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Wilhelm, Anne Garrison; Gillespie Rouse, Amy; Jones, Francesca – Practical Assessment, Research & Evaluation, 2018
Although inter-rater reliability is an important aspect of using observational instruments, it has received little theoretical attention. In this article, we offer some guidance for practitioners and consumers of classroom observations so that they can make decisions about inter-rater reliability, both for study design and in the reporting of data…
Descriptors: Interrater Reliability, Measurement, Observation, Educational Research
Feng, Xiang-Nan; Wu, Hao-Tian; Song, Xin-Yuan – Sociological Methods & Research, 2017
We consider an ordinal regression model with latent variables to investigate the effects of observable and latent explanatory variables on the ordinal responses of interest. Each latent variable is characterized by correlated observed variables through a confirmatory factor analysis model. We develop a Bayesian adaptive lasso procedure to conduct…
Descriptors: Bayesian Statistics, Regression (Statistics), Models, Observation
Green, Samuel B.; Levy, Roy; Thompson, Marilyn S.; Lu, Min; Lo, Wen-Juo – Educational and Psychological Measurement, 2012
A number of psychometricians have argued for the use of parallel analysis to determine the number of factors. However, parallel analysis must be viewed at best as a heuristic approach rather than a mathematically rigorous one. The authors suggest a revision to parallel analysis that could improve its accuracy. A Monte Carlo study is conducted to…
Descriptors: Monte Carlo Methods, Factor Structure, Data Analysis, Psychometrics
Romano, Jeanine L.; Kromrey, Jeffrey D. – Educational and Psychological Measurement, 2009
This study was conducted to evaluate alternative analysis strategies for the meta-analysis method of reliability generalization when the reliability estimates are not statistically independent. Five approaches to dealing with the violation of independence were implemented: ignoring the violation and treating each observation as independent,…
Descriptors: Reliability, Generalization, Meta Analysis, Correlation
Peer reviewedHummel, Thomas J.; Feltovich, Paul J. – Multivariate Behavioral Research, 1975
Monte Carlo methods were used to investigate the robustness of techniques used in judging the magnitude of a sample correlation coefficient when observations are correlated. Empirical distributions of r, t, and Fisher's z were generated. A technique for controlling error rates in certain situations is suggested. (Author/BJG)
Descriptors: Computer Science, Correlation, Error Patterns, Monte Carlo Methods

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