Hi StatDave_sas, Thank you for your comments. I will address each in points as follows: 1. " "Dependent" and "Response" mean the same thing, so it is not clear which variable should be the dependent (response) variable and which should be the independent (predictor) variable in a model." - Thanks for noticing my error. The variables DV1 and DV2 are predictor_variable_1 (PV1) and predictor_variable_1 (PV2). 2. "all of the variables are continuous. To dichotomize a variable throws away a huge amount of data and you should consider whether this is wise and if another approach that uses all of the data is better." - I understand the issue involves dichotomizing continuous variable but my research question requires me to take this step to answer a specific question. 3. "the WHERE statements restrict all of the data seen by PROC LOGISTIC so that all usable observations have the same response and this should cause an error. The response in a binary logistic model should be binary - two distinct values should occur in the response variable being analyzed." - I have revised my code and I think this code should be the correct one: DATA data2;
SET data1;
IF PV1 LT 115 THEN c1=1; ELSE c1=0 ;
IF PV2 LT 115 THEN c2=1; ELSE c2=0 ;
RUN;
PROC LOGISTIC DATA= data2;
MODEL c1 (EVENT="1") = Resp1 / OUTROC= rocdata1;
RUN; 4. "If you provide binary response data to PROC LOGISTIC, the sensitivity and specificity values for each possible event probability cutoff will appear in the OUTROC= data set." - Yes, I can find sensitivity and 1-specificity values in the data set produced from the OUTROC=. However, I do not know the ID of each sensitivity or 1-specificity, and I do not know the value of Resp1 for each sensitivity and 1-specificity calculated. I need to know these variables and values for further analyses. How can I include these variables in the OUTROC produced data set? 5. "A comparative plots of ROC curves for a given response variable can be done as shown in the example titled "Comparing Receiver Operating Characteristic Curves" in the PROC LOGISTIC documentation." - I have read through this documentation, but the problem is I want to create a single ROC graph with three different curves using 2 response variables, 2 predictors and the combination of them (PV1 and Resp1, PV1 and Resp2, and PV2 and Resp2). using MODEL c1= Resp1 Resp2/ OUTROC=rocdata1; ROC 'Response1' resp1; ROC 'Response2' resp2; will not work as I am still lacking the MODEL c2= Resp2 in here. Do you think there is another way to create this graph? I tried using the PROC SGPLOT as you can see from my post. 6. "PROC LOGISTIC itself will produce the ROC plot.", " PROC GPLOT is not needed." - I removed PROC GPLOT from my code. Thanks 7. "If you want to label points on the ROC curve with certain values, use the PLOTS(ONLY)=ROC(ID=value) option in the PROC LOGISTIC statement, where value is one of the values discussed in the PLOT= option description in the PROC LOGISTIC statement Syntax section of the PROC LOGISTIC documentation." - This is the problem, SAS does not give me the option to identify the points with a variable from within my data set. For instance, if I use the PLOTS(ONLY)=ROC(ID=value), where value is PROB, it will label the probability level point, or if I choose OBS it will display the observation number, but from these I cannot know the Resp1 variable value (cutpoint) on the graph nor I can track the point myself down from the observation ID (patient's ID in my original data set). How can I get these inputs on the ROC graph or in the ROC data set created along with the sensitivity and 1-specificity? I really appreciate your time to respond to my inquiries.
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