Matching

In this video, we:
analyze a study of the effectiveness of "get out the phone" phone calls on voter turnout
use matching to create a balanced data set from an initially unbalanced one.

[@DrobbinsMpharm]

Really good video, Mr Scott!

[@Npersonal]

Hi James, thanks for the video. By the way how can I match multiple groups??

[@izzetakosman2154]

Is it possible to find the turnout.csv file online?

[@mightbekev]

Hi James, i am trying to match an intervention group with a control based on gender, age, and domestic/int student. I tried this code: f4s_match = matchit(Condition_Code ~ Age + Gender + DomesticBranch1, data = f4s, ratio=1) but got this error "Error in eval(family$initialize) : y values must be 0

[@JamesScottUT]

Hard to know for sure but it seems plausible that Condition_Code (which I presume is your treatment variable) is not a binary variable (i.e. yes or no, treated or untreated).