Fast Permutation Tests that Maximize Power Under Conventional Monte Carlo Sampling for Pairwise and Multiple Comparisons

While the distribution-free nature of permutation tests makes them the most appropriate method for hypothesis testing under a wide range of conditions, their computational demands can be runtime prohibitive, especially if samples are not very small and/or many tests must be conducted (e.g. all pairwise comparisons). This paper presents statistical code that performs continuous-data permutation tests under such conditions very quickly often more than an order of magnitude faster than widely available commercial alternatives when many tests must be performed and some of the sample pairs contain a large sample. Also presented is an efficient method for obtaining a set of permutation samples containing no duplicates, thus maximizing the power of a pairwise permutation test under a conventional Monte Carlo approach with negligible runtime cost (well under 1% when runtimes are greatest). For multiple comparisons, the code is structured to provide an additional speed premium, making permutation-style p-value adjustments practical to use with permutation test p-values (although for relatively few comparisons at a time). No-replacement sampling also provides a power gain for such multiple comparisons, with similarly negligible runtime cost

A Single, Powerful, Nonparametric Statistic for Continuous-data Telecommunications Parity Testing

Since the enactment of the Telecommunications Act of 1996, extensive expert testimony has justified use of the modified t statistic (Brownie et al., 1990) for performing two-sample hypothesis tests comparing Bell companies’ CLEC and ILEC performance measurement data (known as parity testing). However, Opdyke (Telecommunications Policy, 2004) demonstrated this statistic to be potentially manipulable and to have literally zero power to detect inferior CLEC service provision under a wide range of relevant data conditions. This article develops a single, nonparametric statistic that is easily implemented (i.e., not computationally intensive) and typically provides dramatic power gains over the modified t while simultaneously providing much better Type I error control. The statistic should be useful in a wide range of quality control settings

Summary of Schuck v. Signature Flight Support, 126 Nev. Adv. Op. No. 42

An appeal from a district court’s decisions: (1) granting summary judgment against the plaintiff; (2) awarding unpaid fees and costs to plaintiff’s attorneys; and (3) denying plaintiff’s 60(b) motion for relief from judgment