
Title | Interpreting “outcome does not vary” error message when running logistic | |
Author | Paul Lin, StataCorp |
You probably have a dependent variable that is coded as 1 and 2 for the two outcomes
1 the event did not occur 2 the event did occur
Stata wants the coding
0 the event did not occur 1 the event did occur
All you have to do to fix the problem is
. replace dep_var = dep_var - 1
We create variable y and code it as 1 and 2, and this produces the error message. After recoding the variable, we fit the model.
Here is an example:
. sysuse auto (1978 Automobile Data) . gen y=foreign+1 . codebook y ------------------------------------------------------------------------------- y (unlabeled) ------------------------------------------------------------------------------- type: numeric (float) range: [1,2] units: 1 unique values: 2 missing .: 0/74 tabulation: Freq. Value 52 1 22 2 . capture noisily logit y price weight, nolog outcome does not vary; remember: 0 = negative outcome, all other nonmissing values = positive outcome . replace y=y-1 (74 real changes made) . logit y price weight, nolog Logistic regression Number of obs = 74 LR chi2(2) = 54.11 Prob > chi2 = 0.0000 Log likelihood = -17.976341 Pseudo R2 = 0.6008 ------------------------------------------------------------------------------ y | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- price | .0009296 .0002999 3.10 0.002 .0003418 .0015174 weight | -.0058785 .0016986 -3.46 0.001 -.0092078 -.0025493 _cons | 9.000473 2.627577 3.43 0.001 3.850517 14.15043 ------------------------------------------------------------------------------
The coding
0 the event did not occur 1 the event did occur
is just an example of the type of coding Stata requires. Stata actually assumes the dependent variable is of the form
0 the event did not occur nonzero the event did occur
and draws no distinction between the nonzero numbers. Thus, if you had a dependent variable that recorded the number of times an event occurred and you now wanted to analyze simply whether the event occured 1 or more times, you could use that count variable as a dependent variable with logistic, logit, or probit.