https://github.com/tjmahr/edpsych964

Education Psychology 964: Hierarchical Linear Modeling (Spring 2014)
https://github.com/tjmahr/edpsych964

Last synced: about 1 month ago
JSON representation

Education Psychology 964: Hierarchical Linear Modeling (Spring 2014)

• Host: GitHub
• URL: https://github.com/tjmahr/edpsych964
• Owner: tjmahr
• License: gpl-2.0
• Created: 2014-01-21T16:59:46.000Z (almost 11 years ago)
• Default Branch: master
• Last Pushed: 2014-05-09T23:45:31.000Z (over 10 years ago)
• Last Synced: 2023-06-28T12:20:40.030Z (over 1 year ago)
• Language: R
• Size: 488 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
Hierarchical Linear Modeling (2014)

===================================

## List of topics

* Introduction and overview of HLM applications (S&B, Chs 1, 2)

* Review of simple and multiple regression, fixed and random effects ANOVA

* Statistical treatment of clustered data (S&B, Ch 3)

* Random intercept models (S&B, Ch 4)

* Random slope models (S&B, Ch 5)

* Hypothesis testing and model specification (S&B, Ch 6)

* Explained variance (S&B, Ch 7)

* Heteroscedasticity (S&B, Ch 8)

* Missing data (S&B, Ch 9)

* Evaluation of model assumptions (S&B, Ch 10)

* Designing multilevel studies; power analysis (S&B, Ch 11)

* Alternative estimation methods (S&B, Ch 12)

* Crossed random effects and multiple memberships (S&B, Ch 13)

* Survey weights (S&B, Ch 14)

* Longitudinal data analysis (S&B, Ch 15)

* Multivariate multilevel models (S&B, Ch 16)

* Discrete dependent variables (S&B, Ch 17)

* Latent growth curve models, meta analysis

### Course References

Snijders, T.A.B., & Bosker, R.J. (2011). _Multilevel analysis: An introduction to basic and advanced multilevel modeling_. (2nd ed.) Sage. [S&B]