How to use bootstrap techniques to criticise a linear model?

I have two sets of data to which I have fitted a simple linear model to. How would I use bootstrap techniques using both methods for bootstrapping a regression model (i.e. bootstrap based on residuals & pair bootstrap) to criticise this linear model?

  • You definitely want to increase the bounty for this question.

    • I second that!

    • Ahh. I’m bad at examining how much I should offer for a question. I have used R to generate bootstrap statistics - I’m just not sure how I’m supposed to use original/bias/standard error, or if there is anything else I am supposed to be doing, to criticise the linear model. If you (or anyone else) can offer a very simple explanation or even a link to a book/website which I can read to understand what I’m supposed to be doing, will be an acceptable answer for this question.

    • To decide what a good offer is, think about how much time one may need to spend to write a good solution to your problem, and what a fair hourly rate for such skilled individual is. That would give you a pretty good idea.

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  • Yes, this is clear and easy for me to understand. Thank you again Kav for helping me with my statistics struggles :)

  • Of course! I am glad you liked it.

The answer is accepted.