minus coding, which we call the symmetric autologistic model, is the most natural choice among the autologistic variants.

Using Communicative Action Theory to Analyse Relationships Between Supervisors and Phd Students in a Technical University in Sweden

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Michael Christie

2013-04-01

Full Text Available In this paper the authors use the theory of communicative action (Habermas, 1984-6 to analyse problematic relationships that can occur between supervisors and PhD students, between co-supervisors and between the students themselves. In a situation where power is distributed unequally, instrumental and strategic action on the part of either party can complicate and disturb efficacious relationships. We use Flanagan’s critical incident technique (Flanagan, 1954 to analyse twenty-five incidents that are told from a supervisor perspective and twentyfive from a PhD student perspective. The analysis reveals that a large proportion of incidents involved power struggles. Other categories include lack of professional or emotional support and poor communication. Rational dialogue based on Habermasian principles might have avoided many of these problems. The analysis concludes with some practical suggestions as to how the use of communicative action theory and critical incident technique can improve supervision, supervision training and the PhD process.

Comparing parametric and nonparametric regression methods for panel data

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard; Henningsen, Arne

We investigate and compare the suitability of parametric and non-parametric stochastic regression methods for analysing production technologies and the optimal firm size. Our theoretical analysis shows that the most commonly used functional forms in empirical production analysis, Cobb......-Douglas and Translog, are unsuitable for analysing the optimal firm size. We show that the Translog functional form implies an implausible linear relationship between the (logarithmic) firm size and the elasticity of scale, where the slope is artificially related to the substitutability between the inputs....... The practical applicability of the parametric and non-parametric regression methods is scrutinised and compared by an empirical example: we analyse the production technology and investigate the optimal size of Polish crop farms based on a firm-level balanced panel data set. A nonparametric specification test...

Differentiating regressed melanoma from regressed lichenoid keratosis.

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Chan, Aegean H; Shulman, Kenneth J; Lee, Bonnie A

2017-04-01

Distinguishing regressed lichen planus-like keratosis (LPLK) from regressed melanoma can be difficult on histopathologic examination, potentially resulting in mismanagement of patients. We aimed to identify histopathologic features by which regressed melanoma can be differentiated from regressed LPLK. Twenty actively inflamed LPLK, 12 LPLK with regression and 15 melanomas with regression were compared and evaluated by hematoxylin and eosin staining as well as Melan-A, microphthalmia transcription factor (MiTF) and cytokeratin (AE1/AE3) immunostaining. (1) A total of 40% of regressed melanomas showed complete or near complete loss of melanocytes within the epidermis with Melan-A and MiTF immunostaining, while 8% of regressed LPLK exhibited this finding. (2) Necrotic keratinocytes were seen in the epidermis in 33% regressed melanomas as opposed to all of the regressed LPLK. (3) A dense infiltrate of melanophages in the papillary dermis was seen in 40% of regressed melanomas, a feature not seen in regressed LPLK. In summary, our findings suggest that a complete or near complete loss of melanocytes within the epidermis strongly favors a regressed melanoma over a regressed LPLK. In addition, necrotic epidermal keratinocytes and the presence of a dense band-like distribution of dermal melanophages can be helpful in differentiating these lesions. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Factors Influencing Engineering Students' Decisions to Cheat by Type of Assessment

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Passow, Honor J.; Mayhew, Matthew J.; Finelli, Cynthia J.; Harding, Trevor S.; Carpenter, Donald D.

2006-01-01

Academic dishonesty (cheating) has been prevalent on college campuses for decades, and the percentage of students reporting cheating varies by college major. This study, based on a survey of 643 undergraduate engineering majors at 11 institutions, used two parallel hierarchical multiple regression analyses to predict the frequency of cheating on…

Exploring pre-service science teachers' pedagogical capacity for formative assessment through analyses of student answers

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Aydeniz, Mehmet; Dogan, Alev

2016-05-01

Background: There has been an increasing emphasis on empowering pre-service and in-service science teachers to attend student reasoning and use formative assessments to guide student learning in recent years. Purpose: The purpose of this study was to explore pre-service science teachers' pedagogical capacity for formative assessment. Sample: This study took place in Turkey. The participants include 53 pre-service science teachers in their final year of schooling. All but two of the participants are female. Design and methods: We used a mixed-methods methodology in pursing this inquiry. Participants analyzed 28 responses to seven two-tiered questions given by four students of different ability levels. We explored their ability to identify the strengths and weaknesses in students' answers. We paid particular attention to the things that the pre-service science teachers noticed in students' explanations, the types of inferences they made about students' conceptual understanding, and the affordances of pedagogical decisions they made. Results: The results show that the majority of participants made an evaluative judgment (i.e. the answer is correct or incorrect) in their analyses of students' answers. Similarly, the majority of the participants recognized the type of mistake that the students made. However, they failed to successfully elaborate on fallacies, limitations, or strengths in student reasoning. We also asked the participants to make pedagogical decisions related to what needs to be done next in order to help the students to achieve academic objectives. Results show that 8% of the recommended instructional strategies were of no affordance, 64% of low-affordance, and 28% were of high affordance in terms of helping students achieve the academic objectives. Conclusion: If our goal is to improve pre-service science teachers' noticing skills, and the affordance of feedback that they provide, engaging them in activities that asks them to attend to students' ideas

Which sociodemographic factors are important on smoking behaviour of high school students? The contribution of classification and regression tree methodology in a broad epidemiological survey.

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Ozge, C; Toros, F; Bayramkaya, E; Camdeviren, H; Sasmaz, T

2006-08-01

The purpose of this study is to evaluate the most important sociodemographic factors on smoking status of high school students using a broad randomised epidemiological survey. Using in-class, self administered questionnaire about their sociodemographic variables and smoking behaviour, a representative sample of total 3304 students of preparatory, 9th, 10th, and 11th grades, from 22 randomly selected schools of Mersin, were evaluated and discriminative factors have been determined using appropriate statistics. In addition to binary logistic regression analysis, the study evaluated combined effects of these factors using classification and regression tree methodology, as a new statistical method. The data showed that 38% of the students reported lifetime smoking and 16.9% of them reported current smoking with a male predominancy and increasing prevalence by age. Second hand smoking was reported at a 74.3% frequency with father predominance (56.6%). The significantly important factors that affect current smoking in these age groups were increased by household size, late birth rank, certain school types, low academic performance, increased second hand smoking, and stress (especially reported as separation from a close friend or because of violence at home). Classification and regression tree methodology showed the importance of some neglected sociodemographic factors with a good classification capacity. It was concluded that, as closely related with sociocultural factors, smoking was a common problem in this young population, generating important academic and social burden in youth life and with increasing data about this behaviour and using new statistical methods, effective coping strategies could be composed.

[Associations between dormitory environment/other factors and sleep quality of medical students].

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Zheng, Bang; Wang, Kailu; Pan, Ziqi; Li, Man; Pan, Yuting; Liu, Ting; Xu, Dan; Lyu, Jun

2016-03-01

To investigate the sleep quality and related factors among medical students in China, understand the association between dormitory environment and sleep quality, and provide evidence and recommendations for sleep hygiene intervention. A total of 555 undergraduate students were selected from a medical school of an university in Beijing through stratified-cluster random-sampling to conduct a questionnaire survey by using Chinese version of Pittsburgh Sleep Quality Index (PSQI) and self-designed questionnaire. Analyses were performed by using multiple logistic regression model as well as multilevel linear regression model. The prevalence of sleep disorder was 29.1%(149/512), and 39.1%(200/512) of the students reported that the sleep quality was influenced by dormitory environment. PSQI score was negatively correlated with self-reported rating of dormitory environment (γs=-0.310, Psleep disorder included grade, sleep regularity, self-rated health status, pressures of school work and employment, as well as dormitory environment. RESULTS of multilevel regression analysis also indicated that perception on dormitory environment (individual level) was associated with sleep quality with the dormitory level random effects under control (b=-0.619, Psleep disorder was high in medical students, which was associated with multiple factors. Dormitory environment should be taken into consideration when the interventions are taken to improve the sleep quality of students.

Reading Comprehension and Phonics Research: Review of Correlational Analyses with Deaf and Hard-of-Hearing Students

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Luft, Pamela

2018-01-01

This manuscript reviews 28 studies of reading research on deaf and hard-of-hearing (DHH) students published since 2000 that used correlational analyses. The examination focused on assessment issues affecting measurement and analysis of relationships between early phonological or orthographic skills and reading comprehension. Mixed outcomes…

The Role of Healthy Lifestyle in the Implementation of Regressing Suboptimal Health Status among College Students in China: A Nested Case-Control Study

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Jieyu Chen

2017-02-01

. Further analyses revealed a marked increase (average increased 14.73 points in lifestyle level among those SHS regression to health after 1.5 years, with respect to the HPLP-II behavioral dimensions, in addition to the total score (t = -15.34, p < 0.001. Conclusions: SHS is highly attributable to unhealthy lifestyles, and the Int. J. Environ. Res. Public Health 2017, 14, 240 2 of 17 mitigation of modifiable lifestyle risk factors may lead to SHS regression. Increased efforts to modify unhealthy lifestyles are necessary to prevent SHS.

Expectancy as a mediator of the relation between learning strategies and academic achievement among university students

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Shurbanovska Orhideja

2013-01-01

Full Text Available The aim of this study was to explore the mediation role of the expectancy component of motivation (self-efficacy and control beliefs for learning in the relationship between learning strategies (cognitive, meta-cognitive, resource management strategies and academic achievement. The sample consisted of 155 university students (85 psychology students and 70 architecture students. Learning strategies section from the MSLQ (Motivated Strategies for Learning Questionnaire was taken to assess the extent of learning strategies usage during exam preparation. Motivation for learning was measured by the Expectancy scale as a part of the Motivation section of the MSLQ. Mediation analysis was used for data processing. Following the proposed steps for mediation effect testing, a series of regression analyses was conducted: first, the expectancy component of motivation was regressed on learning strategies; second, academic achievement was regressed on learning strategies; and third, academic achievement was regressed on the expectancy component of motivation. It was found that learning strategies influence academic achievement indirectly through the expectancy component of motivation (Sobel test=2.18; p=.029. It is emphasized that students should be encouraged to use learning strategies in knowledge acquisition.

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

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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

Variable selection and model choice in geoadditive regression models.

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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.

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

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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 ...

Longitudinal changes in telomere length and associated genetic parameters in dairy cattle analysed using random regression models.

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Luise A Seeker

Full Text Available Telomeres cap the ends of linear chromosomes and shorten with age in many organisms. In humans short telomeres have been linked to morbidity and mortality. With the accumulation of longitudinal datasets the focus shifts from investigating telomere length (TL to exploring TL change within individuals over time. Some studies indicate that the speed of telomere attrition is predictive of future disease. The objectives of the present study were to 1 characterize the change in bovine relative leukocyte TL (RLTL across the lifetime in Holstein Friesian dairy cattle, 2 estimate genetic parameters of RLTL over time and 3 investigate the association of differences in individual RLTL profiles with productive lifespan. RLTL measurements were analysed using Legendre polynomials in a random regression model to describe TL profiles and genetic variance over age. The analyses were based on 1,328 repeated RLTL measurements of 308 female Holstein Friesian dairy cattle. A quadratic Legendre polynomial was fitted to the fixed effect of age in months and to the random effect of the animal identity. Changes in RLTL, heritability and within-trait genetic correlation along the age trajectory were calculated and illustrated. At a population level, the relationship between RLTL and age was described by a positive quadratic function. Individuals varied significantly regarding the direction and amount of RLTL change over life. The heritability of RLTL ranged from 0.36 to 0.47 (SE = 0.05-0.08 and remained statistically unchanged over time. The genetic correlation of RLTL at birth with measurements later in life decreased with the time interval between samplings from near unity to 0.69, indicating that TL later in life might be regulated by different genes than TL early in life. Even though animals differed in their RLTL profiles significantly, those differences were not correlated with productive lifespan (p = 0.954.

Effects of perceived social support and family demands on college students' mental well-being: A cross-cultural investigation

OpenAIRE

Khallad, Y.; Jabr, F.

2015-01-01

The effects of perceived social support and family demands on college students' mental well-being (perceived stress and depression) were assessed in 2 samples of Jordanian and Turkish college students. Statistically significant negative correlations were found between perceived support and mental well-being. Multiple regression analyses showed that perceived family support was a better predictor of mental well-being for Jordanian students, while perceived support from friends was a better pre...

A Cross-Cultural Analysis of Achievement and Social Goals among Chinese and Filipino Students

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King, Ronnel B.; Ganotice, Fraide A.; Watkins, David A.

2014-01-01

We examined how achievement (mastery and performance) and social goals (affiliation, approval, concern, and status) influenced various learning outcomes in two collectivist cultures. Filipino (n = 355) and Hong Kong Chinese (n = 697) secondary students answered the relevant questionnaires. Regression analyses using mastery, performance, and social…

Are learning strategies linked to academic performance among adolescents in two States in India? A tobit regression analysis.

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Areepattamannil, Shaljan

2014-01-01

The results of the fourth cycle of the Program for International Student Assessment (PISA) revealed that an unacceptably large number of adolescent students in two states in India-Himachal Pradesh and Tamil Nadu-have failed to acquire basic skills in reading, mathematics, and science (Walker, 2011). Drawing on data from the PISA 2009 database and employing multivariate left-censored to bit regression as a data analytic strategy, the present study, therefore, examined whether or not the learning strategies-memorization, elaboration, and control strategies-of adolescent students in Himachal Pradesh (N = 1,616; Mean age = 15.81 years) and Tamil Nadu (N = 3,210; Mean age = 15.64 years) were linked to their performance on the PISA 2009 reading, mathematics, and science assessments. Tobit regression analyses, after accounting for student demographic characteristics, revealed that the self-reported use of control strategies was significantly positively associated with reading, mathematical, and scientific literacy of adolescents in Himachal Pradesh and Tamil Nadu. While the self-reported use of elaboration strategies was not significantly associated with reading literacy among adolescents in Himachal Pradesh and Tamil Nadu, it was significantly positively associated with mathematical literacy among adolescents in Himachal Pradesh and Tamil Nadu. Moreover, the self-reported use of elaboration strategies was significantly and positively linked to scientific literacy among adolescents in Himachal Pradesh alone. The self-reported use of memorization strategies was significantly negatively associated with reading, mathematical, and scientific literacy in Tamil Nadu, while it was significantly negatively associated with mathematical and scientific literacy alone in Himachal Pradesh. Implications of these findings are discussed.

Correcting for multivariate measurement error by regression calibration in meta-analyses of epidemiological studies.

NARCIS (Netherlands)

Kromhout, D.

2009-01-01

Within-person variability in measured values of multiple risk factors can bias their associations with disease. The multivariate regression calibration (RC) approach can correct for such measurement error and has been applied to studies in which true values or independent repeat measurements of the

Psychological Resources as Stress Buffers: Their Relationship to University Students' Anxiety and Depression

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McCarthy, Christopher J.; Fouladi, Rachel T.; Juncker, Brian D.; Matheny, Kenneth B.

2006-01-01

The association of protective resources, personality variables, life events, and gender with anxiety and depression was examined with university students. Building on regression analyses, a structural equation model was generated with good fit, indicating that with respect to both anxiety and depression, negative life events and coping resources…

Examining the Effects of Perceived Relevance and Work-Related Subjective Well-Being on Individual Performance for Co-Op Students

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Drewery, Dave; Pretti, T. Judene; Barclay, Sage

2016-01-01

The purpose of this study was to examine the relationships between co-op students' perceived relevance of their work term, work-related subjective well-being (SWB), and individual performance at work. Data were collected using a survey of co-op students (n = 1,989) upon completion of a work term. Results of regression analyses testing a…

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

Science.gov (United States)

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

2017-01-01

We performed a secondary analysis of Adolescent Health Risk Behavior Survey data (N=937), examining associations between lifetime alcohol and marijuana use with intrapersonal (i.e., risk perceptions) and interpersonal (e.g., peer approval and behavior) factors. Multinomial and binary logistic regression analyses contend students reporting lifetime…

Measurement Error in Education and Growth Regressions

NARCIS (Netherlands)

Portela, M.; Teulings, C.N.; Alessie, R.

The perpetual inventory method used for the construction of education data per country leads to systematic measurement error. This paper analyses the effect of this measurement error on GDP regressions. There is a systematic difference in the education level between census data and observations

Measurement error in education and growth regressions

NARCIS (Netherlands)

Portela, Miguel; Teulings, Coen; Alessie, R.

2004-01-01

The perpetual inventory method used for the construction of education data per country leads to systematic measurement error. This paper analyses the effect of this measurement error on GDP regressions. There is a systematic difference in the education level between census data and observations

Logistic regression a self-learning text

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Kleinbaum, David G

1994-01-01

This textbook provides students and professionals in the health sciences with a presentation of the use of logistic regression in research. The text is self-contained, and designed to be used both in class or as a tool for self-study. It arises from the author's many years of experience teaching this material and the notes on which it is based have been extensively used throughout the world.

Comparison between Linear and Nonlinear Regression in a Laboratory Heat Transfer Experiment

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Gonçalves, Carine Messias; Schwaab, Marcio; Pinto, José Carlos

2013-01-01

In order to interpret laboratory experimental data, undergraduate students are used to perform linear regression through linearized versions of nonlinear models. However, the use of linearized models can lead to statistically biased parameter estimates. Even so, it is not an easy task to introduce nonlinear regression and show for the students…

Role of the Big Five Personality Traits in Predicting College Students' Academic Motivation and Achievement

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Komarraju, Meera; Karau, Steven J.; Schmeck, Ronald R.

2009-01-01

College students (308 undergraduates) completed the Five Factor Inventory and the Academic Motivations Scale, and reported their college grade point average (GPA). A correlation analysis revealed an interesting pattern of significant relationships. Further, regression analyses indicated that conscientiousness and openness explained 17% of the…

Principal component regression for crop yield estimation

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Suryanarayana, T M V

2016-01-01

This book highlights the estimation of crop yield in Central Gujarat, especially with regard to the development of Multiple Regression Models and Principal Component Regression (PCR) models using climatological parameters as independent variables and crop yield as a dependent variable. It subsequently compares the multiple linear regression (MLR) and PCR results, and discusses the significance of PCR for crop yield estimation. In this context, the book also covers Principal Component Analysis (PCA), a statistical procedure used to reduce a number of correlated variables into a smaller number of uncorrelated variables called principal components (PC). This book will be helpful to the students and researchers, starting their works on climate and agriculture, mainly focussing on estimation models. The flow of chapters takes the readers in a smooth path, in understanding climate and weather and impact of climate change, and gradually proceeds towards downscaling techniques and then finally towards development of ...

Factors affecting Korean nursing student empowerment in clinical practice.

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Ahn, Yang-Heui; Choi, Jihea

2015-12-01

Understanding the phenomenon of nursing student empowerment in clinical practice is important. Investigating the cognition of empowerment and identifying predictors are necessary to enhance nursing student empowerment in clinical practice. To identify empowerment predictors for Korean nursing students in clinical practice based on studies by Bradbury-Jones et al. and Spreitzer. A cross-sectional design was used for this study. This study was performed in three nursing colleges in Korea, all of which had similar baccalaureate nursing curricula. Three hundred seven junior or senior nursing students completed a survey designed to measure factors that were hypothesized to influence nursing student empowerment in clinical practice. Data were collected from November to December 2011. Study variables included self-esteem, clinical decision making, being valued as a learner, satisfaction regarding practice with a team member, perception on professor/instructor/clinical preceptor attitude, and total number of clinical practice fields. Data were analyzed using stepwise multiple regression analyses. All of the hypothesized study variables were significantly correlated to nursing student empowerment. Stepwise multiple regression analysis revealed that clinical decision making in nursing (t=7.59, pempowerment in clinical practice will be possible by using educational strategies to improve nursing student clinical decision making. Simultaneously, attitudes of nurse educators are also important to ensure that nursing students are treated as valued learners and to increase student self-esteem in clinical practice. Finally, diverse clinical practice field environments should be considered to enhance experience. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

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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

What Are the Odds of that? A Primer on Understanding Logistic Regression

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Huang, Francis L.; Moon, Tonya R.

2013-01-01

The purpose of this Methodological Brief is to present a brief primer on logistic regression, a commonly used technique when modeling dichotomous outcomes. Using data from the National Education Longitudinal Study of 1988 (NELS:88), logistic regression techniques were used to investigate student-level variables in eighth grade (i.e., enrolled in a…

Panel data specifications in nonparametric kernel regression

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard; Henningsen, Arne

parametric panel data estimators to analyse the production technology of Polish crop farms. The results of our nonparametric kernel regressions generally differ from the estimates of the parametric models but they only slightly depend on the choice of the kernel functions. Based on economic reasoning, we...

Racial Identity Attitudes and Ego Identity Statuses in Dominican and Puerto Rican College Students

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Sanchez, Delida

2013-01-01

This study explored the relation between racial identity attitudes and ego identity statuses in 94 Dominican and Puerto Rican Latino college students in an urban public college setting. Simultaneous regression analyses were conducted to test the relation between racial identity attitudes and ego identity statuses, and findings indicated that…

Managing Perceived Stress among College Students: The Roles of Social Support and Dysfunctional Coping

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Chao, Ruth Chu-Lien

2012-01-01

The author examined the conditions (i.e., social support and dysfunctional coping) under which perceived stress predicted psychological well-being in 459 college students. Hierarchical regression analyses indicated a significant 2-way interaction (Perceived Stress x Social Support) and a significant 3-way interaction (Perceived Stress x Social…

Family and Cultural Predictors of Depression among Samoan American Middle and High School Students

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Yeh, Christine J.; Borrero, Noah E.; Tito, Patsy

2013-01-01

This study investigated family intergenerational conflict and collective self-esteem as predictors of depression in a sample of 128 Samoan middle and high school students. Simultaneous regression analyses revealed that each independent variable significantly contributed to an overall model that accounted for 13% of the variance in depression.…

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

Science.gov (United States)

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

2017-12-01

We performed a secondary analysis of Adolescent Health Risk Behavior Survey data ( N = 937), examining associations between lifetime alcohol and marijuana use with intrapersonal (i.e., risk perceptions) and interpersonal (e.g., peer approval and behavior) factors. Multinomial and binary logistic regression analyses contend students reporting lifetime alcohol use-compared to students who had never used alcohol or marijuana-perceived lower alcohol risk ( p academic performance decreased the risk of lifetime alcohol and marijuana use ( p = .043). Findings are beneficial to school nurses with students experiencing effects associated with substance use.

Retro-regression--another important multivariate regression improvement.

Science.gov (United States)

Randić, M

2001-01-01

We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.

Modified Regression Correlation Coefficient for Poisson Regression Model

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Kaengthong, Nattacha; Domthong, Uthumporn

2017-09-01

This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

Development of the Exams Data Analysis Spreadsheet as a Tool to Help Instructors Conduct Customizable Analyses of Student ACS Exam Data

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Brandriet, Alexandra; Holme, Thomas

2015-01-01

The American Chemical Society Examinations Institute (ACS-EI) has recently developed the Exams Data Analysis Spread (EDAS) as a tool to help instructors conduct customizable analyses of their student data from ACS exams. The EDAS calculations allow instructors to analyze their students' performances both at the total score and individual item…

SPECIFICS OF THE APPLICATIONS OF MULTIPLE REGRESSION MODEL IN THE ANALYSES OF THE EFFECTS OF GLOBAL FINANCIAL CRISES

Directory of Open Access Journals (Sweden)

Željko V. Račić

2010-12-01

Full Text Available This paper aims to present the specifics of the application of multiple linear regression model. The economic (financial crisis is analyzed in terms of gross domestic product which is in a function of the foreign trade balance (on one hand and the credit cards, i.e. indebtedness of the population on this basis (on the other hand, in the USA (from 1999. to 2008. We used the extended application model which shows how the analyst should run the whole development process of regression model. This process began with simple statistical features and the application of regression procedures, and ended with residual analysis, intended for the study of compatibility of data and model settings. This paper also analyzes the values of some standard statistics used in the selection of appropriate regression model. Testing of the model is carried out with the use of the Statistics PASW 17 program.

University Students' Knowledge Structures and Informal Reasoning on the Use of Genetically Modified Foods: Multidimensional Analyses

Science.gov (United States)

Wu, Ying-Tien

2013-01-01

This study aims to provide insights into the role of learners' knowledge structures about a socio-scientific issue (SSI) in their informal reasoning on the issue. A total of 42 non-science major university students' knowledge structures and informal reasoning were assessed with multidimensional analyses. With both qualitative and…

Predicting Dropouts of University Freshmen: A Logit Regression Analysis.

Science.gov (United States)

Lam, Y. L. Jack

1984-01-01

Stepwise discriminant analysis coupled with logit regression analysis of freshmen data from Brandon University (Manitoba) indicated that six tested variables drawn from research on university dropouts were useful in predicting attrition: student status, residence, financial sources, distance from home town, goal fulfillment, and satisfaction with…

Predicting the mental health of college students with psychological capital.

Science.gov (United States)

Selvaraj, Priscilla Rose; Bhat, Christine Suniti

2018-06-01

Behavioral health treatment is grounded in the medical model with language of deficits and problems, rather than resources and strengths. With developments in the field of positive psychology, re-focusing on well-being rather than illness is possible. The primary purpose of this study was to examine relationships and predictions that exist between levels of mental health in college students, i.e., flourishing, moderate mental health, and languishing, and psychological capital (PsyCap). For this cross-sectional, exploratory study survey method was used for data collection and for analyses of results a series of descriptive, correlation, ANOVA, and multiple regression analyses were done. Results indicated that developing positive psychological strengths such as hope, efficacy, resilience, and optimism (acronym HERO) within college students significantly increased their positive mental health. Based on the predictive nature of PsyCap, mental health professionals may engage more in creating programs incorporating PsyCap development intervention for college students. Implications for counseling and programmatic services for college students are presented along with suggestions for future research.

Are we hammering square pegs into round holes? An investigation of the meta-analyses of reading research with students who are d/Deaf or hard of hearing and students who are hearing.

Science.gov (United States)

Wang, Ye; Williams, Cheri

2014-01-01

In a qualitative meta-analysis, the researchers systematically reviewed qualitative and quantitative meta-analyses on reading research with PK-12 students published after the 2000 National Reading Panel (NRP) report. Eleven qualitative and 39 quantitative meta-analyses were reviewed examining reading research with typically developing hearing students, special education hearing students (including English Language Learners), and d/Deaf or hard of hearing (d/Dhh) students. Generally, the meta-analysis yielded findings similar to and corroborative of the NRP's. Contradictory results (e.g., regarding the role of rhyme awareness in reading outcomes) most often resulted from differing definitions of interventions and their measurements. The analysis provided evidence of several instructional approaches that support reading development. On the basis of the qualitative similarity hypothesis (Paul, 2010, 2012; Paul & Lee, 2010; Paul & Wang, 2012; Paul, Wang, & Williams, 2013), the researchers argue that these instructional strategies also should effectively support d/Dhh children's reading development.

An Exploration of Adlerian Lifestyle Themes and Alcohol-Related Behaviors among College Students

Science.gov (United States)

Lewis, Todd F.; Osborn, Cynthia J.

2004-01-01

The aim of this study was to investigate college student drinking through the lens of Adlerian theory. In a sample of 273 participants, multiple regression analyses confirmed that certain lifestyle themes were associated with alcohol-related behaviors and that men and women who engage in drinking differ in their convictions and goals as defined by…

Independent contrasts and PGLS regression estimators are equivalent.

Science.gov (United States)

Blomberg, Simon P; Lefevre, James G; Wells, Jessie A; Waterhouse, Mary

2012-05-01

We prove that the slope parameter of the ordinary least squares regression of phylogenetically independent contrasts (PICs) conducted through the origin is identical to the slope parameter of the method of generalized least squares (GLSs) regression under a Brownian motion model of evolution. This equivalence has several implications: 1. Understanding the structure of the linear model for GLS regression provides insight into when and why phylogeny is important in comparative studies. 2. The limitations of the PIC regression analysis are the same as the limitations of the GLS model. In particular, phylogenetic covariance applies only to the response variable in the regression and the explanatory variable should be regarded as fixed. Calculation of PICs for explanatory variables should be treated as a mathematical idiosyncrasy of the PIC regression algorithm. 3. Since the GLS estimator is the best linear unbiased estimator (BLUE), the slope parameter estimated using PICs is also BLUE. 4. If the slope is estimated using different branch lengths for the explanatory and response variables in the PIC algorithm, the estimator is no longer the BLUE, so this is not recommended. Finally, we discuss whether or not and how to accommodate phylogenetic covariance in regression analyses, particularly in relation to the problem of phylogenetic uncertainty. This discussion is from both frequentist and Bayesian perspectives.

Identifying predictors of physics item difficulty: A linear regression approach

Science.gov (United States)

Mesic, Vanes; Muratovic, Hasnija

2011-06-01

Large-scale assessments of student achievement in physics are often approached with an intention to discriminate students based on the attained level of their physics competencies. Therefore, for purposes of test design, it is important that items display an acceptable discriminatory behavior. To that end, it is recommended to avoid extraordinary difficult and very easy items. Knowing the factors that influence physics item difficulty makes it possible to model the item difficulty even before the first pilot study is conducted. Thus, by identifying predictors of physics item difficulty, we can improve the test-design process. Furthermore, we get additional qualitative feedback regarding the basic aspects of student cognitive achievement in physics that are directly responsible for the obtained, quantitative test results. In this study, we conducted a secondary analysis of data that came from two large-scale assessments of student physics achievement at the end of compulsory education in Bosnia and Herzegovina. Foremost, we explored the concept of “physics competence” and performed a content analysis of 123 physics items that were included within the above-mentioned assessments. Thereafter, an item database was created. Items were described by variables which reflect some basic cognitive aspects of physics competence. For each of the assessments, Rasch item difficulties were calculated in separate analyses. In order to make the item difficulties from different assessments comparable, a virtual test equating procedure had to be implemented. Finally, a regression model of physics item difficulty was created. It has been shown that 61.2% of item difficulty variance can be explained by factors which reflect the automaticity, complexity, and modality of the knowledge structure that is relevant for generating the most probable correct solution, as well as by the divergence of required thinking and interference effects between intuitive and formal physics knowledge

Identifying predictors of physics item difficulty: A linear regression approach

Directory of Open Access Journals (Sweden)

Hasnija Muratovic

2011-06-01

Full Text Available Large-scale assessments of student achievement in physics are often approached with an intention to discriminate students based on the attained level of their physics competencies. Therefore, for purposes of test design, it is important that items display an acceptable discriminatory behavior. To that end, it is recommended to avoid extraordinary difficult and very easy items. Knowing the factors that influence physics item difficulty makes it possible to model the item difficulty even before the first pilot study is conducted. Thus, by identifying predictors of physics item difficulty, we can improve the test-design process. Furthermore, we get additional qualitative feedback regarding the basic aspects of student cognitive achievement in physics that are directly responsible for the obtained, quantitative test results. In this study, we conducted a secondary analysis of data that came from two large-scale assessments of student physics achievement at the end of compulsory education in Bosnia and Herzegovina. Foremost, we explored the concept of “physics competence” and performed a content analysis of 123 physics items that were included within the above-mentioned assessments. Thereafter, an item database was created. Items were described by variables which reflect some basic cognitive aspects of physics competence. For each of the assessments, Rasch item difficulties were calculated in separate analyses. In order to make the item difficulties from different assessments comparable, a virtual test equating procedure had to be implemented. Finally, a regression model of physics item difficulty was created. It has been shown that 61.2% of item difficulty variance can be explained by factors which reflect the automaticity, complexity, and modality of the knowledge structure that is relevant for generating the most probable correct solution, as well as by the divergence of required thinking and interference effects between intuitive and formal

Analyses of Student Learning in Global Change

Science.gov (United States)

Takle, E. S.; Moser, H.; Sorensen, E. K.

2004-12-01

The Global Change course at Iowa State University is a senior undergraduate and graduate level course that has been delivered over the internet with online dialog and learning activities since 1995. Students may enroll in the course as a distance education course, but in doing so they engage in dialog with students in the conventional on-campus face-to-face course. Online delivery and student participation offer opportunities for promoting use of critical thinking skills and collaborative learning not available in face-to-face environments. Students are required to research, post, and defend with authoritative information their positions on a variety of global change issues and specifically identify how they have demonstrated use of critical thinking skills in their online postings. Threaded dialog is used for structuring interactions toward promoting collaborative learning. We analyze collaborative learning by use of a rubric based on the theory of language games. By random selection of 1,350 online dialog comments posted over the last 10 years we evaluated student response to requirements for demonstrating critical thinking skills and collaboration in learning. We found that, by itself, the requirement of demonstrating critical thinking skills in online dialog was insufficient in promoting collaborative learned as measured by the standards of language game theory. But we also found that if an online comment clearly defines a situation and makes a clear expectation of a response, the likelihood is high that a game will be created. And if a game is established, there is a high probability that it will be closed, thereby giving evidence that collaborative learning had occurred. We conclude that a key component in collaborative online learning lies in establishing a lead-off comment that provides sufficient background information to clearly define an engaging situation. It also must include a clear expectation that a response is expected that will provide dialog

Logistic regression and multiple classification analyses to explore risk factors of under-5 mortality in bangladesh

International Nuclear Information System (INIS)

Bhowmik, K.R.; Islam, S.

2016-01-01

Logistic regression (LR) analysis is the most common statistical methodology to find out the determinants of childhood mortality. However, the significant predictors cannot be ranked according to their influence on the response variable. Multiple classification (MC) analysis can be applied to identify the significant predictors with a priority index which helps to rank the predictors. The main objective of the study is to find the socio-demographic determinants of childhood mortality at neonatal, post-neonatal, and post-infant period by fitting LR model as well as to rank those through MC analysis. The study is conducted using the data of Bangladesh Demographic and Health Survey 2007 where birth and death information of children were collected from their mothers. Three dichotomous response variables are constructed from children age at death to fit the LR and MC models. Socio-economic and demographic variables significantly associated with the response variables separately are considered in LR and MC analyses. Both the LR and MC models identified the same significant predictors for specific childhood mortality. For both the neonatal and child mortality, biological factors of children, regional settings, and parents socio-economic status are found as 1st, 2nd, and 3rd significant groups of predictors respectively. Mother education and household environment are detected as major significant predictors of post-neonatal mortality. This study shows that MC analysis with or without LR analysis can be applied to detect determinants with rank which help the policy makers taking initiatives on a priority basis. (author)

Sequence Modeling for Analysing Student Interaction with Educational Systems

DEFF Research Database (Denmark)

Hansen, Christian; Hansen, Casper; Hjuler, Niklas Oskar Daniel

2017-01-01

as exhibiting unproductive student behaviour. Based on our results this student representation is promising, especially for educational systems offering many different learning usages, and offers an alternative to common approaches like modelling student behaviour as a single Markov chain often done......The analysis of log data generated by online educational systems is an important task for improving the systems, and furthering our knowledge of how students learn. This paper uses previously unseen log data from Edulab, the largest provider of digital learning for mathematics in Denmark...

Prediction, Regression and Critical Realism

DEFF Research Database (Denmark)

Næss, Petter

2004-01-01

This paper considers the possibility of prediction in land use planning, and the use of statistical research methods in analyses of relationships between urban form and travel behaviour. Influential writers within the tradition of critical realism reject the possibility of predicting social...... phenomena. This position is fundamentally problematic to public planning. Without at least some ability to predict the likely consequences of different proposals, the justification for public sector intervention into market mechanisms will be frail. Statistical methods like regression analyses are commonly...... seen as necessary in order to identify aggregate level effects of policy measures, but are questioned by many advocates of critical realist ontology. Using research into the relationship between urban structure and travel as an example, the paper discusses relevant research methods and the kinds...

Dual Regression

OpenAIRE

Spady, Richard; Stouli, Sami

2012-01-01

We propose dual regression as an alternative to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the quantile regression process while avoiding the need for repairing the intersecting conditional quantile surfaces that quantile regression often produces in practice. Our approach introduces a mathematical programming characterization of conditional distribution f...

Intermediate and advanced topics in multilevel logistic regression analysis.

Science.gov (United States)

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.

[How medical students perform academically by admission types?].

Science.gov (United States)

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 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 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.

Heavy Episodic Drinking and Alcohol-Related Consequences: Sex-Specific Differences in Parental Influences among Ninth-Grade Students

Science.gov (United States)

Doumas, Diana M.; Hausheer, Robin; Esp, Susan

2015-01-01

Parents impact adolescent substance abuse, but sex-specific influences are not well-understood. This study examined parental influences on adolescent drinking behavior in a sample of ninth-grade students (N = 473). Hierarchical regression analyses indicated parental monitoring, disapproval of teen alcohol use, and quality of parent-teen general…

Regression Analyses on the Butterfly Ballot Effect: A Statistical Perspective of the US 2000 Election

Science.gov (United States)

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…

Increased prevalence of low back pain among physiotherapy students compared to medical students.

Science.gov (United States)

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.

A Demonstration of Regression False Positive Selection in Data Mining

Science.gov (United States)

Pinder, Jonathan P.

2014-01-01

Business analytics courses, such as marketing research, data mining, forecasting, and advanced financial modeling, have substantial predictive modeling components. The predictive modeling in these courses requires students to estimate and test many linear regressions. As a result, false positive variable selection ("type I errors") is…

Predictors of success of external cephalic version and cephalic presentation at birth among 1253 women with non-cephalic presentation using logistic regression and classification tree analyses.

Science.gov (United States)

Hutton, Eileen K; Simioni, Julia C; Thabane, Lehana

2017-08-01

Among women with a fetus with a non-cephalic presentation, external cephalic version (ECV) has been shown to reduce the rate of breech presentation at birth and cesarean birth. Compared with ECV at term, beginning ECV prior to 37 weeks' gestation decreases the number of infants in a non-cephalic presentation at birth. The purpose of this secondary analysis was to investigate factors associated with a successful ECV procedure and to present this in a clinically useful format. Data were collected as part of the Early ECV Pilot and Early ECV2 Trials, which randomized 1776 women with a fetus in breech presentation to either early ECV (34-36 weeks' gestation) or delayed ECV (at or after 37 weeks). The outcome of interest was successful ECV, defined as the fetus being in a cephalic presentation immediately following the procedure, as well as at the time of birth. The importance of several factors in predicting successful ECV was investigated using two statistical methods: logistic regression and classification and regression tree (CART) analyses. Among nulliparas, non-engagement of the presenting part and an easily palpable fetal head were independently associated with success. Among multiparas, non-engagement of the presenting part, gestation less than 37 weeks and an easily palpable fetal head were found to be independent predictors of success. These findings were consistent with results of the CART analyses. Regardless of parity, descent of the presenting part was the most discriminating factor in predicting successful ECV and cephalic presentation at birth. © 2017 Nordic Federation of Societies of Obstetrics and Gynecology.

Medical students' preparedness for professional activities in early clerkships.

Science.gov (United States)

Bosch, Josefin; Maaz, Asja; Hitzblech, Tanja; Holzhausen, Ylva; Peters, Harm

2017-08-22

Sufficient preparedness is important for transitions to workplace participation and learning in clinical settings. This study aims to analyse medical students' preparedness for early clerkships using a three-dimensional, socio-cognitive, theory-based model of preparedness anchored in specific professional activities and their supervision level. Medical students from a competency-based undergraduate curriculum were surveyed about preparedness for 21 professional activities and level of perceived supervision during their early clerkships via an online questionnaire. Preparedness was operationalized by the three dimensions of confidence to carry out clerkship activities, being prepared through university teaching and coping with failure by seeking support. Factors influencing preparedness and perceived stress as outcomes were analysed through step-wise regression. Professional activities carried out by the students (n = 147; 19.0%) and their supervision levels varied. While most students reported high confidence to perform the tasks, the activity-specific analysis revealed important gaps in preparation through university teaching. Students regularly searched for support in case of difficulty. One quarter of the variance of each preparedness dimension was explained by self-efficacy, supervision quality, amount of prior clerkship experience and nature of professional activities. Preparedness contributed to predicting perceived stress. The applied three-dimensional concept of preparedness and the task-specific approach provided a detailed and meaningful view on medical students' workplace participation and experiences in early clerkships.

Analyses of students' activity in the Internet social networks

Directory of Open Access Journals (Sweden)

Ermakov V.A.

2016-09-01

Full Text Available the article focuses on the empirical study of students' behavior in social networks; the study was conducted by statistical data analysis methods obtained by interviewing students.

A Multivariate Analysis of Personality, Values and Expectations as Correlates of Career Aspirations of Final Year Medical Students

Science.gov (United States)

Rogers, Mary E.; Searle, Judy; Creed, Peter A.; Ng, Shu-Kay

2010-01-01

This study reports on the career intentions of 179 final year medical students who completed an online survey that included measures of personality, values, professional and lifestyle expectations, and well-being. Logistic regression analyses identified the determinants of preferred medical specialty, practice location and hours of work.…

Geodesic least squares regression for scaling studies in magnetic confinement fusion

International Nuclear Information System (INIS)

Verdoolaege, Geert

2015-01-01

In regression analyses for deriving scaling laws that occur in various scientific disciplines, usually standard regression methods have been applied, of which ordinary least squares (OLS) is the most popular. However, concerns have been raised with respect to several assumptions underlying OLS in its application to scaling laws. We here discuss a new regression method that is robust in the presence of significant uncertainty on both the data and the regression model. The method, which we call geodesic least squares regression (GLS), is based on minimization of the Rao geodesic distance on a probabilistic manifold. We demonstrate the superiority of the method using synthetic data and we present an application to the scaling law for the power threshold for the transition to the high confinement regime in magnetic confinement fusion devices

A Simple and Convenient Method of Multiple Linear Regression to Calculate Iodine Molecular Constants

Science.gov (United States)

Cooper, Paul D.

2010-01-01

A new procedure using a student-friendly least-squares multiple linear-regression technique utilizing a function within Microsoft Excel is described that enables students to calculate molecular constants from the vibronic spectrum of iodine. This method is advantageous pedagogically as it calculates molecular constants for ground and excited…

Easy methods for extracting individual regression slopes: Comparing SPSS, R, and Excel

Directory of Open Access Journals (Sweden)

Roland Pfister

2013-10-01

Full Text Available Three different methods for extracting coefficientsof linear regression analyses are presented. The focus is on automatic and easy-to-use approaches for common statistical packages: SPSS, R, and MS Excel / LibreOffice Calc. Hands-on examples are included for each analysis, followed by a brief description of how a subsequent regression coefficient analysis is performed.

Predictors of Stress in College Students.

Science.gov (United States)

Saleh, Dalia; Camart, Nathalie; Romo, Lucia

2017-01-01

University students often face different stressful situations and preoccupations: the first contact with the university, the freedom of schedule organization, the selection of their master's degree, very selective fields, etc. The purpose of this study is to evaluate a model of vulnerability to stress in French college students. Stress factors were evaluated by a battery of six scales that was accessible online during 3 months. A total of 483 students, aged between 18 and 24 years (Mean = 20.23, standard deviation = 1.99), was included in the study. The results showed that 72.9, 86.3, and 79.3% of them were suffering from psychological distress, anxiety and depressive symptoms, respectively. More than half the sample was also suffering from low self-esteem (57.6%), little optimism (56.7%), and a low sense of self-efficacy (62.7%). Regression analyses revealed that life satisfaction, self-esteem, optimism, self-efficacy and psychological distress were the most important predictors of stress. These findings allow us to better understand stress-vulnerability factors in students and drive us to substantially consider them in prevention programs.

The analysis of nonstationary time series using regression, correlation and cointegration

DEFF Research Database (Denmark)

Johansen, Søren

2012-01-01

There are simple well-known conditions for the validity of regression and correlation as statistical tools. We analyse by examples the effect of nonstationarity on inference using these methods and compare them to model based inference using the cointegrated vector autoregressive model. Finally we...... analyse some monthly data from US on interest rates as an illustration of the methods...

The relationship between cultural individualism-collectivism and student aggression across 62 countries.

Science.gov (United States)

Bergmüller, Silvia

2013-01-01

This study examined the relationship between countries' dominant cultural values (i.e., individualism and collectivism) and (a) school principals' perceptions of aggressive student behavior and (b) students' self-reports of being aggressively victimized in school. Data on student aggression and victimization were collected across 62 countries in nationally representative samples of fourth and eighth graders (N = 428,566) and their principals (N = 15,043) by the Trends in International Mathematics and Science Study (TIMSS) 2007. Students were asked about three forms of aggressive victimization: physical, verbal, and relational; principals about two forms of aggressive student behavior: physical and verbal. Country-level regression analyses revealed that the level of cultural individualism, according to the individualism index (IDV) by Hofstede, Hofstede, and Minkov (2010), was not significantly related to either form of student-reported victimization. However, school principals reported aggressive student behavior more often the more individualist, and hence less collectivist, their country's culture. This relation was evident in the principals' reports on 4th and 8th grade students' aggressive behavior for both physical and verbal aggression. Multilevel analyses revealed that cultural individualism was still a powerful predictor of principal-reported aggressive student behavior after controlling for school and country characteristics. The discussion outlines reasons why principals' reports of aggressive student behavior are probably more valid indicators of student aggression than student self-reports of victimization, thereby supporting the hypothesis of culture-dependency of aggression. © 2013 Wiley Periodicals, Inc.

Regression: A Bibliography.

Science.gov (United States)

Pedrini, D. T.; Pedrini, Bonnie C.

Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…

A profile of students receiving counselling services at a university in post-apartheid South Africa.

Science.gov (United States)

Bowman, Brett; Payne, Jarrod

2011-12-01

The purpose of this study was to describe a profile of students seeking counselling at a racially diverse university in post-apartheid South Africa as a means to demonstrate the importance of routinely collecting and analysing student counselling data at university-based centres across the country. Student data were extracted from the only two counselling centres based at the University of the Witwatersrand in Johannesburg that provided services to 831 students during 2008. The 26 243 students that did not seek counselling during this period formed the comparison group. These data were analysed using logistic regression. Black, female and students within the 21-25 year age category were more likely to receive counselling, and presenting problems varied by population group. Given the country's past and continued levels of social asymmetry, we argue that the development of standardised university-based reporting systems able to describe the characteristics and presenting problems of students seeking counselling across South African universities should be prioritised by its higher education sector. Timely access to information of this kind is crucial to the generation of evidence-based mental health interventions in a population that is especially important to the country's development vision.

Use of probabilistic weights to enhance linear regression myoelectric control.

Science.gov (United States)

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

2015-12-01

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. 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. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p linear regression control. 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.

Pathways to Prejudice: Predicting Students' Heterosexist Attitudes with Demographics, Self-Esteem, and Contact with Lesbians and Gay Men.

Science.gov (United States)

Simoni, Jane M.

1996-01-01

A survey of 181 students indicated that negative attitudes toward homosexuals were associated with being younger, having less education, being male, and having less-educated parents. Regression analyses supported a mediational model in which low self-esteem leads to less-positive contact with homosexuals, which leads to more heterosexist beliefs.…

Advanced statistics: linear regression, part I: simple linear regression.

Science.gov (United States)

Marill, Keith A

2004-01-01

Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

Role of social support, hardiness, and acculturation as predictors of mental health among international students of Asian Indian origin.

Science.gov (United States)

Atri, Ashutosh; Sharma, Manoj; Cottrell, Randall

This study determined the role of social support, hardiness, and acculturation as predictors of mental health among international Asian Indian students enrolled at two large public universities in Ohio. A sample of 185 students completed a 75-item online instrument assessing their social support levels, acculturation, hardiness, and their mental health. Regression analyses were conducted to test for variance in mental health attributable to each of the three independent variables. The final regression model revealed that the belonging aspect of social support, acculturation and prejudice of acculturation scale, and commitment and control of hardiness were all predictive of mental health (R2 = 0.523). Recommendations have been offered to develop interventions that will help strengthen the social support, hardiness, and acculturation of international students and help improve their mental health. Recommendations for development of future Web-based studies also are offered.

The relationship among self-efficacy, perfectionism and academic burnout in medical school students.

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Yu, Ji Hye; Chae, Su Jin; Chang, Ki Hong

2016-03-01

The purpose of this study was to examine the relationship among academic self-efficacy, socially-prescribed perfectionism, and academic burnout in medical school students and to determine whether academic self-efficacy had a mediating role in the relationship between perfectionism and academic burnout. A total of 244 first-year and second-year premed medical students and first- to fourth-year medical students were enrolled in this study. As study tools, socially-prescribed perfectionism, academic self-efficacy, and academic burnout scales were utilized. For data analysis, correlation analysis, multiple regression analysis, and hierarchical multiple regression analyses were conducted. Academic burnout had correlation with socially-prescribed perfectionism. It had negative correlation with academic self-efficacy. Socially-prescribed perfectionism and academic self-efficacy had 54% explanatory power for academic burnout. When socially-prescribed perfectionism and academic self-efficacy were simultaneously used as input, academic self-efficacy partially mediated the relationship between socially-prescribed perfectionism and academic burnout. Socially-prescribed perfectionism had a negative effect on academic self-efficacy, ultimately triggering academic burnout. This suggests that it is important to have educational and counseling interventions to improve academic self-efficacy by relieving academic burnout of medical school students.

The Analysis of Nonstationary Time Series Using Regression, Correlation and Cointegration

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Søren Johansen

2012-06-01

Full Text Available There are simple well-known conditions for the validity of regression and correlation as statistical tools. We analyse by examples the effect of nonstationarity on inference using these methods and compare them to model based inference using the cointegrated vector autoregressive model. Finally we analyse some monthly data from US on interest rates as an illustration of the methods.

Tools to support interpreting multiple regression in the face of multicollinearity.

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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.

Testing and Modeling Fuel Regression Rate in a Miniature Hybrid Burner

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Luciano Fanton

2012-01-01

Full Text Available Ballistic characterization of an extended group of innovative HTPB-based solid fuel formulations for hybrid rocket propulsion was performed in a lab-scale burner. An optical time-resolved technique was used to assess the quasisteady regression history of single perforation, cylindrical samples. The effects of metalized additives and radiant heat transfer on the regression rate of such formulations were assessed. Under the investigated operating conditions and based on phenomenological models from the literature, analyses of the collected experimental data show an appreciable influence of the radiant heat flux from burnt gases and soot for both unloaded and loaded fuel formulations. Pure HTPB regression rate data are satisfactorily reproduced, while the impressive initial regression rates of metalized formulations require further assessment.

Differential item functioning (DIF) analyses of health-related quality of life instruments using logistic regression

DEFF Research Database (Denmark)

Scott, Neil W; Fayers, Peter M; Aaronson, Neil K

2010-01-01

Differential item functioning (DIF) methods can be used to determine whether different subgroups respond differently to particular items within a health-related quality of life (HRQoL) subscale, after allowing for overall subgroup differences in that scale. This article reviews issues that arise ...... when testing for DIF in HRQoL instruments. We focus on logistic regression methods, which are often used because of their efficiency, simplicity and ease of application....

Morningness-eveningness and depressive symptoms: Test on the components level with CES-D in Polish students.

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Jankowski, Konrad S

2016-05-15

The study aimed to elucidate previously observed associations between morningness-eveningness and depressive symptomatology in university students. Relations between components of depressive symptomatology and morningness-eveningness were analysed. Nine hundred and seventy-four university students completed Polish versions of the Centre for Epidemiological Studies - Depression scale (CES-D; Polish translation appended to this paper) and the Composite Scale of Morningness. Principal component analysis (PCA) was used to test the structure of depressive symptoms. Pearson and partial correlations (with age and sex controlled), along with regression analyses with morning affect (MA) and circadian preference as predictors, were used. PCA revealed three components of depressive symptoms: depressed/somatic affect, positive affect, interpersonal relations. Greater MA was related to less depressive symptoms in three components. Morning circadian preference was related to less depressive symptoms in depressed/somatic and positive affects and unrelated to interpersonal relations. Both morningness-eveningness components exhibited stronger links with depressed/somatic and positive affects than with interpersonal relations. Three CES-D components exhibited stronger links with MA than with circadian preference. In regression analyses only MA was statistically significant for positive affect and better interpersonal relations, whereas more depressed/somatic affect was predicted by lower MA and morning circadian preference (relationship reversed compared to correlations). Self-report assessment. There are three groups of depressive symptoms in Polish university students. Associations of MA with depressed/somatic and positive affects are primarily responsible for the observed links between morningness-eveningness and depressive symptoms in university students. People with evening circadian preference whose MA is not lowered have less depressed/somatic affect. Copyright © 2016

Comparisons and Analyses of Gifted Students' Characteristics and Learning Methods

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Lu, Jiamei; Li, Daqi; Stevens, Carla; Ye, Renmin

2017-01-01

Using PISA 2009, an international education database, this study compares gifted and talented (GT) students in three groups with normal (non-GT) students by examining student characteristics, reading, schooling, learning methods, and use of strategies for understanding and memorizing. Results indicate that the GT and non-GT gender distributions…

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

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

2018-04-01

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

The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

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Murphy, Kevin; Birn, Rasmus M; Handwerker, Daniel A; Jones, Tyler B; Bandettini, Peter A

2009-02-01

Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step.

Effects of teacher autonomy support and students' autonomous motivation on learning in physical education.

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Shen, Bo; McCaughtry, Nate; Martin, Jeffrey; Fahlman, Mariane

2009-03-01

This study applied self-determination theory to investigate the effects of students' autonomous motivation and their perceptions of teacher autonomy support on need satisfaction adjustment, learning achievement, and cardiorespiratory fitness over a 4-month personal conditioning unit. Participants were 253 urban adolescents (121 girls and 132 boys, ages = 12-14 years). Based on a series of multiple regression analyses, perceived autonomy support by teachers significantly predicted students'need satisfaction adjustment and led to learning achievement, especially for students who were not autonomously motivated to learn in physical education. In turn, being more autonomous was directly associated with cardiorespiratory fitness enhancement. The findings suggest that shifts in teaching approaches toward providing more support for students' autonomy and active involvement hold promise for enhancing learning.

The impact of materialism on the entrepreneurial intention of university students in South Africa

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Olawale Fatoki

2015-11-01

Full Text Available The study investigated the relationship between materialism and the entrepreneurial intention of students at a South African university. In addition, the study examined if there is a significant gender difference in the materialistic values of university students. The quantitative research technique was adopted for the study. The survey method and the self-administered approach were used for data collection. The research participants comprised of 169 conveniently sampled business students. The Cronbach’s alpha was used to ensure reliability. Data was analysed using descriptive statistics, confirmatory factor analysis, T-test, Pearson correlation and regression. The results indicated that there is a positive but insignificant relationship between materialism and the entrepreneurial intention of university students. There is no significant gender difference in the materialistic values of university students. Recommendations were suggested in order to manage the materialistic values of university students.

An examination of the misuse of prescription stimulants among college students using the theory of planned behavior.

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Gallucci, Andrew; Martin, Ryan; Beaujean, Alex; Usdan, Stuart

2015-01-01

The misuse of prescription stimulants (MPS) is an emergent adverse health behavior among undergraduate college students. However, current research on MPS is largely atheoretical. The purpose of this study was to validate a survey to assess MPS-related theory of planned behavior (TPB) constructs (i.e. attitudes, subjective norms, and perceived behavioral control) and determine the relationship between these constructs, MPS-related risk factors (e.g. gender and class status), and current MPS (i.e. past 30 days use) among college students. Participants (N = 978, 67.8% female and 82.9% Caucasian) at a large public university in the southeastern USA completed a survey assessing MPS and MPS-related TPB constructs during fall 2010. To examine the relationship between MPS-related TPB constructs and current MPS, we conducted (1) confirmatory factor analyses to validate that our survey items assessed MPS-related TPB constructs and (2) a series of regression analyses to examine associations between MPS-related TPB constructs, potential MPS-related risk factors, and MPS in this sample. Our factor analyses indicated that the survey items assessed MPS-related TPB constructs and our multivariate logistic regression analysis indicated that perceived behavioral control was significantly associated with current MPS. In addition, analyses found that having a prescription stimulant was a protective factor against MPS when the model included MPS-related TPB variables.

An Original Stepwise Multilevel Logistic Regression Analysis of Discriminatory Accuracy

DEFF Research Database (Denmark)

Merlo, Juan; Wagner, Philippe; Ghith, Nermin

2016-01-01

BACKGROUND AND AIM: Many multilevel logistic regression analyses of "neighbourhood and health" focus on interpreting measures of associations (e.g., odds ratio, OR). In contrast, multilevel analysis of variance is rarely considered. We propose an original stepwise analytical approach that disting...

Development of a Body Image Concern Scale using both exploratory and confirmatory factor analyses in Chinese university students

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He W

2017-05-01

Full Text Available Wenxin He, Qiming Zheng, Yutian Ji, Chanchan Shen, Qisha Zhu, Wei Wang Department of Clinical Psychology and Psychiatry, School of Public Health, Zhejiang University College of Medicine, Hangzhou, People’s Republic of China Background: The body dysmorphic disorder is prevalent in general population and in psychiatric, dermatological, and plastic-surgery patients, but there lacks a structure-validated, comprehensive self-report measure of body image concerns, which is established through both exploratory and confirmatory factor analyses. Methods: We have composed a 34-item matrix targeting the body image concerns and trialed it in 328 male and 365 female Chinese university students. Answers to the matrix dealt with treatments including exploratory factor analyses, reserve of qualified items, and confirmatory factor analyses of latent structures. Results: Six latent factors, namely the Social Avoidance, Appearance Dissatisfaction, Preoccupation with Reassurance, Perceived Distress/Discrimination, Defect Hiding, and Embarrassment in Public, were identified. The factors and their respective items have composed a 24-item questionnaire named as the Body Image Concern Scale. Each factor earned a satisfactory internal reliability, and the intercorrelations between these factors were in a median level. Women scored significantly higher than men did on the Appearance Dissatisfaction, Preoccupation with Reassurance, and Defect Hiding. Conclusion: The Body Image Concern Scale has displayed its structure validation and gender preponderance in Chinese university students. Keywords: body dysmorphic disorder, body image, factor analysis, questionnaire development

A Rubric for Evaluating Student Analyses of Business Cases

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Riddle, Emma Jane; Smith, Marilyn; Frankforter, Steven A.

2016-01-01

This article presents a rubric for evaluating student performance on written case assignments that require qualitative analysis. This rubric is designed for three purposes. First, it informs students of the criteria on which their work will be evaluated. Second, it provides instructors with a reliable instrument for accurately measuring and…

Exploring students' patterns of reasoning

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Matloob Haghanikar, Mojgan

As part of a collaborative study of the science preparation of elementary school teachers, we investigated the quality of students' reasoning and explored the relationship between sophistication of reasoning and the degree to which the courses were considered inquiry oriented. To probe students' reasoning, we developed open-ended written content questions with the distinguishing feature of applying recently learned concepts in a new context. We devised a protocol for developing written content questions that provided a common structure for probing and classifying students' sophistication level of reasoning. In designing our protocol, we considered several distinct criteria, and classified students' responses based on their performance for each criterion. First, we classified concepts into three types: Descriptive, Hypothetical, and Theoretical and categorized the abstraction levels of the responses in terms of the types of concepts and the inter-relationship between the concepts. Second, we devised a rubric based on Bloom's revised taxonomy with seven traits (both knowledge types and cognitive processes) and a defined set of criteria to evaluate each trait. Along with analyzing students' reasoning, we visited universities and observed the courses in which the students were enrolled. We used the Reformed Teaching Observation Protocol (RTOP) to rank the courses with respect to characteristics that are valued for the inquiry courses. We conducted logistic regression for a sample of 18courses with about 900 students and reported the results for performing logistic regression to estimate the relationship between traits of reasoning and RTOP score. In addition, we analyzed conceptual structure of students' responses, based on conceptual classification schemes, and clustered students' responses into six categories. We derived regression model, to estimate the relationship between the sophistication of the categories of conceptual structure and RTOP scores. However, the

Beliefs about meditating among university students, faculty, and staff: a theory-based salient belief elicitation.

Science.gov (United States)

Lederer, Alyssa M; Middlestadt, Susan E

2014-01-01

Stress impacts college students, faculty, and staff alike. Although meditation has been found to decrease stress, it is an underutilized strategy. This study used the Reasoned Action Approach (RAA) to identify beliefs underlying university constituents' decision to meditate. N=96 students, faculty, and staff at a large midwestern university during spring 2012. A survey measured the RAA global constructs and elicited the beliefs underlying intention to meditate. Thematic and frequency analyses and multiple regression were performed. Quantitative analyses showed that intention to meditate was significantly predicted (R2=.632) by attitude, perceived norm, and perceived behavioral control. Qualitative analyses revealed advantages (eg, reduced stress; feeling calmer), disadvantages (eg, takes time; will not work), and facilitating circumstances (eg, having more time; having quiet space) of meditating. Results of this theory-based research suggest how college health professionals can encourage meditation practice through individual, interpersonal, and environmental interventions.

Self-regulated learning in students of pedagogy

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Janete Aparecida da Silva Marini

2014-12-01

Full Text Available Self-regulated learning is the process by which students plan, monitor and regulate their own learning. The aim of this study was to investigate relationships between motivation to learn, implicit theories of intelligence and self-handicapping strategies, and to examine the association of these variables in the prediction of the use of learning strategies in students of Pedagogy. The sample consisted of 107 Pedagogy students of two private universities of a city of São Paulo state. Data were collected using four Likert-type scales. Multivariate linear regression analyses revealed that participants with higher scores in the Learning Strategies Scale also presented significantly higher scores in intrinsic motivation and fewer reports of use of self-handicapping strategies. Higher scores in metacognitive strategies were significantly associated with both intrinsic an extrinsic motivation and with fewer reports of use of self-handicapping strategies. Results are discussed in terms of the contribution of Psychology to teacher education.

Ordinary least square regression, orthogonal regression, geometric mean regression and their applications in aerosol science

International Nuclear Information System (INIS)

Leng Ling; Zhang Tianyi; Kleinman, Lawrence; Zhu Wei

2007-01-01

Regression analysis, especially the ordinary least squares method which assumes that errors are confined to the dependent variable, has seen a fair share of its applications in aerosol science. The ordinary least squares approach, however, could be problematic due to the fact that atmospheric data often does not lend itself to calling one variable independent and the other dependent. Errors often exist for both measurements. In this work, we examine two regression approaches available to accommodate this situation. They are orthogonal regression and geometric mean regression. Comparisons are made theoretically as well as numerically through an aerosol study examining whether the ratio of organic aerosol to CO would change with age

Interpreting Multiple Linear Regression: A Guidebook of Variable Importance

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Nathans, Laura L.; Oswald, Frederick L.; Nimon, Kim

2012-01-01

Multiple regression (MR) analyses are commonly employed in social science fields. It is also common for interpretation of results to typically reflect overreliance on beta weights, often resulting in very limited interpretations of variable importance. It appears that few researchers employ other methods to obtain a fuller understanding of what…

Gender-specific relationships between socioeconomic disadvantage and obesity in elementary school students.

Science.gov (United States)

Zahnd, Whitney E; Rogers, Valerie; Smith, Tracey; Ryherd, Susan J; Botchway, Albert; Steward, David E

2015-12-01

To assess the gender-specific effect of socioeconomic disadvantage on obesity in elementary school students. We evaluated body mass index (BMI) data from 2,648 first- and fourth-grade students (1,377 male and 1,271 female students) in eight elementary schools in Springfield, Illinois, between 2012 and 2014. Other factors considered in analysis were grade level, year of data collection, school, race/ethnicity, gender, and socioeconomic disadvantage (SD). Students were considered SD if they were eligible for free/reduced price lunch, a school-based poverty measure. We performed Fisher's exact test or chi-square analysis to assess differences in gender and obesity prevalence by the other factors and gender-stratified logistic regression analysis to determine if SD contributed to increased odds of obesity. A higher proportion of SD female students (20.8%) were obese compared to their non-SD peers (15.2%) (p=0.01). Unadjusted and adjusted logistic regression analysis indicated no difference in obesity in SD and non-SD male students. However, in both unadjusted and adjusted analyses, SD female students had higher odds of obesity than their peers. Even after controlling for grade level, school, year of data collection, and race/ethnicity, SD female students had 49% higher odds of obesity than their non-SD classmates (odds ratio:1.49; 95% confidence interval: 1.09-2.04). Obesity was elevated in SD female students, even after controlling for factors such as race/ethnicity, but such an association was not seen in male students. Further study is warranted to determine the cause of this disparity, and interventions should be developed to target SD female students. Copyright © 2015 Elsevier Inc. All rights reserved.

Estimating the exceedance probability of rain rate by logistic regression

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Chiu, Long S.; Kedem, Benjamin

1990-01-01

Recent studies have shown that the fraction of an area with rain intensity above a fixed threshold is highly correlated with the area-averaged rain rate. To estimate the fractional rainy area, a logistic regression model, which estimates the conditional probability that rain rate over an area exceeds a fixed threshold given the values of related covariates, is developed. The problem of dependency in the data in the estimation procedure is bypassed by the method of partial likelihood. Analyses of simulated scanning multichannel microwave radiometer and observed electrically scanning microwave radiometer data during the Global Atlantic Tropical Experiment period show that the use of logistic regression in pixel classification is superior to multiple regression in predicting whether rain rate at each pixel exceeds a given threshold, even in the presence of noisy data. The potential of the logistic regression technique in satellite rain rate estimation is discussed.

Physiology of school burnout in medical students: Hemodynamic and autonomic functioning

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Ross W. May

2016-09-01

Full Text Available This study investigated the relationship between burnout and hemodynamic and autonomic functioning in both medical students (N = 55 and premedical undergraduate students (N = 77. Questionnaires screened for health related issues and assessed school burnout and negative affect symptomatology (anxiety and depression. Continuous beat-to-beat blood pressure (BP through finger plethysmography and electrocardiogram (ECG monitoring was conducted during conditions of baseline and cardiac stress induced via the cold pressor task to produce hemodynamic, heart rate variability, and blood pressure variability indices. Independent sample t-tests demonstrated that medical students had significantly higher school burnout scores compared to their undergraduate counterparts. Controlling for age, BMI, anxiety and depressive symptoms, multiple regression analyses indicated that school burnout was a stronger predictor of elevated hemodynamics (blood pressure, decreased heart rate variability, decreased markers of vagal activity and increased markers of sympathetic tone at baseline for medical students than for undergraduates. Analyses of physiological values collected during the cold pressor task indicated greater cardiac hyperactivity for medical students than for undergraduates. The present study supports previous research linking medical school burnout to hemodynamic and autonomic functioning, suggests biomarkers for medical school burnout, and provides evidence that burnout may be implicated as a physiological risk factor in medical students. Study limitations and potential intervention avenues are discussed.

Linear regression and the normality assumption.

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Schmidt, Amand F; Finan, Chris

2017-12-16

Researchers often perform arbitrary outcome transformations to fulfill the normality assumption of a linear regression model. This commentary explains and illustrates that in large data settings, such transformations are often unnecessary, and worse may bias model estimates. Linear regression assumptions are illustrated using simulated data and an empirical example on the relation between time since type 2 diabetes diagnosis and glycated hemoglobin levels. Simulation results were evaluated on coverage; i.e., the number of times the 95% confidence interval included the true slope coefficient. Although outcome transformations bias point estimates, violations of the normality assumption in linear regression analyses do not. The normality assumption is necessary to unbiasedly estimate standard errors, and hence confidence intervals and P-values. However, in large sample sizes (e.g., where the number of observations per variable is >10) violations of this normality assumption often do not noticeably impact results. Contrary to this, assumptions on, the parametric model, absence of extreme observations, homoscedasticity, and independency of the errors, remain influential even in large sample size settings. Given that modern healthcare research typically includes thousands of subjects focusing on the normality assumption is often unnecessary, does not guarantee valid results, and worse may bias estimates due to the practice of outcome transformations. Copyright © 2017 Elsevier Inc. All rights reserved.

Using a Regression Discontinuity Design to Estimate the Impact of Placement Decisions in Developmental Math

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Melguizo, Tatiana; Bos, Johannes M.; Ngo, Federick; Mills, Nicholas; Prather, George

2016-01-01

This study evaluates the effectiveness of math placement policies for entering community college students on these students' academic success in math. We estimate the impact of placement decisions by using a discrete-time survival model within a regression discontinuity framework. The primary conclusion that emerges is that initial placement in a…

Associations between past bullying experiences and psychosocial and academic functioning among college students.

Science.gov (United States)

Holt, Melissa K; Greif Green, Jennifer; Reid, Gerald; DiMeo, Amanda; Espelage, Dorothy L; Felix, Erika D; Furlong, Michael J; Poteat, V Paul; Sharkey, Jill D

2014-01-01

This study examined whether childhood bullying victimization was associated with psychosocial and academic functioning at college. The sample consisted of 413 first-year students from a large northeastern university. Students completed an online survey in February 2012 that included items assessing past bullying involvement, current psychosocial and academic functioning, and victimization experiences since arriving at college. Regression analyses indicated that reports of past bullying and other peer victimization were associated with lower mental health functioning and perceptions of physical and mental health, but were not associated with perceptions of social life at college, overall college experience, or academic performance. Childhood bullying victimization is associated with poorer mental and physical health among first-year college students. Colleges should consider assessing histories of bullying victimization, along with other past victimization exposures, in their service provision to students.

The moderating role of emotional competence in suicidal ideation among Chinese university students.

Science.gov (United States)

Kwok, Sylvia Y C L

2014-04-01

To explore the relationship among perceived family functioning, emotional competence and suicidal ideation and to examine the moderating role of emotional competence in suicidal ideation. Previous studies have highlighted that poor family relationships and emotional symptoms are significant predictors of suicidal ideation. However, the roles of perceived family functioning and emotional competence in predicting suicidal ideation have not been given adequate attention. A cross-sectional survey using convenience sampling. A questionnaire was administered to 302 university students from February-April in 2011 in Hong Kong. The means, standard deviations and Cronbach's alphas of the variables were computed. Pearson correlation analyses and hierarchical regression analyses were performed. Hierarchical regression analyses showed that perceived high family functioning and emotional competence were significant negative predictors of suicidal ideation. Further analyses showed that parental concern, parental control and creative use of emotions were significant predictors of suicidal ideation. Emotional competence, specifically creative use of emotions, was found to moderate the relationship between perceived family functioning and suicidal ideation. The findings support the family ecological framework and provide evidence for emotional competence as a resilience factor that buffers low family functioning on suicidal ideation. Suggested measures to decrease suicidal ideation include enhancing parental concern, lessening parental control, developing students' awareness, regulation and management of their own emotions, fostering empathy towards others' emotional expression, enhancing social skills in sharing and influencing others' emotions and increasing the positive use of emotions for the evaluation and generation of new ideas. © 2013 John Wiley & Sons Ltd.

Daily participation in sports and students' sexual activity.

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Habel, Melissa A; Dittus, Patricia J; De Rosa, Christine J; Chung, Emily Q; Kerndt, Peter R

2010-12-01

Previous studies suggest that student athletes may be less likely than nonathletes to engage in sexual behavior. However, few have explored sexual risk behavior among athletes in early adolescence. In 2005, a sample of 10,487 students in 26 Los Angeles public middle and high schools completed a self-administered survey that asked about their demographic characteristics, sports participation, sexual behaviors and expectations, and parental relationships. Chi-square analyses compared reported levels of daily participation in sports, experience with intercourse, experience with oral sex and condom use at last intercourse by selected characteristics. Predictors of sexual experience and condom use were assessed in multivariate logistic regression analyses. One-third of students reported daily participation in sports. This group had higher odds of ever having had intercourse and ever having had oral sex than their peers who did not play a sport daily (odds ratios, 1.2 and 1.1, respectively). The increases in risk were greater for middle school sports participants than for their high school counterparts (1.5 and 1.6, respectively). Among sexually experienced students, daily sports participants also had elevated odds of reporting condom use at last intercourse (1.4). Students as young as middle school age who participate in sports daily may have an elevated risk for STDs and pregnancy. Health professionals should counsel middle school athletes about sexual risk reduction, given that young students may find it particularly difficult to obtain contraceptives, STD testing and prevention counseling. Copyright © 2010 by the Guttmacher Institute.

Polynomial regression analysis and significance test of the regression function

International Nuclear Information System (INIS)

Gao Zhengming; Zhao Juan; He Shengping

2012-01-01

In order to analyze the decay heating power of a certain radioactive isotope per kilogram with polynomial regression method, the paper firstly demonstrated the broad usage of polynomial function and deduced its parameters with ordinary least squares estimate. Then significance test method of polynomial regression function is derived considering the similarity between the polynomial regression model and the multivariable linear regression model. Finally, polynomial regression analysis and significance test of the polynomial function are done to the decay heating power of the iso tope per kilogram in accord with the authors' real work. (authors)

Predictors of psychological resilience amongst medical students following major earthquakes.

Science.gov (United States)

Carter, Frances; Bell, Caroline; Ali, Anthony; McKenzie, Janice; Boden, Joseph M; Wilkinson, Timothy; Bell, Caroline

2016-05-06

To identify predictors of self-reported psychological resilience amongst medical students following major earthquakes in Canterbury in 2010 and 2011. Two hundred and fifty-three medical students from the Christchurch campus, University of Otago, were invited to participate in an electronic survey seven months following the most severe earthquake. Students completed the Connor-Davidson Resilience Scale, the Depression, Anxiety and Stress Scale, the Post-traumatic Disorder Checklist, the Work and Adjustment Scale, and the Eysenck Personality Questionnaire. Likert scales and other questions were also used to assess a range of variables including demographic and historical variables (eg, self-rated resilience prior to the earthquakes), plus the impacts of the earthquakes. The response rate was 78%. Univariate analyses identified multiple variables that were significantly associated with higher resilience. Multiple linear regression analyses produced a fitted model that was able to explain 35% of the variance in resilience scores. The best predictors of higher resilience were: retrospectively-rated personality prior to the earthquakes (higher extroversion and lower neuroticism); higher self-rated resilience prior to the earthquakes; not being exposed to the most severe earthquake; and less psychological distress following the earthquakes. Psychological resilience amongst medical students following major earthquakes was able to be predicted to a moderate extent.

Assessment of the relationship between the engagement in leisure time and academic motivation among the students of faculty of education

OpenAIRE

SARI, Ihsan; CETIN, Mehmet; KAYA, Erdi; GULLE, Mahmut; KAHRAMANOĞLU, Recep

2014-01-01

The aim of the study was to determine the relationship between leisure time motivation and academic motivation among the students who studied at the Faculty of Education of Mustafa Kemal University. 260 students (Xyears: 21.29±2.11) constituted the sample of the study. For the analyses of the data; Leisure Motivation Scale and Academic Motivation Scale were employed. The data were analyzed using descriptive statistics, Pearson's correlation test and regression analysis. According to the ...

The best of both worlds: Phylogenetic eigenvector regression and mapping

Directory of Open Access Journals (Sweden)

José Alexandre Felizola Diniz Filho

2015-09-01

Full Text Available Eigenfunction analyses have been widely used to model patterns of autocorrelation in time, space and phylogeny. In a phylogenetic context, Diniz-Filho et al. (1998 proposed what they called Phylogenetic Eigenvector Regression (PVR, in which pairwise phylogenetic distances among species are submitted to a Principal Coordinate Analysis, and eigenvectors are then used as explanatory variables in regression, correlation or ANOVAs. More recently, a new approach called Phylogenetic Eigenvector Mapping (PEM was proposed, with the main advantage of explicitly incorporating a model-based warping in phylogenetic distance in which an Ornstein-Uhlenbeck (O-U process is fitted to data before eigenvector extraction. Here we compared PVR and PEM in respect to estimated phylogenetic signal, correlated evolution under alternative evolutionary models and phylogenetic imputation, using simulated data. Despite similarity between the two approaches, PEM has a slightly higher prediction ability and is more general than the original PVR. Even so, in a conceptual sense, PEM may provide a technique in the best of both worlds, combining the flexibility of data-driven and empirical eigenfunction analyses and the sounding insights provided by evolutionary models well known in comparative analyses.

Reduced Rank Regression

DEFF Research Database (Denmark)

Johansen, Søren

2008-01-01

The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

Prosocial behavior and self-concept of Spanish students of Compulsory Secondary Education

OpenAIRE

Inglés, Cándido J.; Martínez-González, Agustín Ernesto; García-Fernández, José Manuel; Torregrosa, María S.; Ruiz Esteban, Cecilia

2012-01-01

This study analyzed the relationship between prosocial behavior and self-concept dimensions in a sample of 2022 Spanish students (51.1% males) of Compulsory Secondary Education. The prosocial behavior was measured with the Prosocial Behavior scale of the Teenage Inventory of Social Skills (TISS) and the self-concept was measured with the Self-Description Questionnaire-II (SDQ-II). Logistic regression analyses revealed that prosocial behavior is a positive and significant statistically predict...

The impact of professional identity on role stress in nursing students: A cross-sectional study.

Science.gov (United States)

Sun, Li; Gao, Ying; Yang, Juan; Zang, Xiao-Ying; Wang, Yao-Gang

2016-11-01

As newcomers to the clinical workplace, nursing students will encounter a high degree of role stress, which is an important predictor of burnout and engagement. Professional identity is theorised to be a key factor in providing high-quality care to improve patient outcomes and is thought to mediate the negative effects of a high-stress workplace and improve clinical performance and job retention. To investigate the level of nursing students' professional identity and role stress at the end of the first sub-internship, and to explore the impact of the nursing students' professional identity and other characteristics on role stress. A cross-sectional study. Three nursing schools in China. Nursing students after a 6-month sub-internship in a general hospital (n=474). The Role Stress Scale (score range: 12-60) and the Professional Identity Questionnaire for Nursing students (score range: 17-85) were used to investigate the levels of nursing students' role stress and professional identity. Higher scores indicated higher levels of role stress and professional identity. Basic demographic information about the nursing students was collected. The Pearson correlation, point-biserial correlation and multiple linear regression analysis were used to analyse the data. The mean total scores of the Role Stress Scale and Professional Identity Questionnaire for Nursing Students were 34.04 (SD=6.57) and 57.63 (SD=9.63), respectively. In the bivariate analyses, the following independent variables were found to be significantly associated with the total score of the Role Stress Scale: the total score of the Professional Identity Questionnaire for Nursing Students (r=-0.295, pNursing Students (standardised coefficient Beta: -0.260, pStress Scale. The multiple linear regression model explained 18.2% (adjusted R 2 scores 16.5%) of the Role Stress Scale scores variance. The nursing students' level of role stress at the end of the first sub-internship was high. The students with higher

Student experiences of participating in five collaborative blended learning courses in Africa and Asia: a survey.

Science.gov (United States)

Atkins, Salla; Yan, Weirong; Meragia, Elnta; Mahomed, Hassan; Rosales-Klintz, Senia; Skinner, Donald; Zwarenstein, Merrick

2016-01-01

As blended learning (BL; a combination of face-to-face and e-learning methods) becomes more commonplace, it is important to assess whether students find it useful for their studies. ARCADE HSSR and ARCADE RSDH (African Regional Capacity Development for Health Systems and Services Research; Asian Regional Capacity Development for Research on Social Determinants of Health) were unique capacity-building projects, focusing on developing BL in Africa and Asia on issues related to global health. We aimed to evaluate the student experience of participating in any of five ARCADE BL courses implemented collaboratively at institutions from Africa, Asia, and Europe. A post-course student survey with 118 students was conducted. The data were collected using email or through an e-learning platform. Data were analysed with SAS, using bivariate and multiple logistic regression. We focused on the associations between various demographic and experience variables and student-reported overall perceptions of the courses. In total, 82 students responded to the survey. In bivariate logistic regression, the course a student took [ p =0.0067, odds ratio (OR)=0.192; 95% confidence interval (CI): 0.058-0.633], male gender of student ( p =0.0474, OR=0.255; 95% CI: 0.066-0.985), not experiencing technical problems ( p learning component to their studies. In contrast, perceiving the assessment as adequate was associated with a worse perception of overall usefulness. In a multiple regression, the course, experiencing no technical problems, and perceiving the discussion as adequate remained significantly associated with a more positively rated perception of the usefulness of the online component of the blended courses. The results suggest that lack of technical problems and functioning discussion forums are of importance during BL courses focusing on global health-related topics. Through paying attention to these aspects, global health education could be provided using BL approaches to student

Prediction of radiation levels in residences: A methodological comparison of CART [Classification and Regression Tree Analysis] and conventional regression

International Nuclear Information System (INIS)

Janssen, I.; Stebbings, J.H.

1990-01-01

In environmental epidemiology, trace and toxic substance concentrations frequently have very highly skewed distributions ranging over one or more orders of magnitude, and prediction by conventional regression is often poor. Classification and Regression Tree Analysis (CART) is an alternative in such contexts. To compare the techniques, two Pennsylvania data sets and three independent variables are used: house radon progeny (RnD) and gamma levels as predicted by construction characteristics in 1330 houses; and ∼200 house radon (Rn) measurements as predicted by topographic parameters. CART may identify structural variables of interest not identified by conventional regression, and vice versa, but in general the regression models are similar. CART has major advantages in dealing with other common characteristics of environmental data sets, such as missing values, continuous variables requiring transformations, and large sets of potential independent variables. CART is most useful in the identification and screening of independent variables, greatly reducing the need for cross-tabulations and nested breakdown analyses. There is no need to discard cases with missing values for the independent variables because surrogate variables are intrinsic to CART. The tree-structured approach is also independent of the scale on which the independent variables are measured, so that transformations are unnecessary. CART identifies important interactions as well as main effects. The major advantages of CART appear to be in exploring data. Once the important variables are identified, conventional regressions seem to lead to results similar but more interpretable by most audiences. 12 refs., 8 figs., 10 tabs

Sick of our loans: Student borrowing and the mental health of young adults in the United States.

Science.gov (United States)

Walsemann, Katrina M; Gee, Gilbert C; Gentile, Danielle

2015-01-01

Student loans are increasingly important and commonplace, especially among recent cohorts of young adults in the United States. These loans facilitate the acquisition of human capital in the form of education, but may also lead to stress and worries related to repayment. This study investigated two questions: 1) what is the association between the cumulative amount of student loans borrowed over the course of schooling and psychological functioning when individuals are 25-31 years old; and 2) what is the association between annual student loan borrowing and psychological functioning among currently enrolled college students? We also examined whether these relationships varied by parental wealth, college enrollment history (e.g. 2-year versus 4-year college), and educational attainment (for cumulative student loans only). We analyzed data from the National Longitudinal Survey of Youth 1997 (NLSY97), a nationally representative sample of young adults in the United States. Analyses employed multivariate linear regression and within-person fixed-effects models. Student loans were associated with poorer psychological functioning, adjusting for covariates, in both the multivariate linear regression and the within-person fixed effects models. This association varied by level of parental wealth in the multivariate linear regression models only, and did not vary by college enrollment history or educational attainment. The present findings raise novel questions for further research regarding student loan debt and the possible spillover effects on other life circumstances, such as occupational trajectories and health inequities. The study of student loans is even more timely and significant given the ongoing rise in the costs of higher education. Copyright © 2014 Elsevier Ltd. All rights reserved.

Logistic Regression Analysis of Operational Errors and Routine Operations Using Sector Characteristics

National Research Council Canada - National Science Library

Pfleiderer, Elaine M; Scroggins, Cheryl L; Manning, Carol A

2009-01-01

Two separate logistic regression analyses were conducted for low- and high-altitude sectors to determine whether a set of dynamic sector characteristics variables could reliably discriminate between operational error (OE...

Quantile Regression Methods

DEFF Research Database (Denmark)

Fitzenberger, Bernd; Wilke, Ralf Andreas

2015-01-01

if the mean regression model does not. We provide a short informal introduction into the principle of quantile regression which includes an illustrative application from empirical labor market research. This is followed by briefly sketching the underlying statistical model for linear quantile regression based......Quantile regression is emerging as a popular statistical approach, which complements the estimation of conditional mean models. While the latter only focuses on one aspect of the conditional distribution of the dependent variable, the mean, quantile regression provides more detailed insights...... by modeling conditional quantiles. Quantile regression can therefore detect whether the partial effect of a regressor on the conditional quantiles is the same for all quantiles or differs across quantiles. Quantile regression can provide evidence for a statistical relationship between two variables even...

Emigration preferences and plans among medical students in Poland

Directory of Open Access Journals (Sweden)

Krajewski-Siuda Krzysztof

2012-04-01

Full Text Available Abstract Background Migration and ethical recruitment of health care workers is receiving increased attention worldwide. Europe’s aging population is creating new opportunities for medical doctors for finding employment in other countries, particularly those of a better standard of living. Methods We conducted a survey among 1214 medical students in five out of eleven universities in Poland with medical schools in October 2008. A series of statistical tests was applied to analyse the characteristics of potential migrants. Projections were obtained using statistical analyses: descriptive, multifactorial logistic regression and other statistical methods . Results We can forecast that 26–36% of Polish medical students will emigrate over the next few years; 62% of respondents estimated the likelihood of emigration at 50%. Students in their penultimate year of study declared a stronger desire to migrate than those in the final year. At the same time, many students were optimistic about career opportunities in Poland. Also noted among students were: the decline in interest in leaving among final year students, their moderate elaboration of departure plans, and their generally optimistic views about the opportunities for professional development in Poland. Conclusions The majority of Polish students see the emigration as a serious alternative to the continuation of their professional training. This trend can pose a serious threat to the Polish health care system, however the observed decline of the interest in leaving among final year students, the moderate involvement in concrete departure plans and the optimistic views about the opportunities for professional development in Poland suggest that the actual scale of brain drain of young Polish doctors due to emigration will be more limited than previously feared.

Affix Meaning Knowledge in First Through Third Grade Students.

Science.gov (United States)

Apel, Kenn; Henbest, Victoria Suzanne

2016-04-01

We examined grade-level differences in 1st- through 3rd-grade students' performance on an experimenter-developed affix meaning task (AMT) and determined whether AMT performance explained unique variance in word-level reading and reading comprehension, beyond other known contributors to reading development. Forty students at each grade level completed an assessment battery that included measures of phonological awareness, receptive vocabulary, word-level reading, reading comprehension, and affix meaning knowledge. On the AMT, 1st-grade students were significantly less accurate than 2nd- and 3rd-grade students; there was no significant difference in performance between the 2nd- and 3rd-grade students. Regression analyses revealed that the AMT accounted for 8% unique variance of students' performance on word-level reading measures and 6% unique variance of students' performance on the reading comprehension measure, after age, phonological awareness, and receptive vocabulary were explained. These results provide initial information on the development of affix meaning knowledge via an explicit measure in 1st- through 3rd-grade students and demonstrate that affix meaning knowledge uniquely contributes to the development of reading abilities above other known literacy predictors. These findings provide empirical support for how students might use morphological problem solving to read unknown multimorphemic words successfully.

A Monte Carlo simulation study comparing linear regression, beta regression, variable-dispersion beta regression and fractional logit regression at recovering average difference measures in a two sample design.

Science.gov (United States)

Meaney, Christopher; Moineddin, Rahim

2014-01-24

In biomedical research, response variables are often encountered which have bounded support on the open unit interval--(0,1). Traditionally, researchers have attempted to estimate covariate effects on these types of response data using linear regression. Alternative modelling strategies may include: beta regression, variable-dispersion beta regression, and fractional logit regression models. This study employs a Monte Carlo simulation design to compare the statistical properties of the linear regression model to that of the more novel beta regression, variable-dispersion beta regression, and fractional logit regression models. In the Monte Carlo experiment we assume a simple two sample design. We assume observations are realizations of independent draws from their respective probability models. The randomly simulated draws from the various probability models are chosen to emulate average proportion/percentage/rate differences of pre-specified magnitudes. Following simulation of the experimental data we estimate average proportion/percentage/rate differences. We compare the estimators in terms of bias, variance, type-1 error and power. Estimates of Monte Carlo error associated with these quantities are provided. If response data are beta distributed with constant dispersion parameters across the two samples, then all models are unbiased and have reasonable type-1 error rates and power profiles. If the response data in the two samples have different dispersion parameters, then the simple beta regression model is biased. When the sample size is small (N0 = N1 = 25) linear regression has superior type-1 error rates compared to the other models. Small sample type-1 error rates can be improved in beta regression models using bias correction/reduction methods. In the power experiments, variable-dispersion beta regression and fractional logit regression models have slightly elevated power compared to linear regression models. Similar results were observed if the

Designing for deeper learning in a blended computer science course for middle school students

Science.gov (United States)

Grover, Shuchi; Pea, Roy; Cooper, Stephen

2015-04-01

The focus of this research was to create and test an introductory computer science course for middle school. Titled "Foundations for Advancing Computational Thinking" (FACT), the course aims to prepare and motivate middle school learners for future engagement with algorithmic problem solving. FACT was also piloted as a seven-week course on Stanford's OpenEdX MOOC platform for blended in-class learning. Unique aspects of FACT include balanced pedagogical designs that address the cognitive, interpersonal, and intrapersonal aspects of "deeper learning"; a focus on pedagogical strategies for mediating and assessing for transfer from block-based to text-based programming; curricular materials for remedying misperceptions of computing; and "systems of assessments" (including formative and summative quizzes and tests, directed as well as open-ended programming assignments, and a transfer test) to get a comprehensive picture of students' deeper computational learning. Empirical investigations, accomplished over two iterations of a design-based research effort with students (aged 11-14 years) in a public school, sought to examine student understanding of algorithmic constructs, and how well students transferred this learning from Scratch to text-based languages. Changes in student perceptions of computing as a discipline were measured. Results and mixed-method analyses revealed that students in both studies (1) achieved substantial learning gains in algorithmic thinking skills, (2) were able to transfer their learning from Scratch to a text-based programming context, and (3) achieved significant growth toward a more mature understanding of computing as a discipline. Factor analyses of prior computing experience, multivariate regression analyses, and qualitative analyses of student projects and artifact-based interviews were conducted to better understand the factors affecting learning outcomes. Prior computing experiences (as measured by a pretest) and math ability were

The relationship among self-efficacy, perfectionism and academic burnout in medical school students

Directory of Open Access Journals (Sweden)

Ji Hye Yu

2016-03-01

Full Text Available Purpose: The purpose of this study was to examine the relationship among academic self-efficacy, socially-prescribed perfectionism, and academic burnout in medical school students and to determine whether academic self-efficacy had a mediating role in the relationship between perfectionism and academic burnout. Methods: A total of 244 first-year and second-year premed medical students and first- to fourth-year medical students were enrolled in this study. As study tools, socially-prescribed perfectionism, academic self-efficacy, and academic burnout scales were utilized. For data analysis, correlation analysis, multiple regression analysis, and hierarchical multiple regression analyses were conducted. Results: Academic burnout had correlation with socially-prescribed perfectionism. It had negative correlation with academic self-efficacy. Socially-prescribed perfectionism and academic self-efficacy had 54% explanatory power for academic burnout. When socially-prescribed perfectionism and academic self-efficacy were simultaneously used as input, academic self-efficacy partially mediated the relationship between socially-prescribed perfectionism and academic burnout. Conclusion: Socially-prescribed perfectionism had a negative effect on academic self-efficacy, ultimately triggering academic burnout. This suggests that it is important to have educational and counseling interventions to improve academic self-efficacy by relieving academic burnout of medical school students.

The Relationship of Self-Efficacy, Sensation Seeking and Coping Sterategies with Aptitude of Substance Use in University Students

Directory of Open Access Journals (Sweden)

Azar Kiamarsi

2012-02-01

Full Text Available Introduction: The purpose of the research was to determine relationship of coping sterategies, self-efficacy and sensation seeking with aptitude of substance use in the students. Method: The population of the study included students of Islamic Azad University Ardabil Branch. The research sample consisted of 313 students who were studying in Islamic Azad University Ardabil Branch. To collect the data Coping Sterategies scale, Sensation Seeking scale, Self-Efficacy inventory and Substance Use Aptitude scale were used. Data was analyzed using of Pearson correlation coefficient and multiple regression analyses. Findings: The result of Pearson correlation coefficients showed that self-efficacy, sensation seeking, emotin coping sterategies and problem solving coping sterategies related to aptitude substance use in students. The results of multiple regression analysis showed that self-efficacy, sensation seeking and coping sterategies explained 43 percent of variance of aptitude of substance use in students. Conclusion: The results indicated that self-efficacy, sensation seeking and coping sterategies are significant predictors in predicting of aptitude of substance use in adolescents. Clinicians can be used these results for prevention of substance abuse by training of effective coping strategies and promotion of self efficacy.

The Use of Online Modules and the Effect on Student Outcomes in a High School Chemistry Class

Science.gov (United States)

Lamb, Richard L.; Annetta, Len

2013-10-01

The purpose of the study was to review the efficacy of online chemistry simulations in a high school chemistry class and provide discussion of the factors that may affect student learning. The sample consisted of 351 high school students exposed to online simulations. Researchers administered a pretest, intermediate test and posttest to measure chemistry content knowledge acquired during the use of online chemistry laboratory simulations. The authors also analyzed student journal entries as an attitudinal measure of chemistry during the simulation experience. The four analyses conducted were Repeated Time Measures Analysis of Variance, a three-way Analysis of Variance, Logistic Regression and Multiple Analysis of Variance. Each of these analyses provides for a slightly different aspect of factors regarding student attitudes and outcomes. Results indicate that there is a statistically significant main effect across grouping type (experimental versus control, p = 0.042, α = 0.05). Analysis of student journal entries suggests that attitudinal factors may affect student outcomes concerning the use of online supplemental instruction. Implications for this study show that the use of online simulations promotes increased understanding of chemistry content through open-ended and interactive questioning.

Regression Phalanxes

OpenAIRE

Zhang, Hongyang; Welch, William J.; Zamar, Ruben H.

2017-01-01

Tomal et al. (2015) introduced the notion of "phalanxes" in the context of rare-class detection in two-class classification problems. A phalanx is a subset of features that work well for classification tasks. In this paper, we propose a different class of phalanxes for application in regression settings. We define a "Regression Phalanx" - a subset of features that work well together for prediction. We propose a novel algorithm which automatically chooses Regression Phalanxes from high-dimensi...

Engaging Community College Students Using an Engineering Learning Community

Science.gov (United States)

Maccariella, James, Jr.

The study investigated whether community college engineering student success was tied to a learning community. Three separate data collection sources were utilized: surveys, interviews, and existing student records. Mann-Whitney tests were used to assess survey data, independent t-tests were used to examine pre-test data, and independent t-tests, analyses of covariance (ANCOVA), chi-square tests, and logistic regression were used to examine post-test data. The study found students that participated in the Engineering TLC program experienced a significant improvement in grade point values for one of the three post-test courses studied. In addition, the analysis revealed the odds of fall-to-spring retention were 5.02 times higher for students that participated in the Engineering TLC program, and the odds of graduating or transferring were 4.9 times higher for students that participated in the Engineering TLC program. However, when confounding variables were considered in the study (engineering major, age, Pell Grant participation, gender, ethnicity, and full-time/part-time status), the analyses revealed no significant relationship between participation in the Engineering TLC program and course success, fall-to-spring retention, and graduation/transfer. Thus, the confounding variables provided alternative explanations for results. The Engineering TLC program was also found to be effective in providing mentoring opportunities, engagement and motivation opportunities, improved self confidence, and a sense of community. It is believed the Engineering TLC program can serve as a model for other community college engineering programs, by striving to build a supportive environment, and provide guidance and encouragement throughout an engineering student's program of study.

Latent Variable Regression 4-Level Hierarchical Model Using Multisite Multiple-Cohorts Longitudinal Data. CRESST Report 801

Science.gov (United States)

Choi, Kilchan

2011-01-01

This report explores a new latent variable regression 4-level hierarchical model for monitoring school performance over time using multisite multiple-cohorts longitudinal data. This kind of data set has a 4-level hierarchical structure: time-series observation nested within students who are nested within different cohorts of students. These…

Analyses of polycyclic aromatic hydrocarbon (PAH) and chiral-PAH analogues-methyl-β-cyclodextrin guest-host inclusion complexes by fluorescence spectrophotometry and multivariate regression analysis.

Science.gov (United States)

Greene, LaVana; Elzey, Brianda; Franklin, Mariah; Fakayode, Sayo O

2017-03-05

The negative health impact of polycyclic aromatic hydrocarbons (PAHs) and differences in pharmacological activity of enantiomers of chiral molecules in humans highlights the need for analysis of PAHs and their chiral analogue molecules in humans. Herein, the first use of cyclodextrin guest-host inclusion complexation, fluorescence spectrophotometry, and chemometric approach to PAH (anthracene) and chiral-PAH analogue derivatives (1-(9-anthryl)-2,2,2-triflouroethanol (TFE)) analyses are reported. The binding constants (K b ), stoichiometry (n), and thermodynamic properties (Gibbs free energy (ΔG), enthalpy (ΔH), and entropy (ΔS)) of anthracene and enantiomers of TFE-methyl-β-cyclodextrin (Me-β-CD) guest-host complexes were also determined. Chemometric partial-least-square (PLS) regression analysis of emission spectra data of Me-β-CD-guest-host inclusion complexes was used for the determination of anthracene and TFE enantiomer concentrations in Me-β-CD-guest-host inclusion complex samples. The values of calculated K b and negative ΔG suggest the thermodynamic favorability of anthracene-Me-β-CD and enantiomeric of TFE-Me-β-CD inclusion complexation reactions. However, anthracene-Me-β-CD and enantiomer TFE-Me-β-CD inclusion complexations showed notable differences in the binding affinity behaviors and thermodynamic properties. The PLS regression analysis resulted in square-correlation-coefficients of 0.997530 or better and a low LOD of 3.81×10 -7 M for anthracene and 3.48×10 -8 M for TFE enantiomers at physiological conditions. Most importantly, PLS regression accurately determined the anthracene and TFE enantiomer concentrations with an average low error of 2.31% for anthracene, 4.44% for R-TFE and 3.60% for S-TFE. The results of the study are highly significant because of its high sensitivity and accuracy for analysis of PAH and chiral PAH analogue derivatives without the need of an expensive chiral column, enantiomeric resolution, or use of a polarized

Only-Child Status in Relation to Perceived Stress and Studying-Related Life Satisfaction among University Students in China: A Comparison with International Students.

Science.gov (United States)

Chu, Janet Junqing; Khan, Mobarak Hossain; Jahn, Heiko J; Kraemer, Alexander

2015-01-01

University students in general face multiple challenges, which may affect their levels of perceived stress and life satisfaction. Chinese students currently face specific strains due to the One-Child Policy (OCP). The aim of this study was to assess (1) whether the levels of perceived stress and studying-related life satisfaction are associated with only-child (OC) status after controlling for demographic and socio-economic characteristics and (2) whether these associations differ between Chinese and international students. A cross-sectional health survey based on a self-administrated standardised questionnaire was conducted among 1,843 (1,543 Chinese, 300 international) students at two Chinese universities in 2010-2011. Cohen's Perceived Stress Scale (PSS-14) and Stock and Kraemer's Studying-related Life Satisfaction Scale were used to measure perceived stress and studying-related life satisfaction respectively. Multivariable logistic regression analyses were used to examine the associations of OC status with perceived stress and studying-related life satisfaction by sex for Chinese students and international students separately. The Chinese non-only-children (NOCs) were more likely to come from small cities. Multivariable regression models indicate that the Chinese NOCs were more stressed than OCs (OR = 1.39, 1.11-1.74) with a stronger association in men (OR = 1.48, 1.08-2.02) than women (OR = 1.26, 0.89-1.77). NOCs were also more dissatisfied than their OC fellows in the Chinese subsample (OR = 1.37, 1.09-1.73). Among international students, no associations between OC status and perceived stress or studying-related life satisfaction were found. To promote equality between OCs and NOCs at Chinese universities, the causes of more stress and less studying-related life satisfaction among NOCs compared to OCs need further exploration.

Only-Child Status in Relation to Perceived Stress and Studying-Related Life Satisfaction among University Students in China: A Comparison with International Students.

Directory of Open Access Journals (Sweden)

Janet Junqing Chu

Full Text Available University students in general face multiple challenges, which may affect their levels of perceived stress and life satisfaction. Chinese students currently face specific strains due to the One-Child Policy (OCP. The aim of this study was to assess (1 whether the levels of perceived stress and studying-related life satisfaction are associated with only-child (OC status after controlling for demographic and socio-economic characteristics and (2 whether these associations differ between Chinese and international students.A cross-sectional health survey based on a self-administrated standardised questionnaire was conducted among 1,843 (1,543 Chinese, 300 international students at two Chinese universities in 2010-2011. Cohen's Perceived Stress Scale (PSS-14 and Stock and Kraemer's Studying-related Life Satisfaction Scale were used to measure perceived stress and studying-related life satisfaction respectively. Multivariable logistic regression analyses were used to examine the associations of OC status with perceived stress and studying-related life satisfaction by sex for Chinese students and international students separately.The Chinese non-only-children (NOCs were more likely to come from small cities. Multivariable regression models indicate that the Chinese NOCs were more stressed than OCs (OR = 1.39, 1.11-1.74 with a stronger association in men (OR = 1.48, 1.08-2.02 than women (OR = 1.26, 0.89-1.77. NOCs were also more dissatisfied than their OC fellows in the Chinese subsample (OR = 1.37, 1.09-1.73. Among international students, no associations between OC status and perceived stress or studying-related life satisfaction were found.To promote equality between OCs and NOCs at Chinese universities, the causes of more stress and less studying-related life satisfaction among NOCs compared to OCs need further exploration.

Only-Child Status in Relation to Perceived Stress and Studying-Related Life Satisfaction among University Students in China: A Comparison with International Students

Science.gov (United States)

Chu, Janet Junqing; Khan, Mobarak Hossain; Jahn, Heiko J.; Kraemer, Alexander

2015-01-01

Objectives University students in general face multiple challenges, which may affect their levels of perceived stress and life satisfaction. Chinese students currently face specific strains due to the One-Child Policy (OCP). The aim of this study was to assess (1) whether the levels of perceived stress and studying-related life satisfaction are associated with only-child (OC) status after controlling for demographic and socio-economic characteristics and (2) whether these associations differ between Chinese and international students. Materials and Methods A cross-sectional health survey based on a self-administrated standardised questionnaire was conducted among 1,843 (1,543 Chinese, 300 international) students at two Chinese universities in 2010–2011. Cohen’s Perceived Stress Scale (PSS-14) and Stock and Kraemer’s Studying-related Life Satisfaction Scale were used to measure perceived stress and studying-related life satisfaction respectively. Multivariable logistic regression analyses were used to examine the associations of OC status with perceived stress and studying-related life satisfaction by sex for Chinese students and international students separately. Results The Chinese non-only-children (NOCs) were more likely to come from small cities. Multivariable regression models indicate that the Chinese NOCs were more stressed than OCs (OR = 1.39, 1.11–1.74) with a stronger association in men (OR = 1.48, 1.08–2.02) than women (OR = 1.26, 0.89–1.77). NOCs were also more dissatisfied than their OC fellows in the Chinese subsample (OR = 1.37, 1.09–1.73). Among international students, no associations between OC status and perceived stress or studying-related life satisfaction were found. Conclusions To promote equality between OCs and NOCs at Chinese universities, the causes of more stress and less studying-related life satisfaction among NOCs compared to OCs need further exploration. PMID:26675032

Coping Strategies and Depression Among College Students Following Child Sexual Abuse in Turkey.

Science.gov (United States)

Yılmaz Irmak, Türkan; Aksel, Şeyda; Thompson, Dennis

2016-01-01

The objective of this study was to investigate the relationship between type of coping style and depression in college students with child sexual abuse experience. A total of 1,055 college students completed self-report measures to assess depressive symptoms, coping strategies, and child sexual abuse history. This study was conducted with a subset of 125 college students who reported that they had been sexually abused in childhood. They were divided into depressive and nondepressive groups according to their depressive symptoms. Data was collected with the Childhood Sexual Abuse Measurement, the Beck Depression Inventory, and the Coping Styles of Stress Scale. Family characteristics were measured with a demographic questionnaire. Analyses involved multiple regression to test for predictive effects. Among college students with child sexual abuse histories, parental education level and both problem-focused and emotion-focused strategies significantly explained depression scores.

Remediation for Students With Mathematics Difficulties: An Intervention Study in Middle Schools.

Science.gov (United States)

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.

Video Game Addiction among High School Students in Hordaland; Prevalence and Correlates

OpenAIRE

Bjordal, Sunniva Alsvik; Skumsnes, Toril; Ørland, Anette

2011-01-01

The aim of this study was to estimate the prevalence and correlates of video game addiction among high school students (N = 531) in Hordaland county, Norway. Video game addiction measured by the Game Addiction Scale for Adolescents was estimated both by a monothetic and a polythetic format. The prevalence was found to be 2.5% and 12.5%, respectively. Regression analyses were conducted where video game addiction comprised the dependent variable. Demographic variables, depression, anxiety, lone...

College student engaging in cyberbullying victimization: cognitive appraisals, coping strategies, and psychological adjustments.

Science.gov (United States)

Na, Hyunjoo; Dancy, Barbara L; Park, Chang

2015-06-01

The study's purpose was to explore whether frequency of cyberbullying victimization, cognitive appraisals, and coping strategies were associated with psychological adjustments among college student cyberbullying victims. A convenience sample of 121 students completed questionnaires. Linear regression analyses found frequency of cyberbullying victimization, cognitive appraisals, and coping strategies respectively explained 30%, 30%, and 27% of the variance in depression, anxiety, and self-esteem. Frequency of cyberbullying victimization and approach and avoidance coping strategies were associated with psychological adjustments, with avoidance coping strategies being associated with all three psychological adjustments. Interventions should focus on teaching cyberbullying victims to not use avoidance coping strategies. Copyright © 2015 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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.

The art of regression modeling in road safety

CERN Document Server

Hauer, Ezra

2015-01-01

This unique book explains how to fashion useful regression models from commonly available data to erect models essential for evidence-based road safety management and research. Composed from techniques and best practices presented over many years of lectures and workshops, The Art of Regression Modeling in Road Safety illustrates that fruitful modeling cannot be done without substantive knowledge about the modeled phenomenon. Class-tested in courses and workshops across North America, the book is ideal for professionals, researchers, university professors, and graduate students with an interest in, or responsibilities related to, road safety. This book also: · Presents for the first time a powerful analytical tool for road safety researchers and practitioners · Includes problems and solutions in each chapter as well as data and spreadsheets for running models and PowerPoint presentation slides · Features pedagogy well-suited for graduate courses and workshops including problems, solutions, and PowerPoint p...

Measurement of math beliefs and their associations with math behaviors in college students.

Science.gov (United States)

Hendy, Helen M; Schorschinsky, Nancy; Wade, Barbara

2014-12-01

Our purpose in the present study was to expand understanding of math beliefs in college students by developing 3 new psychometrically tested scales as guided by expectancy-value theory, self-efficacy theory, and health belief model. Additionally, we identified which math beliefs (and which theory) best explained variance in math behaviors and performance by college students and which students were most likely to have problematic math beliefs. Study participants included 368 college math students who completed questionnaires to report math behaviors (attending class, doing homework, reading textbooks, asking for help) and used a 5-point rating scale to indicate a variety of math beliefs. For a subset of 84 students, math professors provided final math grades. Factor analyses produced a 10-item Math Value Scale with 2 subscales (Class Devaluation, No Future Value), a 7-item single-dimension Math Confidence Scale, and an 11-item Math Barriers Scale with 2 subscales (Math Anxiety, Discouraging Words). Hierarchical multiple regression revealed that high levels of the newly discovered class devaluation belief (guided by expectancy-value theory) were most consistently associated with poor math behaviors in college students, with high math anxiety (guided by health belief model) and low math confidence (guided by self-efficacy theory) also found to be significant. Analyses of covariance revealed that younger and male students were at increased risk for class devaluation and older students were at increased risk for poor math confidence. (c) 2014 APA, all rights reserved.

The study of logistic regression of risk factor on the death cause of uranium miners

International Nuclear Information System (INIS)

Wen Jinai; Yuan Liyun; Jiang Ruyi

1999-01-01

Logistic regression model has widely been used in the field of medicine. The computer software on this model is popular, but it is worth to discuss how to use this model correctly. Using SPSS (Statistical Package for the Social Science) software, unconditional logistic regression method was adopted to carry out multi-factor analyses on the cause of total death, cancer death and lung cancer death of uranium miners. The data is from radioepidemiological database of one uranium mine. The result show that attained age is a risk factor in the logistic regression analyses of total death, cancer death and lung cancer death. In the logistic regression analysis of cancer death, there is a negative correlation between the age of exposure and cancer death. This shows that the younger the age at exposure, the bigger the risk of cancer death. In the logistic regression analysis of lung cancer death, there is a positive correlation between the cumulated exposure and lung cancer death, this show that cumulated exposure is a most important risk factor of lung cancer death on uranium miners. It has been documented by many foreign reports that the lung cancer death rate is higher in uranium miners

Student-generated questions during chemistry lectures: Patterns, self-appraisals, and relations with motivational beliefs and achievement

Science.gov (United States)

Bergey, Bradley W.

Self-generated questions are a central mechanism for learning, yet students' questions are often infrequent during classroom instruction. As a result, little is known about the nature of student questioning during typical instructional contexts such as listening to a lecture, including the extent and nature of student-generated questions, how students evaluate their questions, and the relations among questions, motivations, and achievement. This study examined the questions undergraduate students (N = 103) generated during 8 lectures in an introductory chemistry course. Students recorded and appraised their question in daily question logs and reported lecture-specific self-efficacy beliefs. Self-efficacy, personal interest, goal orientations, and other motivational self-beliefs were measured before and after the unit. Primary analyses included testing path models, multiple regressions, and latent class analyses. Overall, results indicated that several characteristics of student questioning during lectures were significantly related to various motivations and achievement. Higher end-of-class self-efficacy was associated with fewer procedural questions and more questions that reflected smaller knowledge deficits. Lower exam scores were associated with questions reflecting broader knowledge deficits and students' appraisals that their questions had less value for others than for themselves. Individual goal orientations collectively and positively predicted question appraisals. The questions students generated and their relations with motivational variables and achievement are discussed in light of the learning task and academic context.

Differences in the Drinking Behaviors of Chinese, Filipino, Korean, and Vietnamese College Students*

Science.gov (United States)

Lum, Chris; Corliss, Heather L.; Mays, Vickie M.; Cochran, Susan D.; Lui, Camillia K.

2009-01-01

Objective: This study examined alcohol drinking behaviors across ethnic subgroups of Asian college students by gender, foreign-born status, and college-related living arrangements. Method: Univariate and ordinal logistic regression analyses were employed to explore male and female Asian subgroup differences in alcohol drinking behaviors. The sample included 753 male and female undergraduates between the ages of 18 and 27 years who self-identified as Chinese, Filipino, Korean, or Vietnamese and who varied in their foreign-born status. Participants completed a self-administered questionnaire on their alcohol drinking practices. Results: Ordinal regression analysis assessed risks for increased consumption and found that Korean and Filipino students reported higher levels of alcohol consumption compared with other Asian subgroups. Students living in on-campus dormitories and in off-campus apartments reported higher alcohol consumption than did those living at home. Being born in the United States was a significant predictor of higher levels of alcohol consumption for women but not for men. Conclusions: Results of this study indicate the need for campus alcohol education and prevention programs capable of responding to specific Asian subgroup needs. PMID:19515297

Advanced statistics: linear regression, part II: multiple linear regression.

Science.gov (United States)

Marill, Keith A

2004-01-01

The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

Experiential learning in high energy physics: a survey of students at the LHC

Science.gov (United States)

Camporesi, Tiziano; Catalano, Gelsomina; Florio, Massimo; Giffoni, Francesco

2017-03-01

More than 36 000 students and post-docs will be involved until 2025 in research at the Large Hadron Collider (LHC) mainly through international collaborations. To what extent they value the skills acquired? Do students expect that their learning experience will have an impact on their professional future? By drawing from earlier literature on experiential learning, we have designed a survey of current and former students at LHC. To quantitatively measure the students’ perceptions, we compare the salary expectations of current students with the assessment of those now employed in different jobs. Survey data are analysed by ordered logistic regression models, which allow multivariate statistical analyses with limited dependent variables. Results suggest that experiential learning at LHC positively correlates with both current and former students’ salary expectations. Those already employed clearly confirm the expectations of current students. At least two not mutually exclusive explanations underlie the results. First, the training at LHC is perceived to provide students valuable skills, which in turn affect the salary expectations; secondly, the LHC research experience per se may act as signal in the labour market. Respondents put a price tag on their learning experience, a ‘LHC salary premium’ ranging from 5% to 12% compared with what they would have expected for their career without such an experience at CERN.

Boosted beta regression.

Directory of Open Access Journals (Sweden)

Matthias Schmid

Full Text Available Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale. In this paper, we consider beta regression, which is a generalization of logit models to situations where the response is continuous on the interval (0,1. Consequently, beta regression is a convenient tool for analyzing percentage responses. The classical approach to fit a beta regression model is to use maximum likelihood estimation with subsequent AIC-based variable selection. As an alternative to this established - yet unstable - approach, we propose a new estimation technique called boosted beta regression. With boosted beta regression estimation and variable selection can be carried out simultaneously in a highly efficient way. Additionally, both the mean and the variance of a percentage response can be modeled using flexible nonlinear covariate effects. As a consequence, the new method accounts for common problems such as overdispersion and non-binomial variance structures.

A Logistic Regression Analysis of Score Sending and College Matching among High School Students

Science.gov (United States)

Oates, Krystle S.

2015-01-01

College decisions are often the result of a variety of influences related to student background characteristics, academic characteristics, college preferences and college aspirations. College counselors recommend that students choose a variety of schools, especially schools where the general student body matches the academic achievement of…

Analysing Simple Electric Motors in the Classroom

Science.gov (United States)

Yap, Jeff; MacIsaac, Dan

2006-01-01

Electromagnetic phenomena and devices such as motors are typically unfamiliar to both teachers and students. To better visualize and illustrate the abstract concepts (such as magnetic fields) underlying electricity and magnetism, we suggest that students construct and analyse the operation of a simply constructed Johnson electric motor. In this…

ENHANCED PREDICTION OF STUDENT DROPOUTS USING FUZZY INFERENCE SYSTEM AND LOGISTIC REGRESSION

OpenAIRE

A. Saranya; J. Rajeswari

2016-01-01

Predicting college and school dropouts is a major problem in educational system and has complicated challenge due to data imbalance and multi dimensionality, which can affect the low performance of students. In this paper, we have collected different database from various colleges, among these 500 best real attributes are identified in order to identify the factor that affecting dropout students using neural based classification algorithm and different mining technique are implemented for dat...

Correcting for multivariate measurement error by regression calibration in meta-analyses of epidemiological studies

DEFF Research Database (Denmark)

Tybjærg-Hansen, Anne

2009-01-01

Within-person variability in measured values of multiple risk factors can bias their associations with disease. The multivariate regression calibration (RC) approach can correct for such measurement error and has been applied to studies in which true values or independent repeat measurements...... of the risk factors are observed on a subsample. We extend the multivariate RC techniques to a meta-analysis framework where multiple studies provide independent repeat measurements and information on disease outcome. We consider the cases where some or all studies have repeat measurements, and compare study......-specific, averaged and empirical Bayes estimates of RC parameters. Additionally, we allow for binary covariates (e.g. smoking status) and for uncertainty and time trends in the measurement error corrections. Our methods are illustrated using a subset of individual participant data from prospective long-term studies...

The writing approaches of secondary students.

Science.gov (United States)

Lavelle, Ellen; Smith, Jennifer; O'Ryan, Leslie

2002-09-01

process dimensions. The first factor, Elaborative-Expressive, describes a writing strategy based on personal investment and audience concern. The second factor, Planful-Procedural, denotes sticking to a plan, following the rules, and 'preparing' for writing. Achieving-Competitive, the third factor, reflects a 'teacher pleasing' strategy or doing only what needs to be done to get a good grade. Two factors from the college model, Elaborative and Procedural, were replicated, and two were not, Reflective-Revision and Low Self-Efficacy. Regression analyses supported that the processes in writing under a timed condition are different from those used when writing over time, and that students' perceptions of writing self-regulatory efficacy were predictive of writing success under both conditions.

The educational value of online mastery quizzes in a human anatomy course for first-year dental students.

Science.gov (United States)

Lee, Lisa M J; Nagel, Rollin W; Gould, Douglas J

2012-09-01

The purpose of this study was to evaluate the effectiveness of online mastery quizzes in enhancing dental students' learning and preparedness for anatomy examinations. First-year dental students taking an integrated anatomy course at The Ohio State University were administered online mastery quizzes, made available for five days before each examination. The mastery quizzes were comprised of ten multiple-choice questions representative of the upcoming examination in content and difficulty. The students were allowed to access this resource as many times as they desired during the five-day window before each examination; the highest score for each student was added to his or her final course grade. The results indicate that almost all the students took advantage of this resource to reinforce content, clarify concepts, and prepare for the examinations. Statistical analyses of the students' exam performance showed that the mastery quizzes neither improved nor reduced their exam scores, but multiple regression analyses showed that the initial mastery quiz scores had a predictive value for their examination performance, suggesting a potential for mastery quizzes as an intervention tool for such a course. Online mastery quizzes, when used effectively, may be an effective resource to further engage dental and other students in educational endeavors and examination preparation and as a predictor of success.

Determining the Factors of Social Phobia Levels of University Students: A Logistic Regression Analysis

Science.gov (United States)

Ozen, Hamit

2016-01-01

Experiencing social phobia is an important factor which can hinder academic success during university years. In this study, research of social phobia with several variables is conducted among university students. The research group of the study consists of total 736 students studying at various departments at universities in Turkey. Students are…

Exploring Person Fit with an Approach Based on Multilevel Logistic Regression

Science.gov (United States)

Walker, A. Adrienne; Engelhard, George, Jr.

2015-01-01

The idea that test scores may not be valid representations of what students know, can do, and should learn next is well known. Person fit provides an important aspect of validity evidence. Person fit analyses at the individual student level are not typically conducted and person fit information is not communicated to educational stakeholders. In…

Information fusion via constrained principal component regression for robust quantification with incomplete calibrations

International Nuclear Information System (INIS)

Vogt, Frank

2013-01-01

Graphical abstract: Analysis Task: Determine the albumin (= protein) concentration in microalgae cells as a function of the cells’ nutrient availability. Left Panel: The predicted albumin concentrations as obtained by conventional principal component regression features low reproducibility and are partially higher than the concentrations of algae in which albumin is contained. Right Panel: Augmenting an incomplete PCR calibration with additional expert information derives reasonable albumin concentrations which now reveal a significant dependency on the algae's nutrient situation. -- Highlights: •Make quantitative analyses of compounds embedded in largely unknown chemical matrices robust. •Improved concentration prediction with originally insufficient calibration models. •Chemometric approach for incorporating expertise from other fields and/or researchers. •Ensure chemical, biological, or medicinal meaningfulness of quantitative analyses. -- Abstract: Incomplete calibrations are encountered in many applications and hamper chemometric data analyses. Such situations arise when target analytes are embedded in a chemically complex matrix from which calibration concentrations cannot be determined with reasonable efforts. In other cases, the samples’ chemical composition may fluctuate in an unpredictable way and thus cannot be comprehensively covered by calibration samples. The reason for calibration model to fail is the regression principle itself which seeks to explain measured data optimally in terms of the (potentially incomplete) calibration model but does not consider chemical meaningfulness. This study presents a novel chemometric approach which is based on experimentally feasible calibrations, i.e. concentration series of the target analytes outside the chemical matrix (‘ex situ calibration’). The inherent lack-of-information is then compensated by incorporating additional knowledge in form of regression constraints. Any outside knowledge can be

Paradox of spontaneous cancer regression: implications for fluctuational radiothermy and radiotherapy

International Nuclear Information System (INIS)

Roy, Prasun K.; Dutta Majumder, D.; Biswas, Jaydip

1999-01-01

Spontaneous regression of malignant tumours without treatment is a most enigmatic phenomenon with immense therapeutic potentialities. We analyse such cases to find that the commonest cause is a preceding episode of high fever-induced thermal fluctuation which produce fluctuation of biochemical and immunological parameters. Using Prigogine-Glansdorff thermodynamic stability formalism and biocybernetic principles, we develop the theoretical foundation of tumour regression induced by thermal, radiational or oxygenational fluctuations. For regression, a preliminary threshold condition of fluctuations is derived, namely σ > 2.83. We present some striking confirmation of such fluctuation-induced regression of various therapy-resistant masses as Ewing tumour, neurogranuloma and Lewis lung carcinoma by utilising σ > 2.83. Our biothermodynamic stability model of malignancy appears to illuminate the marked increase of aggressiveness of mammalian malignancy which occurred around 250 million years ago when homeothermic warm-blooded pre-mammals evolved. Using experimental data, we propose a novel approach of multi-modal hyper-fluctuation therapy involving modulation of radiotherapeutic hyper-fractionation, temperature, radiothermy and immune-status. (author)

EXPLORING THE RELATIONS BETWEEN STUDENT CYNICISM AND STUDENT BURNOUT.

Science.gov (United States)

Wei, Xueyan; Wang, Rongrong; Macdonald, Elizabeth

2015-08-01

Research on the negative effects of student cynicism has been limited, especially regarding its relation to student burnout. This study examined the relations among student cynicism (policy cynicism, academic cynicism, social cynicism, and institutional cynicism) and student burnout, as evidenced by emotional exhaustion, depersonalization, and reduced personal accomplishment, in a sample of 276 Chinese undergraduates. Hierarchical multiple regressions showed that four aspects of student cynicism together explained substantial variance in student burnout. Policy cynicism was the strongest contributor to emotional exhaustion. Social cynicism was the primary contributor to depersonalization, and also to reduced personal accomplishment. Student cynicism overall had the strongest relationship with reduced sense of personal achievement. The findings outline the negative functional relations between student cynicism and student burnout.

Freshman Year Dropouts: Interactions between Student and School Characteristics and Student Dropout Status

Science.gov (United States)

Zvoch, Keith

2006-01-01

Data from a large school district in the southwestern United States were analyzed to investigate relations between student and school characteristics and high school freshman dropout patterns. Application of a multilevel logistic regression model to student dropout data revealed evidence of school-to-school differences in student dropout rates and…

Physics constrained nonlinear regression models for time series

International Nuclear Information System (INIS)

Majda, Andrew J; Harlim, John

2013-01-01

A central issue in contemporary science is the development of data driven statistical nonlinear dynamical models for time series of partial observations of nature or a complex physical model. It has been established recently that ad hoc quadratic multi-level regression (MLR) models can have finite-time blow up of statistical solutions and/or pathological behaviour of their invariant measure. Here a new class of physics constrained multi-level quadratic regression models are introduced, analysed and applied to build reduced stochastic models from data of nonlinear systems. These models have the advantages of incorporating memory effects in time as well as the nonlinear noise from energy conserving nonlinear interactions. The mathematical guidelines for the performance and behaviour of these physics constrained MLR models as well as filtering algorithms for their implementation are developed here. Data driven applications of these new multi-level nonlinear regression models are developed for test models involving a nonlinear oscillator with memory effects and the difficult test case of the truncated Burgers–Hopf model. These new physics constrained quadratic MLR models are proposed here as process models for Bayesian estimation through Markov chain Monte Carlo algorithms of low frequency behaviour in complex physical data. (paper)

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

Science.gov (United States)

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...

Regressão múltipla stepwise e hierárquica em Psicologia Organizacional: aplicações, problemas e soluções Stepwise and hierarchical multiple regression in organizational psychology: Applications, problemas and solutions

Directory of Open Access Journals (Sweden)

Gardênia Abbad

2002-01-01

Full Text Available Este artigo discute algumas aplicações das técnicas de análise de regressão múltipla stepwise e hierárquica, as quais são muito utilizadas em pesquisas da área de Psicologia Organizacional. São discutidas algumas estratégias de identificação e de solução de problemas relativos à ocorrência de erros do Tipo I e II e aos fenômenos de supressão, complementaridade e redundância nas equações de regressão múltipla. São apresentados alguns exemplos de pesquisas nas quais esses padrões de associação entre variáveis estiveram presentes e descritas as estratégias utilizadas pelos pesquisadores para interpretá-los. São discutidas as aplicações dessas análises no estudo de interação entre variáveis e na realização de testes para avaliação da linearidade do relacionamento entre variáveis. Finalmente, são apresentadas sugestões para lidar com as limitações das análises de regressão múltipla (stepwise e hierárquica.This article discusses applications of stepwise and hierarchical multiple regression analyses to research in organizational psychology. Strategies for identifying type I and II errors, and solutions to potential problems that may arise from such errors are proposed. In addition, phenomena such as suppression, complementarity, and redundancy are reviewed. The article presents examples of research where these phenomena occurred, and the manner in which they were explained by researchers. Some applications of multiple regression analyses to studies involving between-variable interactions are presented, along with tests used to analyze the presence of linearity among variables. Finally, some suggestions are provided for dealing with limitations implicit in multiple regression analyses (stepwise and hierarchical.

Logistic regression analysis to predict Medical Licensing Examination of Thailand (MLET) Step1 success or failure.

Science.gov (United States)

Wanvarie, Samkaew; Sathapatayavongs, Boonmee

2007-09-01

The aim of this paper was to assess factors that predict students' performance in the Medical Licensing Examination of Thailand (MLET) Step1 examination. The hypothesis was that demographic factors and academic records would predict the students' performance in the Step1 Licensing Examination. A logistic regression analysis of demographic factors (age, sex and residence) and academic records [high school grade point average (GPA), National University Entrance Examination Score and GPAs of the pre-clinical years] with the MLET Step1 outcome was accomplished using the data of 117 third-year Ramathibodi medical students. Twenty-three (19.7%) students failed the MLET Step1 examination. Stepwise logistic regression analysis showed that the significant predictors of MLET Step1 success/failure were residence background and GPAs of the second and third preclinical years. For students whose sophomore and third-year GPAs increased by an average of 1 point, the odds of passing the MLET Step1 examination increased by a factor of 16.3 and 12.8 respectively. The minimum GPAs for students from urban and rural backgrounds to pass the examination were estimated from the equation (2.35 vs 2.65 from 4.00 scale). Students from rural backgrounds and/or low-grade point averages in their second and third preclinical years of medical school are at risk of failing the MLET Step1 examination. They should be given intensive tutorials during the second and third pre-clinical years.

An Investigation of Predictors of Life Satisfaction among Overseas Iranian Undergraduate Students

Directory of Open Access Journals (Sweden)

Razieh Tadayon Nabavi

2018-02-01

Full Text Available In recent years, many young people have gone overseas to study and live at least temporarily in new countries that maybe quite different to their homeland. The aim of this study was to determine the predictors of life satisfaction among Iranian undergraduate students studying at Malaysian private universities. A total of 361 undergraduate students were identified as respondents of this study by using Multi-Stage random sampling technique. The results of the study showed that the Iranian undergraduate students were moderately satisfied with their overseas student life. Findings also showed that the results of multiple regression analyses indicated social support emerged as the strongest unique predictor of life satisfaction, followed by academic achievement, and adjustment. Findings revealed that 44.8% of the variability in life satisfaction could be predicted by social support, academic achievement, and adjustment. The results also indicated that social support significantly mediated the effect of loneliness on life satisfaction.

Alcohol use among Hispanic college students along the US/Mexico border.

Science.gov (United States)

Montoya, Jared A; Wittenburg, David; Martinez, Vanessa

2016-11-01

The trend of alcohol use among college students has been shown to vary by ethnicity and has been linked to acculturation among Hispanics. Consistent findings indicate that males consume alcohol more frequently and in greater quantities compared to females. This study investigated the drinking habits of Hispanic college students living in the border region of South Texas. The study evaluated the influence of acculturation on alcohol consumption among Hispanic males and females. Two hundred and ninety-six Hispanic students participated in this study. The participants reported their drinking behaviors over the past 30 days and completed a measure of acculturation. Fifty-nine percent of the participants reported consuming alcohol in the past 30 days with more males than females reporting alcohol consumption. Logistic regression analysis indicated that age and gender, and not acculturation or enculturation, predicted drinking in the last 30 days. Among drinkers, the regression analyses indicated that gender and lower levels of Anglo orientation were linked to increased alcohol consumption, suggesting that Hispanics who were less oriented toward the Anglo culture consumed more alcohol than those more oriented toward the Anglo culture. Among drinkers, males and females did not differ in frequency or binge drinking, but males consumed more alcohol than females. Previous research indicates that greater acculturation is linked to greater consumption of alcohol; however, we found it to be associated with less consumption. The findings regarding gender represent some consistencies with previous research but there are some inconsistencies as well. These results suggest that less acculturated Hispanic male college students residing in the border region may be at a higher risk of alcohol abuse than Hispanic female students and more acculturated male students.

Use of probabilistic weights to enhance linear regression myoelectric control

Science.gov (United States)

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.

Evaluation of Linear Regression Simultaneous Myoelectric Control Using Intramuscular EMG.

Science.gov (United States)

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

2016-04-01

The objective of this study was to evaluate the ability of linear regression models to decode patterns of muscle coactivation from intramuscular electromyogram (EMG) and provide simultaneous myoelectric control of a virtual 3-DOF wrist/hand system. Performance was compared to the simultaneous control of conventional myoelectric prosthesis methods using intramuscular EMG (parallel dual-site control)-an approach that requires users to independently modulate individual muscles in the residual limb, which can be challenging for amputees. Linear regression control was evaluated in eight able-bodied subjects during a virtual Fitts' law task and was compared to performance of eight subjects using parallel dual-site control. An offline analysis also evaluated how different types of training data affected prediction accuracy of linear regression control. The two control systems demonstrated similar overall performance; however, the linear regression method demonstrated improved performance for targets requiring use of all three DOFs, whereas parallel dual-site control demonstrated improved performance for targets that required use of only one DOF. Subjects using linear regression control could more easily activate multiple DOFs simultaneously, but often experienced unintended movements when trying to isolate individual DOFs. Offline analyses also suggested that the method used to train linear regression systems may influence controllability. Linear regression myoelectric control using intramuscular EMG provided an alternative to parallel dual-site control for 3-DOF simultaneous control at the wrist and hand. The two methods demonstrated different strengths in controllability, highlighting the tradeoff between providing simultaneous control and the ability to isolate individual DOFs when desired.

Differences between immigrant and national students in motivational variables and classroom-motivational-climate perception.

Science.gov (United States)

Alonso-Tapia, Jesús; Simón, Carmen

2012-03-01

The objective of this study is to see whether Immigrant (IM) and Spanish (National) students (SP) need different kinds of help from teachers due to differences in motivation, family expectancies and interests and classroom-motivational-climate perception. A sample of Secondary Students -242 Spanish and 243 Immigrants- completed questionnaires assessing goal orientations and expectancies, family attitudes towards academic work, perception of classroom motivational climate and of its effects, satisfaction, disruptive behavior and achievement. ANOVAs showed differences in many of the motivational variables assessed as well as in family attitudes. In most cases, Immigrant students scored lower than Spanish students in the relevant variables. Regression analyses showed that personal and family differences were related to student's satisfaction, achievement and disruptive behavior. Finally, multi-group analysis of classroom-motivational-climate (CMC) showed similarities and differences in the motivational value attributed by IM and SP to each specific teaching pattern that configure the CMC. IM lower self-esteem could explain these results, whose implications for teaching and research are discussed.

Using synthetic data to evaluate multiple regression and principal component analyses for statistical modeling of daily building energy consumption

Energy Technology Data Exchange (ETDEWEB)

Reddy, T.A. (Energy Systems Lab., Texas A and M Univ., College Station, TX (United States)); Claridge, D.E. (Energy Systems Lab., Texas A and M Univ., College Station, TX (United States))

1994-01-01

Multiple regression modeling of monitored building energy use data is often faulted as a reliable means of predicting energy use on the grounds that multicollinearity between the regressor variables can lead both to improper interpretation of the relative importance of the various physical regressor parameters and to a model with unstable regressor coefficients. Principal component analysis (PCA) has the potential to overcome such drawbacks. While a few case studies have already attempted to apply this technique to building energy data, the objectives of this study were to make a broader evaluation of PCA and multiple regression analysis (MRA) and to establish guidelines under which one approach is preferable to the other. Four geographic locations in the US with different climatic conditions were selected and synthetic data sequence representative of daily energy use in large institutional buildings were generated in each location using a linear model with outdoor temperature, outdoor specific humidity and solar radiation as the three regression variables. MRA and PCA approaches were then applied to these data sets and their relative performances were compared. Conditions under which PCA seems to perform better than MRA were identified and preliminary recommendations on the use of either modeling approach formulated. (orig.)

The Application of Classical and Neural Regression Models for the Valuation of Residential Real Estate

Directory of Open Access Journals (Sweden)

Mach Łukasz

2017-06-01

Full Text Available The research process aimed at building regression models, which helps to valuate residential real estate, is presented in the following article. Two widely used computational tools i.e. the classical multiple regression and regression models of artificial neural networks were used in order to build models. An attempt to define the utilitarian usefulness of the above-mentioned tools and comparative analysis of them is the aim of the conducted research. Data used for conducting analyses refers to the secondary transactional residential real estate market.

Medical Student Exposure to Cancer Patients Whilst on Clinical Placement: a Retrospective Analyses of Clinical Log Books.

Science.gov (United States)

Starmer, Darren L

2018-04-19

In Australia, one in two men and one in three women will be diagnosed with cancer by the age of 85. Several studies have demonstrated a decline in the number of medical graduates having examined cancer patients during their training. The aim of this study was to evaluate the exposure of medical students to cancer patients during clinical placements. Eighty-eight logbooks (response rate = 24.75%) containing 9430 patients were analysed. A total of 829 patients (8.79%) had a diagnosis of cancer. Most cancer patients were seen on surgical placements, whilst general practice placements returned the lowest numbers. None were seen in paediatrics or ophthalmology. Given the role surgery plays in the staging and treatment of cancer, it is unsurprising that most cancer patients were seen during surgery.  Most concerning was the number of patients with common cancers seen by our students. Only 46% of students saw a patient with breast cancer. Even fewer saw patients with colorectal (41%), lung (32%) and prostate cancer (30%). Only 14% saw a melanoma patient. Variability in the quality of the logbooks is the main limitation of this study, and therefore, it is not a complete picture of cancer patient exposure. However, it builds upon previous studies by providing insight to the number and types of cancer patients to which students were exposed. Overall, the exposure to common cancers remains concerning and further research is needed to explore the type and quality of these interactions over the course of an entire year.

Determinants of alcohol use and khat chewing among Hawassa University students, Ethiopia: a cross sectional study.

Science.gov (United States)

Kassa, Andargachew; Wakgari, Negash; Taddesse, Fiker

2016-09-01

Students' alcohol and khat use have been associated with various health related problems. However, its magnitude and associated factors among Ethiopian students are not yet well documented. The study aimed to assess the prevalence of alcohol use, khat chewing and its associated factors among Hawassa University students. A cross-sectional study was conducted from June to July 2011. Multistage stratified sampling technique was employed to select 590 students. Self administered questionnaires were used to collect data. Data was entered and analysed by SPSS version 20.0. Logistic regression analyses were used to identify the association of different variables. The current prevalence of student's alcohol and khat use were 29.5% (95% CI: 25.8-33.3) and 16.3% (95% CI: 13.7-20.0) respectively. Being male (AOR 1.8; 95% CI 1.1-3.0) and living alone (AOR 20.1; 95% CI 2.5-166.7) had a higher odds of alcohol use. Similarly, family substance use history (AOR 4.8; 95% CI 2.5-9.3) and peer influence (AOR 4.6; 95% CI 2.3-9.0) had also higher odds of khat use. The proportion of student's khat chewing and alcohol use was significant. Hence, higher education in collaboration with other stakeholders should work on convincing students about the ill effects of these substances.

Student Assistance Program Outcomes for Students at Risk for Suicide

Science.gov (United States)

Biddle, Virginia Sue; Kern, John, III; Brent, David A.; Thurkettle, Mary Ann; Puskar, Kathryn R.; Sekula, L. Kathleen

2014-01-01

Pennsylvania's response to adolescent suicide is its Student Assistance Program (SAP). SAP has been funded for 27 years although no statewide outcome studies using case-level data have been conducted. This study used logistic regression to examine drug-/alcohol-related behaviors and suspensions of suicidal students who participated in SAP. Of the…

Tax System in Poland – Progressive or Regressive?

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Jacek Tomkiewicz

2016-03-01

Full Text Available Purpose: To analyse the impact of the Polish fiscal regime on the general revenue of the country, and specifically to establish whether the cumulative tax burden borne by Polish households is progressive or regressive.Methodology: On the basis of Eurostat and OECD data, the author has analysed fiscal regimes in EU Member States and in OECD countries. The tax burden of households within different income groups has also been examined pursuant to applicable fiscal laws and data pertaining to the revenue and expenditure of households published by the Central Statistical Office (CSO.Conclusions: The fiscal regime in Poland is regressive; that is, the relative fiscal burden decreases as the taxpayer’s income increases.Research Implications: The article contributes to the on-going discussion on social cohesion, in particular with respect to economic policy instruments aimed at the redistribution of income within the economy.Originality: The author presents an analysis of data pertaining to fiscal policies in EU Member States and OECD countries and assesses the impact of the legal environment (fiscal regime and social security system in Poland on income distribution within the economy. The impact of the total tax burden (direct and indirect taxes, social security contributions on the economic situation of households from different income groups has been calculated using an original formula.

PEMODELAN JUMLAH ANAK PUTUS SEKOLAH DI PROVINSI BALI DENGAN PENDEKATAN SEMI-PARAMETRIC GEOGRAPHICALLY WEIGHTED POISSON REGRESSION

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GUSTI AYU RATIH ASTARI

2013-11-01

Full Text Available Dropout number is one of the important indicators to measure the human progress resources in education sector. This research uses the approaches of Semi-parametric Geographically Weighted Poisson Regression to get the best model and to determine the influencing factors of dropout number for primary education in Bali. The analysis results show that there are no significant differences between the Poisson regression model with GWPR and Semi-parametric GWPR. Factors which significantly influence the dropout number for primary education in Bali are the ratio of students to school, ratio of students to teachers, the number of families with the latest educational fathers is elementary or junior high school, illiteracy rates, and the average number of family members.

The non-condition logistic regression analysis of the reason of hypothyroidism after hyperthyroidism with 131I treatment

International Nuclear Information System (INIS)

Dang Yaping; Hu Guoying; Meng Xianwen

1994-01-01

There are many opinions on the reason of hypothyroidism after hyperthyroidism with 131 I treatment. In this respect, there are a few scientific analyses and reports. The non-condition logistic regression solved this problem successfully. It has a higher scientific value and confidence in the risk factor analysis. 748 follow-up patients' data were analysed by the non-condition logistic regression. The results shown that the half-life and 131 I dose were the main causes of the incidence of hypothyroidism. The degree of confidence is 92.4%

Spatial regression analysis on 32 years of total column ozone data

NARCIS (Netherlands)

Knibbe, J.S.; van der A, J.R.; de Laat, A.T.J.

2014-01-01

Multiple-regression analyses have been performed on 32 years of total ozone column data that was spatially gridded with a 1 × 1.5° resolution. The total ozone data consist of the MSR (Multi Sensor Reanalysis; 1979-2008) and 2 years of assimilated SCIAMACHY (SCanning Imaging Absorption spectroMeter

Students' Persistence and Academic Success in a First-Year Professional Bachelor Program: The Influence of Students' Learning Strategies and Academic Motivation

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Gert Vanthournout

2012-01-01

Full Text Available The present study explores whether students' learning strategies and academic motivation predict persistence and academic success in the first year of higher education. Freshmen students in a professional bachelor program in teacher education were questioned on their learning strategy use and motivation at the start and at the end of the academic year. Students' learning strategies were assessed using the inventory of learning styles-SV. Motivation was measured using scales from the self-regulation questionnaire and the academic motivation scale. Gender and students' prior education were incorporated as control variables. Logistic regression analyses and general linear modelling were applied to predict persistence and academic success, respectively. In each case a stepwise approach in data analysis was used. Results on persistence indicate that lack of regulation and amotivation at the start of the year are significant predictors. For academic success, results showed that relating and structuring, lack of regulation, and lack of motivation at the end of the year are meaningful predictors. Overall, our study demonstrates that learning strategies and motivation have a moderate explanatory value regarding academic success and persistence, and that these effects remain even after controlling for the influence of background variables.

The mediating effect of calling on the relationship between medical school students' academic burnout and empathy.

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Chae, Su Jin; Jeong, So Mi; Chung, Yoon-Sok

2017-09-01

This study is aimed at identifying the relationships between medical school students' academic burnout, empathy, and calling, and determining whether their calling has a mediating effect on the relationship between academic burnout and empathy. A mixed method study was conducted. One hundred twenty-seven medical students completed a survey. Scales measuring academic burnout, medical students' empathy, and calling were utilized. For statistical analysis, correlation analysis, descriptive statistics analysis, and hierarchical multiple regression analyses were conducted. For qualitative approach, eight medical students participated in a focus group interview. The study found that empathy has a statistically significant, negative correlation with academic burnout, while having a significant, positive correlation with calling. Sense of calling proved to be an effective mediator of the relationship between academic burnout and empathy. This result demonstrates that calling is a key variable that mediates the relationship between medical students' academic burnout and empathy. As such, this study provides baseline data for an education that could improve medical students' empathy skills.

Raising the stakes: How students' motivation for mathematics associates with high- and low-stakes test achievement.

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Simzar, Rahila M; Martinez, Marcela; Rutherford, Teomara; Domina, Thurston; Conley, AnneMarie M

2015-04-01

This study uses data from an urban school district to examine the relation between students' motivational beliefs about mathematics and high- versus low-stakes math test performance. We use ordinary least squares and quantile regression analyses and find that the association between students' motivation and test performance differs based on the stakes of the exam. Students' math self-efficacy and performance avoidance goal orientation were the strongest predictors for both exams; however, students' math self-efficacy was more strongly related to achievement on the low-stakes exam. Students' motivational beliefs had a stronger association at the low-stakes exam proficiency cutoff than they did at the high-stakes passing cutoff. Lastly, the negative association between performance avoidance goals and high-stakes performance showed a decreasing trend across the achievement distribution, suggesting that performance avoidance goals are more detrimental for lower achieving students. These findings help parse out the ways motivation influences achievement under different stakes.

Economic Analyses of Ware Yam Production in Orlu Agricultural ...

African Journals Online (AJOL)

Economic Analyses of Ware Yam Production in Orlu Agricultural Zone of Imo State. ... International Journal of Agriculture and Rural Development ... statistics, gross margin analysis, marginal analysis and multiple regression analysis. Results ...

Regression Levels of Selected Affective Factors on Science Achievement: A Structural Equation Model with TIMSS 2011 Data

Science.gov (United States)

Akilli, Mustafa

2015-01-01

The aim of this study is to demonstrate the science success regression levels of chosen emotional features of 8th grade students using Structural Equation Model. The study was conducted by the analysis of students' questionnaires and science success in TIMSS 2011 data using SEM. Initially, the factors that are thought to have an effect on science…

Quantile regression for the statistical analysis of immunological data with many non-detects.

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Eilers, Paul H C; Röder, Esther; Savelkoul, Huub F J; van Wijk, Roy Gerth

2012-07-07

Immunological parameters are hard to measure. A well-known problem is the occurrence of values below the detection limit, the non-detects. Non-detects are a nuisance, because classical statistical analyses, like ANOVA and regression, cannot be applied. The more advanced statistical techniques currently available for the analysis of datasets with non-detects can only be used if a small percentage of the data are non-detects. Quantile regression, a generalization of percentiles to regression models, models the median or higher percentiles and tolerates very high numbers of non-detects. We present a non-technical introduction and illustrate it with an implementation to real data from a clinical trial. We show that by using quantile regression, groups can be compared and that meaningful linear trends can be computed, even if more than half of the data consists of non-detects. Quantile regression is a valuable addition to the statistical methods that can be used for the analysis of immunological datasets with non-detects.

Internship workplace preferences of final-year medical students at Zagreb University Medical School, Croatia: all roads lead to Zagreb.

Science.gov (United States)

Polasek, Ozren; Kolcic, Ivana; Dzakula, Aleksandar; Bagat, Mario

2006-04-01

Human resources management in health often encounters problems related to workforce geographical distribution. The aim of this study was to investigate the internship workplace preferences of final-year medical students and the reasons associated with their choices. A total of 204 out of 240 final-year medical students at Zagreb University Medical School, Croatia, were surveyed a few months before graduation. We collected data on each student's background, workplace preference, academic performance and emigration preferences. Logistic regression was used to analyse the factors underlying internship workplace preference, classified into two categories: Zagreb versus other areas. Only 39 respondents (19.1%) wanted to obtain internships outside Zagreb, the Croatian capital. Gender and age were not significantly associated with internship workplace preference. A single predictor variable significantly contributed to the logistic regression model: students who believed they would not get the desired specialty more often chose Zagreb as a preferred internship workplace (odds ratio 0.32, 95% CI 0.12-0.86). A strong preference for Zagreb as an internship workplace was recorded. Uncertainty about getting the desired specialty was associated with choosing Zagreb as a workplace, possibly due to more extensive and diverse job opportunities.

Stressors and psychological symptoms in students of medicine and allied health professions in Nigeria.

Science.gov (United States)

Omigbodun, Olayinka O; Odukogbe, Akin-Tunde A; Omigbodun, Akinyinka O; Yusuf, O Bidemi; Bella, Tolulope T; Olayemi, Oladopo

2006-05-01

Studies suggest that high levels of stress and psychological morbidity occur in health care profession students. This study investigates stressors and psychological morbidity in students of medicine, dentistry, physiotherapy and nursing at the University of Ibadan. The students completed a questionnaire about their socio-demographic characteristics, perceived stressors and the 12-item General Health Questionnaire. Qualitative methods were used initially to categorise stressors. Data was then analysed using univariate and logistic regression to determine odds ratios and 95% confidence intervals. Medical and dental students were more likely to cite as stressors, overcrowding, strikes, excessive school work and lack of holidays while physiotherapy and nursing students focused on noisy environments, security and transportation. Medical and dental students (1.66; SD: 2.22) had significantly higher GHQ scores than the physiotherapy and nursing students (1.22; SD: 1.87) (t = 2.3; P = 0.022). Socio-demographic factors associated with psychological morbidity after logistic regression include being in a transition year of study, reporting financial distress and not being a 'Pentecostal Christian'. Although males were more likely to perceive financial and lecturer problems as stressors and females to perceive faculty strikes and overcrowding as source of stress, gender did not have any significant effect on psychological morbidity. Stressors associated with psychological distress in the students include excessive school work, congested classrooms, strikes by faculty, lack of laboratory equipment, family problems, insecurity, financial and health problems. Several identified stressors such as financial problems, academic pressures and their consequent effect on social life have an adverse effect on the mental health of students in this environment especially for students of medicine and dentistry. While stressors outside the reach of the school authorities are difficult to

Spiritual Well-Being and Its Relationship with Mindfulness, Self-Compassion and Satisfaction with Life in Baccalaureate Nursing Students: A Correlation Study.

Science.gov (United States)

Mathad, Monali D; Rajesh, S K; Pradhan, Balaram

2017-12-06

The present study aimed to explore the correlates and predictors of spiritual well-being among nursing students. One hundred and forty-five BSc nursing students were recruited from three nursing colleges in Bangalore, Karnataka, India. Data were collected using SHALOM, FMI, SCS-SF and SWLS questionnaires and analysed by the Pearson correlation test and multiple regression analysis. The results of our study revealed a significant correlation between variables, and a considerable amount of variance was explained by self-compassion, mindfulness and satisfaction with life on personal, communal, environmental and transcendental domains of spiritual well-being.

[Predictors of success among first-year medical students at the University of Parakou].

Science.gov (United States)

Adoukonou, Thierry; Tognon-Tchegnonsi, Francis; Mensah, Emile; Allodé, Alexandre; Adovoekpe, Jean-Marie; Gandaho, Prosper; Akpona, Simon

2016-01-01

Several factors including grades obtained in the Baccalaureate can influence academic performance of first year medical students. The aim of this study was to evaluate the relationship between results achieved by students taking Baccalaureate exam and student academic success during the first year of medical school. We conducted an analytical study that included the whole number of students regularly enrolled in their first year of medical school at the university of Parakou in the academic year 2010-2011. Data for the scores for each academic discipline and distinction obtained in the Baccalaureate were collected. Multivariate analysis using logistic regression and multiple linear regression made it possible to determine the best predictors of success and grade point average obtained by students at the end of the year. SPSS Statistics 17.0 was used to analyse data and a p value p grade point average obtained in the Baccalaureate and honors obtained in the Baccalaureate were associated with their success at the end of the year, but in multivariate analysis only a score in physical sciences > 15/20 was associated with success (OR: 2,8 [1,32-6,00]). Concerning the general average grade obtained at the end of the year, only an honor obtained in the Baccalaureate was associated (standard error of the correlation coefficient: 0,130 Beta =0,370 and p=0,00001). The best predictors of student academic success during the first year were a good grade point average in physical sciences during the Baccalaureate and an honor obtained in the Baccalaureate The inclusion of these elements in the enrollement of first-year students could improve academic performance.

Sensation seeking and alcohol use by college students: examining multiple pathways of effects.

Science.gov (United States)

Yanovitzky, Itzhak

2006-01-01

This study tests the proposition that peer influence mediates the effect of sensation seeking, a personality trait, on alcohol use among college students. Cross-sectional data to test this proposition were collected from a representative sample of college students at a large public northeastern university (N = 427). Results of hierarchical regression analyses showed that, as hypothesized, sensation seeking influenced personal alcohol use both directly and indirectly, through its impact on students' frequency of association with alcohol-using peers and the size of their drinking norm misperception. The findings suggest that interventions that seek to limit the frequency in which high sensation seekers associate with peers whose alcohol use is extreme or, alternatively, seek to facilitate social interactions of high sensation seekers with normative peers, may supplement efforts to influence sensation seekers' alcohol and other drug use through tailored mass media advertisements.

Strategic analyses in nursing schools: attracting, educating, and graduating more nursing students: part I--strengths, weaknesses, opportunities, and threats analysis.

Science.gov (United States)

Crow, Stephen M; Hartman, Sandra J; Mahesh, Sathiadev; McLendon, Christy L; Henson, Steve W; Jacques, Paul

2008-01-01

The shortage of nurses in the United States remains a persistent problem. Faced with this reality, nursing programs in colleges and universities continue to struggle to expand enrollment levels to meet the spiraling demand. This research uses familiar tools in strategic management: the strengths, weaknesses, opportunities, and threats (SWOT) analysis and stakeholder analysis as initial steps to draw more students to the profession of nursing. In a 2-round modified Delphi survey, chief administrators of schools of nursing identify the main SWOT of schools of nursing and the important internal and external stakeholders that influence nursing school success. The authors of the research suggest ways to use that knowledge to increase the enrollment level of nursing students. Part I of this research focuses on the SWOT analyses.

Predictors of students' self-esteem: The importance of body self-perception and exercise

Directory of Open Access Journals (Sweden)

Lazarević Ljiljana B.

2017-01-01

Full Text Available The goal of this study was to explore the predictive validity of physical self-efficacy, social physique anxiety, and physical activity in the self-esteem of students, as well as to investigate potential gender differences. The Rosenberg's Self-Esteem Scale (SES, Physical Self-Efficacy Scale (PSES, Social Physique Anxiety Scale (SPAS, and a short questionnaire about physical activity were administered to a sample of 232 university students. The overall results show that students are moderately physically active (on the average, 2.75 times per week, have moderately high selfesteem and physical self-efficacy and lower social physique anxiety. No gender differences were detected in self-esteem. In other variables, gender differences are significant and mostly in favour of males. The analyses showed that self-esteem correlated positively with physical self-efficacy and physical activity, and negatively with social physique anxiety. The regression analyses indicated that physical selfefficacy, social physique anxiety and female gender were significant predictors of self-esteem. Physical activity was not a significant predictor of self-esteem. Future studies should investigate the relations of body self-perceptions, physical exercise, and domain-specific self-esteem.

Area under the curve predictions of dalbavancin, a new lipoglycopeptide agent, using the end of intravenous infusion concentration data point by regression analyses such as linear, log-linear and power models.

Science.gov (United States)

Bhamidipati, Ravi Kanth; Syed, Muzeeb; Mullangi, Ramesh; Srinivas, Nuggehally

2018-02-01

1. Dalbavancin, a lipoglycopeptide, is approved for treating gram-positive bacterial infections. Area under plasma concentration versus time curve (AUC inf ) of dalbavancin is a key parameter and AUC inf /MIC ratio is a critical pharmacodynamic marker. 2. Using end of intravenous infusion concentration (i.e. C max ) C max versus AUC inf relationship for dalbavancin was established by regression analyses (i.e. linear, log-log, log-linear and power models) using 21 pairs of subject data. 3. The predictions of the AUC inf were performed using published C max data by application of regression equations. The quotient of observed/predicted values rendered fold difference. The mean absolute error (MAE)/root mean square error (RMSE) and correlation coefficient (r) were used in the assessment. 4. MAE and RMSE values for the various models were comparable. The C max versus AUC inf exhibited excellent correlation (r > 0.9488). The internal data evaluation showed narrow confinement (0.84-1.14-fold difference) with a RMSE models predicted AUC inf with a RMSE of 3.02-27.46% with fold difference largely contained within 0.64-1.48. 5. Regardless of the regression models, a single time point strategy of using C max (i.e. end of 30-min infusion) is amenable as a prospective tool for predicting AUC inf of dalbavancin in patients.

Burnout and Alcohol Abuse/Dependence Among U.S. Medical Students.

Science.gov (United States)

Jackson, Eric R; Shanafelt, Tait D; Hasan, Omar; Satele, Daniel V; Dyrbye, Liselotte N

2016-09-01

To explore the relationship between alcohol abuse/dependence with burnout and other forms of distress among a national cohort of medical students. In 2012, the authors completed a national survey of medical students from the American Medical Association's Physician Masterfile containing validated items assessing alcohol abuse/dependence, burnout, depression, suicidality, quality of life (QOL), and fatigue. Descriptive and comparative statistical analyses were computed, including chi-square and multivariate logistic regression, to determine relationships between variables. Of the 12,500 students, 4,402 (35.2%) responded. Of these, 1,411 (32.4%) met diagnostic criteria for alcohol abuse/dependence. Students who were burned out (P = .01), depressed (P = .01), or reported low mental (P =.03) or emotional (P = .016) QOL were more likely to have alcohol abuse/dependence. Emotional exhaustion and depersonalization domains of burnout were strongly associated with alcohol abuse/dependence. On multivariate analysis, burnout (OR 1.20; 95% CI 1.05-1.37; P $100,000 (OR 1.27 versus dependence. Burnout was strongly related to alcohol abuse/dependence among sampled medical students and increased educational debt predicted a higher risk. A multifaceted approach addressing burnout, medical education costs, and alcohol use is needed.

Flipped-learning course design and evaluation through student self-assessment in a predental science class.

Science.gov (United States)

Ihm, Jungjoon; Choi, Hyoseon; Roh, Sangho

2017-06-01

This study explores how to design a flipped classroom for a predental science course and evaluate its course through student self-assessment in order to provide practical implications for flipped learning in an undergraduate level. Second- and third-year predental students in the Seoul National University School of Dentistry enrolled in Biodiversity and Global Environment, a 15-week, three-credit course based on a flipped learning model. At the end of the course, the students were asked to rate their self-directed learning, attitude toward social media, discussion skills, learning readiness, and class satisfaction. Out of the 82 predental students, 61 (74.3%) answered the survey. Pearson correlation and multivariate regression analyses were employed to examine the relationship between the self-rated measurements and the performance scores. The majority of the students felt somewhat more prepared than the medium level before the class (mean score of 3.17 out of 5.00), whereas they expressed relatively low preference concerning social media use and attitude (mean score of 2.49). Thus, it was found that learning readiness was significantly associated with both discussion skills and class satisfaction. In particular, multivariate regression analysis confirmed that learning readiness had a significant influence on learning outcomes. This study offered insights into how to design a flipped learning course in terms of predental students' preference and their learning readiness. Although learning success in a flipped classroom depends on the students' self-perceived level of preparedness, much still remains to be achieved in order to apply social media benefits in a flipped learning context.

Predicting Performance on MOOC Assessments using Multi-Regression Models

OpenAIRE

Ren, Zhiyun; Rangwala, Huzefa; Johri, Aditya

2016-01-01

The past few years has seen the rapid growth of data min- ing approaches for the analysis of data obtained from Mas- sive Open Online Courses (MOOCs). The objectives of this study are to develop approaches to predict the scores a stu- dent may achieve on a given grade-related assessment based on information, considered as prior performance or prior ac- tivity in the course. We develop a personalized linear mul- tiple regression (PLMR) model to predict the grade for a student, prior to attempt...

Predictors of Prosocial Behavior among Chinese High School Students in Hong Kong

Directory of Open Access Journals (Sweden)

Andrew M. H. Siu

2012-01-01

Full Text Available This study examined the correlates and predictors of prosocial behavior among Chinese adolescents in Hong Kong. A sample of 518 high school students responded to a questionnaire containing measures of antisocial and prosocial behavior, prosocial norms, pragmatic values, moral reasoning, and empathy. Preliminary analyses showed that there were gender differences in some of the measures. While correlation analyses showed that parental education, prosocial norms, pragmatic values, moral reasoning, and empathy were related to prosocial behavior, regression analyses showed that prosocial norms, pragmatic values, and empathy dimensions (personal distress and empathy were key predictors of it. The findings are largely consistent with theoretical predictions and previous research findings, other than the negative relationship between personal distress and prosocial behavior. The study also underscores the importance of values and norms in predicting prosocial behavior, which has been largely neglected in previous studies.

Predictors of Prosocial Behavior among Chinese High School Students in Hong Kong

Science.gov (United States)

Siu, Andrew M. H.; Shek, Daniel T. L.; Lai, Frank H. Y.

2012-01-01

This study examined the correlates and predictors of prosocial behavior among Chinese adolescents in Hong Kong. A sample of 518 high school students responded to a questionnaire containing measures of antisocial and prosocial behavior, prosocial norms, pragmatic values, moral reasoning, and empathy. Preliminary analyses showed that there were gender differences in some of the measures. While correlation analyses showed that parental education, prosocial norms, pragmatic values, moral reasoning, and empathy were related to prosocial behavior, regression analyses showed that prosocial norms, pragmatic values, and empathy dimensions (personal distress and empathy) were key predictors of it. The findings are largely consistent with theoretical predictions and previous research findings, other than the negative relationship between personal distress and prosocial behavior. The study also underscores the importance of values and norms in predicting prosocial behavior, which has been largely neglected in previous studies. PMID:22919326

Logistic Regression in the Identification of Hazards in Construction

Science.gov (United States)

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.

PERSONALITY TRAITS AND STRESS LEVELS AMONG SENIOR DENTAL STUDENTS: EVIDENCE FROM MALAYSIA AND SINGAPORE.

Science.gov (United States)

Yusof, Zamros Y M; Hassan, Wan Nurazreena Wan; Razak, Ishak A; Hashim, Siti Marini N; Tahir, Mohd Khairul A M; Keng, Siong Beng

2016-11-01

This study aimed to evaluate the association between dental students’ personality traits and stress levels in relation to dental education programs among senior dental students in University Malaya (UM) in Malaysia and National University of Singapore (NUS). A cross-sectional survey using a self-administered questionnaire was conducted on UM and NUS senior dental students. The questionnaire comprised items on demographic background, the Big Five Inventory Personality Traits (BFIPT) test and a modified Dental Environment Stress (DES) scale. Rasch analysis was used to convert raw data to interval scores. Analyses were done by t-test, Pearson correlation, and Hierarchical regression statistics. The response rate was 100% (UM=132, NUS=76). Personality trait Agreeableness (mean=0.30) was significantly more prevalent among UM than NUS students (mean=0.15, p=0.016). In NUS, Neuroticism (mean=0.36) was significantly more prevalent than in UM (mean=0.14, p=0.002). The DES mean score was higher among NUS (mean=0.23) than UM students (mean=0.07). In UM, Neuroticism was significantly correlated with stress levels (r=0.338, ppersonality traits. The correlation was strongest for personality trait Neuroticism in both schools. Hierarchical regression analysis showed that gender and Neuroticism were significant predictors for students’ stress levels (ppersonality trait were significant predictors for stress levels among selected groups of dental students in Southeast Asia. Information on students’ personality may be useful in new students’ intake, stress management counseling and future program reviews.

The relationship of proximal normative beliefs and global subjective norms to college students' alcohol consumption.

Science.gov (United States)

Maddock, Jay; Glanz, Karen

2005-02-01

Heavy drinking among college students is a major concern across the country. Several studies have shown that students tend to overestimate the alcohol consumption of students, in general (global social norms), and of their close friends (proximal normative beliefs). Research has also shown that beliefs about others' alcohol consumption is strongly related to alcohol use. We hypothesized that normative beliefs about important referent individuals would mediate the relationship between campus social norms and alcohol consumption. A survey of alcohol use and related variables was completed by 433 university students. Multiple regression was used to examine the mediational role of normative beliefs on social norms and alcohol consumption. These analyses indicate that normative beliefs are a significant mediator of the relationship between social norms and alcohol consumption. Normative beliefs accounted for 52-62% of the proportion of variance mediated. Normative beliefs are an important construct in understanding the relationship between social norms and alcohol use among college students and may be an important area for future interventions.

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

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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.

Use of multiple linear regression and logistic regression models to investigate changes in birthweight for term singleton infants in Scotland.

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Bonellie, Sandra R

2012-10-01

To illustrate the use of regression and logistic regression models to investigate changes over time in size of babies particularly in relation to social deprivation, age of the mother and smoking. Mean birthweight has been found to be increasing in many countries in recent years, but there are still a group of babies who are born with low birthweights. Population-based retrospective cohort study. Multiple linear regression and logistic regression models are used to analyse data on term 'singleton births' from Scottish hospitals between 1994-2003. Mothers who smoke are shown to give birth to lighter babies on average, a difference of approximately 0.57 Standard deviations lower (95% confidence interval. 0.55-0.58) when adjusted for sex and parity. These mothers are also more likely to have babies that are low birthweight (odds ratio 3.46, 95% confidence interval 3.30-3.63) compared with non-smokers. Low birthweight is 30% more likely where the mother lives in the most deprived areas compared with the least deprived, (odds ratio 1.30, 95% confidence interval 1.21-1.40). Smoking during pregnancy is shown to have a detrimental effect on the size of infants at birth. This effect explains some, though not all, of the observed socioeconomic birthweight. It also explains much of the observed birthweight differences by the age of the mother.   Identifying mothers at greater risk of having a low birthweight baby as important implications for the care and advice this group receives. © 2012 Blackwell Publishing Ltd.

Analysing the physics learning environment of visually impaired students in high schools

NARCIS (Netherlands)

Toenders, F.G.C.; de Putter - Smits, L.G.A.; Sanders, W.T.M.; den Brok, P.J.

2017-01-01

Although visually impaired students attend regular high school, their enrolment in advanced science classes is dramatically low. In our research we evaluated the physics learning environment of a blind high school student in a regular Dutch high school. For visually impaired students to grasp

Analysing the physics learning environment of visually impaired students in high schools

Science.gov (United States)

Toenders, Frank G. C.; de Putter-Smits, Lesley G. A.; Sanders, Wendy T. M.; den Brok, Perry

2017-07-01

Although visually impaired students attend regular high school, their enrolment in advanced science classes is dramatically low. In our research we evaluated the physics learning environment of a blind high school student in a regular Dutch high school. For visually impaired students to grasp physics concepts, time and additional materials to support the learning process are key. Time for teachers to develop teaching methods for such students is scarce. Suggestions for changes to the learning environment and of materials used are given.

Time-adaptive quantile regression

DEFF Research Database (Denmark)

Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg; Madsen, Henrik

2008-01-01

and an updating procedure are combined into a new algorithm for time-adaptive quantile regression, which generates new solutions on the basis of the old solution, leading to savings in computation time. The suggested algorithm is tested against a static quantile regression model on a data set with wind power......An algorithm for time-adaptive quantile regression is presented. The algorithm is based on the simplex algorithm, and the linear optimization formulation of the quantile regression problem is given. The observations have been split to allow a direct use of the simplex algorithm. The simplex method...... production, where the models combine splines and quantile regression. The comparison indicates superior performance for the time-adaptive quantile regression in all the performance parameters considered....

Ethnic Variables and Negative Life Events as Predictors of Depressive Symptoms and Suicidal Behaviors in Latino College Students: On the Centrality of "Receptivo a los Demás"

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Chang, Edward C.; Yu, Elizabeth A.; Yu, Tina; Kahle, Emma R.; Hernandez, Viviana; Kim, Jean M.; Jeglic, Elizabeth L.; Hirsch, Jameson K.

2016-01-01

In the present study, we examined ethnic variables (viz., multigroup ethnic identity and other group orientation) along with negative life events as predictors of depressive symptoms and suicidal behaviors in a sample of 156 (38 male and 118 female) Latino college students. Results of conducting hierarchical regression analyses indicated that the…

Alcohol use longitudinally predicts adjustment and impairment in college students with ADHD: The role of executive functions.

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Langberg, Joshua M; Dvorsky, Melissa R; Kipperman, Kristen L; Molitor, Stephen J; Eddy, Laura D

2015-06-01

The primary aim of this study was to evaluate whether alcohol consumption longitudinally predicts the adjustment, overall functioning, and grade point average (GPA) of college students with ADHD and to determine whether self-report of executive functioning (EF) mediates these relationships. Sixty-two college students comprehensively diagnosed with ADHD completed ratings at the beginning and end of the school year. Regression analyses revealed that alcohol consumption rated at the beginning of the year significantly predicted self-report of adjustment and overall impairment at the end of the year, above and beyond ADHD symptoms and baseline levels of adjustment/impairment but did not predict GPA. Exploratory multiple mediator analyses suggest that alcohol use impacts impairment primarily through EF deficits in self-motivation. EF deficits in the motivation to refrain from pursuing immediately rewarding behaviors in order to work toward long-term goals appear to be particularly important in understanding why college students with ADHD who consume alcohol have a higher likelihood of experiencing significant negative outcomes. The implications of these findings for the prevention of the negative functional outcomes often experienced by college students with ADHD are discussed. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Cyberbullying perpetration and victimisation among junior and senior high school students in Guangzhou, China.

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Rao, Jiaming; Wang, Haiqing; Pang, Minhui; Yang, Jianwei; Zhang, Jiayi; Ye, Yunfeng; Chen, Xiongfei; Wang, Shengyong; Dong, Xiaomei

2017-04-06

Cyberbullying research in China is in early stage. This study describes the cyberbullying experiences of junior and senior high school students in Guangzhou, China, and to examine the risk factors associated with cyberbullying perpetrators, victims and perpetrator-victims among students. We also investigated the frequency of cyberbullying and coping strategies of student victims. Participants were 2590 students in grades 7, 8, 9 and 10 from six junior and senior high schools in October 2015 in Guangzhou, in south China, who completed a questionnaire. Data on participants' experiences with cyberbullying perpetration and victimisation during the previous 6 months were collected. Multinomial logistic regression was used to analyse factors associated with being perpetrators, victims and perpetrator-victims. In this sample, 28.0% (725) of participants reported being a perpetrator and 44.5% (1150) reported being a victim in the previous 6 months. Specifically, 2.9% (74) reported being perpetrators only, 19.3% (499) reported being victims only and 25.2% (651) reported being perpetrator-victims (both perpetrator and victim). In addition, flaming was the most common form of cyberbullying in both perpetration and victimisation. Logistic regression analyses indicated that online game addiction in participants was associated with increased odds of being a perpetrator only; no democratic parenting style in the mother and physical discipline by parents were associated with increased odds of being a victim only; male students, students with low academic achievement, those spending over 2 hours a day online, experiencing physical discipline from parents and online game addiction were associated with increased odds of both perpetration and victimisation. Cyberbullying is a common experience among Chinese junior and senior high school students. These findings add to the empirical data on cyberbullying and reinforce the urgent need for cyberbullying prevention in China

Social support and common mental disorder among medical students

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Adriano Gonçalves Silva

2014-03-01

Full Text Available INTRODUCTION: Different kinds of psychological distress have been identified for students in the health field, especially in the medical school. OBJECTIVE: To estimate the prevalence of mental suffering among medical students in the Southeastern Brazil and asses its association with social support. METHODS: It is a cross-sectional study. Structured questionnaires were applied for students from the 1st up to the 6th years of the medical school of Universidade Estadual Paulista "Júlio de Mesquita Filho", assessing demographic variables related to aspects of graduation and adaptation to the city. Psychological suffering was defined as a common mental disorder (CMD assessed by the Self Reporting Questionnaire (SRQ-20. Social support was assessed by the social support scale of the Medical Outcomes Study (MOS. The association between the outcome and explanatory variables was assessed by the χ2 test and Logistic Regression, for the multivariate analyses, using p < 0.05. RESULTS: The response rate was of 80.7%, with no differences between sample and the population regarding gender (p = 0.78. The average age was 22 years old (standard deviation - SD = 2.2, mainly women (58.2% and students who were living with friends (62%. The prevalence of CMD was 44.9% (95%CI 40.2 - 49.6. After the multivariate analyses, the explanatory variables that were associated with CMD were: feeling rejected in the past year (p < 0.001, thinking about leaving medical school (p < 0.001 and "interaction" in the MOS scale (p = 0.002. CONCLUSIONS: The prevalence of CMD among medical students was high and insufficient social support was an important risk factor. Our findings suggest that interventions to improve social interaction among those students could be beneficial, decreasing the prevalence of CMD in this group.

Social support and common mental disorder among medical students.

Science.gov (United States)

Silva, Adriano Gonçalves; Cerqueira, Ana Teresa de Abreu Ramos; Lima, Maria Cristina Pereira

2014-01-01

Different kinds of psychological distress have been identified for students in the health field, especially in the medical school. To estimate the prevalence of mental suffering among medical students in the Southeastern Brazil and asses its association with social support. It is a cross-sectional study. Structured questionnaires were applied for students from the 1st up to the 6th years of the medical school of Universidade Estadual Paulista "Júlio de Mesquita Filho", assessing demographic variables related to aspects of graduation and adaptation to the city. Psychological suffering was defined as a common mental disorder (CMD) assessed by the Self Reporting Questionnaire (SRQ-20). Social support was assessed by the social support scale of the Medical Outcomes Study (MOS). The association between the outcome and explanatory variables was assessed by the χ2 test and Logistic Regression, for the multivariate analyses, using p < 0.05. The response rate was of 80.7%, with no differences between sample and the population regarding gender (p = 0.78). The average age was 22 years old (standard deviation - SD = 2.2), mainly women (58.2%) and students who were living with friends (62%). The prevalence of CMD was 44.9% (95%CI 40.2 - 49.6). After the multivariate analyses, the explanatory variables that were associated with CMD were: feeling rejected in the past year (p < 0.001), thinking about leaving medical school (p < 0.001) and "interaction" in the MOS scale (p = 0.002). The prevalence of CMD among medical students was high and insufficient social support was an important risk factor. Our findings suggest that interventions to improve social interaction among those students could be beneficial, decreasing the prevalence of CMD in this group.

Estimation of Stature from Foot Dimensions and Stature among South Indian Medical Students Using Regression Models

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Rajesh D. R

2015-01-01

Full Text Available Background: At times fragments of soft tissues are found disposed off in the open, in ditches at the crime scene and the same are brought to forensic experts for the purpose of identification and such type of cases pose a real challenge. Objectives: This study was aimed at developing a methodology which could help in personal identification by studying the relation between foot dimensions and stature among south subjects using regression models. Material and Methods: Stature and foot length of 100 subjects (age range 18-22 years were measured. Linear regression equations for stature estimation were calculated. Result: The correlation coefficients between stature and foot lengths were found to be positive and statistically significant. Height = 98.159 + 3.746 × FLRT (r = 0.821 and Height = 91.242 + 3.284 × FLRT (r = 0.837 are the regression formulas from foot lengths for males and females respectively. Conclusion: The regression equation derived in the study can be used reliably for estimation of stature in a diverse population group thus would be of immense value in the field of personal identification especially from mutilated bodies or fragmentary remains.

Mobile Phone Dependence, Social Support and Impulsivity in Chinese University Students.

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Mei, Songli; Chai, Jingxin; Wang, Shi-Bin; Ng, Chee H; Ungvari, Gabor S; Xiang, Yu-Tao

2018-03-13

This study examined the frequency of mobile phone dependence in Chinese university students and explored its association with social support and impulsivity. Altogether, 909 university students were consecutively recruited from a large university in China. Mobile phone use, mobile phone dependence, impulsivity, and social support were measured with standardized instruments. The frequency of possible mobile phone use and mobile phone dependence was 78.3% and 7.4%, respectively. Multinomial logistic regression analyses revealed that compared with no mobile phone dependence, possible mobile phone dependence was significantly associated with being male ( p = 0.04, OR = 0.7, 95% CI: 0.4-0.98), excessive mobile phone use ( p phone dependence was associated with length of weekly phone use ( p = 0.01, OR = 2.5, 95% CI: 1.2-5.0), excessive mobile phone use ( p phone dependence and mobile phone dependence was high in this sample of Chinese university students. A significant positive association with impulsivity was found, but not with social support.

Extracurricular activities associated with stress and burnout in preclinical medical students

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Jawad Fares

2016-09-01

Full Text Available This study aims to assess the prevalence of stress and burnout among preclinical medical students in a private university in Beirut, Lebanon, and evaluate the association between extracurricular involvement and stress and burnout relief in preclinical medical students. A cross-sectional survey was conducted on a random sample of 165 preclinical medical students. Distress level was measured using the 12-item General Health Questionnaire (GHQ-12 while that of burnout was measured through the Maslach Burnout Inventory-Student Survey (MBI-SS. The MBI-SS assesses three interrelated dimensions: emotional exhaustion, cynicism, and academic efficacy. Extracurricular activities were divided into four categories: physical exercise, music, reading, and social activities. All selected participants responded. A substantial proportion of preclinical medical students suffered from stress (62% and burnout (75%. Bivariate and multivariate regression analyses revealed that being a female or a 1st year medical student correlated with higher stress and burnout. Music-related activities were correlated with lower burnout. Social activities or living with parents were associated with lower academic efficacy. The high stress and burnout levels call for action. Addressing the studying conditions and attending to the psychological wellbeing of preclinical medical students are recommendations made in the study.

Extracurricular activities associated with stress and burnout in preclinical medical students.

Science.gov (United States)

Fares, Jawad; Saadeddin, Zein; Al Tabosh, Hayat; Aridi, Hussam; El Mouhayyar, Christopher; Koleilat, Mohamad Karim; Chaaya, Monique; El Asmar, Khalil

2016-09-01

This study aims to assess the prevalence of stress and burnout among preclinical medical students in a private university in Beirut, Lebanon, and evaluate the association between extracurricular involvement and stress and burnout relief in preclinical medical students. A cross-sectional survey was conducted on a random sample of 165 preclinical medical students. Distress level was measured using the 12-item General Health Questionnaire (GHQ-12) while that of burnout was measured through the Maslach Burnout Inventory-Student Survey (MBI-SS). The MBI-SS assesses three interrelated dimensions: emotional exhaustion, cynicism, and academic efficacy. Extracurricular activities were divided into four categories: physical exercise, music, reading, and social activities. All selected participants responded. A substantial proportion of preclinical medical students suffered from stress (62%) and burnout (75%). Bivariate and multivariate regression analyses revealed that being a female or a 1st year medical student correlated with higher stress and burnout. Music-related activities were correlated with lower burnout. Social activities or living with parents were associated with lower academic efficacy. The high stress and burnout levels call for action. Addressing the studying conditions and attending to the psychological wellbeing of preclinical medical students are recommendations made in the study. Copyright © 2015 Ministry of Health, Saudi Arabia. Published by Elsevier Ltd. All rights reserved.

Examination of cyberbullying experiences among Turkish students from different school types.

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Topçu, Cigdem; Erdur-Baker, Ozgür; Capa-Aydin, Yeşim

2008-12-01

The purpose of this study was to examine the nature of cyberbullying experiences among public and private school students in Turkey. One hundred eighty-three participants between the ages of 14 and 15 were recruited for the study. Participants were asked to respond to questionnaires measuring demographic information, usage frequency of Internet-mediated communication tools (IMCT), and cyberbullying experience (as a victim and as a bully). Participants who reported cyberbullying victimization were also asked how they felt and whether they sought help after such experiences. Results indicated that public school students were more likely than private school students to report being cyberbullies and cybervictims despite that private school students were more likely than public school students to report more frequent usage of IMCT. The findings of the logistic regression analyses indicated that usage frequency of IMCT was a significant predictor of cyberbullying/victimization for public school students but not for private school students. While victims from private school revealed that they did not mind the cyberbullying experience because they thought it was a joke, victims from public school reported that they felt angry when they experienced cyberbullying. Both public and private schools indicated that friends were their first choice for help.

The effect of gender, ethnicity, and income on college students' use of communication technologies.

Science.gov (United States)

Junco, Reynol; Merson, Dan; Salter, Daniel W

2010-12-01

Because campus officials are relying on personal communication technologies to communicate with students, a question arises about access and usage. Although communication technologies are popular among college students, some evidence suggests that differences exist in ownership and use. We examined patterns of student ownership and use of cell phones and use of instant messaging, focusing on three predictors of digital inequality: gender, ethnicity, and income. Logistic and hierarchical linear regression analyses were used to analyze results from 4,491 students. The odds that female and white students owned cell phones were more than twice as high as for men and African-American students. Students in the $100,000-$149,000 per year income bracket were more than three times as likely to own a cell phone than those from the median bracket. However, being female, African-American, and/or from the highest income brackets was positively predictive of the number of text messages sent and the amount of time spent talking on a cell phone per week. We found no differences between students on the use of instant messaging. Implications of these results, as well as areas for further research, are provided.

Econometric analysis of realised covariation: high frequency covariance, regression and correlation in financial economics

OpenAIRE

Ole E. Barndorff-Nielsen; Neil Shephard

2002-01-01

This paper analyses multivariate high frequency financial data using realised covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis and covariance. It will be based on a fixed interval of time (e.g. a day or week), allowing the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions and covariances change through time. In particular w...

Mindfulness predicts student nurses' communication self-efficacy: A cross-national comparative study.

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Sundling, Vibeke; Sundler, Annelie J; Holmström, Inger K; Kristensen, Dorte Vesterager; Eide, Hilde

2017-08-01

The aim of this study was to compare student nurses' communication self-efficacy, empathy, and mindfulness across two countries, and to analyse the relationship between these qualities. The study had a cross-sectional design. Data was collected from final year student nurses in Norway and Sweden. Communication self-efficacy, empathy, and mindfulness were reported by questionnaires; Clear-cut communication with patients, Jefferson Scale of Empathy, and Langer 14 items mindfulness scale. The study included 156 student nurses, 94 (60%) were Swedish. The mean communication self-efficacy score was 119 (95% CI 116-122), empathy score 115 (95% CI 113-117) and mindfulness score 79 (95% CI 78-81). A Mann-Whitney test showed that Swedish students scored significantly higher on communication self-efficacy, empathy, and mindfulness than Norwegian students did. When adjusted for age, gender, and country in a multiple linear regression, mindfulness was the only independent predictor of communication self-efficacy. The Swedish student nurses in this study scored higher on communication self-efficacy, empathy, and mindfulness than Norwegian students did. Student nurses scoring high on mindfulness rated their communication self-efficacy higher. A mindful learning approach may improve communication self-efficacy and possibly the effect of communication skills training. Copyright © 2017 Elsevier B.V. All rights reserved.

Suggestibility and signal detection performance in hallucination-prone students.

Science.gov (United States)

Alganami, Fatimah; Varese, Filippo; Wagstaff, Graham F; Bentall, Richard P

2017-03-01

Auditory hallucinations are associated with signal detection biases. We examine the extent to which suggestions influence performance on a signal detection task (SDT) in highly hallucination-prone and low hallucination-prone students. We also explore the relationship between trait suggestibility, dissociation and hallucination proneness. In two experiments, students completed on-line measures of hallucination proneness (the revised Launay-Slade Hallucination Scale; LSHS-R), trait suggestibility (Inventory of Suggestibility) and dissociation (Dissociative Experiences Scale-II). Students in the upper and lower tertiles of the LSHS-R performed an auditory SDT. Prior to the task, suggestions were made pertaining to the number of expected targets (Experiment 1, N = 60: high vs. low suggestions; Experiment 2, N = 62, no suggestion vs. high suggestion vs. no voice suggestion). Correlational and regression analyses indicated that trait suggestibility and dissociation predicted hallucination proneness. Highly hallucination-prone students showed a higher SDT bias in both studies. In Experiment 1, both bias scores were significantly affected by suggestions to the same degree. In Experiment 2, highly hallucination-prone students were more reactive to the high suggestion condition than the controls. Suggestions may affect source-monitoring judgments, and this effect may be greater in those who have a predisposition towards hallucinatory experiences.

Associations between self-esteem, general self-efficacy and approaches to studying in occupational therapy students: A cross-sectional study

OpenAIRE

Bonsaksen, Tore; Sadeghi, Talieh; Thørrisen, Mikkel Magnus

2017-01-01

The aim of this study was to explore associations between self-esteem, general self-efficacy, and the deep, strategic, and surface approaches to studying. Norwegian occupational therapy students (n = 125) completed questionnaires measuring study approaches, self-esteem, and general self-efficacy. Regression analyses were used to explore the direct relationships between self-esteem, general self-efficacy and the approaches to studying, after controlling for age, gender, prior higher education,...

Regression analysis by example

CERN Document Server

Chatterjee, Samprit

2012-01-01

Praise for the Fourth Edition: ""This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable."" -Journal of the American Statistical Association Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded

STUDENT ACADEMIC SUPPORT AS A PREDICTOR OF LIFE SATISFACTION IN UNIVERSITY STUDENTS

OpenAIRE

Ahmet Akýn; Serhat Arslan; Eyüp Çelik; Çýnar Kaya; Nihan Arslan

2015-01-01

The purpose of this study is to examine the relationship between Academic Support and Life Satisfaction. Participants were 458 university students who voluntarily filled out a package of self-report instruments. Student Academic Support Scale and Satisfaction with Life Scale were used as measures. The relationships between student academic support and life satisfaction were examined using correlation analysis and stepwise regression analysis. Life satisfaction was predicted positively by info...

Clinical learning environment and supervision: experiences of Norwegian nursing students - a questionnaire survey.

Science.gov (United States)

Skaalvik, Mari Wolff; Normann, Hans Ketil; Henriksen, Nils

2011-08-01

To measure nursing students' experiences and satisfaction with their clinical learning environments. The primary interest was to compare the results between students with respect to clinical practice in nursing homes and hospital wards. Clinical learning environments are important for the learning processes of nursing students and for preferences for future workplaces. Working with older people is the least preferred area of practice among nursing students in Norway. A cross-sectional design. A validated questionnaire was distributed to all nursing students from five non-randomly selected university colleges in Norway. A total of 511 nursing students completed a Norwegian version of the questionnaire, Clinical Learning Environment, Supervision and Nurse Teacher (CLES+T) evaluation scale in 2009. Data including descriptive statistics were analysed using the Statistical Program for the Social Sciences. Factor structure was analysed by principal component analysis. Differences across sub-groups were tested with chi-square tests and Mann-Whitney U test for categorical variables and t-tests for continuous variables. Ordinal logistic regression analysis of perceptions of the ward as a good learning environment was performed with supervisory relationships and institutional contexts as independent variables, controlling for age, sex and study year. The participating nursing students with clinical placements in nursing homes assessed their clinical learning environment significantly more negatively than those with hospital placements on nearby all sub-dimensions. The evidence found in this study indicates that measures should be taken to strengthen nursing homes as learning environments for nursing students. To recruit more graduated nurses to work in nursing homes, actions to improve the learning environment are needed. © 2011 Blackwell Publishing Ltd.

Applied logistic regression

CERN Document Server

Hosmer, David W; Sturdivant, Rodney X

2013-01-01

 A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-

ADHD Dimensions and Sluggish Cognitive Tempo Symptoms in Relation to Self-Report and Laboratory Measures of Neuropsychological Functioning in College Students.

Science.gov (United States)

Jarrett, Matthew A; Rapport, Hannah F; Rondon, Ana T; Becker, Stephen P

2017-06-01

This study examined ADHD and sluggish cognitive tempo (SCT) symptoms in relation to self-report and laboratory measures of neuropsychological functioning in college students. College students ( N = 298, aged 17-25, 72% female) completed self-reports of ADHD, SCT, depression, sleep, functional impairment, and executive functioning (EF). Participants also completed a visual working memory task, a Stroop test, and the Conners' Continuous Performance Test-II (CPT-II). ADHD inattentive and SCT symptoms were strong predictors of self-reported EF, with inattention the strongest predictor of Time Management and Motivation and SCT the strongest predictor of Self-Organization/Problem Solving. SCT (but not inattention) was associated with Emotion Regulation. No relationships were found between self-reported symptoms and laboratory task performance. Between-group analyses were largely consistent with regression analyses. Self-reported ADHD and SCT symptoms are strongly associated with college students' self-reported EF, but relationships with laboratory task measures of neuropsychological functioning are limited.

Privacy-Preserving Distributed Linear Regression on High-Dimensional Data

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Gascón Adrià

2017-10-01

Full Text Available We propose privacy-preserving protocols for computing linear regression models, in the setting where the training dataset is vertically distributed among several parties. Our main contribution is a hybrid multi-party computation protocol that combines Yao’s garbled circuits with tailored protocols for computing inner products. Like many machine learning tasks, building a linear regression model involves solving a system of linear equations. We conduct a comprehensive evaluation and comparison of different techniques for securely performing this task, including a new Conjugate Gradient Descent (CGD algorithm. This algorithm is suitable for secure computation because it uses an efficient fixed-point representation of real numbers while maintaining accuracy and convergence rates comparable to what can be obtained with a classical solution using floating point numbers. Our technique improves on Nikolaenko et al.’s method for privacy-preserving ridge regression (S&P 2013, and can be used as a building block in other analyses. We implement a complete system and demonstrate that our approach is highly scalable, solving data analysis problems with one million records and one hundred features in less than one hour of total running time.

Normalization Ridge Regression in Practice I: Comparisons Between Ordinary Least Squares, Ridge Regression and Normalization Ridge Regression.

Science.gov (United States)

Bulcock, J. W.

The problem of model estimation when the data are collinear was examined. Though the ridge regression (RR) outperforms ordinary least squares (OLS) regression in the presence of acute multicollinearity, it is not a problem free technique for reducing the variance of the estimates. It is a stochastic procedure when it should be nonstochastic and it…

Quantile regression for the statistical analysis of immunological data with many non-detects

NARCIS (Netherlands)

Eilers, P.H.C.; Roder, E.; Savelkoul, H.F.J.; Wijk, van R.G.

2012-01-01

Background Immunological parameters are hard to measure. A well-known problem is the occurrence of values below the detection limit, the non-detects. Non-detects are a nuisance, because classical statistical analyses, like ANOVA and regression, cannot be applied. The more advanced statistical

Quantile regression for the statistical analysis of immunological data with many non-detects

NARCIS (Netherlands)

P.H.C. Eilers (Paul); E. Röder (Esther); H.F.J. Savelkoul (Huub); R. Gerth van Wijk (Roy)

2012-01-01

textabstractBackground: Immunological parameters are hard to measure. A well-known problem is the occurrence of values below the detection limit, the non-detects. Non-detects are a nuisance, because classical statistical analyses, like ANOVA and regression, cannot be applied. The more advanced

Students' Preference for Science Careers: International comparisons based on PISA 2006

Science.gov (United States)

Kjærnsli, Marit; Lie, Svein

2011-01-01

This article deals with 15-year-old students' tendencies to consider a future science-related career. Two aspects have been the focus of our investigation. The first is based on the construct called 'future science orientation', an affective construct consisting of four Likert scale items that measure students' consideration of being involved in future education and careers in science-related areas. Due to the well-known evidence for Likert scales providing culturally biased estimates, the aim has been to go beyond the comparison of simple country averages. In a series of regression and correlation analyses, we have investigated how well the variance of this construct in each of the participating countries can be accounted for by other Programme for International Student Assessment (PISA) student data. The second aspect is based on a question about students' future jobs. By separating science-related jobs into what we have called 'soft' and 'hard' science-related types of jobs, we have calculated and compared country percentages within each category. In particular, gender differences are discussed, and interesting international patterns have been identified. The results in this article have been reported not only for individual countries, but also for groups of countries. These cluster analyses of countries are based on item-by-item patterns of (residual values of) national average values for the combination of cognitive and affective items. The emerging cluster structure of countries has turned out to contribute to the literature of similarities and differences between countries and the factors behind the country clustering both in science education and more generally.

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

Science.gov (United States)

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.

Analyses of inter-rater reliability between professionals, medical students and trained school children as assessors of basic life support skills.

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Beck, Stefanie; Ruhnke, Bjarne; Issleib, Malte; Daubmann, Anne; Harendza, Sigrid; Zöllner, Christian

2016-10-07

Training of lay-rescuers is essential to improve survival-rates after cardiac arrest. Multiple campaigns emphasise the importance of basic life support (BLS) training for school children. Trainings require a valid assessment to give feedback to school children and to compare the outcomes of different training formats. Considering these requirements, we developed an assessment of BLS skills using MiniAnne and tested the inter-rater reliability between professionals, medical students and trained school children as assessors. Fifteen professional assessors, 10 medical students and 111-trained school children (peers) assessed 1087 school children at the end of a CPR-training event using the new assessment format. Analyses of inter-rater reliability (intraclass correlation coefficient; ICC) were performed. Overall inter-rater reliability of the summative assessment was high (ICC = 0.84, 95 %-CI: 0.84 to 0.86, n = 889). The number of comparisons between peer-peer assessors (n = 303), peer-professional assessors (n = 339), and peer-student assessors (n = 191) was adequate to demonstrate high inter-rater reliability between peer- and professional-assessors (ICC: 0.76), peer- and student-assessors (ICC: 0.88) and peer- and other peer-assessors (ICC: 0.91). Systematic variation in rating of specific items was observed for three items between professional- and peer-assessors. Using this assessment and integrating peers and medical students as assessors gives the opportunity to assess hands-on skills of school children with high reliability.

Coping with examinations: exploring relationships between students' coping strategies, implicit theories of ability, and perceived control.

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Doron, Julie; Stephan, Yannick; Boiché, Julie; Le Scanff, Christine

2009-09-01

Relatively little is known about the contribution of students' beliefs regarding the nature of academic ability (i.e. their implicit theories) on strategies used to deal with examinations. This study applied Dweck's socio-cognitive model of achievement motivation to better understand how students cope with examinations. It was expected that students' implicit theories of academic ability would be related to their use of particular coping strategies to deal with exam-related stress. Additionally, it was predicted that perceived control over exams acts as a mediator between implicit theories of ability and coping. Four hundred and ten undergraduate students (263 males, 147 females), aged from 17 to 26 years old (M=19.73, SD=1.46) were volunteers for the present study. Students completed measures of coping, implicit theories of academic ability, and perception of control over academic examinations during regular classes in the first term of the university year. Multiple regression analyses revealed that incremental beliefs of ability significantly and positively predicted active coping, planning, venting of emotions, seeking social support for emotional and instrumental reasons, whereas entity beliefs positively predicted behavioural disengagement and negatively predicted active coping and acceptance. In addition, analyses revealed that entity beliefs of ability were related to coping strategies through students' perception of control over academic examinations. These results confirm that exam-related coping varies as a function of students' beliefs about the nature of academic ability and their perceptions of control when approaching examinations.

Vector regression introduced

Directory of Open Access Journals (Sweden)

Mok Tik

2014-06-01

Full Text Available This study formulates regression of vector data that will enable statistical analysis of various geodetic phenomena such as, polar motion, ocean currents, typhoon/hurricane tracking, crustal deformations, and precursory earthquake signals. The observed vector variable of an event (dependent vector variable is expressed as a function of a number of hypothesized phenomena realized also as vector variables (independent vector variables and/or scalar variables that are likely to impact the dependent vector variable. The proposed representation has the unique property of solving the coefficients of independent vector variables (explanatory variables also as vectors, hence it supersedes multivariate multiple regression models, in which the unknown coefficients are scalar quantities. For the solution, complex numbers are used to rep- resent vector information, and the method of least squares is deployed to estimate the vector model parameters after transforming the complex vector regression model into a real vector regression model through isomorphism. Various operational statistics for testing the predictive significance of the estimated vector parameter coefficients are also derived. A simple numerical example demonstrates the use of the proposed vector regression analysis in modeling typhoon paths.

A note on the use of multiple linear regression in molecular ecology.

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Frasier, Timothy R

2016-03-01

Multiple linear regression analyses (also often referred to as generalized linear models--GLMs, or generalized linear mixed models--GLMMs) are widely used in the analysis of data in molecular ecology, often to assess the relative effects of genetic characteristics on individual fitness or traits, or how environmental characteristics influence patterns of genetic differentiation. However, the coefficients resulting from multiple regression analyses are sometimes misinterpreted, which can lead to incorrect interpretations and conclusions within individual studies, and can propagate to wider-spread errors in the general understanding of a topic. The primary issue revolves around the interpretation of coefficients for independent variables when interaction terms are also included in the analyses. In this scenario, the coefficients associated with each independent variable are often interpreted as the independent effect of each predictor variable on the predicted variable. However, this interpretation is incorrect. The correct interpretation is that these coefficients represent the effect of each predictor variable on the predicted variable when all other predictor variables are zero. This difference may sound subtle, but the ramifications cannot be overstated. Here, my goals are to raise awareness of this issue, to demonstrate and emphasize the problems that can result and to provide alternative approaches for obtaining the desired information. © 2015 John Wiley & Sons Ltd.

Applied linear regression

CERN Document Server

Weisberg, Sanford

2013-01-01

Praise for the Third Edition ""...this is an excellent book which could easily be used as a course text...""-International Statistical Institute The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world exercises and examples. Stressing central concepts such as model building, understanding parameters, assessing fit and reliability, and drawing conclusions, the new edition illus

Regression Models and Fuzzy Logic Prediction of TBM Penetration Rate

Directory of Open Access Journals (Sweden)

Minh Vu Trieu

2017-03-01

Full Text Available This paper presents statistical analyses of rock engineering properties and the measured penetration rate of tunnel boring machine (TBM based on the data of an actual project. The aim of this study is to analyze the influence of rock engineering properties including uniaxial compressive strength (UCS, Brazilian tensile strength (BTS, rock brittleness index (BI, the distance between planes of weakness (DPW, and the alpha angle (Alpha between the tunnel axis and the planes of weakness on the TBM rate of penetration (ROP. Four (4 statistical regression models (two linear and two nonlinear are built to predict the ROP of TBM. Finally a fuzzy logic model is developed as an alternative method and compared to the four statistical regression models. Results show that the fuzzy logic model provides better estimations and can be applied to predict the TBM performance. The R-squared value (R2 of the fuzzy logic model scores the highest value of 0.714 over the second runner-up of 0.667 from the multiple variables nonlinear regression model.

Regression Models and Fuzzy Logic Prediction of TBM Penetration Rate

Science.gov (United States)

Minh, Vu Trieu; Katushin, Dmitri; Antonov, Maksim; Veinthal, Renno

2017-03-01

This paper presents statistical analyses of rock engineering properties and the measured penetration rate of tunnel boring machine (TBM) based on the data of an actual project. The aim of this study is to analyze the influence of rock engineering properties including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), rock brittleness index (BI), the distance between planes of weakness (DPW), and the alpha angle (Alpha) between the tunnel axis and the planes of weakness on the TBM rate of penetration (ROP). Four (4) statistical regression models (two linear and two nonlinear) are built to predict the ROP of TBM. Finally a fuzzy logic model is developed as an alternative method and compared to the four statistical regression models. Results show that the fuzzy logic model provides better estimations and can be applied to predict the TBM performance. The R-squared value (R2) of the fuzzy logic model scores the highest value of 0.714 over the second runner-up of 0.667 from the multiple variables nonlinear regression model.

Analysing student written solutions to investigate if problem-solving processes are evident throughout

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Kelly, Regina; McLoughlin, Eilish; Finlayson, Odilla E.

2016-07-01

An interdisciplinary science course has been implemented at a university with the intention of providing students the opportunity to develop a range of key skills in relation to: real-world connections of science, problem-solving, information and communications technology use and team while linking subject knowledge in each of the science disciplines. One of the problems used in this interdisciplinary course has been selected to evaluate if it affords students the opportunity to explicitly display problem-solving processes. While the benefits of implementing problem-based learning have been well reported, far less research has been devoted to methods of assessing student problem-solving solutions. A problem-solving theoretical framework was used as a tool to assess student written solutions to indicate if problem-solving processes were present. In two academic years, student problem-solving processes were satisfactory for exploring and understanding, representing and formulating, and planning and executing, indicating that student collaboration on problems is a good initiator of developing these processes. In both academic years, students displayed poor monitoring and reflecting (MR) processes at the intermediate level. A key impact of evaluating student work in this way is that it facilitated meaningful feedback about the students' problem-solving process rather than solely assessing the correctness of problem solutions.

Zero inflated Poisson and negative binomial regression models: application in education.

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Salehi, Masoud; Roudbari, Masoud

2015-01-01

The number of failed courses and semesters in students are indicators of their performance. These amounts have zero inflated (ZI) distributions. Using ZI Poisson and negative binomial distributions we can model these count data to find the associated factors and estimate the parameters. This study aims at to investigate the important factors related to the educational performance of students. This cross-sectional study performed in 2008-2009 at Iran University of Medical Sciences (IUMS) with a population of almost 6000 students, 670 students selected using stratified random sampling. The educational and demographical data were collected using the University records. The study design was approved at IUMS and the students' data kept confidential. The descriptive statistics and ZI Poisson and negative binomial regressions were used to analyze the data. The data were analyzed using STATA. In the number of failed semesters, Poisson and negative binomial distributions with ZI, students' total average and quota system had the most roles. For the number of failed courses, total average, and being in undergraduate or master levels had the most effect in both models. In all models the total average have the most effect on the number of failed courses or semesters. The next important factor is quota system in failed semester and undergraduate and master levels in failed courses. Therefore, average has an important inverse effect on the numbers of failed courses and semester.

Understanding poisson regression.

Science.gov (United States)

Hayat, Matthew J; Higgins, Melinda

2014-04-01

Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur. These outdated methods for analyzing count data have been replaced with more appropriate statistical methods that make use of the Poisson probability distribution, which is useful for analyzing count data. The purpose of this article is to provide an overview of the Poisson distribution and its use in Poisson regression. Assumption violations for the standard Poisson regression model are addressed with alternative approaches, including addition of an overdispersion parameter or negative binomial regression. An illustrative example is presented with an application from the ENSPIRE study, and regression modeling of comorbidity data is included for illustrative purposes. Copyright 2014, SLACK Incorporated.

Alternative Methods of Regression

CERN Document Server

Birkes, David

2011-01-01

Of related interest. Nonlinear Regression Analysis and its Applications Douglas M. Bates and Donald G. Watts ".an extraordinary presentation of concepts and methods concerning the use and analysis of nonlinear regression models.highly recommend[ed].for anyone needing to use and/or understand issues concerning the analysis of nonlinear regression models." --Technometrics This book provides a balance between theory and practice supported by extensive displays of instructive geometrical constructs. Numerous in-depth case studies illustrate the use of nonlinear regression analysis--with all data s

Time series regression model for infectious disease and weather.

Science.gov (United States)

Imai, Chisato; Armstrong, Ben; Chalabi, Zaid; Mangtani, Punam; Hashizume, Masahiro

2015-10-01

Time series regression has been developed and long used to evaluate the short-term associations of air pollution and weather with mortality or morbidity of non-infectious diseases. The application of the regression approaches from this tradition to infectious diseases, however, is less well explored and raises some new issues. We discuss and present potential solutions for five issues often arising in such analyses: changes in immune population, strong autocorrelations, a wide range of plausible lag structures and association patterns, seasonality adjustments, and large overdispersion. The potential approaches are illustrated with datasets of cholera cases and rainfall from Bangladesh and influenza and temperature in Tokyo. Though this article focuses on the application of the traditional time series regression to infectious diseases and weather factors, we also briefly introduce alternative approaches, including mathematical modeling, wavelet analysis, and autoregressive integrated moving average (ARIMA) models. Modifications proposed to standard time series regression practice include using sums of past cases as proxies for the immune population, and using the logarithm of lagged disease counts to control autocorrelation due to true contagion, both of which are motivated from "susceptible-infectious-recovered" (SIR) models. The complexity of lag structures and association patterns can often be informed by biological mechanisms and explored by using distributed lag non-linear models. For overdispersed models, alternative distribution models such as quasi-Poisson and negative binomial should be considered. Time series regression can be used to investigate dependence of infectious diseases on weather, but may need modifying to allow for features specific to this context. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Relationships between dietary habits and the prevalence of fatigue in medical students.

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Tanaka, Masaaki; Mizuno, Kei; Fukuda, Sanae; Shigihara, Yoshihito; Watanabe, Yasuyoshi

2008-10-01

Fatigue, which is a common complaint among medical students, is related to poor academic outcomes. Because impaired dietary habits, such as skipping breakfast and taking meals irregularly, are correlated with poor school performances, whether those dietary habits were associated with the prevalence of fatigue was determined in medical students. The study group consisted of 127 healthy second-year medical students attending Osaka City University Graduate School of Medicine. They completed a questionnaire dealing with fatigue (Japanese version of the Chalder Fatigue Scale), lifestyle, and academic performance. On multivariate logistic regression analyses adjusted for age, gender, body mass index, and nocturnal sleeping hours, skipping breakfast (completely skipping breakfast everyday versus having breakfast everyday; odds ratio 7.81, 95% confidence interval 2.00-30.52, P = 0.003) and taking meals irregularly (completely irregular versus always regular; odds ratio 6.89, 95% confidence interval 1.20-39.55, P = 0.030) were positively correlated with the prevalence of fatigue. Skipping breakfast and taking meals irregularly are associated with the prevalence of fatigue in medical students.

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

Science.gov (United States)

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.

A classical regression framework for mediation analysis: fitting one model to estimate mediation effects.

Science.gov (United States)

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.

Food and Culinary Knowledge and Skills: Perceptions of Undergraduate Dietetic Students.

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Cooper, Marcia J; Mezzabotta, Leanne; Murphy, Joseph

2017-03-01

The objective of the current study was to examine food and culinary skills and knowledge of dietetic students. An online bilingual survey was created using Survey Monkey TM to explore the skills, knowledge, and perceptions of undergraduate dietetic students regarding food and cooking. Chi-square and logistic regression analyses were used to compare skills and knowledge of food and culinary concepts. The final sample included second- (n = 22) and third-year (n = 22) students within the Baccalauréat specialisé en sciences de la nutrition program at the University of Ottawa. There were no significant differences (P > 0.05) on 3 of 4 skills (preparing a cake, whipping egg whites, or baking a yeast bread) or knowledge concepts (fold, baste, braise, grill, and poach) amongst second- and third-year students. Third-year students perceived more skill in preparing a béchamel sauce. There was a trend for third-year students (59%) to have higher food and cooking skills and knowledge compared with second-year students (32%). Perceived knowledge and confidence was proportional with the academic year, whereas overall knowledge and skills of food and culinary concepts were moderate among both groups of students. This research suggests that more dedicated time may need to be spent on food and cooking competencies in undergraduate dietetic education.

Political activism and mental health among Black and Latinx college students.

Science.gov (United States)

Hope, Elan C; Velez, Gabriel; Offidani-Bertrand, Carly; Keels, Micere; Durkee, Myles I

2018-01-01

The current study investigates the utility of political activism as a protective factor against experiences of racial/ethnic (R/E) discrimination that negatively affect stress, anxiety, and depressive symptoms among Black and Latinx college freshmen at predominately White institutions. Data come from the Minority College Cohort Study, a longitudinal investigation of Black and Latinx college students (N = 504; 44% Black). We conducted multiple regression analyses for each mental health indicator and tested for interaction effects. For Black and Latinx students, the relationship between R/E microaggressions and end of freshman year stress varied by political activism. For Black students, the relationship between R/E microaggressions and end of the year anxiety varied by political activism. There was a significant interaction effect for depressive symptoms among Latinx students. Political activism serves as a protective factor to mitigate the negative effect of R/E discrimination on stress and depressive symptoms for Latinx students. For Black students, higher levels of political activism may exacerbate experiences of R/E microaggressions and relate to more stress and anxiety compared with Black students who are less politically involved. Findings point to the need for a deeper understanding of phenomenological variation in experiences of microaggressions among R/E minorities and how students leverage political activism as an adaptive coping strategy to mitigate race-related stress during college. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Effective behaviour change techniques for physical activity and healthy eating in overweight and obese adults; systematic review and meta-regression analyses.

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Samdal, Gro Beate; Eide, Geir Egil; Barth, Tom; Williams, Geoffrey; Meland, Eivind

2017-03-28

This systematic review aims to explain the heterogeneity in results of interventions to promote physical activity and healthy eating for overweight and obese adults, by exploring the differential effects of behaviour change techniques (BCTs) and other intervention characteristics. The inclusion criteria specified RCTs with ≥ 12 weeks' duration, from January 2007 to October 2014, for adults (mean age ≥ 40 years, mean BMI ≥ 30). Primary outcomes were measures of healthy diet or physical activity. Two reviewers rated study quality, coded the BCTs, and collected outcome results at short (≤6 months) and long term (≥12 months). Meta-analyses and meta-regressions were used to estimate effect sizes (ES), heterogeneity indices (I 2 ) and regression coefficients. We included 48 studies containing a total of 82 outcome reports. The 32 long term reports had an overall ES = 0.24 with 95% confidence interval (CI): 0.15 to 0.33 and I 2  = 59.4%. The 50 short term reports had an ES = 0.37 with 95% CI: 0.26 to 0.48, and I 2  = 71.3%. The number of BCTs unique to the intervention group, and the BCTs goal setting and self-monitoring of behaviour predicted the effect at short and long term. The total number of BCTs in both intervention arms and using the BCTs goal setting of outcome, feedback on outcome of behaviour, implementing graded tasks, and adding objects to the environment, e.g. using a step counter, significantly predicted the effect at long term. Setting a goal for change; and the presence of reporting bias independently explained 58.8% of inter-study variation at short term. Autonomy supportive and person-centred methods as in Motivational Interviewing, the BCTs goal setting of behaviour, and receiving feedback on the outcome of behaviour, explained all of the between study variations in effects at long term. There are similarities, but also differences in effective BCTs promoting change in healthy eating and physical activity and

Introduction to regression graphics

CERN Document Server

Cook, R Dennis

2009-01-01

Covers the use of dynamic and interactive computer graphics in linear regression analysis, focusing on analytical graphics. Features new techniques like plot rotation. The authors have composed their own regression code, using Xlisp-Stat language called R-code, which is a nearly complete system for linear regression analysis and can be utilized as the main computer program in a linear regression course. The accompanying disks, for both Macintosh and Windows computers, contain the R-code and Xlisp-Stat. An Instructor's Manual presenting detailed solutions to all the problems in the book is ava

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

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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.

Assistive Technologies for Second-Year Statistics Students Who Are Blind

Science.gov (United States)

Erhardt, Robert J.; Shuman, Michael P.

2015-01-01

At Wake Forest University, a student who is blind enrolled in a second course in statistics. The course covered simple and multiple regression, model diagnostics, model selection, data visualization, and elementary logistic regression. These topics required that the student both interpret and produce three sets of materials: mathematical writing,…

Regression analysis of growth responses to water depth in three wetland plant species

DEFF Research Database (Denmark)

Sorrell, Brian K; Tanner, Chris C; Brix, Hans

2012-01-01

depths from 0 – 0.5 m. Morphological and growth responses to depth were followed for 54 days before harvest, and then analysed by repeated measures analysis of covariance, and non-linear and quantile regression analysis (QRA), to compare flooding tolerances. Principal results Growth responses to depth...

A Spreadsheet Tool for Learning the Multiple Regression F-Test, T-Tests, and Multicollinearity

Science.gov (United States)

Martin, David

2008-01-01

This note presents a spreadsheet tool that allows teachers the opportunity to guide students towards answering on their own questions related to the multiple regression F-test, the t-tests, and multicollinearity. The note demonstrates approaches for using the spreadsheet that might be appropriate for three different levels of statistics classes,…

Time-trend of melanoma screening practice by primary care physicians: A meta-regression analysis

OpenAIRE

Valachis, Antonis; Mauri, Davide; Karampoiki, Vassiliki; Polyzos, Nikolaos P; Cortinovis, Ivan; Koukourakis, Georgios; Zacharias, Georgios; Xilomenos, Apostolos; Tsappi, Maria; Casazza, Giovanni

2009-01-01

Objective To assess whether the proportion of primary care physicians implementing full body skin examination (FBSE) to screen for melanoma changed over time. Methods Meta-regression analyses of available data. Data Sources: MEDLINE, ISI, Cochrane Central Register of Controlled Trials. Results Fifteen studies surveying 10,336 physicians were included in the analyses. Overall, 15%?82% of them reported to perform FBSE to screen for melanoma. The proportion of physicians using FBSE screening ten...

Prevalence and determinants of susceptibility to cigarette smoking among school students in Pakistan: secondary analysis of Global Youth Tobacco Survey.

Science.gov (United States)

Aslam, Syeda Kanwal; Zaheer, Sidra; Rao, Saadiyah; Shafique, Kashif

2014-02-21

Susceptibility to smoke has been recognized as a strong predictor of smoking experimentation and taking up regular smoking habit. The identification of smoking susceptible individuals and its determinants is important in the efforts to reduce future smoking prevalence. The aims of this study are to estimate prevalence of susceptibility to smoke among adolescents, and identify factors associated with it. Cross sectional data was obtained from Global Youth Tobacco Survey conducted in three cities of Pakistan in year 2004. Study population consisted of students in grades, 8th, 9th, and 10th; aged 13 to 15 years. Secondary analysis using univariate and multivariate logistic regression analyses were performed to estimate the associations between smoking susceptibility and co-variates. Descriptive statistics were reported in proportions, and adjusted odds ratios with 95% confidence interval were used to report logistic regression analyses. Approximately 12% of nonsmoking students were found susceptible to smoking. Students, who were females (OR = 1.53, 95% CI [1.24-1.89]); whose parents (OR = 1.64, 95% CI [1.35-1.99]); or close friend smoked (OR = 2.77, 95% CI [2.27- 3.40]) were more susceptible to cigarette smoking. Students who had good knowledge about harmful effects of smoking (OR = 0.54, 95% CI [0.43-0.69]); and had access to anti-smoking media (OR = 0.73, 95% CI [0.59-0.89]) were less likely to be susceptible to smoking. Students who were females, had smoking parents, friends or exposure to newspaper/magazines cigarette marketing, were more susceptible to cigarette smoking among Pakistani adolescents. While knowledge of harmful effects of smoking and access to anti-smoking media served as protective factors against susceptibility to smoking.

perception of indonesian nursing students regaring caring behavior and teaching characteristics of their clinical nursing instructors

Directory of Open Access Journals (Sweden)

madiha mukhtar

2016-11-01

Full Text Available Student’s learning and performance reflects the professional attitude, behavior, ethics and standards of their instructors. The aim of this study is to analyse the perception of Indonesian Nursing students regarding caring behavior and teaching characteristics of their CNIs. In this exploratory cross-sectional study, 149 Professional Nursing students from Regular program (Baccalaureate and Post diploma BSN and 15 Clinical Nursing Instructors were recruited from nursing faculty of public university located in Surabaya Indonesia. Data were collected by questionnaire and FGD was conducted to explore detailed information. In descriptive analysis: 6 % students perceived the caring behavior of their clinical instructors as low, 52.3% responds it as enough and 41.6 % considered it good. Teaching characteristics of CNI; 2.7% low, 26.8 as enough and 70.5 % good as perceived by their students. Data collected from students was analysed by using logistic regression test. Professional commitment with (P-value .038, motivation (P-value .010 and clinical placement environment (P-value .002 in main category (significance value is < 0.05 shows influence on perception of Indonesian nursing students regarding caring behaviour and teaching characteristics of their CNIs. In focused group discussion students’ recommended to increase the number of visits in clinical area and emphasises on bed side clinical demonstration. It can be concluded that students’ characteristics does have influence on their perception regarding caring behavior and clinical setting environment influence their perception regarding teaching characteristics of their CNIs.

The influence of activities and nutrition status to university students' achievements

Science.gov (United States)

Fathonah, Siti

2018-03-01

The purpose of this research is to analyse the influence of activity and nutrition status to the achievement of students from Engineering Faculty of UNNES. The subject of this research is the students of Engineering Faculty of UNNES. Using proportional random sampling, there are 5% (214 students of 2015 batch) taken as the samples of the research. The methods of collecting the data were using documentation from akademik.unnes.ac.id on students' achievement, questionnaire to ask upon students' activity, and BMI measurement for nutrition status. The data analysis was using percentage description, chi-square analysis, and regression. The data obtained that the average grade points of engineering students are satisfying in the level of 3.29 with light activities with the energy of 2.220 kkal. The average sleeping time of the students were 5.68 hours, whereas the total of their studying and private activity were 18.18 hours. The status of students' nutrition is Normal weight with the details of 64.2% of students are Normal weight, 23.5% of them are wasting, 4.0% are overweight, and 5.2% are obesity. The activity and nutrition status were proven not significantly influencing students grade point of achievements. The suggestions proposed by the researcher are 1) the students need to increase their sleeping time to be 6-9 hours, and they need to habituate themselves in working out at least 3 times a week in 30 - 45 minutes, and 2) further research on nutrition status and students' achievements can focus on the influence of food consumption and students' clean lifestyle.

Multivariate differential analyses of adolescents' experiences of aggression in families

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Chris Myburgh

2011-01-01

Full Text Available Aggression is part of South African society and has implications for the mental health of persons living in South Africa. If parents are aggressive adolescents are also likely to be aggressive and that will impact negatively on their mental health. In this article the nature and extent of adolescents' experiences of aggression and aggressive behaviour in the family are investigated. A deductive explorative quantitative approach was followed. Aggression is reasoned to be dependent on aspects such as self-concept, moral reasoning, communication, frustration tolerance and family relationships. To analyse the data from questionnaires of 101 families (95 adolescents, 95 mothers and 91 fathers Cronbach Alpha, various consecutive first and second order factor analyses, correlations, multiple regression, MANOVA, ANOVA and Scheffè/ Dunnett tests were used. It was found that aggression correlated negatively with the independent variables; and the correlations between adolescents and their parents were significant. Regression analyses indicated that different predictors predicted aggression. Furthermore, differences between adolescents and their parents indicated that the experienced levels of aggression between adolescents and their parents were small. Implications for education are given.

Preference learning with evolutionary Multivariate Adaptive Regression Spline model

DEFF Research Database (Denmark)

Abou-Zleikha, Mohamed; Shaker, Noor; Christensen, Mads Græsbøll

2015-01-01

This paper introduces a novel approach for pairwise preference learning through combining an evolutionary method with Multivariate Adaptive Regression Spline (MARS). Collecting users' feedback through pairwise preferences is recommended over other ranking approaches as this method is more appealing...... for function approximation as well as being relatively easy to interpret. MARS models are evolved based on their efficiency in learning pairwise data. The method is tested on two datasets that collectively provide pairwise preference data of five cognitive states expressed by users. The method is analysed...

A random regression model in analysis of litter size in pigs | Lukovi& ...

African Journals Online (AJOL)

Dispersion parameters for number of piglets born alive (NBA) were estimated using a random regression model (RRM). Two data sets of litter records from the Nemščak farm in Slovenia were used for analyses. The first dataset (DS1) included records from the first to the sixth parity. The second dataset (DS2) was extended ...

Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis.

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Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

2015-01-01

Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended.

The Leicester AATSR Global Analyser (LAGA) - Giving Young Students the Opportunity to Examine Space Observations of Global Climate-Related Processes

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Llewellyn-Jones, David; Good, Simon; Corlett, Gary

A pc-based analysis package has been developed, for the dual purposes of, firstly, providing ‘quick-look' capability to research workers inspecting long time-series of global satellite datasets of Sea-surface Temperature (SST); and, secondly, providing an introduction for students, either undergraduates, or advanced high-school students to the characteristics of commonly used analysis techniques for large geophysical data-sets from satellites. Students can also gain insight into the behaviour of some basic climate-related large-scale or global processes. The package gives students immediate access to up to 16 years of continuous global SST data, mainly from the Advanced Along-Track Scanning Radiometer, currently flying on ESA's Envisat satellite. The data are available and are presented in the form of monthly averages and spatial averaged to half-degree or one-sixth degree longitude-latitude grids. There are simple button-operated facilities for defining and calculating box-averages; producing time-series of such averages; defining and displaying transects and their evolution over time; and the examination anomalous behaviour by displaying the difference between observed values and values derived from climatological means. By using these facilities a student rapidly gains familiarity with such processes as annual variability, the El Nĩo effect, as well as major current systems n such as the Gulf Stream and other climatically important phenomena. In fact, the student is given immediate insights into the basic methods of examining geophysical data in a research context, without needing to acquire special analysis skills are go trough lengthy data retrieval and preparation procedures which are more generally required, as precursors to serious investigation, in the research laboratory. This software package, called the Leicester AAATSR Global Analyser (LAGA), is written in a well-known and widely used analysis language and the package can be run by using software

The Association between Family Structure and Adolescent Smoking among Multicultural Students in Hawaii.

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Du, Yajun; Palmer, Paula H; Sakuma, Kari-Lyn; Blake, Jerome; Johnson, C Anderson

The purpose of this study was to examine whether the prevalence of smoking was associated with family structure among multicultural adolescents and whether there was gender disparity on the association. Data were collected from a sample of 7 th graders in Hawaii who completed in-class questionnaires in 2004. The final sample included 821 multicultural students from different family structures. Descriptive analyses, Chi-square tests and logistic regression were performed to examine the prevalence of smoking and the association between family structure and smoking prevalence. This sample contained students who lived in intact (61.7%), single-parent (16.5%), step-parent (15.6%), and no-parent (6.2%) families. The overall prevalence of ever/lifetime smoking was 24.0%, and was not significantly different between genders in each family structure ( p >0.05). Compared with living in intact families, living in single-parent, step-parent, or no-parent families was significantly associated with higher odds of ever/lifetime smoking among all students ( p multicultural students. Anti-smoking programs should consider this factor.

Association between problematic Internet use and impulse control disorders among Iranian university students.

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Mazhari, Shahrzad

2012-05-01

Previous studies have examined the relationship between problematic Internet use (PIU) with pathological gambling and impulsivity. However, few studies have investigated the association between PIU and other impulse control disorders. This study aimed to assess whether PIU is related to compulsive buying, kleptomania, trichotillomania, intermittent explosive disorder, and pyromania, among a sample of Iranian university students. A cross-sectional study design was used among a random sample of (n=950) university students. Self-reported questionnaires, including demographic, Problematic Internet Use Questionnaire (PIUQ) and Minnesota Impulse Disorders Interview were utilized. The prevalence of PIU was 21.2 percent. Students with diagnosis of either compulsive buying, or intermittent explosive disorder, or pyromania had significantly higher scores on PIUQ compared to the students without the diagnosis. Multivariate regression analyses indicated that in the male gender, the diagnosis of either compulsive buying or intermittent explosive disorder were significant predictors of the risk of the PIU. The results support the proposal that PIU should be considered as a spectrum of impulse control disorder.

Fitness, fatness, and academic performance in seventh-grade elementary school students

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2014-01-01

Background In addition to the benefits on physical and mental health, cardiorespiratory fitness has shown to have positive effects on cognition. This study aimed to investigate the relationship between cardiorespiratory fitness and body weight status on academic performance among seventh-grade students. Methods Participants included 1531 grade 7 students (787 male, 744 female), ranging in age from 12 to 14 years (Mage = 12.3 ± 0.60), from 3 different cohorts. Academic performance was measured using the marks students had, at the end of their academic year, in mathematics, language (Portuguese), foreign language (English), and sciences. To assess cardiorespiratory fitness the Progressive Aerobic Cardiovascular Endurance Run, from Fitnessgram, was used as the test battery. The relationship between academic achievement and the independent and combined association of cardiorespiratory fitness/weight status was analysed, using multinomial logistic regression. Results Cardiorespiratory fitness and weight status were independently related with academic achievement. Fit students, compared with unfit students had significantly higher odds for having high academic achievement (OR = 2.29, 95% CI: 1.48-3.55, p academic achievement (OR = 3.65, 95% CI: 1.82-7.34, p academic achievement in seventh-grade students independent of the different cohorts, providing further support that aerobically fit and normal weight students are more likely to have better performance at school regardless of the year that they were born. PMID:25001376

ATTITUDE TOWARDS THE USE OF LEARNING MANAGEMENT SYSTEM AMONG UNIVERSITY STUDENTS: A Case Study

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Fuad A. A.TRAYEK

2013-07-01

Full Text Available Learning management system (LMS is a learning platform for both full time and distant learning students at the International Islamic University in Malaysia (IIUM. LMS becomes a tool for IIUM to disseminate information and learning resources to the students. The objectives of this study were to Ø investigate students' attitudes toward the use of LMS, Ø to verify the impact of perceived usefulness and perceived ease of use on attitude towards use of learning management system, Ø to examine the differences in attitudes toward the use of LMS between distance learning and full time students. There were 120 (70 full time and 50 distance learning students at the Institute of Education responded for the study. The collected data was analysed using descriptive statistics, t-test and Multiple Regression Analysis (MRA. The results of the study showed that perceived ease of use and perceived usefulness determine students' attitudes toward the use of LMS. However, this study did not find any significant differences between distance learning and full time students. According to the findings the study recommended that the University should continue using LMS because it is useful for both distance learning and full time students. Further suggestions are made to customize and upgrade the LMS suitable for innovative teaching and learning.

Reporting Misconduct of a Coworker to Protect a Patient: A Comparison between Experienced Nurses and Nursing Students

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Abraham Mansbach

2014-01-01

Full Text Available Purpose. Whistleblowing is the reporting of illegal, immoral, or illegitimate practices to persons or organizations that may affect the action. The current study compares experienced nurses to nursing students regarding their willingness to blow the whistle to protect a patient’s interests. Methods. 165 participants were divided into two groups: 82 undergraduate nursing students and 83 experienced nurses. Participants responded to two vignettes that described a colleague’s and a manager’s misconduct at work. Results. The nursing students perceived the severity of the misconduct significantly lower compared to the experienced nurses. The nursing students also ranked the internal and external whistleblowing indices higher than the nurses, but the differences did not reach statistical significance. For each of the examined internal and external indices, professional experience was found to be significant in multivariate regression analyses. Conclusions. Even though nursing students perceived the severity of the misconduct significantly lower than the experienced nurses, the students demonstrated a greater readiness to blow the whistle, both internally and externally. Recommendations for handling comparable situations are offered.

Association Between Smartphone Use and Musculoskeletal Discomfort in Adolescent Students.

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Yang, Shang-Yu; Chen, Ming-De; Huang, Yueh-Chu; Lin, Chung-Ying; Chang, Jer-Hao

2017-06-01

Despite the substantial increase in the number of adolescent smartphone users, few studies have investigated the behavioural effects of smartphone use on adolescent students as it relates to musculoskeletal discomfort. The purpose of this study was to explore the association between smartphone use and musculoskeletal discomfort in students at a Taiwanese junior college. We hypothesised that the duration of smartphone use would be associated with increased instances of musculoskeletal discomfort in these students. This cross-sectional study employed a convenience sampling method to recruit students from a junior college in southern Taiwan. All the students (n = 315) were asked to answer questionnaires on smartphone use. A descriptive analysis, stepwise regression, and logistic regression were used to examine specific components of smartphone use and their relationship to musculoskeletal discomfort. Nearly half of the participants experienced neck and shoulder discomfort. The stepwise regression results indicated that the number of body parts with discomfort (F = 6.009, p smartphone functions. The logistic regression analysis showed that the students who talked on the phone >3 h/day had a higher risk of upper back discomfort than did those who talked on the phone smartphone use and musculoskeletal discomfort is related to the duration of smartphone ancillary function use. Moreover, hours spent talking on the phone was a predictor of upper back discomfort.

Relationship Between Age, Experience, and Student Preference for Types of Learning Activities in Online Courses

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Thomas A. Simonds

2017-10-01

Full Text Available In this study, two researchers explored student learning preferences in online courses. They used the scholarship of teaching and learning process as a research model, and embedded a web-based survey and online focus groups in the online courses they were teaching. After collecting data, the researchers conducted multiple logistic regression analyses to test their hypothesis that a relationship existed between some student factors and student preferences for types of online learning activities. The results of the data analysis revealed a statistically significant relationship between student age and student preference for certain types of online learning activities. Older students in the study indicated a much stronger preference for videos of the professor lecturing, while younger students tended to prefer more interactive learning strategies. Focus group comments from the older students provide insights into some of the reasons why they found watching video lectures to be helpful for their learning, and comments from younger students illustrate how they learn best in online courses. The researchers offer suggestions for online instructors based on the findings of this study, and they explain why online instructors may find the scholarship of teaching and learning research process especially helpful for both teaching and research efforts.

[Prevalence of and factors related to depression in high school students].

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Eskin, Mehmet; Ertekin, Kamil; Harlak, Hacer; Dereboy, Ciğdem

2008-01-01

The study aimed at investigating the prevalence of and factors related to depression in high school students. A total of 805 (n = 367 girls; n = 438 boys) first year students from three high schools in the city of Aydin filled in a self-report questionnaire that contained questions about socio-demographics, academic achievement and religious belief. It included also a depression rating scale, social support scale, problem solving inventory and an assertiveness scale. T-tests, chi-square tests, Pearson moment products correlation coefficients, and logistic regression analysis were used to analyze the data. 141 students (17.5%) scored on and above the cut-off point on the Children Depression Inventory (CDI). In the first regression analyses low self-esteem, low grade point average (GPA) and low perceived social support from friends in boys, and low self-esteem, low paternal educational level and low social support from friends were the predictors of girls' depression. When self-esteem scores were excluded, low GPA, low perceived social support from friends and family, and inefficient problem solving skills were predictors of depression in boys; low perceived social support from friends and family, low paternal educational level, and inefficient problem solving skills were the independent predictors of depression in girls. Depression is prevalent in high school students. Low self-esteem, low perceived social support from peers and family, and inefficient problem solving skills appears to be risk factors for adolescent depression. Low GPA for boys and low paternal education for girls were gender specific risk factors. Psychosocial interventions geared for increasing self-esteem, social support and problem solving skills may be effective in the prevention and treatment of adolescent depression.

Can smartphones measure momentary quality of life and participation? A proof of concept using experience sampling surveys with university students.

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Liddle, Jacki; Wishink, Anna; Springfield, Liz; Gustafsson, Louise; Ireland, David; Silburn, Peter

2017-08-01

Understanding quality of life and participation is a key aspect of occupational therapy research. The use of smartphones to deliver experience-sampling surveys may provide an accessible way to monitor these outcomes. This study used smartphone-based experience sampling methods (ESM) to investigate factors influencing momentary quality of life (mQOL) of university students. A convenience sample of students at an Australian university participated. Using a custom smartphone application, ESM surveys were sent six to eight times, every second day, over a week. Participants indicated their mQOL, occupational participation, occupational enjoyment, social context and location via surveys and provided demographic and health information in a single self-report questionnaire. The relationship between mQOL and variables was analysed at the survey level using logistic regression. Forty students completed 391 surveys. Higher mQOL was significantly related to participation in productive occupations (z = 3.48; P = 0.001), moderate (z = 4.00; P sample, analysing at the individual level, and using ESM in conjunction with other methodologies is recommended. © 2017 Occupational Therapy Australia.

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

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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.

Application of support vector regression (SVR) for stream flow prediction on the Amazon basin

CSIR Research Space (South Africa)

Du Toit, Melise

2016-10-01

Full Text Available regression technique is used in this study to analyse historical stream flow occurrences and predict stream flow values for the Amazon basin. Up to twelve month predictions are made and the coefficient of determination and root-mean-square error are used...

Teaching quality: High school students' autonomy and competence.

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León, Jaime; Medina-Garrido, Elena; Ortega, Miriam

2018-05-01

How teachers manage class learning and interact with students affects students’ motivation and engagement. However, it could be that the effect of students’ representation of teaching quality on the students’ motivation varies between classes. Students from 90 classes participated in the study. We used multilevel random structural equation modeling to analyze whether the relationship of the students’ perception of teaching quality (as an indicator of the students’ mental representation) and students’ motivation varies between classes, and if this variability depends on the class assessment of teaching quality (as an indicator of teaching quality). The effect of teachers’ structure on the regression slope of student perception of student competence was .127. The effect of teachers’ autonomy support on the regression slope of student perception of student autonomy was .066. With this study we contribute a more detailed description of the relationship between teaching quality, competence and autonomy.

Regression and regression analysis time series prediction modeling on climate data of quetta, pakistan

International Nuclear Information System (INIS)

Jafri, Y.Z.; Kamal, L.

2007-01-01

Various statistical techniques was used on five-year data from 1998-2002 of average humidity, rainfall, maximum and minimum temperatures, respectively. The relationships to regression analysis time series (RATS) were developed for determining the overall trend of these climate parameters on the basis of which forecast models can be corrected and modified. We computed the coefficient of determination as a measure of goodness of fit, to our polynomial regression analysis time series (PRATS). The correlation to multiple linear regression (MLR) and multiple linear regression analysis time series (MLRATS) were also developed for deciphering the interdependence of weather parameters. Spearman's rand correlation and Goldfeld-Quandt test were used to check the uniformity or non-uniformity of variances in our fit to polynomial regression (PR). The Breusch-Pagan test was applied to MLR and MLRATS, respectively which yielded homoscedasticity. We also employed Bartlett's test for homogeneity of variances on a five-year data of rainfall and humidity, respectively which showed that the variances in rainfall data were not homogenous while in case of humidity, were homogenous. Our results on regression and regression analysis time series show the best fit to prediction modeling on climatic data of Quetta, Pakistan. (author)

Aerobic exercise, ball sports, dancing, and weight lifting as moderators of the relationship between stress and depressive symptoms: an exploratory cross-sectional study with swiss university students.

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Gerber, Markus; Brand, Serge; Elliot, Catherine; Holsboer-Trachsler, Edith; Pühse, Uwe

2014-12-01

This exploratory study was designed to compare four types of exercise activities in Swiss university students. A sample of 201 medical students (136 women, 65 men; M age = 23.2 yr., SD = 2.4) and 250 exercise and health sciences students (144 women, 106 men; M age = 22.3 yr., SD = 2.2) participated in the study. They completed the Perceived Stress Scale, the Depression Scale, and the Office in Motion Questionnaire. Interaction effects between stress and exercise activities were analysed using hierarchical regression analyses, after controlling for age, sex, and academic discipline. Frequent participation in ball sports and dancing were associated with decreased depressive symptoms among students with elevated perceived stress, whereas no such relationship existed among their peers with lower perceived stress. No stress-moderating effect was found for aerobic exercise. Weight lifting was only associated with lower depressive symptoms among students with low perceived stress. The present findings suggest that, among Swiss university students, certain exercises may have better potential to moderate the relationship between perceived stress and depressive symptoms than others. Future research could analyze whether personalized exercise programs created to satisfy participants' individual needs are more beneficial for stress management.

Linear regression in astronomy. I

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Isobe, Takashi; Feigelson, Eric D.; Akritas, Michael G.; Babu, Gutti Jogesh

1990-01-01

Five methods for obtaining linear regression fits to bivariate data with unknown or insignificant measurement errors are discussed: ordinary least-squares (OLS) regression of Y on X, OLS regression of X on Y, the bisector of the two OLS lines, orthogonal regression, and 'reduced major-axis' regression. These methods have been used by various researchers in observational astronomy, most importantly in cosmic distance scale applications. Formulas for calculating the slope and intercept coefficients and their uncertainties are given for all the methods, including a new general form of the OLS variance estimates. The accuracy of the formulas was confirmed using numerical simulations. The applicability of the procedures is discussed with respect to their mathematical properties, the nature of the astronomical data under consideration, and the scientific purpose of the regression. It is found that, for problems needing symmetrical treatment of the variables, the OLS bisector performs significantly better than orthogonal or reduced major-axis regression.

Logic regression and its extensions.

Science.gov (United States)

Schwender, Holger; Ruczinski, Ingo

2010-01-01

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

The Impact of Problem Sets on Student Learning

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Kim, Myeong Hwan; Cho, Moon-Heum; Leonard, Karen Moustafa

2012-01-01

The authors examined the role of problem sets on student learning in university microeconomics. A total of 126 students participated in the study in consecutive years. independent samples t test showed that students who were not given answer keys outperformed students who were given answer keys. Multiple regression analysis showed that, along with…

Practical Aspects of Log-ratio Coordinate Representations in Regression with Compositional Response

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Fišerová Eva

2016-10-01

Full Text Available Regression analysis with compositional response, observations carrying relative information, is an appropriate tool for statistical modelling in many scientific areas (e.g. medicine, geochemistry, geology, economics. Even though this technique has been recently intensively studied, there are still some practical aspects that deserve to be further analysed. Here we discuss the issue related to the coordinate representation of compositional data. It is shown that linear relation between particular orthonormal coordinates and centred log-ratio coordinates can be utilized to simplify the computation concerning regression parameters estimation and hypothesis testing. To enhance interpretation of regression parameters, the orthogonal coordinates and their relation with orthonormal and centred log-ratio coordinates are presented. Further we discuss the quality of prediction in different coordinate system. It is shown that the mean squared error (MSE for orthonormal coordinates is less or equal to the MSE for log-transformed data. Finally, an illustrative real-world example from geology is presented.

Analysing Student Programs in the PHP Intelligent Tutoring System

Science.gov (United States)

Weragama, Dinesha; Reye, Jim

2014-01-01

Programming is a subject that many beginning students find difficult. The PHP Intelligent Tutoring System (PHP ITS) has been designed with the aim of making it easier for novices to learn the PHP language in order to develop dynamic web pages. Programming requires practice. This makes it necessary to include practical exercises in any ITS that…

MENENTUKAN PROBABILITAS QUALITAS LULUSAN PROGRAM STUDI MENGGUNAKAN LOGISTIC REGRESSION

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Maxsi Ary

2016-03-01

Full Text Available Abstract – Human resources (HR is one of the success factors in the economic field, namely how to create a human resources (HR qualified and have the skills and highly competitive in the global competition. Educational level of the labor force that is still relatively low. The structure of education of the workforce is still dominated Indonesian basic education which is about 63.2%. The issue raised is to determine the probability of a program of study (whether or not to see some of the ratio of the number of graduates by the number of students per class, the amount of quota size class (large or small using logistic regression models. Data were obtained from a search result based on the amount of data the study program students and graduates in 2010 Data processing using SPSS. The results of the analysis by assessing model fit and the results will be given for each model fit. Starting with the hypothesis for assessing model fit, statistical -2LogL, Cox and Snell's R Square, Hosmer and Lemeshow's Goodness of Fit Test, and the classification table. The results of the analysis using SPSS as a tool aimed at measuring quality of graduate courses at a university, college, or academy, whether or not based on the ratio of the number of graduates and class quotas. Keywords: Quota Class, Probability, Logistic Regression Abstrak – Sumberdaya manusia (SDM adalah salah satu faktor kesuksesan dalam bidang ekonomi, yaitu bagaimana menciptakan sumber daya manusia (SDM yang berkualitas dan memiliki keterampilan serta berdaya saing tinggi dalam persaingan global. Tingkat pendidikan angkatan kerja yang ada masih relatif rendah. Struktur pendidikan angkatan kerja Indonesia masih didominasi pendidikan dasar yaitu sekitar 63,2%. Persoalan yang dikemukakan adalah menentukan probabilitas sebuah program studi (baik atau tidak dengan melihat beberapa rasio jumlah lulusan dengan jumlah mahasiswa per angkatan, ukuran besarnya kuota kelas (besar atau kecil menggunakan

Tumor regression patterns in retinoblastoma

International Nuclear Information System (INIS)

Zafar, S.N.; Siddique, S.N.; Zaheer, N.

2016-01-01

To observe the types of tumor regression after treatment, and identify the common pattern of regression in our patients. Study Design: Descriptive study. Place and Duration of Study: Department of Pediatric Ophthalmology and Strabismus, Al-Shifa Trust Eye Hospital, Rawalpindi, Pakistan, from October 2011 to October 2014. Methodology: Children with unilateral and bilateral retinoblastoma were included in the study. Patients were referred to Pakistan Institute of Medical Sciences, Islamabad, for chemotherapy. After every cycle of chemotherapy, dilated funds examination under anesthesia was performed to record response of the treatment. Regression patterns were recorded on RetCam II. Results: Seventy-four tumors were included in the study. Out of 74 tumors, 3 were ICRB group A tumors, 43 were ICRB group B tumors, 14 tumors belonged to ICRB group C, and remaining 14 were ICRB group D tumors. Type IV regression was seen in 39.1% (n=29) tumors, type II in 29.7% (n=22), type III in 25.6% (n=19), and type I in 5.4% (n=4). All group A tumors (100%) showed type IV regression. Seventeen (39.5%) group B tumors showed type IV regression. In group C, 5 tumors (35.7%) showed type II regression and 5 tumors (35.7%) showed type IV regression. In group D, 6 tumors (42.9%) regressed to type II non-calcified remnants. Conclusion: The response and success of the focal and systemic treatment, as judged by the appearance of different patterns of tumor regression, varies with the ICRB grouping of the tumor. (author)

Mobile Phone Dependence, Social Support and Impulsivity in Chinese University Students

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Mei, Songli; Chai, Jingxin; Wang, Shi-Bin; Ng, Chee H.; Ungvari, Gabor S.; Xiang, Yu-Tao

2018-01-01

This study examined the frequency of mobile phone dependence in Chinese university students and explored its association with social support and impulsivity. Altogether, 909 university students were consecutively recruited from a large university in China. Mobile phone use, mobile phone dependence, impulsivity, and social support were measured with standardized instruments. The frequency of possible mobile phone use and mobile phone dependence was 78.3% and 7.4%, respectively. Multinomial logistic regression analyses revealed that compared with no mobile phone dependence, possible mobile phone dependence was significantly associated with being male (p = 0.04, OR = 0.7, 95% CI: 0.4–0.98), excessive mobile phone use (p mobile phone dependence was associated with length of weekly phone use (p = 0.01, OR = 2.5, 95% CI: 1.2–5.0), excessive mobile phone use (p mobile phone dependence and mobile phone dependence was high in this sample of Chinese university students. A significant positive association with impulsivity was found, but not with social support. PMID:29533986

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

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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.

Combining Alphas via Bounded Regression

Directory of Open Access Journals (Sweden)

Zura Kakushadze

2015-11-01

Full Text Available We give an explicit algorithm and source code for combining alpha streams via bounded regression. In practical applications, typically, there is insufficient history to compute a sample covariance matrix (SCM for a large number of alphas. To compute alpha allocation weights, one then resorts to (weighted regression over SCM principal components. Regression often produces alpha weights with insufficient diversification and/or skewed distribution against, e.g., turnover. This can be rectified by imposing bounds on alpha weights within the regression procedure. Bounded regression can also be applied to stock and other asset portfolio construction. We discuss illustrative examples.

The 1-min Screening Test for Reading Problems in College Students: Psychometric Properties of the 1-min TIL.

Science.gov (United States)

Fernandes, Tânia; Araújo, Susana; Sucena, Ana; Reis, Alexandra; Castro, São Luís

2017-02-01

Reading is a central cognitive domain, but little research has been devoted to standardized tests for adults. We, thus, examined the psychometric properties of the 1-min version of Teste de Idade de Leitura (Reading Age Test; 1-min TIL), the Portuguese version of Lobrot L3 test, in three experiments with college students: typical readers in Experiment 1A and B, dyslexic readers and chronological age controls in Experiment 2. In Experiment 1A, test-retest reliability and convergent validity were evaluated in 185 students. Reliability was >.70, and phonological decoding underpinned 1-min TIL. In Experiment 1B, internal consistency was assessed by presenting two 45-s versions of the test to 19 students, and performance in these versions was significantly associated (r = .78). In Experiment 2, construct validity, criterion validity and clinical utility of 1-min TIL were investigated. A multiple regression analysis corroborated construct validity; both phonological decoding and listening comprehension were reliable predictors of 1-min TIL scores. Logistic regression and receiver operating characteristics analyses revealed the high accuracy of this test in distinguishing dyslexic from typical readers. Therefore, the 1-min TIL, which assesses reading comprehension and potential reading difficulties in college students, has the necessary psychometric properties to become a useful screening instrument in neuropsychological assessment and research. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

The relationship between future orientation and street substance use among Texas alternative school students.

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Peters, R J; Tortolero, Susan R; Johnson, Regina Jones; Addy, Robert C; Markham, Christine M; Escobar-Chaves, S Liliana; Lewis, Holly; Yacoubian, George S

2005-01-01

Self-reported substance use data were collected from 963 alternative school students in grades 7-12 who were surveyed through the Safer Choices 2 study in Houston, Texas. Data were collected between October 2000 and March 2001. Logistic regression analyses indicated that lower levels of future orientation was significantly associated (OR = 0.88, 95% CI = 0.81-0.97) with thirty-day substance use after controlling for age and gender. In addition, lower levels of future orientation was found to have a significant association with students' lifetime substance use (OR = 0.93, 95% CI = 0.87-.99) after controlling for age, race, and gender. While the relationships tested in this study are exploratory, they provide evidence for an important connection between future orientation and substance use among adolescents attending alternative schools.

riskRegression

DEFF Research Database (Denmark)

Ozenne, Brice; Sørensen, Anne Lyngholm; Scheike, Thomas

2017-01-01

In the presence of competing risks a prediction of the time-dynamic absolute risk of an event can be based on cause-specific Cox regression models for the event and the competing risks (Benichou and Gail, 1990). We present computationally fast and memory optimized C++ functions with an R interface...... for predicting the covariate specific absolute risks, their confidence intervals, and their confidence bands based on right censored time to event data. We provide explicit formulas for our implementation of the estimator of the (stratified) baseline hazard function in the presence of tied event times. As a by...... functionals. The software presented here is implemented in the riskRegression package....

QUEST for Quality for Students: A Student Quality Concept. Volume 3

Science.gov (United States)

Galán Palomares, Fernando Miguel; Todorovski, Blazhe; Kažoka, Asnate; Saarela, Henni

2013-01-01

This is the final publication of the QUEST for Quality for Students (QUEST) project, run by the European Students' Union. The QUEST project has managed to analyse students' views on the quality of higher education to identify areas in which students can become increasingly involved in quality assurance and enhancement processes. This publication…

Econometric analysis of realized covariation: high frequency based covariance, regression, and correlation in financial economics

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler; Shephard, N.

2004-01-01

This paper analyses multivariate high frequency financial data using realized covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis, and covariance. It will be based on a fixed interval of time (e.g., a day or week), allowing...... the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions, and covariances change through time. In particular we provide confidence intervals for each of these quantities....

Cannabis use among middle and high school students in Ontario: a school-based cross-sectional study

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Sampasa-Kanyinga, Hugues; Hamilton, Hayley A.; LeBlanc, Allana G.; Chaput, Jean-Philippe

2018-01-01

Background: Cannabis use can have serious detrimental effects in children and adolescents. It is therefore important to continually assess the use of cannabis among young people in order to inform prevention efforts. We assessed the prevalence of cannabis use among middle and high school students in Ontario and examined its association with demographic and behavioural factors. Methods: Data were obtained from the 2015 Ontario Student Drug Use and Health Survey, a province-wide school-based survey of students in grades 7 through 12. Analyses included a representative sample of 9920 middle and high school students. Bivariate cross-tabulations and logistic regression analyses were used to investigate the factors associated with cannabis use. Results: Overall, 21.5% and 13.9% of students reported using cannabis in the previous year and previous month, respectively. The conditional probability that an adolescent who reported cannabis use in the previous year would report daily use was 12.5%. There was a significant dose-response gradient with age, with older students being more likely to use cannabis than younger students. In multivariable analyses, being in grades 10 through 12 (odds ratios [ORs] ranged from 3.71 to 3.85), being black (OR 2.67 [95% confidence interval (CI) 1.76-4.05]), using tobacco cigarettes (OR 10.10 [95% CI 8.68-13.92]) and being an occasional (OR 5.35 [95% CI 4.01-7.13]) or regular (OR 14.6 [95% CI 10.8-19.89]) alcohol user were associated with greater odds of cannabis use. Being an immigrant was associated with lower odds of cannabis use (OR 0.55 [95% CI 0.39-0.78]). Interpretation: The findings suggest that cannabis use is prevalent among middle and high school students in Ontario and is strongly associated with tobacco cigarette smoking and alcohol consumption. Future research should document trends in cannabis use over time, including its risks, especially when the legalization of recreational cannabis comes into effect. PMID:29367264

Students' Outcome Expectation on Spiritual and Religious Competency: A Hierarchical Regression Analysis

Science.gov (United States)

Lu, Junfei; Woo, Hongryun

2017-01-01

In this study, 74 master's-level counseling students from various programs completed a questionnaire inquiring about their perceived program environment in relation to the topics of spirituality and religion (S/R), program emphasis on nine specific S/R competencies, as well as their outcome expectations toward being S/R competent through training.…

Sexual coercion and health-risk behaviors among urban Chinese high school students

Directory of Open Access Journals (Sweden)

Yi Song

2014-05-01

Full Text Available Objective: To determine the association between health-risk behaviors and a history of sexual coercion among urban Chinese high school students. Design: A cross-sectional study was performed among 109,754 high school students who participated in the 2005 Chinese Youth Risk Behavior Survey. Data were analyzed for 5,215 students who had experienced sexual intercourse (1,483 girls, 3,732 boys. Multivariate logistic regression was used to determine the relationship between sexual coercion and the related covariates, and data were stratified by gender. Results: Of those students who had had sexual intercourse, 40.9% of the females and 29.6% of the males experienced sexual coercion (p<0.01. When analyses controlled for demographic characteristics, in the study sample, that is, students who had sexual intercourse, drug use (odds ratios [OR], 2.44, attempted suicide (OR, 2.30, physical abuse (OR, 1.74, binge drinking (OR, 1.62, verbal abuse (OR, 1.29, experience of being drunk (OR, 0.68, and smoking of cigarettes (OR, 0.52 were related to a history of sexual coercion. Patterns of health-risk behaviors also differed among female and male students who had experienced sexual coercion. Conclusions: Sexual coercion is associated with health-risk behaviors. Initiatives to reduce the harm associated with sexual coercion among high school students are needed.

Prevalence and predictors of suicidality among medical students in a public university.

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Tan, S T; Sherina, M S; Rampal, L; Normala, I

2015-02-01

Undergraduate medical students have been the most distressed group among the student population. Depression and anxiety have been found to be more prevalent in this group of students compared to others. This study was conducted to determine the prevalence and predictors of suicidality among undergraduate medical students in a public university. This was an analytical cross-sectional study, conducted in a public university in Selangor, Malaysia. Data were collected using self-administered questionnaires from January to February 2013, and analysed using the Statistical Package for Social Sciences Software (version 21). Out of 625 undergraduate medical students, 537 (85.9%) participated in the study. The prevalence of the suicidality among undergraduate medical students was 7.0%. The significant predictors of suicidality based on multiple logistic regression were the respondent's lifetime suicide attempts (Adjusted Odds Ratio, AOR 10.4, 95% CI 2.7 to 40.9); depression (AOR 5.9, 95% CI 1.5 to 23.0); breaking off a steady love relationship (AOR 5.4, 95% CI 1.3 to 22.4); hopelessness (AOR 4.9, 95% CI 1.1 to 21.6); and something valued being lost or stolen (AOR 4.4, 95% CI 1.2 to 15.9). These findings indicate that mental health care services should be strengthened at university level. The results show a need for an intervention programme to reduce suicidality among the undergraduate medical students.

Validation and Application of the Survey of Teaching Beliefs and Practices for Undergraduates (STEP-U): Identifying Factors Associated with Valuing Important Workplace Skills among Biology Students

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Marbach-Ad, Gili; Rietschel, Carly; Thompson, Katerina V.

2016-01-01

We present a novel assessment tool for measuring biology students’ values and experiences across their undergraduate degree program. Our Survey of Teaching Beliefs and Practices for Undergraduates (STEP-U) assesses the extent to which students value skills needed for the workplace (e.g., ability to work in groups) and their experiences with teaching practices purported to promote such skills (e.g., group work). The survey was validated through factor analyses in a large sample of biology seniors (n = 1389) and through response process analyses (five interviewees). The STEP-U skills items were characterized by two underlying factors: retention (e.g., memorization) and transfer (e.g., knowledge application). Multiple linear regression models were used to examine relationships between classroom experiences, values, and student characteristics (e.g., gender, cumulative grade point average [GPA], and research experience). Student demographic and experiential factors predicted the extent to which students valued particular skills. Students with lower GPAs valued retention skills more than those with higher GPAs. Students with research experience placed greater value on scientific writing and interdisciplinary understanding. Greater experience with specific teaching practices was associated with valuing the corresponding skills more highly. The STEP-U can provide feedback vital for designing curricula that better prepare students for their intended postgraduate careers. PMID:27856547

The Attitudes of First Year Senior Secondary School Students toward Their Science Classes in the Sudan

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Lado, Longun Moses

This study examined the influence of a set of relevant independent variables on students' decision to major in math or science disciplines, on the one hand, or arts or humanities disciplines, on the other. The independent variables of interest in the study were students' attitudes toward science, their gender, their socioeconomic status, their age, and the strength and direction of parents' and peers' influences on their academic decisions. The study answered five research questions that concerned students' intention in math or science, the association between students' attitudes and their choice to major in math or science, the extent to which parents' and peers' perspectives influence students' choice of major, and the influence of a combination of relevant variables on students' choice of major. The scholarly context for the study was literature relating to students' attitudes toward science and math, their likelihood of taking courses or majoring in science or math and various conditions influencing their attitudes and actions with respect to enrollment in science or math disciplines. This literature suggested that students' experiences, their gender, parents' and peers' influence, their socio-economic status, teachers' treatment of them, school curricula, school culture, and other variables may influence students' attitudes toward science and math and their decision regarding the study of these subjects. The study used a questionnaire comprised of 28 items to elicit information from students. Based upon cluster sampling of secondary schools, the researcher surveyed 1000 students from 10 secondary schools and received 987 responses. The researcher used SPSS to analyze students' responses. Descriptive statistics, logistic regression, and multiple regression analyses to provide findings that address the study's research questions. The following are the major findings from the study: (1) The instrument used to measure students' attitudes toward science and

Regression in autistic spectrum disorders.

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Stefanatos, Gerry A

2008-12-01

A significant proportion of children diagnosed with Autistic Spectrum Disorder experience a developmental regression characterized by a loss of previously-acquired skills. This may involve a loss of speech or social responsitivity, but often entails both. This paper critically reviews the phenomena of regression in autistic spectrum disorders, highlighting the characteristics of regression, age of onset, temporal course, and long-term outcome. Important considerations for diagnosis are discussed and multiple etiological factors currently hypothesized to underlie the phenomenon are reviewed. It is argued that regressive autistic spectrum disorders can be conceptualized on a spectrum with other regressive disorders that may share common pathophysiological features. The implications of this viewpoint are discussed.

Fourth-year dental students' perceived barriers to providing tobacco intervention services.

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Pendharkar, Bhagyashree; Levy, Steven M; McQuistan, Michelle R; Qian, Fang; Squier, Christopher A; Slach, Nancy A; Aquilino, Mary L

2010-10-01

In order to facilitate effective tobacco cessation services within dental school clinics, it is necessary to understand the perceived barriers encountered by dental students while providing these services. The aim of this study was to identify which factors fourth-year dental students perceive to be associated with barriers to providing tobacco intervention services. A written survey was developed and completed by incoming fourth-year dental students (a convenience sample of seventy students) at the University of Iowa College of Dentistry in 2008. The survey assessed the perceived barriers to providing tobacco intervention services and related factors. Descriptive, bivariate, and linear regression analyses were conducted. The response rate was 97 percent. The most frequently reported barriers were patients' resistance to tobacco intervention services (96 percent), inadequate time available for tobacco intervention services (96 percent), and forgetting to give tobacco intervention advice (91 percent). The following variables were significantly (p<0.05) related to greater perceived barriers in providing tobacco intervention services: lower "adequacy of tobacco intervention curriculum coverage of specific topics covered over the previous three years" and greater "perceived importance of incorporating objective structured clinical examination teaching method for learning tobacco intervention." Students probably could benefit from additional didactic training, but most important may be enhanced clinical experiences and faculty reinforcement to facilitate effective practical student learning and adaptation for future delivery of intervention services in private practice settings.

Understanding logistic regression analysis

OpenAIRE

Sperandei, Sandro

2014-01-01

Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using ex...

Analysing a Whole CLIL School: Students' Attitudes, Motivation, and Receptive Vocabulary Outcomes

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Arribas, Mario

2016-01-01

CLIL keeps on gaining ground in the European educational context, one clear example is Spain, where the number of schools adopting this methodology has kept growing exponentially in recent years. The present study has a dual perspective looking at the motivation of students towards English and CLIL and showing students' receptive vocabulary…

Conflict management styles, emotional intelligence and implicit theories of personality of nursing students: a cross-sectional study.

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Chan, Joanne C Y; Sit, Emily N M; Lau, W M

2014-06-01

Conflict management is an essential skill that nursing students need to master as conflict is unavoidable in clinical settings. Examining nursing students' conflict management styles and the associating factors can inform nurse educators on how to equip nursing students for effective conflict management. This study aimed at examining undergraduate nursing students conflict management styles in managing conflict with their supervisors in clinical placement. The associations of emotional intelligence and implicit theories of personality with conflict management styles were also investigated. This is a cross-sectional quantitative survey. This study took place at a nursing school at a university in Hong Kong. 568 undergraduate nursing students participated in the study. Students completed a questionnaire which consisted of demographics, Measure of Implicit Theories of Personality, The Schutte Emotional Intelligence Scale (SEIS) and The Rahim Organizational Conflict Inventory-II (ROCI-II) and received a HKD 20 book coupon as compensation. The data were analyzed by descriptive statistics, reliability analyses, t-tests, correlational and linear regression analyses. For managing conflict with clinical supervisors, students used obliging and integrating most frequently whereas used dominating least. Emotional intelligence was a significant predictor of all five conflict management styles. The higher the emotional intelligence, the more students used integrating, obliging, compromising and dominating. The lower the emotional intelligence, the more students used avoiding. There was a significant association between implicit theories of personality and compromising. The less malleable students perceived personality to be, the more they used compromising. Emotional intelligence was significantly associated with all five conflict management styles while implicit theories of personality were significantly associated with compromising style only. Efforts of nurse educators to

Nonparametric regression using the concept of minimum energy

International Nuclear Information System (INIS)

Williams, Mike

2011-01-01

It has recently been shown that an unbinned distance-based statistic, the energy, can be used to construct an extremely powerful nonparametric multivariate two sample goodness-of-fit test. An extension to this method that makes it possible to perform nonparametric regression using multiple multivariate data sets is presented in this paper. The technique, which is based on the concept of minimizing the energy of the system, permits determination of parameters of interest without the need for parametric expressions of the parent distributions of the data sets. The application and performance of this new method is discussed in the context of some simple example analyses.

Psychoactive substances use and associated factors among middle and high school students in the North Center of Morocco: a cross-sectional questionnaire survey.

Science.gov (United States)

Zarrouq, B; Bendaou, B; El Asri, A; Achour, S; Rammouz, I; Aalouane, R; Lyoussi, B; Khelafa, S; Bout, A; Berhili, N; Hlal, H; Najdi, A; Nejjari, C; El Rhazi, K

2016-06-04

Data on psychoactive substance (PAS) consumption among adolescents in the North Center of Morocco are not at all available. Therefore, the current study aimed at investigating the prevalence and the determinants of psychoactive substances use among middle and high school students in this region. A cross-sectional study was conducted from April 2012 to November 2013 in public middle and high schools in the North Central Region of Morocco. An anonymous self-administered questionnaire was used to assess psychoactive substances use among a representative sample of school students from the 7th to the 12th grade, aged 11-23 years, selected by stratified cluster random sampling. Factors associated with psychoactive substance use were identified using multivariate stepwise logistic regression analyses. A total of 3020 school students completed the questionnaires, 53.0 % of which were males. The overall lifetime smoking prevalence was 16.1 %. The lifetime, annual and past month rates of any psychoactive substance use among the study subjects were 9.3, 7.5, and 6.3 % respectively. Cannabis recorded the highest lifetime prevalence of 8.1 %, followed by alcohol 4.3 %, inhalants 1.7 %, psychotropic substances without medical prescription 1.0, cocaine 0.7, heroine 0.3, and amphetamine with only 0.2 %. Psychoactive substance use was associated with males more than females. The risk factors identified by multivariate stepwise logistic regression analyses were being male, studying in secondary school level, smoking tobacco, living with a family member who uses tobacco, and feeling insecure within the family. The prevalence among all school students reported by the current study was comparable to the national prevalence. Efforts to initiate psychoactive substance prevention programs among school students should be made by designing such programs based on the significant factors associated with psychoactive substance use identified in this study.

Linear regression in astronomy. II

Science.gov (United States)

Feigelson, Eric D.; Babu, Gutti J.

1992-01-01

A wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.

Meeting students halfway: Increasing self-efficacy and promoting knowledge change in astronomy

Science.gov (United States)

Bailey, Janelle M.; Lombardi, Doug; Cordova, Jacqueline R.; Sinatra, Gale M.

2017-12-01

Two motivational factors—self-efficacy and interest—may be especially relevant to deepening students' understanding of astronomy. We examined the relationship between students' self-efficacy for, interest in learning about, and changes in their knowledge of stars, as measured by the Star Properties Concept Inventory (SPCI). Approximately 700 undergraduate students taking introductory astronomy responded to surveys at the start and end of their semester-long course. A sequential multiple regression analysis showed that self-efficacy post explains an appreciable percentage of variance in SPCI posttest scores, more than twice the percentage explained by all the pretest variables (SPCI, self-efficacy, and interest) combined. Knowledge and self-efficacy improved significantly over instruction; interest did not. Follow-up analyses revealed that instructors whose classes increased in self-efficacy also had the greatest increases in knowledge scores. Interviews with these instructors suggest they provide their students with more opportunities for mastery experiences with elaborated, performance-related feedback, as well as strong positive verbal persuasion and vicarious experiences through peer instruction. Through increased understanding of the relationship between motivational constructs (e.g., self-efficacy, interest) and knowledge, we can both improve our models and better inform instruction.

Student characteristics and behaviors at age 12 predict occupational success 40 years later over and above childhood IQ and parental socioeconomic status.

Science.gov (United States)

Spengler, Marion; Brunner, Martin; Damian, Rodica I; Lüdtke, Oliver; Martin, Romain; Roberts, Brent W

2015-09-01

Drawing on a 2-wave longitudinal sample spanning 40 years from childhood (age 12) to middle adulthood (age 52), the present study was designed to examine how student characteristics and behaviors in late childhood (assessed in Wave 1 in 1968) predict career success in adulthood (assessed in Wave 2 in 2008). We examined the influence of parental socioeconomic status (SES), childhood intelligence, and student characteristics and behaviors (inattentiveness, school entitlement, responsible student, sense of inferiority, impatience, pessimism, rule breaking and defiance of parental authority, and teacher-rated studiousness) on 2 important real-life outcomes (i.e., occupational success and income). The longitudinal sample consisted of N = 745 persons who participated in 1968 (M = 11.9 years, SD = 0.6; 49.9% female) and 2008 (M = 51.8 years, SD = 0.6; 53.3% female). Regression analyses and path analyses were conducted to evaluate the direct and indirect effects (via education) of the predictors on career success. The results revealed direct and indirect influences of student characteristics (responsible student, rule breaking and defiance of parental authority, and teacher-rated studiousness) across the life span on career success after adjusting for differences in parental SES and IQ at age 12. rd (c) 2015 APA, all rights reserved).

ANYOLS, Least Square Fit by Stepwise Regression

International Nuclear Information System (INIS)

Atwoods, C.L.; Mathews, S.

1986-01-01

Description of program or function: ANYOLS is a stepwise program which fits data using ordinary or weighted least squares. Variables are selected for the model in a stepwise way based on a user- specified input criterion or a user-written subroutine. The order in which variables are entered can be influenced by user-defined forcing priorities. Instead of stepwise selection, ANYOLS can try all possible combinations of any desired subset of the variables. Automatic output for the final model in a stepwise search includes plots of the residuals, 'studentized' residuals, and leverages; if the model is not too large, the output also includes partial regression and partial leverage plots. A data set may be re-used so that several selection criteria can be tried. Flexibility is increased by allowing the substitution of user-written subroutines for several default subroutines

Does private tutoring increase students' academic performance? Evidence from Turkey

Science.gov (United States)

Berberoğlu, Giray; Tansel, Aysit

2014-10-01

This paper investigates the effectiveness of private tutoring in Turkey. The authors introduce their study by providing some background information on the two major national examinations and three different kinds of tutoring. They then describe how they aimed to analyse whether attending private tutoring centres (PTCs) enhances Turkish students' academic performance. By way of multiple linear regression analysis, their study sought to evaluate whether the impact of private tutoring varies in different subject areas, taking into account several student-related characteristics such as family and academic backgrounds as well as interest in and perception of academic success. In terms of subject areas, the results indicate that while private tutoring does have a positive impact on academic performance in mathematics and Turkish language, this is not the case in natural sciences. However, as evidenced by the effect sizes, these impacts are rather small compared to the impacts of other variables such as interest in and perception of academic success, high school graduation fields of study, high school cumulative grade point average (CGPA), parental education and students' sociocultural background. While the authors point out that more research on the impact of further important variables needs to be done, their view is that school seems to be an important factor for determining students' academic performance.

A Matlab program for stepwise regression

Directory of Open Access Journals (Sweden)

Yanhong Qi

2016-03-01

Full Text Available The stepwise linear regression is a multi-variable regression for identifying statistically significant variables in the linear regression equation. In present study, we presented the Matlab program of stepwise regression.

Test Anxiety Among College Students With Specific Reading Disability (Dyslexia): Nonverbal Ability and Working Memory as Predictors.

Science.gov (United States)

Nelson, Jason M; Lindstrom, Will; Foels, Patricia A

2015-01-01

Test anxiety and its correlates were examined with college students with and without specific reading disability (RD; n = 50 in each group). Results indicated that college students with RD reported higher test anxiety than did those without RD, and the magnitude of these differences was in the medium range on two test anxiety scales. Relative to college students without RD, up to 5 times as many college students with RD reported clinically significant test anxiety. College students with RD reported significantly higher cognitively based test anxiety than physically based test anxiety. Reading skills, verbal ability, and processing speed were not correlated with test anxiety. General intelligence, nonverbal ability, and working memory were negatively correlated with test anxiety, and the magnitude of these correlations was medium to large. When these three cognitive constructs were considered together in multiple regression analyses, only working memory and nonverbal ability emerged as significant predictors and varied based on the test anxiety measure. Implications for assessment and intervention are discussed. © Hammill Institute on Disabilities 2013.

Sources of stress and psychological morbidity among undergraduate physiotherapy students.

Science.gov (United States)

Walsh, J M; Feeney, C; Hussey, J; Donnellan, C

2010-09-01

Professional education can be a stressful experience for some individuals, and may impact negatively on emotional well-being and academic performance. Psychological morbidity and associated sources of stress have not been investigated extensively in physiotherapy students. This study explored sources of stress, psychological morbidity and possible associations between these variables in undergraduate physiotherapy students. A questionnaire-based survey. The Undergraduate Sources of Stress Questionnaire was used to identify sources of stress, and the General Health Questionnaire-12 (GHQ-12) was used to rate the prevalence of psychological morbidity, using a conservative GHQ threshold of 3 to 4 to determine probable 'cases'. Uni- and multivariate tests of correlation were used to analyse the data. An Irish educational institution. One hundred and twenty-five physiotherapy undergraduate students. More than one-quarter of all students (27%) scored above the GHQ threshold, indicating probable psychological morbidity. This is higher than the level of psychological morbidity reported by the general population. Regression analysis showed that academic (beta=0.31, Pphysiotherapy students, with academic and personal issues being the greatest concern. While personal causes of stress such as stressful events and mood are more difficult to control, manipulation of curricular factors may have positive effects on academic sources of stress. Copyright 2010 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

Sleep and Mental Health in Undergraduate Students with Generally Healthy Sleep Habits.

Science.gov (United States)

Milojevich, Helen M; Lukowski, Angela F

2016-01-01

Whereas previous research has indicated that sleep problems tend to co-occur with increased mental health issues in university students, relatively little is known about relations between sleep quality and mental health in university students with generally healthy sleep habits. Understanding relations between sleep and mental health in individuals with generally healthy sleep habits is important because (a) student sleep habits tend to worsen over time and (b) even time-limited experience of sleep problems may have significant implications for the onset of mental health problems. In the present research, 69 university students with generally healthy sleep habits completed questionnaires about sleep quality and mental health. Although participants did not report clinically concerning mental health issues as a group, global sleep quality was associated with mental health. Regression analyses revealed that nighttime sleep duration and the frequency of nighttime sleep disruptions were differentially related to total problems and clinically-relevant symptoms of psychological distress. These results indicate that understanding relations between sleep and mental health in university students with generally healthy sleep habits is important not only due to the large number of undergraduates who experience sleep problems and mental health issues over time but also due to the potential to intervene and improve mental health outcomes before they become clinically concerning.

Prevalence of Stuttering in Javanroud\\'s Bilingual Students

Directory of Open Access Journals (Sweden)

Hiva Mohammadi

2008-04-01

Full Text Available Objective: Study of prevalence of stuttering in Iranian bilingual societies is essential for determine the effects of linguistic factors in stuttering and therapy demands in these bilingual societies. The aim of this study is to determine the prevalence of stuttering among Javanrud’s bilingual students. Materials & Methods: In this cross- sectional, descriptive and analytical study, all of bilingual students of Javanrud’s schools were examined and in order to this purpose, teacher referral method was used for the primary screening of speech disorders at all. Essential information about speech disorders specifically stuttering had been given to teachers before this primary step. Then researcher diagnosed stuttering students based on personal interview, reading, spontaneous speech and description of serial images that tell a story in Kurdish and Persian. Data were analysed by statistical tests such as Chi-square and Logistic Regression. Results: Among 11425 bilingual students of Javanrud’s schools, 129 students were identified as stutterers. These findings indicated that overall prevalence of stuttering in this population is 1/13 percent. Among primary, guidance and high school students the prevalence of stuttering was 2/06, 0/87 and 0/5 percent respectively. Prevalence of stuttering among boys was 1/35 and among girls was 0/88 percent. An overall male/female ratio was 1/5. Prevalence of stuttering in primary, guidance and high school was differ from each other significantly (P<0/001. Prevalence of stuttering in male was higher than female significantly (P=0/034. Conclusion: Prevalence of stuttering among Javanrood’s bilingual students was higher than accepted prevalence in monolinguals (1%. Risk of being stuttering in male was higher than female.

Implementing partnerships in nonreactor facility safety analyses

International Nuclear Information System (INIS)

Courtney, J.C.; Perry, W.H.; Phipps, R.D.

1996-01-01

Faculty and students from LSU have been participating in nuclear safety analyses and radiation protection projects at ANL-W at INEL since 1973. A mutually beneficial relationship has evolved that has resulted in generation of safety-related studies acceptable to Argonne and DOE, NRC, and state regulatory groups. Most of the safety projects have involved the Hot Fuel Examination Facility or the Fuel Conditioning Facility; both are hot cells that receive spent fuel from EBR-II. A table shows some of the major projects at ANL-W that involved LSU students and faculty

Quantile regression theory and applications

CERN Document Server

Davino, Cristina; Vistocco, Domenico

2013-01-01

A guide to the implementation and interpretation of Quantile Regression models This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods. The main focus of this book is to provide the reader with a comprehensivedescription of the main issues concerning quantile regression; these include basic modeling, geometrical interpretation, estimation and inference for quantile regression, as well as issues on validity of the model, diagnostic tools. Each methodological aspect is explored and

An appraisal of convergence failures in the application of logistic regression model in published manuscripts.

Science.gov (United States)

Yusuf, O B; Bamgboye, E A; Afolabi, R F; Shodimu, M A

2014-09-01

Logistic regression model is widely used in health research for description and predictive purposes. Unfortunately, most researchers are sometimes not aware that the underlying principles of the techniques have failed when the algorithm for maximum likelihood does not converge. Young researchers particularly postgraduate students may not know why separation problem whether quasi or complete occurs, how to identify it and how to fix it. This study was designed to critically evaluate convergence issues in articles that employed logistic regression analysis published in an African Journal of Medicine and medical sciences between 2004 and 2013. Problems of quasi or complete separation were described and were illustrated with the National Demographic and Health Survey dataset. A critical evaluation of articles that employed logistic regression was conducted. A total of 581 articles was reviewed, of which 40 (6.9%) used binary logistic regression. Twenty-four (60.0%) stated the use of logistic regression model in the methodology while none of the articles assessed model fit. Only 3 (12.5%) properly described the procedures. Of the 40 that used the logistic regression model, the problem of convergence occurred in 6 (15.0%) of the articles. Logistic regression tends to be poorly reported in studies published between 2004 and 2013. Our findings showed that the procedure may not be well understood by researchers since very few described the process in their reports and may be totally unaware of the problem of convergence or how to deal with it.

Fungible weights in logistic regression.

Science.gov (United States)

Jones, Jeff A; Waller, Niels G

2016-06-01

In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The confidence of speech-language pathology students regarding communicating with people with aphasia.

Science.gov (United States)

Finch, Emma; Fleming, Jennifer; Brown, Kyla; Lethlean, Jennifer; Cameron, Ashley; McPhail, Steven M

2013-06-27

Aphasia is an acquired language disorder that can present a significant barrier to patient involvement in healthcare decisions. Speech-language pathologists (SLPs) are viewed as experts in the field of communication. However, many SLP students do not receive practical training in techniques to communicate with people with aphasia (PWA) until they encounter PWA during clinical education placements. This study investigated the confidence and knowledge of SLP students in communicating with PWA prior to clinical placements using a customised questionnaire. Confidence in communicating with people with aphasia was assessed using a 100-point visual analogue scale. Linear, and logistic, regressions were used to examine the association between confidence and age, as well as confidence and course type (graduate-entry masters or undergraduate), respectively. Knowledge of strategies to assist communication with PWA was examined by asking respondents to list specific strategies that could assist communication with PWA. SLP students were not confident with the prospect of communicating with PWA; reporting a median 29-points (inter-quartile range 17-47) on the visual analogue confidence scale. Only, four (8.2%) of respondents rated their confidence greater than 55 (out of 100). Regression analyses indicated no relationship existed between confidence and students' age (p = 0.31, r-squared = 0.02), or confidence and course type (p = 0.22, pseudo r-squared = 0.03). Students displayed limited knowledge about communication strategies. Thematic analysis of strategies revealed four overarching themes; Physical, Verbal Communication, Visual Information and Environmental Changes. While most students identified potential use of resources (such as images and written information), fewer students identified strategies to alter their verbal communication (such as reduced speech rate). SLP students who had received aphasia related theoretical coursework, but not commenced clinical placements

Implications of Interactions among Society, Education and Technology: A Comparison of Multiple Linear Regression and Multilevel Modeling in Mathematics Achievement Analyses

Science.gov (United States)

Deering, Pamela Rose

2014-01-01

This research compares and contrasts two approaches to predictive analysis of three years' of school district data to investigate relationships between student and teacher characteristics and math achievement as measured by the state-mandated Maryland School Assessment mathematics exam. The sample for the study consisted of 3,514 students taught…