I did a bootstrapping with a mixed model (several variables with interaction and one random variable). I got this result (only partial):
> boot_out ORDINARY NONPARAMETRIC BOOTSTRAP Call: boot(data = a001a1, statistic = bootReg, R = 1000) Bootstrap Statistics : original bias std. error t1* 4.887383e+01 -1.677061e+00 4.362948e-01 t2* 3.066825e+01 1.264024e+00 5.328387e-01 t3* 8.105422e+01 2.368599e+00 6.789091e-01 t4* 1.620562e+02 4.908711e+00 1.779522e+00 ......
Now, I wanted to get the confidence intervals for the intercept:
> boot.ci(boot_out,type=c("norm","basic","perc"), index=1) BOOTSTRAP CONFIDENCE INTERVAL CALCULATIONS Based on 1000 bootstrap replicates CALL : boot.ci(boot.out = boot_out, type = c("norm", "basic", "perc"), index = 1) Intervals : Level Normal Basic Percentile 95% (49.70, 51.41 ) (49.70, 51.41 ) (46.34, 48.05 ) Calculations and Intervals on Original Scale
The bias corrected estimated is:
The problem I have is that the normal and basic CI are outside of the estimate (original and corrected). I just wonder how to cope with that.
Here is a similar questions with a lot of responses.