Dear David and the list, Thanks for your comment. Unfortunately, I don't have an instructor on R. And I usually don't deal with contingency table analysis.
I have consulted more than two books on R already, but I found no good answer. Could you point me to some references about log linear modeling / GLM with Poisson with R that mention techniques of specific cell-to-cell comparisons and interpretation of the results? Any other suggestion is greatly appreciated. Thanks in advance. Best regards, John On Wed, Jul 21, 2010 at 2:24 PM, David Winsemius <dwinsem...@comcast.net> wrote: > > On Jul 21, 2010, at 8:07 AM, Tsunhin John Wong wrote: > >> Dear R users, >> >> I have a question of how to do some specific cell to cell comparisons >> on a R x C contingency table. >> The table is a 3 x 5 table with frequency / count data. >> >>> langcons.table <- table(lang, cons) >>> langcons.table[cbind(lang,cons)] <- freq >>> langcons.table >> >> Adj Int Oth Pas Tra >> C 69 221 17 3 198 >> E 56 214 33 31 174 >> J 36 291 8 9 164 >> >> I know how to do an independent model test using Poisson in glm >>> >>> glm.out1 <- glm(freq~lang+cons, family=poisson, data=langcons.data) >>> summary(glm.out1) >> >> And then fit the saturated model >>> >>> glm.out2 <- glm(freq~lang*cons, family=poisson, data=langcons.data) >>> summary(glm.out2) >> >> However, the results are difficult to interpret: >> C and Adj are used to as a baseline. >> And I can only see main effects and interactions and *always according >> to the baseline*. >> Coefficients: >> Estimate Std. Error z value Pr(>|z|) >> (Intercept) >> lang1 >> lang2 >> cons1 >> cons2 >> cons3 >> cons4 >> lang1:cons1 >> lang2:cons1 >> lang1:cons2 >> lang2:cons2 >> lang1:cons3 >> lang2:cons3 >> lang1:cons4 >> lang2:cons4 >> >> If anyone know, please suggest me some way to do specific cell to cell >> comparison on such a contingency table. > > Even if you are daunted by the task of plugging the covariates into the > formula, exp(intercept+sum(beta_N*var_n)), you can always use the predict > function to create an estimate for all (or a specific set) of the > covariates. They come out on the log(rate) scale so would need to be > exponentiated. Consult your instructor for further help. > > >> Say, to compare pairs of cells: >> along a column: 3 vs 31, 9 vs 31, 3 vs 9 >> along a row: 36 vs 9 >> or even across column and row: 36 vs 31, and 36 vs 3 > > > David Winsemius, MD > West Hartford, CT > > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.