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Padilla, Miguel A.; Divers, Jasmin; Newton, Matthew – Applied Psychological Measurement, 2012
Three different bootstrap methods for estimating confidence intervals (CIs) for coefficient alpha were investigated. In addition, the bootstrap methods were compared with the most promising coefficient alpha CI estimation methods reported in the literature. The CI methods were assessed through a Monte Carlo simulation utilizing conditions…
Descriptors: Intervals, Monte Carlo Methods, Computation, Sampling
Dorans, Neil J.; Liu, Jinghua; Hammond, Shelby – Applied Psychological Measurement, 2008
This exploratory study was built on research spanning three decades. Petersen, Marco, and Stewart (1982) conducted a major empirical investigation of the efficacy of different equating methods. The studies reported in Dorans (1990) examined how different equating methods performed across samples selected in different ways. Recent population…
Descriptors: Test Format, Equated Scores, Sampling, Evaluation Methods

Baker, Frank B. – Applied Psychological Measurement, 1997
Examined the sampling distributions of equating coefficients produced by the characteristic curve method for tests using graded and nominal response scoring using simulated data. For both models and across all three equating situations, the sampling distributions were generally bell-shaped and peaked, and occasionally had a small degree of…
Descriptors: Equated Scores, Sampling, Simulation, Statistical Distributions

Raju, Nambury S.; Brand, Paul A. – Applied Psychological Measurement, 2003
Proposed a new asymptotic formula for estimating the sampling variance of a correlation coefficient corrected for unreliability and range restriction. A Monte Carlo simulation study of the new formula results in several positive conclusions about the new approach. (SLD)
Descriptors: Correlation, Monte Carlo Methods, Reliability, Sampling

Emons, Wilco H. M.; Meijer, Rob R.; Sijtsma, Klaas – Applied Psychological Measurement, 2002
Studied whether the theoretical sampling distribution of the U3 person-fit statistic is in agreement with the simulated sampling distribution under different item response theory models and varying item and test characteristics. Simulation results suggest that the use of standard normal deviates for the standardized version of the U3 statistic may…
Descriptors: Item Response Theory, Sampling, Simulation, Statistical Distributions

Nevo, Baruch – Applied Psychological Measurement, 1980
Computer simulations were employed to investigate sample sizes needed for item analysis when one's primary purpose is to rank order items in terms of indices of quality or to compare indices of quality against a fixed criterion. Necessary sample sizes were much smaller than those indicated by the literature. (Author/JKS)
Descriptors: Foreign Countries, Higher Education, Item Analysis, Sampling
Huitzing, Hiddo A. – Applied Psychological Measurement, 2004
This article shows how set covering with item sampling (SCIS) methods can be used in the analysis and preanalysis of linear programming models for test assembly (LPTA). LPTA models can construct tests, fulfilling a set of constraints set by the test assembler. Sometimes, no solution to the LPTA model exists. The model is then said to be…
Descriptors: Mathematical Applications, Simulation, Item Sampling, Item Response Theory

And Others; Drasgow, Fritz – Applied Psychological Measurement, 1979
A Monte Carlo experiment was used to evaluate four procedures for estimating the population squared cross-validity of a sample least squares regression equation. One estimator was particularly recommended. (Author/BH)
Descriptors: Correlation, Least Squares Statistics, Mathematical Formulas, Multiple Regression Analysis

Cliff, Norman; And Others – Applied Psychological Measurement, 1979
Monte Carlo research with TAILOR, a program using implied orders as a basis for tailored testing, is reported. TAILOR typically required about half the available items to estimate, for each simulated examinee, the responses on the remainder. (Author/CTM)
Descriptors: Adaptive Testing, Computer Programs, Item Sampling, Nonparametric Statistics