Ok, I’m back. Not a lot of lines of code to go through, actually.
This is what he says he does in Fig.1:
“Left panel estimated from probit model with offer size, treatment condition, interaction between offer and treatment, and dichotomous variable for the repetition of the experiment … Standard errors clustered at individual level and confidence intervals calculated using a parametric bootstrap running for 1000 iterations.”
Sample size is very small (only 72 students), so I can see why a reviewer asked him to bootstrap his data. Also, data is clustered, so simple bootstrap won’t do.
Replication data is here: http://hdl.handle.net/1902.1/14820
From his readme file:
“The .R and .do files provide all of the statistical analyses.”
There are only one of each. Stata file only does tests of equality of proportion (prtest).
R file has the Zelig code for the probit models:
ProbReject<-zelig(OfferReject~Delta*SubjAOffer+ repetition , model="probit.gee", robust=TRUE, id="ID", corstr = "exchangeable", data=ExpData)
Several such models, none using the bootstrap option.
Zelig documentation says that if bootstrap argument is not specified, the default is bootstrap=FALSE. That is, no bootstrap.
http://docs.zeligproject.org/articles/bootstraps.html
“The zelig() bootstrap argument has a default of FALSE, and can be set to TRUE or a numeric value giving the number of bootstrapped datasets to run. If set to TRUE the default is 100 bootstraps. The bootstrap works in combination with other Zelig arguments as follows:
…
Examples:
z.out <- zelig(unem ~ gdp + capmob + trade, model = "ls", data = macro, bootstrap = 500)“
Oops, I just couldn’t find any evidence of bootstrap in the code. Check for yourselves and report here if you find any.