A structural model for projecting public school enrollment by grade, program, and district is outlined. Main points of consideration are illustrated by an application to the problem of forecasting enrollment in Florida. (Author/GK)

A statistical model is proposed that describes the determination of an educational outcome variable as a nonlinear function of explanatory variables defined at different levels of a survey data hierarchy, such as students and classes. The theoretical and practical derivation of the model is discussed, and an example is given. (Author/BW)

Applies neural network methods for forecasting 1991-95 per-pupil expenditures in U.S. public elementary and secondary schools. Forecasting models included the National Center for Education Statistics' multivariate regression model and three neural architectures. Regarding prediction accuracy, neural network results were comparable or superior to…

Explores race, class, educational level, and parental perceptions as they affect parental participation in schools, analyzing data generated by a 1991 National Commission on Children survey. Discovered clear interactions and correlations among all variables and respondents' participation in various school activities. Suggests a prediction model…

This paper discusses the application of Hierarchical Linear Modeling (HLM) to the evaluation of the effectiveness of Basic Skills programs in the Newark (New Jersey) school district. Whether HLM is able to handle regression effects in Basic Skills examination data is studied. The analysis uses data from the Stanford Achievement Tests for…

A meta-analysis of studies conducted between 1974 and mid-1987 on sex differences in mathematical tasks is presented. Methods used include estimations of: (1) parameters for a random effects model, and (2) coefficients for a linear-regression equation, all based on effect sizes calculated from each study. Differences have been decreasing. (TJH)

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…

A three-equation simultaneous regression model was developed with regular education spending, the prevalence of handicapped children, and handicapped spending as endogenous variables. A tentative test of the model was made using recently available data from the Wisconsin special needs assessment survey and supplementary special education aids…

The development of new statistical methods of log-linear models by Leo Goodman has led to major advances in the statistical analysis of categorical data. Goodman's logit analysis, (the simplest form of log-linear models) can be applied in evaluation studies to estimate the "main effects" and "interaction effects" of categorical…

Statistical models for school effectiveness rankings are assessed. An analysis of linear models with fixed regression parameters and models with separate regression parameters for each school is presented. In the first case, the regression lines are parallel and the ranking of the schools is the same for all student backgrounds. In the second…

Investigates the effect of state and federal grants on South Carolina local revenues for 1978 and 1982. Although local revenues are stimulated by federal aid, some of the latter is used for tax relief. (MLF)

Using longitudinal data on career paths of 3,941 special educators, maximum likelihood estimators are derived for the parameters of a discrete-time hazard model, and it is shown that the model can be fit using standard logistic regression software. Illustrative computer codes from the Statistical Analysis System (SAS) are offered. (SLD)

Title I evaluations using the RMC Model C design depend for their interpretation on the assumption that the regression of posttest on pretest is linear across the cut score level when there is no treatment; but there are many instances where nonlinearities may occur. If one applies the analysis of covariance, or model C analysis, large errors may…

The issues of achieving school desegregation and providing programs for students with special needs, while at the same time facing enrollment declines, have forced school administrators to improve techniques for projecting demand. This paper describes a new procedure that combines forecasting of enrollments and management of facilities and that…