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McDonald, Roderick P. – Psychometrika, 2011
A distinction is proposed between measures and predictors of latent variables. The discussion addresses the consequences of the distinction for the true-score model, the linear factor model, Structural Equation Models, longitudinal and multilevel models, and item-response models. A distribution-free treatment of calibration and…
Descriptors: Measurement, Structural Equation Models, Item Response Theory, Error of Measurement
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Yuan, Ke-Hai; Chan, Wai – Psychometrika, 2011
The paper obtains consistent standard errors (SE) and biases of order O(1/n) for the sample standardized regression coefficients with both random and given predictors. Analytical results indicate that the formulas for SEs given in popular text books are consistent only when the population value of the regression coefficient is zero. The sample…
Descriptors: Statistical Bias, Error of Measurement, Regression (Statistics), Predictor Variables
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Bentler, Peter M.; Yuan, Ke-Hai – Psychometrika, 2011
Indefinite symmetric matrices that are estimates of positive-definite population matrices occur in a variety of contexts such as correlation matrices computed from pairwise present missing data and multinormal based methods for discretized variables. This note describes a methodology for scaling selected off-diagonal rows and columns of such a…
Descriptors: Scaling, Factor Analysis, Correlation, Predictor Variables
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Haberman, Shelby J. – Psychometrika, 2006
When a simple random sample of size n is employed to establish a classification rule for prediction of a polytomous variable by an independent variable, the best achievable rate of misclassification is higher than the corresponding best achievable rate if the conditional probability distribution is known for the predicted variable given the…
Descriptors: Bias, Computation, Sample Size, Classification