The purpose of this research is to first estimate the item and ability parameters and the standard error values related to those parameters obtained from Unidimensional Item Response Theory (UIRT), bifactor (BIF) and Testlet Response Theory models (TRT) in the tests including testlets, when the number of testlets, number of independent items, and…

The method of least-squares (LS) has a built-in procedure for estimating the standard errors (SEs) of the adjustable parameters in the fit model: They are the square roots of the diagonal elements of the covariance matrix. This means that one can use least-squares to obtain numerical values of propagated errors by defining the target quantities as…

This study develops a tool to identify errors in the presentation of natural laws based on the epistemology and ontology of the Scientific Realism of Mario Bunge. The tool is able to identify errors of different types: (1) epistemological, in which the law is incorrectly presented as data correlation instead of as a pattern of causality; (2)…

The usual formulas for the reliability of differences between two test scores are based on the assumption that the error scores are uncorrelated. Formulas are presented for the general case where this assumption is unnecessary. (Author/JKS)

A procedure is presented for the analysis of rating data with correlated intrajudge and uncorrelated interjudge measurement errors. Correlations between true scores on different rating dimensions, reliabilities for each judge on each dimension and correlations between intrajudge errors can be estimated given a minimum of three raters and two…

The correction for attenuation formulas for partial, multiple, and canonical correlation coefficients are discussed and the effects of measurement errors on these statistics are explored. The notation is standardized and the derivation extended where appropriate. It is shown that as the reliabilities of the predictors become more disparate, the…

The present paper suggests that multivariate methods ought to be used more frequently in behavioral research and explores the potential consequences of failing to use multivariate methods when these methods are appropriate. The paper explores in detail two reasons why multivariate methods are usually vital. The first is that they limit the…

Failure to consider errors of measurement when using partial correlation or analysis of covariance techniques can result in erroneous conclusions. Certain aspects of this problem are discussed and particular attention is given to issues raised in a recent article by Brewar, Campbell, and Crano. (Author)