170 citations · 909 across the 66 of their papers we have counts for
6 papers · 1 filter
Testing goodness-of-fit for logistic regression
Mark Tygert, Rachel Ward
Explicitly accounting for all applicable independent variables, even when the model being tested does not, is critical in testing goodness-of-fit for logistic regression. This can…
Significance testing without truth
William Perkins, Mark Tygert, Rachel Ward
A popular approach to significance testing proposes to decide whether the given hypothesized statistical model is likely to be true (or false). Statistical decision theory provides…
Testing Hardy-Weinberg equilibrium with a simple root-mean-square statistic
Rachel Ward, Raymond J. Carroll
We provide evidence that a root-mean-square test of goodness-of-fit can be significantly more powerful than state-of-the-art exact tests in detecting deviations from Hardy-Weinberg…
A comparison of the discrete Kolmogorov-Smirnov statistic and the Euclidean distance
Jacob Carruth, Mark Tygert, Rachel Ward
Goodness-of-fit tests gauge whether a given set of observations is consistent (up to expected random fluctuations) with arising as independent and identically distributed (i.i.d.)…
An introduction to how chi-square and classical exact tests often wildly misreport significance and how the remedy lies in computers
William Perkins, Mark Tygert, Rachel Ward
Goodness-of-fit tests based on the Euclidean distance often outperform chi-square and other classical tests (including the standard exact tests) by at least an order of magnitude w…
Chi-square and classical exact tests often wildly misreport significance; the remedy lies in computers
William Perkins, Mark Tygert, Rachel Ward
If a discrete probability distribution in a model being tested for goodness-of-fit is not close to uniform, then forming the Pearson chi-square statistic can involve division by ne…