OECD Discriminatory family code data analysis 4 - Bootstrap method for getting Confidence Interval with R

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This post is following of above post.
In the previous post, I get Confidence Interval using standard error.

In this post, I will get Confidence Interval using Bootstrap method.

Bootstrap method is to draw random samples many times and calclates sample averages and get quantile value.

Let's start with "atwm"; Attitudes Towards Working Mothers.

I draw 100,000 samples and calculate average 100,000 times. I use for() loop.

Those 100,000 averages are store in avgs_atwm object.

Let's see a histogram of avgs_atwm.

Vertical red line is an average of avgs_atwm.

Then, I use quantile() function to get 2.5% quantile and 97.5% quantile values.

Bootstrap confidence interval is 40.76 ~ 49.04 while standard error confidence interval is 40.64 ~ 49.09. The both are quite similar value.

Next, let's do with "em"; Early Marriage.

Make a histogram.

Let's compare Bootstrap Confidence Interval and Standard Error Confidence Interval.

The both CI are quite similar.

That's it. Thank you!

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