Hi Joe, You are right about the Behrens-Fisher problem. I was merely referring to situations where the distribution of error terms is - assumed to be - known, and not necessarily equal for all observations. Thanks for pointing this out. Best wishes, Guido
--- On Mon, 9/11/09, JLucke at ria.buffalo.edu <JLucke at ria.buffalo.edu> wrote:
From: JLucke at ria.buffalo.edu <JLucke at ria.buffalo.edu> Subject: Re: [R] The equivalence of t.test and the hypothesis testing of one way ANOVA To: "Guido van Steen" <gvsteen at yahoo.com> Cc: "Peng Yu" <pengyu.ut at gmail.com>, r-help at r-project.org Date: Monday, 9 November, 2009, 8:44 PM Guido wrote "However, using a transformation matrix one can transform a model assuming unequal variances into an equivalent model assuming equal variances. On such a transformed model the F test or T test can be applied." This is indeed news to me. ?I thought such transformations for unequal variances applied only to cases where the variances were known. ?Unknown, unequal variances leads to the Behrens-Fisher problem and its generalizations, a problem not resolved by mere linear transformation. ?Correct me and point me to the literature if I've misunderstood. Joe
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