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Kush, Joseph M.; Konold, Timothy R.; Bradshaw, Catherine P. – Educational and Psychological Measurement, 2022
Multilevel structural equation modeling (MSEM) allows researchers to model latent factor structures at multiple levels simultaneously by decomposing within- and between-group variation. Yet the extent to which the sampling ratio (i.e., proportion of cases sampled from each group) influences the results of MSEM models remains unknown. This article…
Descriptors: Structural Equation Models, Factor Structure, Statistical Bias, Error of Measurement
Kush, Joseph M.; Konold, Timothy R.; Bradshaw, Catherine P. – Grantee Submission, 2021
Multilevel structural equation (MSEM) models allow researchers to model latent factor structures at multiple levels simultaneously by decomposing within- and between-group variation. Yet the extent to which the sampling ratio (i.e., proportion of cases sampled from each group) influences the results of MSEM models remains unknown. This paper…
Descriptors: Sampling, Structural Equation Models, Factor Structure, Monte Carlo Methods
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Rujun Xu; James Soland – International Journal of Testing, 2024
International surveys are increasingly being used to understand nonacademic outcomes like math and science motivation, and to inform education policy changes within countries. Such instruments assume that the measure works consistently across countries, ethnicities, and languages--that is, they assume measurement invariance. While studies have…
Descriptors: Surveys, Statistical Bias, Achievement Tests, Foreign Countries
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Kilic, Abdullah Faruk; Uysal, Ibrahim; Atar, Burcu – International Journal of Assessment Tools in Education, 2020
This Monte Carlo simulation study aimed to investigate confirmatory factor analysis (CFA) estimation methods under different conditions, such as sample size, distribution of indicators, test length, average factor loading, and factor structure. Binary data were generated to compare the performance of maximum likelihood (ML), mean and variance…
Descriptors: Factor Analysis, Computation, Methods, Sample Size
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Garnier-Villarreal, Mauricio; Rhemtulla, Mijke; Little, Todd D. – International Journal of Behavioral Development, 2014
We examine longitudinal extensions of the two-method measurement design, which uses planned missingness to optimize cost-efficiency and validity of hard-to-measure constructs. These designs use a combination of two measures: a "gold standard" that is highly valid but expensive to administer, and an inexpensive (e.g., survey-based)…
Descriptors: Longitudinal Studies, Data Analysis, Error of Measurement, Research Problems
Vasu, Ellen S.; Elmore, Patricia B. – 1975
The effects of the violation of the assumption of normality coupled with the condition of multicollinearity upon the outcome of testing the hypothesis Beta equals zero in the two-predictor regression equation is investigated. A monte carlo approach was utilized in which three differenct distributions were sampled for two sample sizes over…
Descriptors: Correlation, Error of Measurement, Factor Structure, Hypothesis Testing
Wolfle, Lee M.; Robertshaw, Dianne – 1982
Comparisons between whites and blacks in models of educational achievement were found to be suspect when based solely on least-square estimates, since the estimates are biased by measurement error varying by race. In this study, white high school seniors were shown to report their parents' status characteristics more reliably than black high…
Descriptors: Academic Achievement, Analysis of Covariance, Black Students, Error of Measurement