st: Design-based truncated regression

[Eric Sevigny <els21+@pitt.edu>]

Hello Statalist,

My question involves Stata's capability to estimate design-based truncation 
regression models.  I am using complex survey data, incorporating weights, 
strata, and psu. I also have a truncated dependent variable in which I have 
no observations for cases when y is below a certain cutoff and, therefore, 
want to estimate a truncated regression model. While Stata's survey 
estimation capabilities include models for other limited dependent 
variables (e.g., svyintreg), it does not explicitly implement this 
capability for truncated regression. Thus, as I see it, I have several 
options, which I would appreciate any comment on.

1) Use -truncreg- options to estimate truncated regression models that 
partially adjust for design elements. Specifically, that would mean 
ignoring strata (or disaggregating analyses by strata) while accounting for 
just the pweights and clusters. This is unsatisfactory because (i) possible 
problems in variance estimates for analyses that are not fully 
disaggregated by strata and (ii) problems with having incorrect df in any 
postestimation tests.

2) Estimate totally model-based -truncreg- and then use -suest- to survey 
adjust the estimates. Unfortunately, this won't work unless -truncreg- is 
somehow reprogrammed to accept iweights, which are needed for use with 
-suest-. Even if this capability were implemented, I am not sure 
postestimation tests would be performed with correct df.

3) This is probably the best option, but I'm not sure I have the 
statistical/programming ability to implement it. It is to use Stata's -ml- 
capabilities to create an estimation command that accounts for both the 
truncation and survey design. I know -ml- has survey estimation 
capabilities, but am not sure if truncated regression estimation has any 
inherent or theoretical limitations for such implementation.

In any event, I would greatly appreciate any technical, methodological, 
programming, and/or theoretical comments anyone could provide on this issue.

Thanks,

Eric Sevigny


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