limma design question
0
0
Entering edit mode
Jenny Drnevich ★ 2.0k
@jenny-drnevich-2812
Last seen 1 day ago
United States
Hi Gordon, I've been out for a while and finally read your detailed reply. Thanks so much - it really helps clarify things for me!! Cheers, Jenny At 05:55 PM 11/27/2008, Gordon K Smyth wrote: >Hi Jenny, > >Should blocks be fixed (in the design matrix) or treated as random >(hence enter the covariance matrix as correlations)? This question >has a long history in mathematical statistics, so long that you can >be sure than the answer is somewhat subtle. > >Neither approach is right or wrong. The random approach makes more >assumptions and allows you, in some circumstances, to extract more >information. The limma approach with dupcor etc makes even more >assumptions than classical random effects models. If the blocks are >treated as fixed, then treatments can only be compared within >blocks. If blocks are treated as random, then it is possible to >compare treatments between blocks as well as within. > >So the first key issue is whether treatment comparisons are made >between blocks or within blocks. > >Suppose you do an experiment on random samples of subjects from two >groups, in which each subject is subjected to several tests. The >subjects are blocks. The total sums of squares can be divided into >between and within subject sums of squares. In other words, the >information in the data can be divided into a between-subject error >strata and a within-subject strata. > >Suppose you want to compare the two groups. All the information is >in the between-subject error strata. You cannot do any statistical >test unless you treat the subjects as random. > >Suppose now you want to compare the treatments. If the experiment >is balanced (all subjects do all tests), then all the information >about the treatments is in the within-block strata. So you may as >well treat the subjects as fixed effects (as for example is done in >a paired t-test). > >If the experiment is unbalanced (each subject does only a subset of >the tests, subjects do tests a different number of times), then you >can extract more information about the treatment comparisons from >the between-subject error strata. To do this, you have to treat the >blocks as random. > >The second key issue to consider is whether it makes sense >scientifically to treat the blocks as random. If there are only two >or three blocks, then there is little to be gained by treating them >as random. If the blocks have large unpredictable effects, then it >is much safer to treat them as fixed. If you want to make specific >conclusions about each of the blocks, then it doesn't make sense to >treat them as a random. In general, random is natural if there are >lots of blocks with relatively small effects and not of interest in >themselves. Sometimes you can go either way. > >Hope this helps >Gordon > >On Tue, 25 Nov 2008, Jenny Drnevich wrote: > >>Hi Jim, >> >>I've seen you suggest this way for account for blocks by fitting >>extra columns in the design matrix before. I'm just wondering how >>this differs from the suggestion in the limma vignette (Section 8.2 >>Technical Replication) to use duplicateCorrelation() to determine >>the average correlation between blocks. I know they are not >>mathematically equivalent; the coefficients for the treatment >>groups are slightly different, they use different DF, and the >>p-values tend to be larger using the duplicateCorrelation() method >>(at least for the one experiment I'm using). So, is one more >>"correct" than the other? Or are blocks of technical replicates >>different somehow than blocks of patients or cell lines, etc.? >> >>Thanks, >>Jenny > >Jenny Drnevich, Ph.D. > >Functional Genomics Bioinformatics Specialist >W.M. Keck Center for Comparative and Functional Genomics >Roy J. Carver Biotechnology Center >University of Illinois, Urbana-Champaign > >330 ERML >1201 W. Gregory Dr. >Urbana, IL 61801 >USA > >ph: 217-244-7355 >fax: 217-265-5066 >e-mail: drnevich at illinois.edu
GO limma GO limma • 639 views
ADD COMMENT

Login before adding your answer.

Traffic: 838 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6