05-27-2018 12:08 AM - last edited on 05-29-2018 01:51 PM by Rick_SAS
Can some one explain the following question?
The following LOGISTIC procedure output analyzes the relationship between a binary response and an ordinal predictor variable, wrist_size Using reference cell coding, the analyst selects Large (L) as the reference level.
Analysis of Maximum likelihood estimates
Parameter DF Estimate standard error Wald Chi-sq Pr>Chisq
Intercept 1 -1.0415 0.4749 4.8101 0 .0283
wrist_size M 1 1.1234 0.4989 5.0697 0.0243
wrist_size S 1 1.6078 0.5478 8.6133 0.0033
What is the estimated logit for a person with large wrist size?
05-27-2018 02:30 AM
Always a good idea to post your code. Gives us a lot of information and makes it easier to help you.
You can get the desired quantity by using the ESTIMATE Statement like this
estimate 'Coef for wrist_size L' wrist_size -1 -1;
05-27-2018 07:05 AM
According to SAS documentation about parameterization method.
There is not a column of Large (L), which means its parameter should be zero. Therefore, its logit = parameter estimator of intercept.
05-27-2018 04:15 PM - edited 05-27-2018 04:17 PM
@Ksharp provides some important information regarding how SAS handles categorical (CLASS) variables in its modeling. One level will always have a coefficient of zero, making the true value of the coefficient for this level = zero + intercept (for a simple one-way design), while the other variables will have a coefficient = (coefficient shown) + intercept (for a simple one-way design).
A better way to estimate the effect of CLASS variables in SAS is to use the LSMEANS command, and then this problem goes away. Each level (even the one with the zero coefficient) is shown with the math above computed for you.
If I may be so bold, you have entitled two recent posts "Statistics", and "Statistics" is a very very very very broad topic, and not a good title. You would be wise to provide more meaningful (and not so broad) title such as "Coefficients in PROC LOGISTIC".