Applications of Hierarchical Linear Models for Evaluations of Health Interventions

Despite the wide availability of statistical programs designed to deal with longitudinal data from a multilevel perspective, many applied researchers remain unfamiliar with the benefits of this methodology, particularly for the evaluation of interventions. The authors present an example of multilevel modeling as part of the analysis of evaluation data from an HIV intervention study. Strategies for understanding multilevel models using longitudinal (panel) data are demonstrated and discussed. The authors illustrate how multiple linear regression models provide a convenient conceptual background to understanding how hierarchical linear models can be developed and interpreted. Multilevel analysis results are compared and contrasted with typical approaches through general linear models for repeated-measures data. Analyses are presented using the SPSS and HLM 5 software.

[1]  G. Y. Wong,et al.  The Hierarchical Logistic Regression Model for Multilevel Analysis , 1985 .

[2]  J. Fisher,et al.  Dynamics of Sexual Risk Behavior in HIV-Infected Men Who Have Sex with Men , 1998, AIDS and Behavior.

[3]  J. Stevens.  Applied Multivariate Statistics for the Social Sciences , 1986 .

[4]  R. Gonzalez.  Applied Multivariate Statistics for the Social Sciences , 2003 .

[5]  Peter Dolton.  ML3: Software for three-level analysis. , 1993 .

[6]  Barbara G. Tabachnick,et al.  Computer-Assisted Research Design and Analysis , 2000 .

[7]  A. O'connell,et al.  Evaluation Issues and Strategies for Community-Based Organizations Developing Women's HIV Prevention Programs , 1997, Evaluation & the health professions.

[8]  T. Koepsell,et al.  Multi-level analysis in epidemiologic research on health behaviors and outcomes. , 1992, American journal of epidemiology.

[9]  C. Arnold.  An Introduction to Hierarchical Linear Models , 1992 .

[10]  David M. Murray,et al.  Design and Analysis of Group- Randomized Trials , 1998 .

[11]  S. Brooks,et al.  Applied Multivariate Statistics for the Social Sciences , 1993 .

[12]  Richard A. Johnson,et al.  Applied Multivariate Statistical Analysis , 1983 .

[13]  S. Geisser,et al.  On methods in the analysis of profile data , 1959 .

[14]  P. Games.  Alternative Analyses of Repeated-Measure Designs by ANOVA and MANOVA , 1990 .

[15]  H. Keselman,et al.  The analysis of repeated measures designs: a review. , 2001, The British journal of mathematical and statistical psychology.

[16]  William A. Fisher,et al.  Theoretical Approaches to Individual-Level Change in HIV Risk Behavior , 2000 .

[17]  Judith D. Singer,et al.  Using SAS PROC MIXED to Fit Multilevel Models, Hierarchical Models, and Individual Growth Models , 1998 .

[18]  Kelvyn Jones,et al.  Individuals and their ecologies: analysing the geography of chronic illness within a multilevel modelling framework , 1995 .

[19]  W. Shadish,et al.  Experimental and Quasi-Experimental Designs for Generalized Causal Inference , 2001 .

[20]  Joop J. Hox,et al.  Multilevel analysis of grouped and longitudinal data , 2000 .

[21]  David Rogosa,et al.  Longitudinal Data Analysis Examples With Random Coefficient Models , 1995 .

[22]  Leo J. Th. van der Kamp,et al.  Longitudinal Data Analysis: Designs, Models and Methods , 1999 .

[23]  Martin Fishbein,et al.  Community-level HIV intervention in 5 cities: final outcome data from the CDC AIDS Community Demonstration Projects. , 1999, American journal of public health.

[24]  K. Weinfurt,et al.  Repeated measures analyses : ANOVA MANOVA, and HLM , 2000 .

[25]  William G. Cochran,et al.  Experimental Designs, 2nd Edition , 1950 .

[26]  Linda M. Collins,et al.  New methods for the analysis of change , 2001 .

[27]  Jan de Leeuw,et al.  Introducing Multilevel Modeling , 1998 .

[28]  Judith D. Singer,et al.  Fitting individual growth models using SAS PROC MIXED. , 2002 .

[29]  Jürgen Baumert,et al.  Modeling longitudinal and multilevel data , 2000 .

[30]  R. Littell.  SAS System for Mixed Models , 1996 .

[31]  G. Wingood,et al.  Health behavior and health education: Theory, research, and practice, 2nd edition , 1997 .

[32]  R. MacCallum,et al.  Studying Multivariate Change Using Multilevel Models and Latent Curve Models. , 1997, Multivariate behavioral research.

[33]  Contents , 1997, Current Opinion in Neurobiology.

[34]  K. Glanz,et al.  Health behavior and health education : theory, research, and practice , 1991 .

[35]  J. Singer,et al.  Applied Longitudinal Data Analysis , 2003 .

[36]  Anthony S. Bryk,et al.  Hierarchical Linear Models: Applications and Data Analysis Methods , 1992 .

[37]  Noah E. Friedkin,et al.  Quantitative Methods for Studying Social Context in Multilevels and through Interpersonal Relations for Review of Research in Education , 1998 .

[38]  Toon W. Taris,et al.  A Primer in Longitudinal Data Analysis , 2000 .

[39]  Ian H. Langford,et al.  A User’s Guide to MLwiN, Version 2.10 , 2000 .

[40]  H. Huynh,et al.  Estimation of the Box Correction for Degrees of Freedom from Sample Data in Randomized Block and Split-Plot Designs , 1976 .

[41]  R. DiClemente,et al.  Handbook of HIV Prevention , 2012, Aids Prevention and Mental Health.

[42]  Paul R. Yarnold,et al.  Reading and understanding MORE multivariate statistics. , 2000 .

[43]  Dennis Wallace,et al.  Analysis of repeated measures designs with linear mixed models. , 2001 .

[44]  Stephen W. Raudenbush,et al.  Toward a coherent framework for comparing trajectories of individual change. , 2001 .

[45]  B. Tabachnick,et al.  Using Multivariate Statistics , 1983 .

[46]  S. Michael.  Handbook in research and evaluation , 1971 .

[47]  Scott E. Maxwell,et al.  Designing Experiments and Analyzing Data: A Model Comparison Perspective , 1990 .

[48]  C RuizdeVillaMdel,et al.  Repeated measures analysis , 2004 .

[49]  Yeow Meng Thum,et al.  Hierarchical Linear Models for Multivariate Outcomes , 1997 .