Bootstrapping and p-values (t-test when using bootci)

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Kilin
Kilin il 4 Feb 2016
Risposto: John Williams il 15 Ott 2018
Hello,
I have to report some results from random experiments, and I need to report confidence intervals and p-values as well. I am not very familiar with statistics, so I hope you can help me with this.
Given that I can't assume that my distribution is normally distributed, and that I don't have many samples, I've been suggested to adopt a bootstrapping method.
RESAMPLING_SIZE = 10000;
CI = bootci(RESAMPLING_SIZE, {@mean, myData});
I then plot mean(myData) along with CI.
First question: Is it correct to plot mean(myData), or I should plot an overal mean as estimated by the bootstrapping method?
Second question: say I want to compare results from two different experiments, and I have already applied bootstrapping on the two sets of data. How to compute p-values? Can I use ttest or ttest2 in combination with bootci?
Thank you very much
Best regards

Risposte (1)

John Williams
John Williams il 15 Ott 2018
While this post is 2 years old, just in case it helps someone - here is some code that can compute bootstrap CIs and P values based on some precomputed resample and leave one out statistics.
https://www.mathworks.com/matlabcentral/fileexchange/69119-bca_bootstrap
The methods are described in the eAppendix of this paper:
https://www.ncbi.nlm.nih.gov/pubmed/19581566

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