I forgot to mention (sorry for double posting) that str(infert) shows that "induced" and "spontaneous" are not factors:
'data.frame': 248 obs. of 8 variables: $ education : Factor w/ 3 levels "0-5yrs","6-11yrs",..: 1 1 1 1 2 2 2 2 2 2 ... $ age : num 26 42 39 34 35 36 23 32 21 28 ... $ parity : num 6 1 6 4 3 4 1 2 1 2 ... $ induced : num 1 1 2 2 1 2 0 0 0 0 ... $ case : num 1 1 1 1 1 1 1 1 1 1 ... $ spontaneous : num 2 0 0 0 1 1 0 0 1 0 ... $ stratum : int 1 2 3 4 5 6 7 8 9 10 ... $ pooled.stratum: num 3 1 4 2 32 36 6 22 5 19 ... This explains why you did not see reference levels in those variables. HTH, Jorge.- On Tue, Dec 13, 2011 at 11:48 PM, Jorge I Velez <> wrote: > Hi, > > Are you sure? That's not what I got: > > > require(epicalc) > > ?logistic.display > > model0 <- glm(case ~ induced + spontaneous, family=binomial, > data=infert) > > logistic.display(model0) > > Logistic regression predicting case > > crude OR(95%CI) adj. OR(95%CI) P(Wald's test) > induced (cont. var.) 1.05 (0.74,1.5) 1.52 (1.02,2.27) 0.042 > > spontaneous (cont. var.) 2.9 (1.97,4.26) 3.31 (2.19,5.01) < 0.001 > > P(LR-test) > induced (cont. var.) 0.042 > > spontaneous (cont. var.) < 0.001 > > Log-likelihood = -139.806 > No. of observations = 248 > AIC value = 285.612 > > > My impression is that you did something else and you are not telling us > the full story. Here is my sessionInfo(): > > R version 2.14.0 Patched (2011-11-12 r57642) > Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit) > > locale: > [1] US.UTF-8 > > attached base packages: > [1] grid splines stats graphics grDevices utils datasets > methods > [9] base > > other attached packages: > [1] ggplot2_0.8.9 proto_0.3-9.2 reshape_0.8.4 plyr_1.6 > [5] epicalc_2.14.0.0 nnet_7.3-1 MASS_7.3-16 survival_2.36-10 > [9] maptools_0.8-10 lattice_0.20-0 foreign_0.8-47 sp_0.9-91 > [13] maps_2.2-2 > > loaded via a namespace (and not attached): > [1] tools_2.14.0 > * > * > > > Could you please share your sessionInfo() as well as your OS, i.e., see > http://www.r-project.org/posting-guide.html? > > HTH, > Jorge.- > > > 2011/12/13 å欣 <> > >> According to the example of logistic.display: >> model0 <- glm(case ~ induced + spontaneous, family=binomial, data=infert) >> summary(model0) >> logistic.display(model0) >> >> induced: 3levels 0,1,2 >> spontaneous: 3levels 0,1,2 >> >> So if 0 is reference, we should get 2 OR for >> " induced1"," induced2"," spontaneous1"," spontaneous2" >> >> But the acturally OR is as the following,which is not what I expected: >> >> crude OR(95%CI) adj. OR(95%CI) P(Wald's >> test) P(LR-test) >> induced (cont. var.) 1.05 (0.74,1.5) 1.52 (1.02,2.27) 0.042 >> 0.042 >> spontaneous (cont. var.) 2.9 (1.97,4.26) 3.31 (2.19,5.01) < 0.001 >> < 0.001 >> >> >> Can anyone give me some suggestions? >> >> Many thanks! >> >> >> >> >> >> >> Hi sir: >> I follow your suggestion: >> >> result<-glm(y ~ factor(age) + factor(gender) + CD4,family = binomial) >> logistic.display(result) >> >> Error in coeff[, 1] : incorrect number of dimensions >> >> >> >> >> >> >> At 2011-12-14 01:59:36,"Jorge I Velez" <> wrote: >> >> Hi there, >> >> Try >> >> require(epicalc) >> logistic.display(result) >> >> HTH, >> Jorge >> >> On Tue, Dec 13, 2011 at 7:16 AM, å欣 <> wrote: >> >>> Hi all: >>> My data has 3 variables: >>> age(3levels : <30y=1 30-50y=2, >50y=3) >>> gender(Male=0, Female=1) >>> CD4 cell count(raw lab measurement) >>> y(1:death 0:alive) >>> >>> I perform logistic regression to find out the factors that influence y. >>> >>> result<-glm(y ~ factor(age) + factor(gender) + CD4,family = binomial) >>> >>> >From the result,I can get OR(Odds Ratio) of gender via exp(Estimate of >>> Female, since Male is regarded as reference group and has no result).But >>> how can I compute the 95%CI of OR of gender? >>> >>> >>> Thanks a lot for your help. >>> >>> My best! >>> >>> >>> >>> >>> [[alternative HTML version deleted]] >>> >>> ______________________________________________ >>> 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. >>> >> >> >> >> >> >> > [[alternative HTML version deleted]]
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