Hlm/2l and Hlm/3l Programs
Published on 1. March 1994
Book
Paperback/Softback
978-1-56321-129-4 (ISBN)
Description
HLM/2L (2-level) and HLM/3L (3-level) are designed to analyze growth and change within individuals; to study responses of persons in organizations such as schools, businesses, community and religious groups; and to conduct meta-analysis of research results.
The programs handle two- and three-level hierarchical linear models. The programs have been substantially revised and expanded over the past years so that the basic program structure, input specification, and output of results now closely coordinate with the text, Hierarchical Linear Models, Applications and Data Analysis Methods by Anthony S. Bryk and Stephen W. Raudenbush. Many of the illustrative examples described in the completely rewritten user's guide and distributed with the program are analyzed more fully in the text.
The programs compute a number of useful statistics including:
* an overall average reliability for each level-1 coefficient across the set of level-2 units,
* least-square residuals, based on the deviation of an ordinary least-squares estimate of a level-1 coefficient from its predicted or "fitted" value based on the level-2 model, and
* empirical Bayes residuals, based on the deviation of the empirical Bayes estimates of a randomly varying level-1 coefficient from its predicted or "fitted" value based on the level-2 model.
Corresponding to the three basic types of parameters estimated in a hierarchical linear model are single-parameter and multi-parameter hypothesis-testing procedures. The current versions of HLM/2L and HLM/3L execute a variety of hypothesis tests for the fixed effects and the variance-covariance components including:
* multivariate hypothesis tests for fixed effects,
* testing homogeneity of each random effect, and
* multivariance tests of variance-covariance components specification.
Both programs are 32-bit versions with a built-in DOS Extender that will address all available memory in your system. Add to that dynamic memory allocation, and you are now able to analyze on your 386 (or better) problems that previously required a mainframe. The programs can be used interactively or in batch mode.
The programs handle two- and three-level hierarchical linear models. The programs have been substantially revised and expanded over the past years so that the basic program structure, input specification, and output of results now closely coordinate with the text, Hierarchical Linear Models, Applications and Data Analysis Methods by Anthony S. Bryk and Stephen W. Raudenbush. Many of the illustrative examples described in the completely rewritten user's guide and distributed with the program are analyzed more fully in the text.
The programs compute a number of useful statistics including:
* an overall average reliability for each level-1 coefficient across the set of level-2 units,
* least-square residuals, based on the deviation of an ordinary least-squares estimate of a level-1 coefficient from its predicted or "fitted" value based on the level-2 model, and
* empirical Bayes residuals, based on the deviation of the empirical Bayes estimates of a randomly varying level-1 coefficient from its predicted or "fitted" value based on the level-2 model.
Corresponding to the three basic types of parameters estimated in a hierarchical linear model are single-parameter and multi-parameter hypothesis-testing procedures. The current versions of HLM/2L and HLM/3L execute a variety of hypothesis tests for the fixed effects and the variance-covariance components including:
* multivariate hypothesis tests for fixed effects,
* testing homogeneity of each random effect, and
* multivariance tests of variance-covariance components specification.
Both programs are 32-bit versions with a built-in DOS Extender that will address all available memory in your system. Add to that dynamic memory allocation, and you are now able to analyze on your 386 (or better) problems that previously required a mainframe. The programs can be used interactively or in batch mode.