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Karabatsos, George; Talbott, Elizabeth; Walker, Stephen G. – Research Synthesis Methods, 2015
In a meta-analysis, it is important to specify a model that adequately describes the effect-size distribution of the underlying population of studies. The conventional normal fixed-effect and normal random-effects models assume a normal effect-size population distribution, conditionally on parameters and covariates. For estimating the mean overall…
Descriptors: Bayesian Statistics, Meta Analysis, Prediction, Nonparametric Statistics
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Rindskopf, David – Society for Research on Educational Effectiveness, 2013
Single case designs (SCDs) generally consist of a small number of short time series in two or more phases. The analysis of SCDs statistically fits in the framework of a multilevel model, or hierarchical model. The usual analysis does not take into account the uncertainty in the estimation of the random effects. This not only has an effect on the…
Descriptors: Research Design, Bayesian Statistics, Computation, Data
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Zhou, Bo; Konstorum, Anna; Duong, Thao; Tieu, Kinh H.; Wells, William M.; Brown, Gregory G.; Stern, Hal S.; Shahbaba, Babak – Psychometrika, 2013
We propose a hierarchical Bayesian model for analyzing multi-site experimental fMRI studies. Our method takes the hierarchical structure of the data (subjects are nested within sites, and there are multiple observations per subject) into account and allows for modeling between-site variation. Using posterior predictive model checking and model…
Descriptors: Brain, Diagnostic Tests, Bayesian Statistics, Hierarchical Linear Modeling
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Society for Research on Educational Effectiveness, 2013
One of the vexing problems in the analysis of SSD is in the assessment of the effect of intervention. Serial dependence notwithstanding, the linear model approach that has been advanced involves, in general, the fitting of regression lines (or curves) to the set of observations within each phase of the design and comparing the parameters of these…
Descriptors: Research Design, Effect Size, Intervention, Statistical Analysis
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Wells, Ryan S.; Kolek, Ethan A.; Williams, Elizabeth A.; Saunders, Daniel B. – Journal of Higher Education, 2015
This study replicates and extends a 2004 content analysis of three major higher education journals. The original study examined the methodological characteristics of all published research in these journals from 1996 to 2000, recommending that higher education programs adjust their graduate training to better match the heavily quantitative and…
Descriptors: Research Methodology, Higher Education, Journal Articles, Educational Research
American Educational Research Association, Washington, DC. – 1967
This document contains summaries of six courses presented at the Second Annual Presessions of the American Educational Research Association: (1) Bayesian statistical analysis, (2) curriculum research and evaluation, (3) design and analysis of comparative experiments in education, (4) educational research management procedures, (5) multivariate…
Descriptors: Bayesian Statistics, Comparative Analysis, Computer Programs, Conference Reports
Fyans, Leslie J., Jr. – 1978
Unlike the past models guiding cross-cultural psychological research, a new paradigm facilitates multiple level investigations by incorporating both culture-specific (nested) and culture-general (crossed) independent variables within its partially-hierarchical framework. Based upon the generalizability analysis, this model generates sequential…
Descriptors: Analysis of Variance, Bayesian Statistics, Cognitive Processes, Comparative Analysis