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Showing all 5 results
Kaplan, David – Journal of Educational and Behavioral Statistics, 2005
This article considers the problem of estimating dynamic linear regression models when the data are generated from finite mixture probability density function where the mixture components are characterized by different dynamic regression model parameters. Specifically, conventional linear models assume that the data are generated by a single…
Descriptors: Regression (Statistics), Modeling (Psychology), Responses, Models
Peer reviewedKaplan, David – Journal of Educational and Behavioral Statistics, 2002
Considers the problem of modeling sustained educational change through the use of dynamic multipliers applied to panel data and attempts to develop and advocate dynamic multiplier analysis for educational research. Presents three examples to illustrate the approach and closes with a discussion of the implications of dynamic multiplier analysis for…
Descriptors: Educational Change, Educational Research, Models, Policy Formation
Peer reviewedKaplan, David; George, Rani – Journal of Educational and Behavioral Statistics, 1998
The use of ex post (historical) simulation statistics as means of evaluating latent growth models is considered, and a variety of simulation quality statistics are applied to such models. Results illustrate the importance of using these measures as adjuncts to more traditional forms of model evaluation. (SLD)
Descriptors: Evaluation Methods, Models, Research Methodology, Simulation
Peer reviewedKaplan, David; Elliott, Pamela R. – Journal of Educational and Behavioral Statistics, 1997
Considers an approach to validating the selection of education indicators by incorporating them into a multilevel structural model and using the estimates from that model in policy-relevant simulations. The potential of this approach is demonstrated with data from the National Education Longitudinal Study of 1988. (SLD)
Descriptors: Educational Indicators, Educational Policy, Estimation (Mathematics), National Surveys
Peer reviewedKaplan, David – Journal of Educational and Behavioral Statistics, 1995
This article considers the impact of missing data arising from balanced incomplete block (BIB) spiraled designs on the chi-square goodness-of-fit test in factor analysis. The new approach is shown to outperform the pairwise available case method for continuous variables and to be comparatively better for dichotomous variables. (SLD)
Descriptors: Chi Square, Factor Analysis, Goodness of Fit, Monte Carlo Methods

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