1. Stratified Covariate Balancing Using R
Farrokh Alemi, PhD

2. Download Stratified Balancing
Note Capital Letters

3. Load Package into Library

4. Remove Impossible Values
Prepare Your Data
Remove Impossible Values
Visit after Death
Negative ID
Zero Blood Pressure
Pregnant Males

5. Predict from Other Variables
Prepare Your Data
Impute Missing Values
Predict from Other Variables
Use Mode
Use Average
No Report No Diagnosis

6. Prepare Your Data Binary Indicators
Initial Analysis
Binary Indicators
More cases match to controls
Use R discretization
software
Above or below average
Worst category vs. all others
No report then no diagnosis

7. Prepare Your Data Binary Indicators
Initial Analysis
Binary Indicators
More cases match to controls
Use R discretization
software
Above or below average
Worst category vs. all others
No report then no diagnosis

8. Read Simulated Data Download from Read into directory
Read into directory

9. Look at Data Using fix(data)

10. Select Subset of Data for Analysis
Data should list only treatment and covariates to be balanced

11. Don’t Stratify Variables
on Causal Path
Examine sequence of events
Avoid complications of treatment
Don’t stratify mediators
Conduct Collider Tests

12. Balance Data
> balanced=stratadisc(4,5,subset)

13. Common Odds Ratio does not include one so it is significant
Balance Data
Common Odds Ratio does not include one so it is significant

14. In large data, effect size should at least doubling
Balance Data
In large data, effect size should at least doubling

15. 60% of cases matched to controls
Balance Data
60% of cases matched to controls

16. Check the Strata You Created
# Check the strata you have created
fix(balanced)

17. Check Balance

18. Conduct Sensitivity Analysis
# Sensitivity analysis of treatment in column 4
# Outcome in column 5
# In data set called subset
revised=sensdisc(4,5,subset)
revised