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Jung, Kwanghee; Takane, Yoshio; Hwang, Heungsun; Woodward, Todd S. – Psychometrika, 2012
We propose a new method of structural equation modeling (SEM) for longitudinal and time series data, named Dynamic GSCA (Generalized Structured Component Analysis). The proposed method extends the original GSCA by incorporating a multivariate autoregressive model to account for the dynamic nature of data taken over time. Dynamic GSCA also…
Descriptors: Structural Equation Models, Longitudinal Studies, Data Analysis, Reliability
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Brown, Morton B. – Psychometrika, 1975
Estimates of conditional uncertainty, contingent uncertainty, and normed modifications of contingent uncertainity have been proposed for the two-way contingency table. The asymptotic standard errors of the estimates are derived. (Author)
Descriptors: Data Analysis, Sampling, Statistical Analysis
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Yung, Yiu-Fai – Psychometrika, 1997
Various types of finite mixtures of confirmatory factor analysis models are proposed for handling data heterogeneity. Proposed classes of mixture models differ in their unique representations of data heterogeneity, and three sampling schemes for these mixtures are distinguished. Advantages of the Approximate Scoring method are outlined. (SLD)
Descriptors: Data Analysis, Mathematical Models, Sampling, Scoring
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Smith, Robert A. – Psychometrika, 1971
Descriptors: Data Analysis, Data Collection, Groups, Probability
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Hettmansperger, Thomas P. – Psychometrika, 1975
Treats the problem of testing an ordered hypothesis based on the ranks of the data. Statistical procedures for the randomized block design with more than one observation per cell are derived. Multiple comparisions and estimation procedures are included. (Author/RC)
Descriptors: Correlation, Data Analysis, Hypothesis Testing, Nonparametric Statistics
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Lewis, Charles; And Others – Psychometrika, 1975
A Bayesian Model II approach to the estimation of proportions in m groups is extended to obtain posterior marginal distributions for the proportions. The approach is extended to allow greater use of prior information than previously and the specification of this prior information is discussed. (Author/RC)
Descriptors: Bayesian Statistics, Data Analysis, Individualized Instruction, Models