This post summarizes how to work on the Fragile Families Challenge data in Stata.

We only cover the basics here. For more detailed example code, see our open-source repository, thanks to Jeremy Freese.

How do I import the data?

Before loading the data, you may need to increase the number of variables Stata will hold.
set maxvar 13000

Then, change your working directory to the place where the file is located, using
cd your_directory.

Load the training outcomes
import delimited train.csv, clear case(preserve) numericcols(_all)
Two options there are critical:

• The case(preserve) option ensures that the case of variable names is preserved. Omitting this option will produce errors in your submission since capitalization in variable names is required (i.e. challengeID), but Stata’s default makes all variable names lower case.
• The numericcols(_all) option ensures that the outcomes are read as numeric,
  rather than as character strings.

Merge the background variables to that file using the challengeID identifier.
merge 1:1 challengeID using background.dta

• You will see that 2,121 observations were in both datasets. These are the training observations for which we are providing the age 15 outcomes.
• You will also see that 2,121 observations were only in the using file, since the background variables but not the outcomes are available for these cases. These are the test cases on which your predictions will be evaluated.

If you have an older version of Stata, you may not be able to open the .dta file with metadata. You can still load the background file from the .csv format. To do that, you should first load the .csv file and save it in a .dta format you can use. Then, follow the instructions above.
import delimited background.csv, clear case(preserve)
save background.dta, replace
Again, note the important case(preserve) option!

How do I make predictions?

If your model is linear or logistic regression, then you can use the predict function.
regress gpa your_predictors
predict pred_gpa, replace

Then the variable gpa_pred has your predictions for GPA. You can do this for all 6 outcomes.

How do I export my submission?

This section assumes your predicted values are named pred_gpa, pred_grit, etc. First, select only the identifier and the predictions.
keep challengeID pred_*
Then, rename all your predictions to not have the prefix pred_
local outcomes gpa grit materialHardship eviction layoff jobTraining
foreach outcome of local outcomes {
rename pred_`outcome' `outcome'
}
Finally, export the prediction file as a .csv.
export delimited using prediction.csv, replace
Finally, bundle this with your code and narrative description as described in the blog post on uploading your contribution!