Suggestions to analyse the dat

[Nicolas Orgeira]

Hi,

I'm working with a panel data from a quasi-experimental study with the following characteristics

1) Unbalanced covariates between the control and the treatment group (according to Hotelling's T-squared test), though I've read that it's not cause for concern (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4310023/);

2) High level of attrition, though similar in rate for both the control and treatment group, and no statistical difference in covariates between drop-outs from the two groups (Pearson chi2 for each covariate) but significant using Hotelling's T-squared test;

3) Treatment assignment at the regional level, participants were randomly selected in three random towns within a region;

4) Defiers in both the control and the treatment group;

5) Most likely heterogenous effects by region.

I was thinking of using a DID analysis, given that the control and treatment groups' covariates and key indicators differ, and then use a LATE approach to estimate the average treatment on the treated. I was wondering if:

a) that would be the correct approach?
b) I read somewhere that DID is ATE, and that for LATE, I would need to estimate the ITT. How can I estimate the ITT?
c) can I estimate ATT on DID?
d) any suggestions on different approaches, given the type of data (i.e. FE, PSM)?

Thank you!

[Phil Bromiley]

You didn't get a quick answer. You'll increase your chances of a helpful answer by following the FAQ on asking questions - provide Stata code in code delimiters, readable Stata output, and sample data using dataex.

This kind of general question (of which I have posted a few) has a lower response rate than more targeted questions. I can't really help much with DID. I would look at the treatment estimators if I had this kind of problem but in many cases they are quite similar to DID estimates.