Randomization is a critical step for ensuring exogeneity in experimental methods and randomized control trials (RCTs).
Stata Coding Practices
Randomization is a critical step for ensuring exogeneity in experimental methods and randomized control trials (RCTs).
Researchers use Stata in all stages of an impact evaluation (or study), such as sampling, randomizing, monitoring data quality,
Researchers use Stata in all stages of an impact evaluation (or study), such as sampling, randomizing, monitoring data quality,
Modern Stata versions have extremely powerful graphics capabilities which allow the rapid creation of publication-quality graphics from almost any kind of tabular data. Although the default graphical commands and settings leave much to be desired, the customizability and interoperability of Stata's visualization tools mean that almost any imaginable output can be rendered using Stata's built-in graphics engine.
Programs and ado-files are the main methods by which Stata code is condensed and generalized. By writing versions of code that apply to arbitrary inputs and saving that code in a separate file, the application of the code is cleaner in the main do-file and it becomes easier to re-use the same analytical process on other datasets in the future. Stata has special commands that enable this functionality.
Debugging is the process of fixing runtime errors or other unexpected behaviors in Stata code. Unlike normal code execution, debugging involves intentionally preventing code from running completely so the user can investigate the current state of data or memory and determine what code would produce the desired outputs in a complete execution of the code.
DIME Analytics has developed the ietoolkit package for Stata to simplify the process of data management and analysis in impact evaluations.