I did not understand complete separation quite well.. Thank you very much for clarification.
Kengo 2015-05-27 17:03 GMT-05:00 David Winsemius <dwinsem...@comcast.net>: > > On May 27, 2015, at 3:00 PM, Kengo Inagaki wrote: > >> Here is the result- >> >>> with(a, table(Sex, Therapy1, Outcome) ) >> , , Outcome = Alive >> >> Therapy1 >> Sex no yes >> female 0 4 >> male 4 5 >> >> , , Outcome = Death >> >> Therapy1 >> Sex no yes >> female 6 3 >> male 3 0 > > So no deaths when Female had no-Therapy1 and no survivors with the opposite > for those variables. Complete separation. > > -- > David. > >> >> >> 2015-05-27 16:57 GMT-05:00 David Winsemius <dwinsem...@comcast.net>: >>> >>> On May 27, 2015, at 2:49 PM, Kengo Inagaki wrote: >>> >>>> Thank you very much for your rapid response. I sincerely appreciate your >>>> input. >>>> I am sorry for sending the previous email in HTML format. >>>> >>>> with(a, table(Sex, Therapy1) ) shows the following. >>>> Therapy1 >>>> Sex no yes >>>> female 6 7 >>>> male 7 5 >>>> >>>> and with(a, table(Therapy1, Outcome) ) >>>> elicit the following >>>> >>>> Outcome >>>> Sex Alive Death >>>> female 4 9 >>>> male 9 3 >>>> >>>> Outcome >>>> Therapy1 Alive Death >>>> no 4 9 >>>> yes 9 3 >>> >>> Then what about: >>> >>> with(a, table(Sex, Therapy1, Outcome) ) >>> >>> -- >>> David >>> >>> >>>> >>>> As there is no zero cells, it does not seem to be complete separation. >>>> I really appreciate comments. >>>> >>>> Kengo Inagaki >>>> Memphis, TN >>>> >>>> >>>> 2015-05-27 13:57 GMT-05:00 David Winsemius <dwinsem...@comcast.net>: >>>>> >>>>> On May 27, 2015, at 10:10 AM, Kengo Inagaki wrote: >>>>> >>>>>> I am currently working on a health care related project using R. I am >>>>>> learning R while working on data analysis. >>>>>> >>>>>> Below is the part of the data in which i am encountering a problem. >>>>>> >>>>>> >>>>>> Case# Sex Therapy1 Therapy2 Outcome >>>>>> >>>>>> 1 male no >>>>>> no Alive >>>>>> >>>>> >>>>> snipped mangled data sent in HTML >>>>> >>>>>> >>>>>> >>>>>> "Outcome" is the response variable and "Sex", "Therapy1", "Therapy2" are >>>>>> predictor variables. >>>>>> >>>>>> All of the predictors are significantly associated with the outcome by >>>>>> univariate analysis. >>>>>> >>>>>> Logistic regression runs fine with most of the predictors when "Sex" and >>>>>> "Therapy1" are not included at the same time (This is a part of table >>>>>> that >>>>>> I cut out from a larger table for ease of >>>>>> >>>>>> presentation and there are more predictors that i tested). >>>>> >>>>> Please examine the data before reaching for ridge regression: >>>>> >>>>> What does this show: ... >>>>> >>>>> with(a, table(Sex, Therapy1) ) >>>>> >>>>> I predict you will see a zero cell entry. The read about "complete >>>>> separation" and the so-called "Hauck-Donner effect". >>>>> >>>>> -- >>>>> David. >>>>>> >>>>>> However, when "Sex" and "Therapy1" are included in logistic regression >>>>>> model at the same time, standard error inflates and p value gets close >>>>>> to 1. >>>>>> >>>>>> The formula used is, >>>>>> >>>>>> >>>>>> >>>>>>> Model<-glm(Outcome~Sex+Therapy1,data=a,family=binomial) #I assigned a >>>>>> vector "a" to represent above table. >>>>>> >>>>>> >>>>>> >>>>>> After doing some reading, I suspect this might be collinearity, as vif >>>>>> values (using "vif()" function in car package) were sky high (8,875,841 >>>>>> for >>>>>> both "Sex" and "Therapy1"). >>>>>> >>>>>> Learning that ridge regression may be a solution, I attempted using >>>>>> logisticRidge {ridge} using the following formula, but i get the >>>>>> accomapnying error message. >>>>>> >>>>>> >>>>>> >>>>>>> logisticRidge(a$Outcome~a$Sex+a$Therapy1) >>>>>> >>>>>> >>>>>> >>>>>> Error in ifelse(y, log(p), log(1 - p)) : >>>>>> >>>>>> invalid to change the storage mode of a factor >>>>>> >>>>>> >>>>>> >>>>>> At this point I do not have an idea how to solve this and would like to >>>>>> seek help. >>>>>> >>>>>> I really really appreciate your input!!! >>>>>> >>>>>> [[alternative HTML version deleted]] >>>>>> >>>>> >>>>> >>>>> David Winsemius >>>>> Alameda, CA, USA >>>>> >>> >>> David Winsemius >>> Alameda, CA, USA >>> > > David Winsemius > Alameda, CA, USA > ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.