11-25-2014 04:20 PM
Hi guys, this is my first post on this forum. I need some advice. I have done a number of analyses on binary data (taking on the value 0,1) where a logistic model is appropriate. The output is a sigmoid function for the probability of being 0 or 1 that ranges from a lower asymtote of 0 to an upper asymtote of 1. I have a problem now where my data is binary (0=male, 1=female) and the relationship is sigmoid, but with an expected lower asymtote of 0.5 and an upper asymtote of 1. What procedure exists in SAS to take the binary data as input to estimate the probability of being male or female. The predictor variable is continuous -- temperature. The more general question is, I guess, what procedure in SAS allows you to estimate the parameters of a any specified function p (of being male or female) as a general non-linear regression against a continuous predictor variable. Sort of like PROC NLIN but on binary data with a binomial error structure.
11-26-2014 03:39 PM
That worked a treat, thanks. Not sure why I did not look there first?
Thank you so much.
ods graphics on;
proc probit data=combined c=0.5 optc plots=(predpplot ippplot);
model sex = temp / dist=logistic;
output out=results p=p_hat;
ods graphics off;
Analysis of Maximum Likelihood Parameter Estimates
Standard 95% Confidence Chi-
Parameter DF Estimate Error Limits Square Pr > ChiSq
Intercept 1 -80.3676 24.0010 -127.409 -33.3266 11.21 0.0008
TEMP 1 2.3631 0.7007 0.9898 3.7365 11.37 0.0007
_C_ 1 0.5047 0.0191 0.4673 0.5421
Need further help from the community? Please ask a new question.