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Haardörfer, Regine – Health Education & Behavior, 2019
In this article, Regine Haardörfer outlines five general steps taken by good data analysts and how they need to be theory-driven data-informed. She uses these to discuss some issues and propose approaches to promote better data analysis and reporting. The proposed steps to rigorous data analysis are to: (1) create an a priori data analysis plan;…
Descriptors: Data Analysis, Theories, Social Science Research, Behavioral Science Research
Blaine, Bruce Evan – Scholarship and Practice of Undergraduate Research, 2019
Reproducibility crises have arisen in psychology and other behavioral sciences, spurring efforts to ensure research findings are credible and replicable. Although reforms are occurring at professional levels in terms of new publication parameters and open science initiatives, the credibility and reproducibility of undergraduate research deserves…
Descriptors: Undergraduate Students, Student Research, Behavioral Science Research, Research Methodology
Enders, Craig K.; Keller, Brian T.; Levy, Roy – Grantee Submission, 2018
Specialized imputation routines for multilevel data are widely available in software packages, but these methods are generally not equipped to handle a wide range of complexities that are typical of behavioral science data. In particular, existing imputation schemes differ in their ability to handle random slopes, categorical variables,…
Descriptors: Hierarchical Linear Modeling, Behavioral Science Research, Computer Software, Bayesian Statistics
Gottschall, Amanda C.; West, Stephen G.; Enders, Craig K. – Multivariate Behavioral Research, 2012
Behavioral science researchers routinely use scale scores that sum or average a set of questionnaire items to address their substantive questions. A researcher applying multiple imputation to incomplete questionnaire data can either impute the incomplete items prior to computing scale scores or impute the scale scores directly from other scale…
Descriptors: Questionnaires, Data Analysis, Computation, Monte Carlo Methods
Vallejo, G.; Fernandez, M. P.; Livacic-Rojas, P. E.; Tuero-Herrero, E. – Multivariate Behavioral Research, 2011
Missing data are a pervasive problem in many psychological applications in the real world. In this article we study the impact of dropout on the operational characteristics of several approaches that can be easily implemented with commercially available software. These approaches include the covariance pattern model based on an unstructured…
Descriptors: Personality Problems, Psychosis, Prevention, Patients
Fields, Lanny; Travis, Robert; Roy, Deborah; Yadlovker, Eytan; de Aguiar-Rocha, Liliane; Sturmey, Peter – Journal of Applied Behavior Analysis, 2009
Many students struggle with statistical concepts such as interaction. In an experimental group, participants took a paper-and-pencil test and then were given training to establish equivalent classes containing four different statistical interactions. All participants formed the equivalence classes and showed maintenance when probes contained novel…
Descriptors: Experimental Groups, Control Groups, Interaction, Concept Formation
Parker, Richard I.; Hagan-Burke, Shanna – Behavior Therapy, 2007
An obstacle to broader acceptability of effect sizes in single case research is their lack of intuitive and useful interpretations. Interpreting Cohen's d as "standard deviation units difference" and R[superscript 2] as "percent of variance accounted for" do not resound with most visual analysts. In fact, the only comparative analysis widely…
Descriptors: Meta Analysis, Effect Size, Comparative Analysis, Behavioral Sciences

Glass, Gene V. – American Educational Research Journal, 1972
The time-series process postulated is a more general form of the integrated moving average model than for which estimation and testing procedures were formerly available. (Author)
Descriptors: Behavioral Science Research, Data Analysis, Intervention, Mathematical Models

Wampold, Bruce E.; Freund, Richard D. – Journal of Counseling Psychology, 1987
Explains multiple regression, demonstrates its flexibility for analyzing data from various designs, and discusses interpretation of results from multiple regression analysis. Presents regression equations for single independent variable and for two or more independent variables, followed by a discussion of coefficients related to these. Compares…
Descriptors: Behavioral Science Research, Counseling, Data Analysis, Multiple Regression Analysis
Byrd, Jimmy K. – Educational Administration Quarterly, 2007
Purpose: The purpose of this study was to review research published by Educational Administration Quarterly (EAQ) during the past 10 years to determine if confidence intervals and effect sizes were being reported as recommended by the American Psychological Association (APA) Publication Manual. Research Design: The author examined 49 volumes of…
Descriptors: Research Design, Intervals, Statistical Inference, Effect Size

Schaefer, Vernon H. – Teaching of Psychology, 1976
Understanding the concept of interaction is vital to understanding the relationships of dimensions of phenomena under study. Use of multivariate analysis of variance is described as a useful approach for discovering the extent to which events may be complexly interaffecting. (Author/AV)
Descriptors: Behavioral Science Research, Concept Teaching, Data Analysis, Higher Education
Timm, Neil H. – 1971
Pearson's unrestricted chi-square procedure is reviewed, and an historical presentation of Neyman's restricted chi-square test is introduced with a discussion of its theory and applicability to education. An example of the Neyman procedure is discussed in detail to familiarize researchers with this useful technique for analyzing contingency…
Descriptors: Behavioral Science Research, Data Analysis, Hypothesis Testing, Mathematical Applications
Christensen, James E.; Christensen, Charlene E. – Research Quarterly, 1977
More attention should focus on sample sizes and the concept of statistical power in research in the field of health, physical education, and recreation. (JD)
Descriptors: Behavioral Science Research, Data Analysis, Data Collection, Evaluation Methods
Jenkins, W. O. – 1967
This paper is an ardent plea for simplifying experimental design and the associated statistics. The emphasis is on design itself. Traditional designs from simple to complex and reviewed and the simplest, most basic ways of handling the data are presented. Design is stressed in such a way that simple statistics follow. The intactness of…
Descriptors: Analysis of Covariance, Analysis of Variance, Behavioral Science Research, Correlation
Nesselroade, John R.; Baltes, Paul B. – 1977
This manual is intended to improve both the design of longitudinal studies and analysis of the resulting data. Issues related to educational and developmental research have been emphasized in these eight chapters. Topics of particular interest to longitudinal researchers include stochastic models of developmental change, mathematical…
Descriptors: Behavioral Science Research, Data Analysis, Educational Research, Human Development
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