Propensity Score Matching (PSM) for causal inference using the R MatchIt package is introduced in this tutorial. You will learn:
👉 How do the Propensity Score Matching (PSM) algorithms work?
👉 How to conduct Propensity Score Matching (PSM) using the R package MatchIt?
👉 How to check the balance of the matched dataset?
👉 How to calculate causal impact using a t-test or a regression model?
⏰ Timecodes ⏰
0:00 - Intro
0:51 - Step 0: Propensity Score Matching (PSM) Algorithms for Causal Inference
1:37 - Step 1: Install and Import Libraries
2:44 - Step 2: Create Dataset for Causal inference
3:26 - Step 3: Unadjusted Mean Differences before Propensity Score Matching (PSM)
3:42 - Step 4: Pre-Matching Standardized Mean Difference of Confounders
4:18 - Step 5: Propensity Score Matching (PSM) Using R Package MatchIt
5:49 - Step 6: Matched Dataset Balance Checking
7:46 - Step 7: Estimating Treatment Effect Using T-Test
8:09 - Step 8: Estimating Treatment Effect Using Model
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