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Extending Generalized Symmetric Means to Arbitrary Matrix Sampling Designs
Peer reviewed Peer reviewed
Wellington, Roger – Psychometrika, 1976
Generalized symmetric means are redefined in a way which allows them to be calculated for any matrix sampling design. It is proved that these sample generalized symmetric means are unbiased estimates of the analogous population generalized symmetric means. Illustrative examples are given. (Author)
Descriptors: Item Sampling, Matrices, Research Design, Sampling
A Note on Rippe's Test of Significance in Common Factor Analysis
Peer reviewed Peer reviewed
McDonald, Roderick P. – Psychometrika, 1975
Descriptors: Analysis of Covariance, Factor Analysis, Hypothesis Testing, Matrices
A Class of Factor Analysis Estimation Procedures with Common Asymptotic Sampling Properties
Peer reviewed Peer reviewed
Swain, A. J. – Psychometrika, 1975
Considers a class of estimation procedures for the factor model. The procedures are shown to yield estimates possessing the same asymptotic sampling properties as those from estimation by maximum likelihood or generalized last squares, both special members of the class. General expressions for the derivatives needed for Newton-Raphson…
Descriptors: Factor Analysis, Least Squares Statistics, Matrices, Maximum Likelihood Statistics
The Role of Secondary Covariates When Estimating Latent Trait Population Distributions.
Peer reviewed Peer reviewed
Thomas, Neal – Psychometrika, 2002
Studied the improvement in precision of population estimates from the inclusion of extensive covariates in the multivariate procedure that imputes values for the missing proficiencies. Analysis of data from the National Assessment of Educational Progress (samples of 10,291 eighth graders and 8,416 fourth graders) shows that improvement in…
Descriptors: Elementary Education, Elementary School Students, Estimation (Mathematics), Junior High School Students