Thanks for your advice. I sometimes really don't know how much I should post about a problem in newsgroups.
For Question 1, I am testing whether two types of rehab. programs are useful in improving employment rate (employed or unemployed). I prefer using Chi-square to t-tests for proportions in this case. For Question 2, it was an non-equivalent group design for a community program. The experimental and comparison groups had rather different samples sizes and baselines, and I am trying to consider if t-test is appropriate for testing the difference between the mean differences for the two groups. I am not aware of the possible use of F-tests in this context. "Rich Ulrich" <[EMAIL PROTECTED]> ???????:[EMAIL PROTECTED] > On Mon, 30 Dec 2002 23:47:34 +0800, "K�J" > <[EMAIL PROTECTED]> wrote: > > > I hear people saying that t-tests could be used to test: > > > > 1. difference between two proportions > > You can use a t-test to test a 0/1 variable (proportions). > Use the usual test, with the pooled variance estimate, > if you are in the midst of reporting dozens of other results > using a t. If you are trying to report a single result, folks > will be happier if you give them the usual 2x2 contingency > table, and the chi square value. > > > 2. difference between two mean differences (i.e. between (M12 - M11) > > and (M22 - M21). > > If that is change-score(1) and change-score(2), where > you can actually compute the scores, then you could > make that the explicit case of comparing two scores: > and that is where you would use a t-test automatically, > based on the degrees of freedom for sample (1) + (2). > > In the more general ANOVA context, that might be a > "special contrast". It can be reported as t, using the > DF of the error term. Some folks prefer to report tests > on contrasts as F-tests -- Once-upon-a-time, I ran > into an innumerate reviewer who had a textbook with an > example, and therefore wanted to insist that only F was > acceptable. > > > > Could somebody please advice me on this or give me a reference to read > > about these tests? > > I think this went unanswered when posted in sci.stat.consult > because the <above> are two Unusual Cases, and you give > no hint about whether you recognize that... or just why > it is that you are interested in testing in general, or t-tests > in specific; or where you have looked already. > > For information, or for references: > You could browse my stats-FAQ; also, the home pages > of other people who post answers to these stats groups. > > -- > Rich Ulrich, [EMAIL PROTECTED] > http://www.pitt.edu/~wpilib/index.html . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
