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Taxon sampling has been shown to affect the performance of statistical tests of trait associations [53].
In this article, we compare the performance of statistical tests assuming simple binomial variation, Williams' extra-binomial variation and our modified extra-binomial model using quantile quantile (Q Q) plots.
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The number of trials included in our review was small, precluding the construction of meaningful funnel plots and the performance of statistical testing for publication bias, and this may be a limitation of our review.
Romualdi et al. (2001) investigated the performance of a number of statistical tests when applied to multi-library comparisons with one and two outliers (i.e. genes simulated as differentially expressed in either one or two libraries), and assessed the performance by studying the percentage of false negatives (rather than true positives, as in our study).
The CSEP Testing Center software implements a number of statistical tests for model performance.
Additionally, the TSM statistic based on Wald test (WTSM) (implemented by PLINK [40]) was also calculated, and compared with FTSM to investigate potential impact of statistical tests on the performance of TSM-based MLAS.
Analyzing tables of statistical tests.
That's crucial for many kinds of statistical tests.
Some trends were observed, but of little significance and might result from the performance of multiple statistical tests.
To assess the performance of our statistical tests, a human Affymetrix microarray dataset corresponding to 47 subjects with acute lymphoblastic leukaemia (ALL) and 25 subjects with acute myeloid leukaemia (AML), as previously described by Golub and colleagues [5], was downloaded from: http://wwwmaths.anu.edu.au/johnm/r/hddplot/.anu.edu.au/johnm/r/hddplot/
Recently, Basu and Pan [ 24] compared the performance of multiple statistical tests to identify an association with rare variants.
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CEO of Professional Science Editing for Scientists @ prosciediting.com