Hierarchical Linear Models: Applications and Data Analysis Methods

@inproceedings{Raudenbush1992HierarchicalLM,
  title={Hierarchical Linear Models: Applications and Data Analysis Methods},
  author={S. Raudenbush and Anthony S. Bryk},
  year={1992}
}
  • S. Raudenbush, Anthony S. Bryk
  • Published 1992
  • Computer Science, Sociology
  • Introduction The Logic of Hierarchical Linear Models Principles of Estimation and Hypothesis Testing for Hierarchical Linear Models An Illustration Applications in Organizational Research Applications in the Study of Individual Change Applications in Meta-Analysis and Other Cases Where Level-1 Variances are Known Three-Level Models Assessing the Adequacy of Hierarchical Models Technical Appendix 
    23,297 Citations

    Topics from this paper

    Hierarchical data structures, institutional research, and multilevel modeling
    • 11
    • Highly Influenced
    • PDF
    Recommendations for Estimating Cross-level interaction effects Using Multilevel Modeling
    • 8
    • Highly Influenced
    • PDF
    On Multilevel Model Reliability Estimation From the Perspective of Structural Equation Modeling
    • 92
    • Highly Influenced
    Evaluation of Reliability Coefficients for Two-Level Models via Latent Variable Analysis
    • 8
    • Highly Influenced
    Using Hierarchical Linear Modeling to Analyze Grouped Data
    • 20
    • Highly Influenced
    • PDF
    An Examination of Firm, Industry, and Time Effects on Performance Using Random Coefficients Modeling
    • 92
    • Highly Influenced
    Hierarchical Linear Modeling of Multilevel Data
    • 61
    • Highly Influenced
    • PDF

    References

    SHOWING 1-2 OF 2 REFERENCES