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Busk, Patricia L.; Marascuilo, Leonard A. – Australian Journal of Education, 1989
An extension of the discussion of loglinear models presents post hoc procedures for statistically evaluating treatment effects, contrasts, and confidence intervals, illustrating methods for main effect and interaction contrasts and paying special attention to odds ratios and their interval estimates. Procedures for treating variables as…
Descriptors: Estimation (Mathematics), Hypothesis Testing, Interaction, Mathematical Models
Wolfle, Lee M. – 1982
Direct and indirect effects in decomposed zero-order correlations among variables in causal models are considered. Under certain circumstances, the components of the decompositions could be interpreted as direct, indirect, and spurious causal effects, plus a component called joint associations. The sum of the direct and indirect effects is the…
Descriptors: Elementary Secondary Education, Estimation (Mathematics), Mathematical Formulas, Mathematical Models
Shah, Babubhai V.; And Others – 1981
Aside from the theoretical issues involving the validity of inferences from surveys, the basic problem of producinq unbiased estimates of regression parameters and estimates of the associated standard errors has been a particularly difficult issue in dealing with results from stratified multistage sample designs such as the one used in the…
Descriptors: Computer Programs, Estimation (Mathematics), Graduate Surveys, High Schools
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Harris, Deborah – Educational Measurement: Issues and Practice, 1989
This instructional module discusses the one-, two-, and three-parameter logistic item response theory (IRT) models. Mathematical formulas are given for each model and they are compared, with figures illustrating the effects of changing parameters. A single data set is used to demonstrate the effects of changing parameter values. (SLD)
Descriptors: Comparative Analysis, Equations (Mathematics), Estimation (Mathematics), Instructional Materials
Wise, Lauress L.; McLaughlin, Donald H. – 1980
This guidebook is designed for data analysts who are working with computer data files that contain records with incomplete data. It indicates choices the analyst must make and the criteria for making those choices in regard to the following questions: (1) What resources are available for performing the imputation? (2) How big is the data file? (3)…
Descriptors: Algorithms, Computer Software, Data Analysis, Data Collection
Choppin, Bruce – 1982
A strategy for overcoming problems with the Rasch model's inability to handle missing data involves a pairwise algorithm which manipulates the data matrix to separate out the information needed for the estimation of item difficulty parameters in a test. The method of estimation compares two or three items at a time, separating out the ability…
Descriptors: Difficulty Level, Estimation (Mathematics), Goodness of Fit, Item Analysis