Bootstrapping in Psychology I am interested in bootstrap, especially how it's entering the psychologist's world.

Boostrapping is used to 'omit' classical assumptions to get statistics. Bootstrapping starts with creating new samples from an original sample (that is considered as a population). Those new samples are generated via resampling with replacement (so that in a new sample observations can be repeated). Doing this (for example) 1000 times, you can get 1000 new samples and then calculate statistics of interest on each of a new sample. Thus you get 1000 of means (as an example). In the end you can calculate (bootstrapped) confidence interval.

I am looking for papers on bootstrap in social sciences (like this one Wright, D.B, London, K., Field, A.P. (2011) Using Bootstrap Estimation and the Plug-in Principle for Clinical Psychology Data, Journal of Experimental Psychology, DOI: 10.5127/jep.013611), where the authors explain bootstrap technique to psychologists in their subfield or those papers (in social science) where bootstrap is used extensively.

Has anyone has seen, read or known such papers?
When I embarked on using bootstrapping in my research I found this chapter/lecture notes by Cosma Shalizi very useful:


The Bootstrap, 36-402, Advanced Data Analysis, 3 February 2011
http://www.stat.cmu.edu/~cshalizi/402/lectures/08-bootstrap/lecture-08.pdf


I see now that he has also written a short introduction for American Scientist


Shalizi, C. (2010). The bootstrap. American Scientist, 98(3),
186-190. http://www.americanscientist.org/libraries/documents/201048159157846-2010-05Shalizi.pdf


We published this paper, which uses bootstrapping in the third analysis (and so may directly answer your question). 


Stafford, T., &amp; Dewar, M. (2014). Tracing the trajectory of skill learning with a very large sample of online game players. Psychological science, 25(2), 511-518. http://pss.sagepub.com/content/25/2/511.full


Aside from mere egotism on my part, the analysis code for the paper is available, so you can see mechanically how I did it for my analysis (in Python)


https://github.com/tomstafford/axongame