Latent trait models for binary responses to a set of test items are considered from the point of view of estimating latent trait parameters=(
1, ,
n) and item parameters=(
1, ,
k), where
j may be vector valued. With considered a random sample from a prior distribution with parameter, the estimation of (, ) is studied under the theory of the EM algorithm. An example and computational details are presented for the Rasch model.This work was supported by Contract No. N00014-81-K-0265, Modification No. P00002, from Personnel and Training Research Programs, Psychological Sciences Division, Office of Naval Research. The authors wish to thank an anonymous reviewer for several valuable suggestions. 相似文献
Parceling—using composites of observed variables as indicators for a common factor—strengthens loadings, but reduces the number of indicators. Factor indeterminacy is reduced when there are many observed variables per factor, and when loadings and factor correlations are strong. It is proven that parceling cannot reduce factor indeterminacy. In special cases where the ratio of loading to residual variance is the same for all items included in each parcel, factor indeterminacy is unaffected by parceling. Otherwise, parceling worsens factor indeterminacy. While factor indeterminacy does not affect the parameter estimates, standard errors, or fit indices associated with a factor model, it does create uncertainty, which endangers valid inference.
Researchers have long been aware of the mathematics of factor indeterminacy. Yet, while occasionally discussed, the phenomenon is mostly ignored. In metrology, the measurement discipline of the physical sciences, uncertainty – distinct from both random error (but encompassing it) and systematic error – is a crucial characteristic of any measurement. This research argues that factor indeterminacy is uncertainty. Factor indeterminacy fundamentally threatens the validity of psychometric measurement, because it blurs the linkage between a common factor and the conceptual variable that the factor represents. Acknowledging and quantifying factor indeterminacy is important for progress in reducing this component of uncertainty in measurement, and thus improving psychological measurement over time. Based on our elaborations, we offer a range of recommendations toward achieving this goal. 相似文献
This article examines the role of socioeconomic status (SES) in the relationships among college admissions-test scores, secondary school grades, and subsequent academic performance. Scores on the SAT (a test widely used in the admissions process in the United States), secondary school grades, college grades, and SES measures from 143,606 students at 110 colleges and universities were examined, and results of these analyses were compared with results obtained using a 41-school data set including scores from the prior version of the SAT and using University of California data from prior research on the role of SES. In all the data sets, the SAT showed incremental validity over secondary school grades in predicting subsequent academic performance, and this incremental relationship was not substantially affected by controlling for SES. The SES of enrolled students was very similar to that of specific schools' applicant pools, which suggests that the barrier to college for low-SES students in the United States is a lower rate of entering the college admissions process, rather than exclusion on the part of colleges. 相似文献