Calculate p-values from a set of observed test statistics and simulated null test statistics
Calculates p-values from a set of observed test statistics and simulated null test statistics
A vector of calculated test statistics.
A vector or matrix of simulated or data-resampled null test statistics.
If FALSE, stat0 must be a matrix with the number of rows equal to
the length of
stat must be such that the larger the value is
the more deviated (i.e., "more extreme") from the null hypothesis it is.
Examples include an F-statistic or the absolute value of a t-statistic. The
stat0 should be calculated analogously on data that
represents observations from the null hypothesis distribution. The p-values
are calculated as the proportion of values from
stat0 that are
greater than or equal to that from
selected, then all of
stat0 is used in calculating the p-value for a
given entry of
pool=FALSE, then it is assumed that
stat0 is a matrix, where
stat0[i,] is used to calculate the
stat[i]. The function
"pooled" p-values faster than using a for-loop.
See page 18 of the Supporting Information in Storey et al. (2005) PNAS (http://www.pnas.org/content/suppl/2005/08/26/0504609102.DC1/04609SuppAppendix.pdf) for an explanation as to why calculating p-values from pooled empirical null statistics and then estimating FDR on these p-values is equivalent to directly thresholding the test statistics themselves and utilizing an analogous FDR estimator.
A vector of p-values calculated as described above.
John D. Storey
Storey JD and Tibshirani R. (2003) Statistical significance for
genome-wide experiments. Proceedings of the National Academy of Sciences,
Storey JD, Xiao W, Leek JT, Tompkins RG, Davis RW. (2005) Significance
analysis of time course microarray experiments. Proceedings of the
National Academy of Sciences, 102 (36), 12837-12842.
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# import data data(hedenfalk) stat <- hedenfalk$stat stat0 <- hedenfalk$stat0 #vector from null distribution # calculate p-values p.pooled <- empPvals(stat=stat, stat0=stat0) p.testspecific <- empPvals(stat=stat, stat0=stat0, pool=FALSE) # compare pooled to test-specific p-values qqplot(p.pooled, p.testspecific); abline(0,1)
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