Univariate repeated measures techniques applied to multivariate data

Repeated measures designs in psychology have traditionally been analyzed by the univariate mixed model approach, in which the repeated measures effect is tested against an error term based on the subject by treatment interaction. This paper considers the extension of this analysis to designs in which the individual repeated measures are multivariate. Sufficient conditions for a valid multivariate mixed model analysis are given, and a test is described to determine whether or not given data satisfy these conditions.     

Ordinal data: An alternative distribution

To date, virtually all techniques appropriate for ordinal data are based on the uniform probability distribution over the permutations. In this paper we introduce and examine an alternative probability model for the distribution of ordinal data. Preliminary to deriving the expectations of Spearman's rho and Kendall's tau under this model, we show how to compute certain conditional expectations of rho and tau under the uniform distribution. The alternative probability model is then applied to ordinal test theory, and the calculation of true scores and test reliability are discussed.     

ANOVA and ANCOVA of pre- and post-test,ordinal data

With random assignment to treatments and standard assumptions, either a one-way ANOVA of post-test scores or a two-way, repeated measures ANOVA of pre- and post-test scores provides a legitimate test of the equal treatment effect null hypothesis for latent variable . In an ANCOVA for pre- and post-test variablesX andY which are ordinal measures of and , respectively, random assignment and standard assumptions ensure the legitimacy of inferences about the equality of treatment effects on latent variable . Sample estimates of adjustedY treatment means are ordinal estimators of adjusted post-test means on latent variable .     

Adults' estimates of pre-school children's verbal and motor abilities compared with those children's scores on an individual developmental test

Forty-seven mothers estimated their pre-school children's development on a psychometrically constructed multidomain mothers' inventory. Similar data were obtained for the same children from 13 pre-school teachers. The mothers' and pre-school teachers' estimates were compared to the children's scores on McCarthy Scales of Children's Abilities (MSCA). The mothers' inventory responses yielded convergent–divergent correlations with the MSCA results; in two domains out of seven, their standardized estimations were significantly lower than standardized MSCA scores, and in no case higher. Teachers' estimates deviated more than mothers' estimates from MSCA verbal and motor development scores, though in the latter case the difference between teachers and mothers were less marked. Both mothers' and teachers' difference scores (i.e. deviation of their estimates from MSCA scores) were highly correlated with the respective MSCA scores. However, when the difference scores are adjusted for shared error variance, the correlations shrink and are in most cases non-significant.     

On the relation between demographic variables and neuropsychological test performance

This paper reports a study of the relation between demographic variables and neuropsychological test performance in a sample of 141 normal subjects. A preliminary analysis demonstrated the importance of age, educational level, sex, and Verbal IQ for the prediction of neuropsychological test performance. The main study is a detailed analysis of the relation between these four variables and neuropsychological test performance. The results are presented in the form of standardized regression coefficients and are discussed in relation to the problem of predicting expected premorbid performance in neuropsychological tests.     

Classical test theory based and factor analytic structural models for analyzing change: A note on differences and similarities

This note is concerned with differences and similarities between structural models for analyzing change, which are conceptualized within two different modelling traditions: the one based on the classical test theory, and that within the factor-analytic approach. It is shown that these two possibilities lead to models for studying change, which are indistinguishable when using for data analytic purposes structural modeling programs, such as LISREL, EQS, COSAN, LISCOMP, RAMONA, EzPATH, SAS PROC CALIS. The reason for this data-analytic equivalence of the two conceptually different types of models is the confounding of their differences in the corresponding implied covariance matrix structures.     

A model-based standardization approach that separates true bias/DIF from group ability differences and detects test bias/DTF as well as item bias/DIF

A model-based modification (SIBTEST) of the standardization index based upon a multidimensional IRT bias modeling approach is presented that detects and estimates DIF or item bias simultaneously for several items. A distinction between DIF and bias is proposed. SIBTEST detects bias/DIF without the usual Type 1 error inflation due to group target ability differences. In simulations, SIBTEST performs comparably to Mantel-Haenszel for the one item case. SIBTEST investigates bias/DIF for several items at the test score level (multiple item DIF called differential test functioning: DTF), thereby allowing the study of test bias/DIF, in particular bias/DIF amplification or cancellation and the cognitive bases for bias/DIF.This research was partially supported by Office of Naval Research Cognitive and Neural Sciences Grant N0014-90-J-1940, 4421-548 and National Science Foundation Mathematics Grant NSF-DMS-91-01436. The research reported here is collaborative in every respect and the order of authorship is alphabetical. The assistance of Hsin-hung Li and Louis Roussos in conducting the simulation studies was of great help. Discussions with Terry Ackerman, Paul Holland, and Louis Roussos were very helpful.     

运动竞赛焦虑量表中国常模的修订

运动竞赛焦虑量表是由美国的马腾斯专为运动员编制的特质焦虑量表。它是一种与特定的情境相结合的、能够有效地测出被测者通常在运动竞赛(或游戏)时焦虑水平的量表。我们在全国六大区十四个省市抽取了2,988名被试,修订了10—12岁(男、女),13—15岁(男、女),16—18岁(男、女)和19—25岁(男、女)的八个常模。同时,进行了效度和信度检验。本量表可以作为对业余的或专业的运动员进行运动竞赛焦虑的诊断与研究用。     

Rasch-representable reaction time distributions

This article investigates properties of a representation based on the Rasch test model for reaction times (RT) that was proposed by Micko. Necessary and sufficient conditions for a set of RT distributions to be Rasch-representable are derived. It is shown that independent serial and independent parallel processing models cannot be reconciled with the representation. However, random extreme models compatible with the Reasch-representation exist that assume RT is determined by the longest or he shortest processing time of a random number of independent paraloel channels. Nonparametric properties of Rasch-representable distributions are derived that can be used for testing the model and for estimating its parameters. Conditions are presented for Rasch-representable distributions to form a scale family. Finally, Rasch-represent-able distributions are characterized interms of their hazard functions.For helpful discussions, we are grateful to Hans Irtel, Christoph Micko, Hartmann Scheiblechner, and Hans-Henning Schultz.