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Rrita Zejnullahi; Larry V. Hedges – Research Synthesis Methods, 2024
Conventional random-effects models in meta-analysis rely on large sample approximations instead of exact small sample results. While random-effects methods produce efficient estimates and confidence intervals for the summary effect have correct coverage when the number of studies is sufficiently large, we demonstrate that conventional methods…
Descriptors: Robustness (Statistics), Meta Analysis, Sample Size, Computation
Friede, Tim; Röver, Christian; Wandel, Simon; Neuenschwander, Beat – Research Synthesis Methods, 2017
Meta-analyses in orphan diseases and small populations generally face particular problems, including small numbers of studies, small study sizes and heterogeneity of results. However, the heterogeneity is difficult to estimate if only very few studies are included. Motivated by a systematic review in immunosuppression following liver…
Descriptors: Meta Analysis, Diseases, Medical Research, Research Problems
Wagler, Amy E. – Journal of Educational and Behavioral Statistics, 2014
Generalized linear mixed models are frequently applied to data with clustered categorical outcomes. The effect of clustering on the response is often difficult to practically assess partly because it is reported on a scale on which comparisons with regression parameters are difficult to make. This article proposes confidence intervals for…
Descriptors: Hierarchical Linear Modeling, Cluster Grouping, Heterogeneous Grouping, Monte Carlo Methods
Linting, Marielle; van Os, Bart Jan; Meulman, Jacqueline J. – Psychometrika, 2011
In this paper, the statistical significance of the contribution of variables to the principal components in principal components analysis (PCA) is assessed nonparametrically by the use of permutation tests. We compare a new strategy to a strategy used in previous research consisting of permuting the columns (variables) of a data matrix…
Descriptors: Intervals, Simulation, Statistical Significance, Factor Analysis
Romano, Jeanine L.; Kromrey, Jeffrey D.; Owens, Corina M.; Scott, Heather M. – Journal of Experimental Education, 2011
In this study, the authors aimed to examine 8 of the different methods for computing confidence intervals around alpha that have been proposed to determine which of these, if any, is the most accurate and precise. Monte Carlo methods were used to simulate samples under known and controlled population conditions wherein the underlying item…
Descriptors: Intervals, Monte Carlo Methods, Rating Scales, Computation
Gorman, Jamie C.; Cooke, Nancy J. – Journal of Experimental Psychology: Applied, 2011
This paper examines the retention of team cognition with changes in team membership. Hypotheses are developed from shared cognition and interactive team cognition theories. We report a study of the effects of Short (3-6 weeks) versus Long (10-13 weeks) retention intervals and change (Mixed) versus no change (Intact) in team membership during the…
Descriptors: Intervals, Teamwork, Program Effectiveness, Retention (Psychology)
Essid, Hedi; Ouellette, Pierre; Vigeant, Stephane – Economics of Education Review, 2010
The objective of this paper is to measure the efficiency of high schools in Tunisia. We use a statistical data envelopment analysis (DEA)-bootstrap approach with quasi-fixed inputs to estimate the precision of our measure. To do so, we developed a statistical model serving as the foundation of the data generation process (DGP). The DGP is…
Descriptors: High Schools, Intervals, Statistical Data, Foreign Countries
Thompson, Nathan A. – Practical Assessment, Research & Evaluation, 2011
Computerized classification testing (CCT) is an approach to designing tests with intelligent algorithms, similar to adaptive testing, but specifically designed for the purpose of classifying examinees into categories such as "pass" and "fail." Like adaptive testing for point estimation of ability, the key component is the…
Descriptors: Adaptive Testing, Computer Assisted Testing, Classification, Probability
Finkelman, Matthew David – Applied Psychological Measurement, 2010
In sequential mastery testing (SMT), assessment via computer is used to classify examinees into one of two mutually exclusive categories. Unlike paper-and-pencil tests, SMT has the capability to use variable-length stopping rules. One approach to shortening variable-length tests is stochastic curtailment, which halts examination if the probability…
Descriptors: Mastery Tests, Computer Assisted Testing, Adaptive Testing, Test Length
Thomas, D. Roland; Zhu, PengCheng; Decady, Yves J. – Journal of Educational and Behavioral Statistics, 2007
The topic of variable importance in linear regression is reviewed, and a measure first justified theoretically by Pratt (1987) is examined in detail. Asymptotic variance estimates are used to construct individual and simultaneous confidence intervals for these importance measures. A simulation study of their coverage properties is reported, and an…
Descriptors: Intervals, Simulation, Regression (Statistics), Computation
Maydeu-Olivares, Alberto; Coffman, Donna L.; Hartmann, Wolfgang M. – Psychological Methods, 2007
The point estimate of sample coefficient alpha may provide a misleading impression of the reliability of the test score. Because sample coefficient alpha is consistently biased downward, it is more likely to yield a misleading impression of poor reliability. The magnitude of the bias is greatest precisely when the variability of sample alpha is…
Descriptors: Intervals, Scores, Sample Size, Simulation
Van Rijn, P. W.; Eggen, T. J. H. M.; Hemker, B. T.; Sanders, P. F. – Applied Psychological Measurement, 2002
In the present study, a procedure that has been used to select dichotomous items in computerized adaptive testing was applied to polytomous items. This procedure was designed to select the item with maximum weighted information. In a simulation study, the item information function was integrated over a fixed interval of ability values and the item…
Descriptors: Intervals, Simulation, Adaptive Testing, Computer Assisted Testing