Dear colleagues, When we run a logistic regression, we assume that the Wald test for a specific parameter has an asymptotic standard Normal distribution. Therefore, when we look at the 95% confidence interval provided for the parameter, before being exponentiated,it is calculated by the following expression: B±1.96SE. But, if the number of observations for the category associated to the parameter estimated is low, then the parameter will not have a Standard Normal distribution. If I am not mistaken, is there a way to change it when estimating a logistic regression? Thank you in advance. Best regards, Iuri ... View more

Dear All, I have some questions that are not related to the SAS use. I am reading about the distributions that belong to the exponential family. There is also a subgroup that belongs to the canonical exponential family. The Bernoulli is one of them, it belongs to the exponential family and the canonical exponential family. When writing the Bernoulli distribution in the canonical form we identify the canonical link which is the natural ling for a Generalized Linear Model for binary variable. In this case, the natural link is the logit. Still dealing with a GLM for binary variable, we have the probit model, in which the link function is The Inverse CDF of the normal distribution. It also maps the probability that assumes values between 0 and 1 into something that assumes values between minus infinity and plus infinity. However, the link function is not a natural one. Both are appropriate to work with dichotomous variable (associated to Bernoulli distribution), but in the canonical form the natural link is the logit. Is that correct? The canonical link function refers to the natural one? The Inverse CDF of the normal distribution used in the probit is a link function, but not a canonical link function? Thanks a a lot. ... View more

Dear members of SAS community, I do not have a SAS specific question. In fact, I would like to argue about the need to give enough time of follow-up to analyze data with logistic regressions instead of any survival model that incorporates censoring. Suppose I am interested in identifying factors associated with loss of follow-up of participants from a cohort study. Suppose further that the loss of follow up is defined as failure to return for a period of six months. I could use a cox proportional hazards model to consider patients who were enrolled less than six months before the ending date of the study. If I use a logistic regression instead of a survival model that incorporates censoring, shouldn’t I exclude all the patients who were enrolled less than six months before the ending date of the study? I ask that because I did not follow them for enough time to observer the event. It seems to be that a worse decision is to exclude those who did not return in the six months before the end of the study and keep in the analysis those who return in the six months. Is that correct? Best regards, ... View more

  Dear All, We are carrying out a study in which patients are followed-up during a year with quarterly visits. In each visit they are teste for many diseases. One of them is hepatitis B. We are running a logistic model to measure the difference in proportions of participants with hepatitis B (HEPAT_B) in week 0 and week 52. As the measures are from the same individuals, we used a conditional logistic. Generally, I use proc genmod with the identification of individuals (copid). PROC GENMOD DESCENDING; CLASS COPID Week (REF='0'); MODEL HEPAT_B=week/ DIST=BIN LINK=LOGIT; REPEATED SUBJECT=COPID/TYPE=UN; ESTIMATE 'TEMPO' week 1 -1/EXP; RUN;   It runs perfectly.   But because there in no event at week 52, I tried to include some exact test.   I used the following command:   PROC LOGISTIC DATA=TOTAL exactonly; CLASS week; STRATA COPID; MODEL HEPAT_B=week; EXACT week; RUN;   It did not work.   However, if I used only the exact logistic without the option strata, the model works fine.     proc logistic data=TOTAL;          class week/ param=ref;          model HEPAT_B=week;          exact week;          run;   I would like to know how to can I used a conditional logistic model  with a option exact. Thank you in advance. Regards, Iuri   SAS Output: NOTE: ODS Graphics are not available when the EXACTONLY option is specified. WARNING: There are no valid observations since all strata are noninformative. NOTE: The SAS System stopped processing this step because of errors. NOTE: There were 4473 observations read from the data set WORK.TOTAL. NOTE: PROCEDURE LOGISTIC used (Total process time):       real time           0.04 seconds       cpu time            0.01 seconds   ... View more

Hi All,   We are carrying out a GEE logistic analysis to see if there is difference between the two categories of a dummy variable. However, when the dummy variable assumes the value one the response variable assumes the value zero. So, we have a complete separation. So, I would like to know if there is a possibility of doing an exact test when running a GEE logistic regression and it is a solution to my problem. Thank you in advance. Regards ... View more

We observe are carrying out a longitudinal study event in different moments of time. But in one specific analysis we observe an event (identified by a medical exam) at enrollment (baseline) and 52 weeks later (week 52).  We would like to see if there is difference between the proportions observed at baseline and week 52. It is important to emphasize that we will not observe the event for all the participants, either because the medical exam was not realized or because the participants did not have enough time to have the medical exam carried out in the week 52. To evaluate the difference in proportions we used a logistic GEE model considering time (dummy variable indicating baseline and week 52) as a explanatory variable. So, I would like to know if this is the best way to implement this analysis. Thank you in advance. Regards,   Iuri Leite ... View more