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Hierarchical Linear Modeling: Guide and Applications

Catalog Record Details


Hierarchical Linear Modeling: Guide and Applications

G. David Garson

Los Angeles: Sage

Publication Year:

Call Number:
QA 279 .H54 2013

Alternate Location:
New Acquisitions

On Loan (contact Library for recall)

  • 1) Fundamentals of Hierarchical Linear and Multilevel Modeling. G. David Garson. pp3-26.
  • 2) Preparing to Analyze Multilevel Data. G. David Garson. pp27-54.
  • 3) Introductory Guide to HLM with HLM 7 Software. G. David Garson. pp55-96.
  • 4) Introductory Guide to HLM with SAS Software. G. David Garson. pp97-120.
  • 5) Introductory Guide to HLM with SPSS Software. G. David Garson. pp121-146.
  • 6) A Random Intercepts Model of Part-Time Employment and Standardized Testing Using SPSS. G. David Garson. pp149-166.
  • 7) A Random Intercept Regression Model Using HLM: Cohort Analysis of a Mathematics Curriculum for Mathematically Promising Students. G. David Garson. pp167-182.
  • 8) Random Coefficients Modeling With HLM: Assessment Practices and the Achievement Gap in Schools. Gregory J. Palardy. pp183-204.
  • 9) Emotional Reactivity to Daily Stressors Using a Random Coefficients Model With SAS PROC MIXED: A Repeated Measures Analysis. Shevaun D. Neupert. pp205-218.
  • 10) Hierarchical Linear Modeling of Growth Curve Trajectories Using HLM. David F. Greenberg Julie A. Phillips. pp219-248.
  • 11) A Piecewise Growth Model Using HLM 7 to Examine Change in Teaching Practices Following a Science Teacher Professional Development Intervention. Jaime L. Maerten-Rivera. pp249-272.
  • 12) Studying Reaction to Repeated Life Events With Discontinuous Change Models Using HLM. Maike Luhmann Michael Eid. pp273-290.
  • 13) A Cross-Classified Multilevel Model for First-Year College Natural Science Performance Using SAS. Brian F. Patterson. pp291-310.
  • 14) Cross-Classfied Multilevel Models Using Stata: How Important Are Schools and Neighborhoods for Students' Educational Attainment?. George Leckie. pp311-332.
  • 15) Predicting Future Events From Longitudinal Data With Multivariate Hierarchical Models and Bayes' Theorem Using SAS. Larry J. Brant Shan L. Sheng. pp333-352.

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