Thanks Nicola,
I have been trying the code that you sent and I am having some trouble with
it. Admittedly, I am not familiar with some of the commands that you're
using and the -help- command doesn't really provide for much more clarity.
So, let me tell you what I am doing (verbatim) and you can tell me if there
is an error in my use of the syntax you have so generously provided.
First, the dataset I am using is called das1995r and it is located in the
main Stata folder. The variable I would like to generate values for is
'income.' the variables I would like to generate 'income' from are: 'black',
'male', 'age2' and 'educate.'
The commands that I am not familiar with have an * after them. I did not
actually put the * in my syntax, but I thought it might help for you to know
my level of novice :-). After looking at your sample, I tried the following:
clear
sysuse* das1995r
forv* i = 1(1)5 {
preserve*
uvis* regress income black male age2 educate, gen(income`i') seed(123695`i')
replace income = income`i'
save das`i', replace
restore*
}
[[Here I am told: "already preserved r(621);"]]
forv* i = 1(1)5 {
use das`i', clear
tab income, miss
}
[[Here is where I get the error message that stops the progress. I get a
message that says: "file das1.dta not found." I proceed nonetheless.]]
miset* using das
[[Here is where I figure out that I can go no further for real. I get the
error message: "file das1.dta not found."]]
I am assuming that I am making an error somewhere, but I just don't know
where. As you can see, I skipped the part where you created missing values,
because my values are already missing in the 'income' variable. Other then
that the syntax is the same as you provided it, I think.
Thank you for your time and energy,
M.
=====
Hi Rose,
this is an example of multiple imputation.
clear
* findfile cancer.dta
sysuse cancer
set seed 1234
* create some missing at random for the outcome variable died (0/1)
gen u = uniform()
replace died = . if u > 0.6
codebook died
* impute 5 times the outcome variable died using uvis
* every time generating a new variable (died1, died2, ..., died5)
forv i = 1(1)5 {
preserve
* specify a model to predict missing values
uvis logistic died drug age, gen(died`i') seed(123695`i')
replace died = died`i'
* save a new dataset with the imputed dataset (canc1, canc2, ..., canc5)
save canc`i', replace
restore
}
* have a look at the imputed variables saved in the new datasets
forv i = 1(1)5 {
use canc`i', clear
tab died , miss
}
* set the imputed dataset before combine results
miset using canc
* specify the estimation command to be executed on each imputed dataset
* and get the overall estimates
mifit, indiv: logistic died drug age
Best,
Nicola
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
