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Bonett, Douglas G. – Journal of Educational and Behavioral Statistics, 2022
The limitations of Cohen's ? are reviewed and an alternative G-index is recommended for assessing nominal-scale agreement. Maximum likelihood estimates, standard errors, and confidence intervals for a two-rater G-index are derived for one-group and two-group designs. A new G-index of agreement for multirater designs is proposed. Statistical…
Descriptors: Statistical Inference, Statistical Data, Interrater Reliability, Design
Bonett, Douglas G. – Journal of Educational and Behavioral Statistics, 2015
Paired-samples designs are used frequently in educational and behavioral research. In applications where the response variable is quantitative, researchers are encouraged to supplement the results of a paired-samples t-test with a confidence interval (CI) for a mean difference or a standardized mean difference. Six CIs for standardized mean…
Descriptors: Educational Research, Sample Size, Statistical Analysis, Effect Size
Bonett, Douglas G. – Psychological Methods, 2009
The fixed-effects (FE) meta-analytic confidence intervals for unstandardized and standardized mean differences are based on an unrealistic assumption of effect-size homogeneity and perform poorly when this assumption is violated. The random-effects (RE) meta-analytic confidence intervals are based on an unrealistic assumption that the selected…
Descriptors: Intervals, Effect Size, Meta Analysis, Statistical Analysis
Bonett, Douglas G. – Psychological Methods, 2009
L. Wilkinson and the Task Force on Statistical Inference (1999) recommended reporting confidence intervals for measures of effect sizes. If the sample size is too small, the confidence interval may be too wide to provide meaningful information. Recently, K. Kelley and J. R. Rausch (2006) used an iterative approach to computer-generate tables of…
Descriptors: Intervals, Sample Size, Effect Size, Statistical Inference
Bonett, Douglas G. – Psychological Methods, 2008
The currently available meta-analytic methods for correlations have restrictive assumptions. The fixed-effects methods assume equal population correlations and exhibit poor performance under correlation heterogeneity. The random-effects methods do not assume correlation homogeneity but are based on an equally unrealistic assumption that the…
Descriptors: Intervals, Multivariate Analysis, Meta Analysis, Correlation
Bonett, Douglas G. – Applied Psychological Measurement, 2006
Comparing variability of test scores across alternate forms, test conditions, or subpopulations is a fundamental problem in psychometrics. A confidence interval for a ratio of standard deviations is proposed that performs as well as the classic method with normal distributions and performs dramatically better with nonnormal distributions. A simple…
Descriptors: Intervals, Mathematical Concepts, Comparative Analysis, Psychometrics
Bonett, Douglas G.; Price, Robert M. – Journal of Educational and Behavioral Statistics, 2005
The tetrachoric correlation describes the linear relation between two continuous variables that have each been measured on a dichotomous scale. The treatment of the point estimate, standard error, interval estimate, and sample size requirement for the tetrachoric correlation is cursory and incomplete in modern psychometric and behavioral…
Descriptors: Correlation, Predictor Variables, Measures (Individuals), Error of Measurement