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Peer reviewedSawyer, Richard – Journal of Educational Statistics, 1982
Rules are given for estimating accuracy of predictions based on a multiple regression equation. Formulas for moments of distribution and other parameters are noted. The approximate inflation in mean absolute error due to estimating the regression coefficients is a function of the base sample size and number of predictors. (DWH)
Descriptors: Colleges, Estimation (Mathematics), Multiple Regression Analysis, Predictive Validity
Peer reviewedCooil, Bruce; Rust, Roland T. – Psychometrika, 1994
It is proposed that proportional reduction in loss (PRL) be used as a theoretical basis to derive, justify, and interpret reliability measures to gauge reliability on a zero-to-one scale. This PRL approach simplifies the interpretation of existing measures (e.g., generalizability-theory measures). (SLD)
Descriptors: Data Analysis, Equations (Mathematics), Estimation (Mathematics), Generalizability Theory
Peer reviewedCornwell, John M.; Ladd, Robert T. – Educational and Psychological Measurement, 1993
Simulated data typical of those from meta analyses are used to evaluate the reliability, Type I and Type II errors, bias, and standard error of the meta-analytic procedures of Schmidt and Hunter (1977). Concerns about power, reliability, and Type I errors are presented. (SLD)
Descriptors: Bias, Computer Simulation, Correlation, Effect Size
Farish, Stephen J. – 1984
The stability of Rasch test item difficulty parameters was investigated under varying conditions. Data were taken from a mathematics achievement test administered to over 2,000 Australian students. The experiments included: (1) relative stability of the Rasch, traditional, and z-item difficulty parameters using different sample sizes and designs;…
Descriptors: Achievement Tests, Difficulty Level, Estimation (Mathematics), Foreign Countries


