Thomas de Hoop wrote:
I have created dummy variables for 214 countries. For each of these
countries I want to estimate several logit models to estimate chances of
certain situations to occur, and create chance variables from the
prediction of these models. I estimate these chances using data from the
past. I have data of these situation For this I created loops with the
foreach and forvalue commands from stata. The problem is that in some
countries a certain situation never occurred. For these situations there
are only 0 value observations. Of course logistic regression is not
possible in these kind of situations. For this reason I would like to
skip these equations in the loop.
For this reason I counted the number of times a situation did occur in
the past and created a variable.
I tried to skip the equation as follows:
forval i=1/214 {
logit drought`i' variable1 variable 2 etc. if droughtcount`i'>0
}
i= the country number
variable1 variable2 etc are the explanatory variables.
drought`i'=the situation in a certain country
droughtcount`i'=the number of times a situation did occur in the past.
For country 3 this results in the following error:
no observations
r(2000);
---------------------------------------------------------------------
I believe that you became a victim to the dangerous "missing is large"
trap: missing values are very large numbers, and the expression
droughtcount3>0 is evaluated to true if droughtcount3 is missing.
Solution:
logit drought`i' ... if droughtcount`i'>0 & droughtcount`i'<.
Read more in
help missing
Hope this helps,
Svend
__________________________________________
Svend Juul
Institut for Folkesundhed, Afdeling for Epidemiologi
(Institute of Public Health, Department of Epidemiology)
Vennelyst Boulevard 6
DK-8000 Aarhus C, Denmark
Phone: +45 8942 6090
Home: +45 8693 7796
Email: sj@soci.au.dk
__________________________________________
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