I’ve spent the last week and a half or so getting the kids started with school; in the meantime my Ph.D. comp prep has fallen off the schedule. Now I’m trying to get back to it, as the exam is less than two months away.
I searched online for information about doctoral comprehensive or qualifying exams from other departments, and found a useful exam description (pdf) from Rutgers’ doctoral program in planning and public policy. Their suggestions for preparing include this useful tip:
Practice defining concepts and succinctly discussing their relevance (e.g., What is an ANOVA test and under what circumstances is it used?). Also practice comparing concepts and commenting on the appropriateness of alternative methods (e.g., clustered vs. stratified sampling, t distribution vs. normal curve, logit model vs. linear regression). Finally, prepare yourself to discuss “big picture” issues such as research design in longer essay questions.
Their topic and reading list covers almost everything I am expected to know: research design, quantitative and qualitative methods, basic measurement, and survey sampling. To that, I’ll have to add item response theory and research ethics. I’ll also have to attack ANOVA in more depth, since that is a special favorite of my department head. Oh, and let me not forget the advanced statistical techniques I love so well: structural equation modeling, latent growth curve modeling, and (my favorite) hierarchical linear modeling.
Here’s my eight-week plan. I’m going to have to cover a lot of ground each week. For each subtopic, I’ll write a blog post, make flashcards for key points, sources, and formulas, then formulate some essay questions of my own and write answers for them.
|1||9/6||Research design, introductory stats|
|2||9/13||Correlation and regression, ANOVA|
|3||9/20||Psychometrics, validity and reliability|
|4||9/27||Multivariate methods, qualitative methods|
|5||10/4||Structural equation modeling, hierarchical linear modeling, latent growth curve modeling|
|6||10/11||Program evaluation theory, survey research, research ethics|