Hello everyone, I have survey data of approximately 5000 participants and I am currently looking to model the outcome of a dichotomized response variable to a predictor. Our question is if there is a trend of participants being more likely to be in the 1 level of the response variable as we move from 4 to 1 in the ordinal response predictor. The dichotomized response has levels 1 and 0 while the predictor is an ordinal survey response with levels 1 - "Yes - completely", 2 - "Yes - mostly", 3 - "Yes - somewhat", and 4 - "No". I am currently wondering how to structure my proc logistic code and also weighing the use of proc logistic vs. proc surveylogistic. I do not have survey weights, so it seems that proc surveylogistic would not be useful in comparison to proc logisitic. Here is my code so far: proc logistic data = import plots=all;
class outcome q1 / param=ordinal;
model outcome = q1;
run; I chose ordinal for the param= statement however I am not sure about that, though changing the param= option does not change the model fit statistics. I will continue to read documentation about proc logistic to see what other options might suit, but if there are any suggestions please let me know. Thank you!
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