Lecture: Introduction to Propensity Scoring  


Assigned Reading


Question 1:  For this assignment you can use any statistical software you are familiar with or use R.  You can also use MatchIt or other software designed to do propensity scoring.  The objective is to find response to citalopram for patients with different types of depression. These data come from STAR*D experiment conducted by NIMH.

  1. Read about the study protocol. Protocol►
  2. Download data.  Use instructor's last name as password.  Must enter password twice. Data 2010► Data 2003►
  3. Summarize the data. Describe different types of depression related diagnoses.
  4. Select a set of variables and construct a model to predict presence of a particular type of depression.
  5. Balance the data to remove the effects of other types of co-occurring mental health diagnoses on remission/response to treatment.  Show visually that the propensity scoring has been able to remove the effects of other predictors of response to citalopram
  6. Estimate response to citalopram for the particular depression type
  7. Describe what predicts success of citalopram.
  8. Describe how well the model predicts response to citalopram.

Question 2: In the following assignment, analyze the data provided by Morgan and Harding and calculate the unconfounded impact of college education. In this example, "Y is a measure of an individual’s economic success at age 40, D is the indicator of receipt of a college degree, and S is a mix of family background and preparedness-for-college variable that completely accounts for the pattern of self-selection into college that is relevant for lifetime economic success."  

Solution by Morgan and Harding Read►


For additional information (not part of the required reading), please see the following links:

  1. Example of propensity scoring to understand if racial differences exist in readmission Read
  2. Predictors of response to citalopram Read►
  3. Does citalopram help anxious depressions Read►

This page is part of the course on Comparative Effectiveness.   Edited by Farrokh Alemi, Ph.D.