A study found that a hospital program significantly reduced the number of hospitalizations and emergency department visits. Great. But then the researchers realized that the data was recoded incorrectly, and the program actually increased hospitalizations and emergency department visits. Not so great.
The identified programming error was in a file used for preparation of the analytic data sets for statistical analysis and occurred while the variable referring to the study “arm” (ie, group) assignment was recoded. The purpose of the recoding was to change the randomization assignment variable format of “1, 2” to a binary format of “0, 1.” However, the assignment was made incorrectly and resulted in a reversed coding of the study groups. Even though the data analyst created and conducted some test analysis programs, they were of the type that did not show any labeling of the arm categories, only the “arm” variable in a regression, for example.
Data can be tricky and could lead to unintended consequences if you don’t handle it correctly. Be careful out there.