S******y
发帖数: 1123 | 1 I have a data set A with binary reponse variable 'event' - 0, 1 (i.e.
failure, success).
I already have prior knowledge of effects from X1 and X2 as baseline. i.e.,
I know -
log (p/(1-p)) = 0.34 + 0.25 * X1 + 0.81 * X2
The parameters above were obtained from previous analysis on a different
data set B.
Now I would like to evaluate the lift I can gain from including additional
variable X3. So here is what I did -
data A;
set A;
z = 0.34 + 0.25 * X1 + 0.81 * X2;
run;
proc logistic data=A;
model | D******n
发帖数: 2836 | 2 i guess for model 2 u should dump all the variables to fit a new model, rest
ricting the coefficients is weird,
.,
【在 S******y 的大作中提到】
: I have a data set A with binary reponse variable 'event' - 0, 1 (i.e.
: failure, success).
: I already have prior knowledge of effects from X1 and X2 as baseline. i.e.,
: I know -
: log (p/(1-p)) = 0.34 + 0.25 * X1 + 0.81 * X2
: The parameters above were obtained from previous analysis on a different
: data set B.
: Now I would like to evaluate the lift I can gain from including additional
: variable X3. So here is what I did -
: data A;
| j*****e
发帖数: 182 | 3 Try this:
proc logistic data=A;
model event = X3/offset=z;
run; |
|
