Reading Assignments - Model Selection and Missing Data

These are two more readings that were incorporated into a 3rd year stats course geared towards life and health sciences. One is a model selection paper geared towards ecologists, and the other is a paper on missing data and imputation in the context of medicine and survival analysis.

Take-home lessons and code from a factor-cluster analysis with imputation

Recently I was tapped to examine data from a survey of ~200 children to find if their learning preferences fell into well-defined profiles (i.e. clusters). The relevant part of the survey had more than 50 Likert scale questions The client and I had decided that a factor analysis, followed by a cluster analysis would be most appropriate.

I learned some things in doing this analysis, and wanted to share that and some relevant code.

Lesson Prototype - First Lecture on Multiple Imputation

Continuing the work on my data management course, here's the start of the Imputation unit. I'm intending three units in total - Text processing, principles of data manipulation (cleaning, merging, formatting, and database access), and imputation.