Oh okay,
Are the new values generated from multiple datasets or just from predicting
the missing values from independent variables in the old dataset?
M.
On 1/24/06 2:25 PM, "Nicola Orsini" <[email protected]> wrote:
> Mosi,
>
> if you want to have just one imputed variable in the original dataset
> it's even easier than what I suggested earlier.
>
> Just type one line
>
> uvis regress income black male age2 educate, gen(imp_income)
>
> Nicola
>
> Mosi A. Ifatunji wrote:
>> Nicola,
>>
>> Okay, so the syntax seems to have worked with the new commands. That is,
>> after running the syntax I find myself working with a dataset that is
>> representative of multiple datasets and if I run -tab income- I get a
>> crosstab with imputed values.
>>
>> Ultimately, I would like to have a dataset ('das1995r') that has one
>> observation per variable per person in the dataset. I would like to have a
>> variable in such a dataset with a variable named, say 'imp_income' (for
>> imputed income). How do I get from where I am now to where I want to end up?
>>
>> M.
>>
>>
>> On 1/24/06 11:29 AM, "Nicola Orsini" <[email protected]> wrote:
>>
>>
>>> Mose,
>>>
>>> 1) define a working directory -help cd-
>>>
>>> clear
>>> cd "mypath"
>>>
>>> 2) use the command -use- instead of -sysuse- to open your dataset (help
>>> sysuse)
>>>
>>> use das1995r
>>>
>>> The rest of the lines should be fine. I hope you are using a do-file to
>>> run the analysis.
>>>
>>> Best,
>>> Nicola
>>>
>>> Mosi A. Ifatunji wrote:
>>>
>>>> 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/
>>>
>>> *
>>> * 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/
>>
>>
>>
>> *
>> * 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/
>
>
> *
> * 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/
*
* 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/
