
Determining the Factors of Social Phobia Levels of University Students: A Logistic Regression Analysis
Science.gov (United States)
Ozen, Hamit
20160101
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…

A Logistic Regression Analysis of Score Sending and College Matching among High School Students
Science.gov (United States)
Oates, Krystle S.
20150101
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…

Classification and regression tree (CART) analyses of genomic signatures reveal sets of tetramers that discriminate temperature optima of archaea and bacteria
Science.gov (United States)
Dyer, Betsey D.; Kahn, Michael J.; LeBlanc, Mark D.
20080101
Classification and regression tree (CART) analysis was applied to genomewide 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 purineloading and codon biases of thermophiles may explain some of the results. PMID:19054742

Assessing the suitability of summary data for twosample Mendelian randomization analyses using MREgger regression: the role of the I2 statistic.
Science.gov (United States)
Bowden, Jack; Del Greco M, Fabiola; Minelli, Cosetta; Davey Smith, George; Sheehan, Nuala A; Thompson, John R
20161201
: MREgger 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. MREgger 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 Fstatistic. The effect of NOME violation on MREgger regression has yet to be studied. An adaptation of the I2 statistic from the field of metaanalysis is proposed to quantify the strength of NOME violation for MREgger. It lies between 0 and 1, and indicates the expected relative bias (or dilution) of the MREgger causal estimate in the twosample 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 twosample MR analyses we show that, when a causal effect exists, the MREgger 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 MREgger test for pleiotropy is inflated and the causal effect underestimated. Simulation extrapolation is shown to substantially mitigate these adverse effects. We

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)
20151022
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 q1 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, goodnessoffit 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
20150101
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 q1 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, goodnessoffit 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

Collaborative Learning with Web 2.0 Tools: Analysing Malaysian Students' Perceptions and Peer Interaction
Science.gov (United States)
Leow, Fui Theng; Neo, Mai
20150101
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 coconstructing new meaning. This study analyses student's perception and their peer interaction in the constructivistcollaborative…

The more total cognitive load is reduced by cues, the better retention and transfer of multimedia learning: A metaanalysis and two metaregression analyses.
Science.gov (United States)
Xie, Heping; Wang, Fuxing; Hao, Yanbin; Chen, Jiaxue; An, Jing; Wang, Yuxin; Liu, Huashan
20170101
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 cuerelated cognitive load and learning outcomes. A metaanalysis and two subsequent metaregression 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 SCLrelated metaanalysis. Among them, 25 articles containing 2,910 participants were included in the retentionrelated metaanalysis and the following retentionrelated metaregression, while there were 29 articles containing 3,204 participants included in the transferrelated metaanalysis and the transferrelated metaregression. The metaanalysis 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 metaregression 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.

Estimation of Stature from Foot Dimensions and Stature among South Indian Medical Students Using Regression Models
Directory of Open Access Journals (Sweden)
Rajesh D. R
20150101
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 1822 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.

ENHANCED PREDICTION OF STUDENT DROPOUTS USING FUZZY INFERENCE SYSTEM AND LOGISTIC REGRESSION
OpenAIRE
A. Saranya; J. Rajeswari
20160101
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...

HOW SFG INCREASE STUDENTS ABILITY TO PRODUCE AND ANALYSE TEXT MEDIA
Directory of Open Access Journals (Sweden)
Abd. Ghofur
20130501
Full Text Available This article explores the use of Systemic Functional Grammar for students of english language teaching entitled Analysing Media Texts. This is aims at assisting students to produce their own texts and to help them develop an understanding of the linguistic choices they make. Students are introduced to the key principles of CDA and to Halliday’s SFG to provide them with tools to assist them to understand the social and constructed nature of discourses, especially those typically found in media texts. This article focuses on students’ interpretation of media texts, their ability to read with greater understanding and to apply key concepts that they had learnt to their analyses. The students demonstrated clearly that they had developed an understanding of CDA, acquired the basic metalanguage necessary for Hallidayan analysis and some of them could produce much more rigorous textual analyses than before.

Predictors of success of external cephalic version and cephalic presentation at birth among 1253 women with noncephalic presentation using logistic regression and classification tree analyses.
Science.gov (United States)
Hutton, Eileen K; Simioni, Julia C; Thabane, Lehana
20170801
Among women with a fetus with a noncephalic 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 noncephalic 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 (3436 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, nonengagement of the presenting part and an easily palpable fetal head were independently associated with success. Among multiparas, nonengagement 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.

Students' Outcome Expectation on Spiritual and Religious Competency: A Hierarchical Regression Analysis
Science.gov (United States)
Lu, Junfei; Woo, Hongryun
20170101
In this study, 74 master'slevel 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.…

Understanding the Greenhouse Effect by Embodiment  Analysing and Using Students' and Scientists' Conceptual Resources
Science.gov (United States)
Niebert, Kai; Gropengießer, Harald
20140101
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 experiencebased schemata they use as source domains for metaphorical understanding of the greenhouse effect. By uncovering themostly unconsciousdeployed schemata, we gave students access to their source domains. We implemented these teaching guidelines in interventions and evaluated them in teaching experiments to develop evidencebased and theoryguided learning activities on the greenhouse effect.

Predicting Student Success in a Major's Introductory Biology Course via Logistic Regression Analysis of Scientific Reasoning Ability and Mathematics Scores
Science.gov (United States)
Thompson, E. David; Bowling, Bethany V.; Markle, Ross E.
20180201
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 (ACTM) scores to predict student success. In summary, we found that the model—with both SR and ACTM 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.

Analysing task design and students' responses to contextbased problems through different analytical frameworks
Science.gov (United States)
Broman, Karolina; Bernholt, Sascha; Parchmann, Ilka
20150501
Background:Contextbased 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 nonconventional approaches, while effects on learning outcomes are less coherent. Hence, further insights are needed into the structure of contextbased problems in comparison to traditional problems, and into students' problemsolving 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 contextbased tasks as well as students' responses to exemplary tasks to identify a suitable framework for future design and analyses of contextbased problems. The paper discusses different established frameworks and applies the HigherOrder Cognitive Skills/LowerOrder Cognitive Skills (HOCS/LOCS) taxonomy and the Model of Hierarchical Complexity in Chemistry (MHCC) 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 contextbased 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 contextbased problem. Content analysis using HOCS/LOCS and MHCC frameworks has been applied to analyse both quantitative and qualitative data, allowing us to describe different problemsolving 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

Analyses of polycyclic aromatic hydrocarbon (PAH) and chiralPAH analoguesmethylβcyclodextrin guesthost inclusion complexes by fluorescence spectrophotometry and multivariate regression analysis.
Science.gov (United States)
Greene, LaVana; Elzey, Brianda; Franklin, Mariah; Fakayode, Sayo O
20170305
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 guesthost inclusion complexation, fluorescence spectrophotometry, and chemometric approach to PAH (anthracene) and chiralPAH analogue derivatives (1(9anthryl)2,2,2triflouroethanol (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 TFEmethylβcyclodextrin (MeβCD) guesthost complexes were also determined. Chemometric partialleastsquare (PLS) regression analysis of emission spectra data of MeβCDguesthost inclusion complexes was used for the determination of anthracene and TFE enantiomer concentrations in MeβCDguesthost inclusion complex samples. The values of calculated K b and negative ΔG suggest the thermodynamic favorability of anthraceneMeβCD and enantiomeric of TFEMeβCD inclusion complexation reactions. However, anthraceneMeβCD and enantiomer TFEMeβCD inclusion complexations showed notable differences in the binding affinity behaviors and thermodynamic properties. The PLS regression analysis resulted in squarecorrelationcoefficients 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 RTFE and 3.60% for STFE. 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

BisphenolA exposures and behavioural aberrations: median and linear spline and metaregression analyses of 12 toxicity studies in rodents.
Science.gov (United States)
Peluso, Marco E M; Munnia, Armelle; Ceppi, Marcello
20141105
Exposures to bisphenolA, a weak estrogenic chemical, largely used for the production of plastic containers, can affect the rodent behaviour. Thus, we examined the relationships between bisphenolA and the anxietylike behaviour, spatial skills, and aggressiveness, in 12 toxicity studies of rodent offspring from females orally exposed to bisphenolA, while pregnant and/or lactating, by median and linear splines analyses. Subsequently, the metaregression analysis was applied to quantify the behavioural changes. Ushaped, inverted Ushaped and Jshaped doseresponse curves were found to describe the relationships between bisphenolA with the behavioural outcomes. The occurrence of anxiogeniclike effects and spatial skill changes displayed Ushaped and inverted Ushaped curves, respectively, providing examples of effects that are observed at lowdoses. Conversely, a Jdoseresponse 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 metaregression indicated that a borderline significant increment of anxiogeniclike effects was present at lowdoses regardless of sexes (β)=0.8%, 95% C.I. 1.7/0.1, P=0.076, at ≤120 μg bisphenolA. Whereas, only bisphenolAmales 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, bisphenolA treatments significantly abrogated spatial learning and ability in males (PbisphenolA, e.g. ≤120 μg/day, were associated to behavioural aberrations in offspring. Copyright © 2014. Published by Elsevier Ireland Ltd.

Targeted Funding for Educationally Disadvantaged Students: A Regression Discontinuity Estimate of the Impact on High School Student Achievement
Science.gov (United States)
Henry, Gary T.; Fortner, C. Kevin; Thompson, Charles L.
20100101
Evaluating the impacts of public school funding on student achievement has been an important objective for informing education policymaking but fraught with data and methodological limitations. Findings from prior research have been mixed at best, leaving policymakers with little advice about the benefits of allocating public resources to schools…

Exploring reasons for the observed inconsistent trial reports on intraarticular injections with hyaluronic acid in the treatment of osteoarthritis: Metaregression analyses of randomized trials.
Science.gov (United States)
Johansen, Mette; Bahrt, Henriette; Altman, Roy D; Bartels, Else M; Juhl, Carsten B; Bliddal, Henning; Lund, Hans; Christensen, Robin
20160801
The aim was to identify factors explaining inconsistent observations concerning the efficacy of intraarticular hyaluronic acid compared to intraarticular sham/control, or nonintervention control, in patients with symptomatic osteoarthritis, based on randomized clinical trials (RCTs). A systematic review and metaregression analyses of available randomized trials were conducted. The outcome, pain, was assessed according to a prespecified hierarchy of potentially available outcomes. Hedges׳s standardized mean difference [SMD (95% CI)] served as effect size. REstricted Maximum Likelihood (REML) mixedeffects models were used to combine study results, and heterogeneity was calculated and interpreted as Tausquared and Isquared, respectively. Overall, 99 studies (14,804 patients) met the inclusion criteria: Of these, only 71 studies (72%), including 85 comparisons (11,216 patients), had adequate data available for inclusion in the primary metaanalysis. Overall, compared with placebo, intraarticular hyaluronic acid reduced pain with an effect size of 0.39 [0.47 to 0.31; P hyaluronic acid. Based on available trial data, intraarticular hyaluronic acid showed a better effect than intraarticular saline on pain reduction in osteoarthritis. Publication bias and the risk of selective outcome reporting suggest only small clinical effect compared to saline. Copyright © 2016 Elsevier Inc. All rights reserved.