Implements Bayesian methods, described in Hugh-Jones (2019) <doi:10.1007/s40881-019-00069-x>, for estimating the proportion of liars in coin flip-style experiments, where subjects report a random outcome and are paid for reporting a "good" outcome.
To estimate the proportion of liars in an experiment, use
To get confidence intervals for an estimate, use
dist_hdr(posterior, conf_level = 0.95)
To test whether two different samples have the same proportion of
difference_dist() followed by
1 2 3
To test power for detecting a given proportion of liars, use
power_calc(N = 100, P = 0.5, lambda = 0.2)
To test power for detecting differences between groups, use
power_calc_difference(N1 = 100, P = 5/6, lambda1 = 0.1, lambda2 = 0.25)
To compare different samples by empirical Bayes estimation, use
1 2 3
To run tests on the package:
You will need dplyr, purrr, tidyr and ggplot2 installed.
This will take some time and will produce data frames of test results for different parameter values, along with some plots.
Hugh-Jones, David (2019). True Lies: Comment on Garbarino, Slonim and Villeval (2018). Journal of the Economic Science Association. https://link.springer.com/article/10.1007/s40881-019-00069-x.
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