bootstrap stata
DESCRIPTION
Bootstrap StataTRANSCRIPT
Bootstrapping Let's begin with a dictionary definition of bootstrap:
A data-based simulation method for statistical inference, which can be used to study the variability of values of a set of observations and provide confidence interbvals for for parameters in situations where these are difficult or impossible to to derive analytically. The basic idea involves sampling with replacement to produce random samples of size n from the original data. Each of these samples is known as a bootstrap sample and each provides and estimate of the parameter of interest. Repeating the sampling a large number of times provides information on the variability of the estimator.
Say that we wanted to test whether or not the write test score came from a population with median of 50. Let's try the bootstrap command by estimating the standard error of the median.
use http://www.ats.ucla.edu/stat/stata/notes/hsb2 bs "summarize write, detail" "r(p50)", reps(400) command: summarize write, detail statistic: r(p50) (obs=200) Bootstrap statistics Variable | Reps Observed Bias Std. Err. [95% Conf. Interval] ---------+------------------------------------------------------------------- bs1 | 400 54 .11 .8838002 52.26251 55.73749 (N) | 52 57 (P) | 54 57 (BC) ----------------------------------------------------------------------------- N = normal, P = percentile, BC = bias-corrected
Now let's compare the results of a bootstrap estimate with the analytically derived standard error uing the ci command.
ci write Variable | Obs Mean Std. Err. [95% Conf. Interval] ---------+------------------------------------------------------------- write | 200 52.775 .6702372 51.45332 54.09668 bs "summarize write" "r(mean)", reps(400) command: summarize write statistic: r(mean) (obs=200) Bootstrap statistics Variable | Reps Observed Bias Std. Err. [95% Conf. Interval] ---------+------------------------------------------------------------------- bs1 | 400 52.775 -.0054515 .6444644 51.50803 54.04197 (N) | 51.49 53.9525 (P) | 51.485 53.945 (BC) ----------------------------------------------------------------------------- N = normal, P = percentile, BC = bias-corrected
One last time, let's find the standard error of the coefficient of variation.
bs "summarize write" "r(sd)/r(mean)*100", reps(400)
Bootstrapping 30/01/2002
http://www.ats.ucla.edu/stat/stata/stat130/bootstrap.htm... Page 1 sur 2
command: summarize write statistic: r(sd)/r(mean)*100 (obs=200) Bootstrap statistics Variable | Reps Observed Bias Std. Err. [95% Conf. Interval] ---------+------------------------------------------------------------------- bs1 | 400 17.96037 -.0649681 .7773613 16.43214 19.48861 (N) | 16.39493 19.3167 (P) | 16.42824 19.375 (BC) ----------------------------------------------------------------------------- N = normal, P = percentile, BC = bias-corrected
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Send your questions/comments/suggestions to Michael Mitchell at [email protected] These pages are Copyrighted (c) by UCLA Academic Technology Services
Please send comments about this site to [email protected]. 08 Jan 2001 15:30
Bootstrapping 30/01/2002
http://www.ats.ucla.edu/stat/stata/stat130/bootstrap.htm... Page 2 sur 2