Hierarchical linear modeling
Subtitle: guide and applications
By: G. David Garson, editor
Publisher: Sage Publications
Published: 2013
Place of publication: Thousand Oaks, Calif
Language: eng
ISBN-13: 9781412998857
Subjects: Linear models (Statistics)
Notes: Includes bibliographical references and index.
Table of contents: title: Preface; title: Fundamentals of hierarchical linear (multilevel) modeling / G. David Garson; title: Preparing to analyze multilevel data / G. David Garson; title: Introductory guide to hlm with hlm6 software / G. David Garson; title: Introductory guide to hlm with sas software / G. David Garson; title: Introductory guide to hlm with spss software / G. David Garson; title: Introductory and intermediate applications; title: A random intercepts model of gpa and sat scores using spss / Forrest C. Lane, Kim F. Nimon, & J. Kyle Roberts; title: A random intercept regression model using hlm : cohort analysis of a mathematics curriculum for mathematically promising students / Carissa L. Shafto & Jill L. Adelson; title: Random coefficients modeling with hlm : assessment practices and the achievement gap schools / Gregory J. Palardy; title: Emotional reactivity to daily stressors using a random coefficients model with sas proc mixed : a repeated measures analysis / Shevaun Neupert; title: Hierarchical linear modeling of growth curve trajectories using hlm / David F. Greenberg & Julie A. Phillips; title: A piecewise growth model using hlm to examine change in teaching practices following a science teacher professional development intervention / Jaime L. Maerten-Rivera; title: Studying reaction to repeated life events with discontinuous change models using hlm / Maike Luhmann & Michael Eid; title: A cross-classified multilevel model for first-year college natural science performance using sas / Brian F. Patterson; title: Cross-classified multilevel models using stata: how important are schools and neighbourhoods for children's educational attainment? / George Leckie; title: Predicting future events from longitudinal data with multivariate hierarchical models and bayes' theorem using sas / Larry J. Brant & Shan L. Sheng; title: Index.