Mathematically, you only need the coefficient for the predictor to derive an odds ratio (you don't need the intercept value).
oddsratio=exp(coefficient_size)


Mathematically, you only need the coefficient for the predictor to derive an odds ratio (you don't need the intercept value). oddsratio=exp(coefficient_size)
One can obtain odds ratios from the results of logistic regression model. Odds ratios derived are adjusted for predictors included in the model and explains the relationship between two groups (e.g., treatment and control group) and outcome (binary outcome). I wrote the following Excel document that calculates odds ratio based on logit coefficients from […] http://support.sas.com/resources/papers/proceedings11/3422011.pdf Can this be right? If right, it helps reduce the computational demand off the procedure. Page 4: "When thousands of persons take a test, the procedure takes a long time to estimate the parameters. It is well known that the Rasch model gives the same parameter estimates for each person who receives the […] Why do switching of values in a dummy variable and the use of class statement in PROC LOGISTIC change the coefficients in logistic regression? (1) and (2) produce the same results. (3) and (4) produce the same results. (1) proc logistic data=here.asdf descending ; model college= boy ; run; (2) proc logistic data=here.asdf descending ; […] /*ROC Curve Analysis Macro*/ /*a hypothetical data set*/ data asdf;set sashelp.class; EVENT=0; if Weight > 100 then EVENT=1; PREDICTOR=height; run; /*data name*/ %let dataname=asdf; %let outcome=EVENT; %let ind=PREDICTOR; %let save_graphic=C:\Documents and Settings\19702\My Documents\sas; ods html PATH="&save_graphic" (url=none) file="&dataname &ind .html"; ods graphics on / imagename="&dataname&ind"; proc logistic data=&dataname descending OUTEST=&dataname.result; title "&dataname"; model &outcome = […] 

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