Further Statistical Methods, HT05

Overview of Lectures

The preliminary content of each of the lectures is as follows:

1. Introduction to categorical data
2. Conditional independence and graphical models
3. Ordinal data
4. Association measures. Models for square tables
5. Missing data
6. The EM algorithm
7. Latent variable models
8. Factor analysis
9. Multi-level models
10. Longitudinal data

The material in the first 4 lectures is largely contained in books by Edwards and Agresti, see synopses for details on books. For most examples I am using the David Edwards' software MIM, which can be downloaded from here. For the MIM manual, see Edwards (2002) appendix A and B.

For lectures 5 and 6, see R. J. A. Little and D. B. Rubin (2002). Statistical Analysis with Missing Data, 2nd ed. Wiley, New York.

For lectures 7 and 8, see D. J. Bartholomew (1987). Latent Variable Models and Factor Analysis. Griffin, London.

For lecture 9, see T. A. B. Snijders and R. J. Bosker (1999). Sage Publications, London.

For lecture 10, see P. J. Diggle, P. Heagerty, K.-Y. Liang and S. L. Zeger (2002). Analysis of longitudinal data. Oxford University Press, Oxford.

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Last updated: Thursday, 14 April 2005 11:32.  Steffen L. Lauritzen