I need to plot the data from a simple linear regression with its values x and y with the fitted y values from fitting a logistic regression model. How do I plot the x values with two different y's, y values on the left side with fitted y values on the right? I want to generate the fitted/predicted y values using logistic regression and then create a plot using all those three variables? Here is an example of my SAS code that doesn't work. data coupons; input redeemed discount; cards; 100 5 147 9 176 11 211 13 244 15 277 17 310 19 343 21 ; run; ods graphics on; proc logistic data=coupons; model redeemed(event='1') = discount; effectplot; run; It give me this warnings and I do not understand…. NOTE: Option EVENT= is ignored since LINK=CLOGIT. NOTE: PROC LOGISTIC is fitting the cumulative logit model. The probabilities modeled are summed over the responses having the lower Ordered Values in the Response Profile table. Use the response variable option DESCENDING if you want to reverse the assignment of Ordered Values to the response levels. WARNING: There is a complete separation of data points. The maximum likelihood estimate does not exist. WARNING: The LOGISTIC procedure continues in spite of the above warning. Results shown are based on the last maximum likelihood iteration. Validity of the model fit is questionable.
I need to plot the data from a simple linear regression with its values x and y with the fitted y values from fitting a logistic regression model. How do I plot the x values with two different y's, y values on the left side with fitted y values on the right? I want to generate the fitted/predicted y values using logistic regression and then create a plot using all those three variables? Here is an example of my SAS code that doesn't work.
data coupons;
input redeemed discount;
cards;
100 5
147 9
176 11
211 13
244 15
277 17
310 19
343 21
;
run;
ods graphics on;
proc logistic data=coupons;
model redeemed(event='1') = discount;
effectplot;
run;
It give me this warnings and I do not understand….
NOTE: Option EVENT= is ignored since LINK=CLOGIT.
NOTE: PROC LOGISTIC is fitting the cumulative logit model. The probabilities modeled are summed over the responses having the lower
Ordered Values in the Response Profile table. Use the response variable option DESCENDING if you want to reverse the
assignment of Ordered Values to the response levels.
WARNING: There is a complete separation of data points. The maximum likelihood estimate does not exist.
WARNING: The LOGISTIC procedure continues in spite of the above warning. Results shown are based on the last maximum likelihood
iteration. Validity of the model fit is questionable.
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