This subject contains a 2 day Optional Residential School.
This subject extends the linear model into situations involving non independent observations. Such correlated data arise in repeated measures, spatial data and time series observations. Advanced techiques such as REML and GLMMs will be covered, but the modifying constraint will be the availability of solutions in software that will allow familiarisation via empirical demonstations on selected problems.
No offerings have been identified for this subject in 2020.
HD/FL
One session
School of Science and Technology
Overview of correlated data using general examples; Consequences of dependent errors; extensions of the independent error linear model: Regression - simple autoregressive models - time series models (time domain) - generalised least squares (GLS) Experimental Design - repeated measures - random effects model - mixed models - unbalanced designs - variance components (REML) - GLMMS; Tests of assumptions; Interpretation.
This subject contains a 2 day Optional Residential School.
The information contained in the CSU Handbook was accurate at the date of publication: October 2020. The University reserves the right to vary the information at any time without notice.