The material on this page is
mainly textual and represents some
of the stuff that I couldn't fit in either book, but
wanted to write up. This material is
all in draft form, and it may be revised from time to
time. Please remember where you
found it, and always give credit if you use it. Again, I
would appreciate suggestions for
further additions and/or clarification.
This is a discussion of alternative ways to handle missing data, whether those data come from a multiigroup experiment or are continuous variables used in a regression problem.
I have written a chapter on missing data for the Handbook of Social Science Methodology, edited by Outhwaite and Turner and published by Sage. A preprint of that chapter is available by writing to me at David.Howell@uvm.edu.
This is a discussion that begins to show how sample sizes can affect the interpretation of a study when you have unequal cell frequencies. Near the end of the article is an e-mail message that I sent to someone else, illustrating how what appears to be one effect can actually come out to be a different effect.
This is a discussion under construction of what it means to talk about power when we wouldn't be satisfied just to prove that one mean is trivially greater than another.
If you are correlating variables (such as scores from twins or gay partners) where there is no ordering within a pair (e.g. either twin could be considered twinA or twinB), you want an intraclass correlation coefficient.
This is a discussion of ways to run multiple comparisons when you have a repeated measure. It addresses the often-asked question "How do I do a Tukey test on my repeated measure?".
I was asked for a demonstration of how you would compute the different types of sums of squares using the general linear model. Here that is.
.
David C. Howell
Last revised:
6/29/2007
