Hi Statalisters,

Apologies if answered elsewhere - have looked. Using version 12.

Is it possible to automatically generate the bias-corrected accelerated confidence interval for the mean of a ratio which has both sides generated from 2 different samples?

The process is as follows:

Then produce the BCa CI for ratio

Currently I am doing the final stage manually by estimating the bias and acceleration associated with the newly generated variable using Efron's formulas - as included in [R] bootstrap - where for the acceleration n=nx0+nx1. This is tedious and error-prone.

Is there a way to do all this automatically using -bootstrap- ?

I have tried programming the bs, for example:

but this does not use the correct samples.

Thanks in advance,

Chris

Apologies if answered elsewhere - have looked. Using version 12.

Is it possible to automatically generate the bias-corrected accelerated confidence interval for the mean of a ratio which has both sides generated from 2 different samples?

The process is as follows:

Code:

bs, saving (bsx0.dta) bca: mean var1x0 var2x0 //based on sample nx0 bs, saving (bsx1.dta) bca: mean var1x1 var2x1 //based on sample nx1 use bsx0.dta, clear merge using bsx1.dta gen ratio=(var1x1-var1x0)/(var2x1-var2x0)

Currently I am doing the final stage manually by estimating the bias and acceleration associated with the newly generated variable using Efron's formulas - as included in [R] bootstrap - where for the acceleration n=nx0+nx1. This is tedious and error-prone.

Is there a way to do all this automatically using -bootstrap- ?

I have tried programming the bs, for example:

Code:

program ratioest, rclass sum var1x0 local var1x0 = r(mean) sum var2x0 local var2x0 = r(mean) sum var1x1 local var1x1 = r(mean) sum var2x1 local var2x1 = r(mean) return scalar ratio = (`var1x1'-`var1x0')/(`var2x1'-`var2x0') end bs r(ratio), bca: ratioest

Thanks in advance,

Chris