A New Nonparametric Approach to the Comparison of K Independent Samples of Response Curves II: A K Sample Generalization of the FRIEDMAN Test

A K sample generalization of the FRIEDMAN test (1937) is introduced which can be used as a nonparametric procedure for testing the homogeneity of the profiles of K independent samples of response curves measured at T identical points of time. While a similar procedure in LEHMACHER & WALL (1978), section 3, is based on T combined tests, each of them at level a/T, here a finite and asymptotic test is presented which is based on a single test statistic. The application of the new multivariate test is illustrated by the same numerical example as in LEHMACHER & WALL (1978). The properties of this test are discussed and compared with the combined test mentioned above.     

The Matched Pairs Problem with Exponential Variates

Two classes of tests for the hypothesis of bivariate symmetry are studied. For paired exponential survival times (t_1j, t_2j), the classes of tests are those based on t_1j-t_2j and those based on log t_1j–log t_2j. For each class the sign, signed ranks, t and likelihood ratio tests are compared via Pitman's criterion of asymptotic relative efficiency (ARE). For tests based on t_1j — t_2j, it is found that: (1) the efficacy of the paired t depends on the coefficient of variation (CV) of the pair means, (2) the signed rank test has the same ARE to the sign test as for the usual location problem. For tests based on log t_1j — log t_2j, the ARE comparisons reduce to the well-known results for the one-sample location problem for samples from a logistic density. Hence, the signed rank test is asymptotically efficient. Furthermore, analyses based on log t_1j — log t_2j are not complicated by the underlying pairing mechanism.     

Bivariate Sign Tests Sensitive to Homeo- and Heteropoetic Treatment Effects

Starting from N paired differences of a continuous variable, BENNETT 's (1962) bivariate sign test is identified as a test against so called homeopoetic treatment effects (or location shifts in one or both variables X and Y). As a complement, a new sign test is identified to be sensitive to so called heteropoetic treatment effects (shifts in dispersion). Both tests are shown to be important in biomedical and psychosocial research. A numerical example is given from psychopharmacology using the new bivariate sign test.     

Testing the Intraclass Version of Kappa Coeffcient of Agreement with Binary Scale and Sample Size Determination

The intraclass version of kappa coefficient has been commonly applied as a measure of agreement for two ratings per subject with binary outcome in reliability studies. We present an efficient statistic for testing the strength of kappa agreement using likelihood scores, and derive asymptotic power and sample size formula. Exact evaluation shows that the score test is generally conservative and more powerful than a method based on a chi‐square goodness‐of‐fit statistic (Donner and Eliasziw , 1992, Statistics in Medicine 11 , 1511–1519). In particular, when the research question is one directional, the one‐sided score test is substantially more powerful and the reduction in sample size is appreciable.     

A New Nonparametric Approach to the Comparison of K Independent Samples of Response Curves

Two simultaneous distribution free test procedures to test the homogeneity of K samples of response curves measured at T points of time each are proposed which react upon the shape of the response curve. One procedure is based on the comparison of K T-tupels of FRIEDMAN-rank sums, the other on the comparison of K T × T-incidence tables, which first were introduced by KANNEMANN (1976). The application of the two procedures is illustrated by a numerical example. In the discussion the tests are compared with each other and with concurring tests.     

An Exact Paired Rank Test

An exact rank test for two dependent samples based on overall mid‐ranks is discussed which can be applied to metric as well as to ordinal data. The exact conditional distribution of the test statistic given the observed vector of rank differences is determined. A recursion formula is given as well as a fast shift algorithm in SAS/IML code. Moreover, it is demonstrated that the paired rank test can be more powerful than other tests for paired samples by means of a simulation study. Finally, the test is applied to a psychiatric trial with longitudinal ordinal data.     

UMP(U)‐Tests for a Binomial Parameter: A Paradox

We consider uniformly most powerful (UMP) as well as uniformly most powerful unbiased (UMPU) tests and their non‐randomized versions for certain hypotheses concerning a binomial parameter. It will be shown that the power function of a UMP(U)‐test based on sample size n can coincide on the entire parameter space with the power function of the corresponding test based on sample size n + 1. A complete characterization of this paradox will be derived. Apart some exceptional cases for two‐sided tests and equivalence tests the paradox appears if and only if a test based on sample size n is non‐randomized.     

Distribution-free simultaneous tests for location–scale and Lehmann alternative in two-sample problem

The paper deals with the classical two-sample testing problem for the equality of two populations, one of the most fundamental problems in biomedical experiments and case–control studies. The most familiar alternatives are the difference in location parameters or the difference in scale parameters or in both the parameters of the population density. All the tests designed for classical location or scale or location–scale alternatives assume that there is no change in the shape of the distribution. Some authors also consider the Lehmann-type alternative that addresses the change in shape. Two-sample tests under Lehmann alternative assume that the location and scale parameters are invariant. In real life, when a shift in the distribution occurs, one or more of the location, scale, and shape parameters may change simultaneously. We refer to change of one or more of the three parameters as a versatile alternative. Noting the dearth of literature for the equality two populations against such versatile alternative, we introduce two distribution-free tests based on the Euclidean and Mahalanobis distance. We obtain the asymptotic distributions of the two test statistics and study asymptotic power. We also discuss approximating p-values of the proposed tests in real applications with small samples. We compare the power performance of the two tests with several popular existing distribution-free tests against various fixed alternatives using Monte Carlo. We provide two illustrations based on biomedical experiments. Unlike existing tests which are suitable only in certain situations, proposed tests offer very good power in almost all types of shifts.     

High sensitivity of both sequencing and real‐time PCR analysis of KRAS mutations in colorectal cancer tissue

The KRAS mutation status predicts the outcome of treatment with epidermal growth factor receptor targeted agents, and therefore the testing for KRAS mutations has become an important diagnostic procedure. To optimize the quality of this test, we compared the results of the two most commonly used KRAS mutation tests, cycle sequencing and a real‐time PCR‐based assay, in DNA extracted from formalin‐fixed paraffin‐embedded (FFPE) colorectal cancer samples of 511 patients. The results were interpreted in the context of the tumour cell percentage and the assay parameters. In 510 samples KRAS mutation status assessment was successful. A KRAS mutation was detected in 201 tumours (39.4%). Sequencing and the real‐time PCR‐based assay generated the same result in 486 samples (95.3%). The sequencing result was considered false positive in one (0.2%) and false negative in nine samples (1.8%). The assay result was considered false positive in six (1.2%) and false negative in seven samples (1.4%). Explanations for discrepant test results were a higher sensitivity of the assay in samples with a low tumour cell percentage, occurrence of mutations that are not covered by the assay and δ Ct values approximating the cut‐off value of the assay. In conclusion, both sequencing and the real‐time PCR‐based assay are reliable tests for KRAS mutation analysis in FFPE colorectal cancer samples, with a sensitivity of 95.5% (95% confidence interval [CI] 91.7–97.9%) and 96.5% (95% CI 93.0–98.6%), respectively. The real‐time PCR based assay is the method of choice in samples with a tumour cell percentage below 30%.     

Order‐restricted Scores Test for the Evaluation of Population‐based Case–control Studies when the Genetic Model is Unknown

The Cochran–Armitage (CA) linear trend test for proportions is often used for genotype‐based analysis of candidate gene association. Depending on the underlying genetic mode of inheritance, the use of model‐specific scores maximises the power. Commonly, the underlying genetic model, i.e. additive, dominant or recessive mode of inheritance, is a priori unknown. Association studies are commonly analysed using permutation tests, where both inference and identification of the underlying mode of inheritance are important. Especially interesting are tests for case–control studies, defined by a maximum over a series of standardised CA tests, because such a procedure has power under all three genetic models. We reformulate the test problem and propose a conditional maximum test of scores‐specific linear‐by‐linear association tests. For maximum‐type, sum and quadratic test statistics the asymptotic expectation and covariance can be derived in a closed form and the limiting distribution is known. Both the limiting distribution and approximations of the exact conditional distribution can easily be computed using standard software packages. In addition to these technical advances, we extend the area of application to stratified designs, studies involving more than two groups and the simultaneous analysis of multiple loci by means of multiplicity‐adjusted p‐values for the underlying multiple CA trend tests. The new test is applied to reanalyse a study investigating genetic components of different subtypes of psoriasis. A new and flexible inference tool for association studies is available both theoretically as well as practically since already available software packages can be easily used to implement the suggested test procedures.     

Tests for profile analysis of paired curves based on friedman ranking methods

Two nonparametric tests are proposed for the comparison of a paired sample of response curves with T congruent time points. The first procedure rank transforms each curve and tests the homogeneity of the resulting pair of averaged rank vectors. The second procedure rank transforms each pair of curves and tests the homogeneity of the related pair of averaged rank vectors. The first test detects only pure interactions; the second test checks if any difference exists between the rank curves. Both tests are presented in finite and asymptotic as well as in combined (by T singular tests) and multivariate form.     

Sequentially Rejective Test Procedures for Detecting Outlying Cells in One- and Two-Sample Multinomial Experiments

For multiple testing of multinomial models in the case of one or two samples we propose using test procedures based on the principle described by MARCUS, PERITZ and GABRIEL (1976). These methods are based in each step of the sequentially rejective strategy on tests which exhaust the full α level (i.e. which are not conservative). The tests can be performed in a finite or asymptotic version.     

Tests for Monotonic Trend from Case‐Control Data: Cochran‐Armitage‐Mantel Trend Test,Isotonic Regression and Single and Multiple Contrast Tests

Tests for a monotonic trend between an ordered categorical exposure and disease status are routinely carried out from case‐control data using the Mantel‐extension trend test or the asymptotically equivalent Cochran‐Armitage test. In this study, we considered two alternative tests based on isotonic regression, namely an order‐restricted likelihood ratio test and an isotonic modification of the Mantel‐extension test extending the recent proposal by Mancuso, Ahn and Chen (2001) to case‐control data. Furthermore, we considered three tests based on contrasts, namely a single contrast (SC) test based on Schaafsma's coefficients, the Dosemeci and Benichou (DB) test, a multiple contrast (MC) test based on the Helmert, reverse‐Helmert and linear contrasts and we derived their case‐control versions. Using simulations, we compared the statistical properties of these five alternative tests to those of the Mantel‐extension test under various patterns including no relationship, as well as monotonic and non‐monotonic relationships between exposure and disease status. In the case of no relationship, all tests had close to nominal type I error except in situations combining a very unbalanced exposure distribution and small sample size, where the asymptotic versions of the three tests based on contrasts were highly anticonservative. The use of bootstrap instead of asymptotic versions corrected this anticonservatism. For monotonic patterns, all tests had close powers. For non monotonic patterns, the DB‐test showed the most favourable results as it was the least powerful test. The two tests based on isotonic regression were the most powerful tests and the Mantel‐extension test, the SC‐ and MC‐tests had in‐between powers. The six tests were applied to data from a case‐control study investigating the relationship between alcohol consumption and risk of laryngeal cancer in Turkey. In situations with no evidence of a monotonic relationship between exposure and disease status, the three tests based on contrasts did not conclude in favour of a significant trend whereas all the other tests did. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

A sampling study of the size and power of tests for paired survival data

The paired-t, sign, and signed rank tests were compared for samples from a bivariate exponential distribution. Each is a valid α-level test. One test was not uniformly more powerful than the others for all sample sizes, α levels, correlations, and alternative hypotheses considered, but the signed rank test did well consistently. It was always preferable to the sign test and never was appreciably worse than the paired-t test. The relative performance of the tests depends on α as well as the sample size.     

Multivariate extensions of McNemar's test

This article considers global tests of differences between paired vectors of binomial probabilities, based on data from two dependent multivariate binary samples. Difference is defined as either an inhomogeneity in the marginal distributions or asymmetry in the joint distribution. For detecting the first type of difference, we propose a multivariate extension of McNemar's test and show that it is a generalized score test under a generalized estimating equations (GEE) approach. Univariate features such as the relationship between the Wald and score tests and the dropout of pairs with the same response carry over to the multivariate case and the test does not depend on the working correlation assumption among the components of the multivariate response. For sparse or imbalanced data, such as occurs when the number of variables is large or the proportions are close to zero, the test is best implemented using a bootstrap, and if this is computationally too complex, a permutation distribution. We apply the test to safety data for a drug, in which two doses are evaluated by comparing multiple responses by the same subjects to each one of them.     

TESTING FOR PHYLOGENETIC SIGNAL IN BIOLOGICAL TRAITS: THE UBIQUITY OF CROSS‐PRODUCT STATISTICS

To evaluate rates of evolution, to establish tests of correlation between two traits, or to investigate to what degree the phylogeny of a species assemblage is predictive of a trait value so‐called tests for phylogenetic signal are used. Being based on different approaches, these tests are generally thought to possess quite different statistical performances. In this article, we show that the Blomberg et al. K and K*, the Abouheif index, the Moran's I, and the Mantel correlation are all based on a cross‐product statistic, and are thus all related to each other when they are associated to a permutation test of phylogenetic signal. What changes is only the way phylogenetic and trait similarities (or dissimilarities) among the tips of a phylogeny are computed. The definitions of the phylogenetic and trait‐based (dis)similarities among tips thus determines the performance of the tests. We shortly discuss the biological and statistical consequences (in terms of power and type I error of the tests) of the observed relatedness among the statistics that allow tests for phylogenetic signal. Blomberg et al. K* statistic appears as one on the most efficient approaches to test for phylogenetic signal. When branch lengths are not available or not accurate, Abouheif's C_mean statistic is a powerful alternative to K*.     

Unconditional Confidence Interval for the Difference between Two Proportions

In applied statistics it is customary to have to obtain a one‐ or two‐tail confidence interval for the difference d = p₂ – p₁ between two independent binomial proportions. Traditionally, one is looking for a classic and non‐symmetric interval (with respect to zero) of the type d ∈ [δ_L;δ_U], d ≤ δ₀ or d ≥ δ₀. However, in clinical trials, equivalence studies, vaccination efficacy studies, etc., and even after performing the classic homogeneity test, intervals of the type |d| ≤ Δ₀ or |d| ≥ Δ₀, where Δ₀ > 0, may be necessary. In all these cases it is advisable to obtain the interval by inverting the appropriate test. The advantage of this procedure is that the conclusions obtained using the test are compatible with those obtained using the interval. The article shows how this is done using the new exact and asymptotic unconditional tests published. The programs for performing these tests may be obtained at URL http://www.ugr.es/~bioest/software.htm.     

Asymptotical Tests on the Equivalence,Substantial Difference and Non‐inferiority Problems with Two Proportions

Let d = p₂ ? p₁ be the difference between two binomial proportions obtained from two independent trials. For parameter d, three pairs of hypothesis may be of interest: H₁: d ≤ δ vs. K₁: d > δ; H₂: d ? (δ₁, δ₂) vs. K₂: d ∈ (δ₁, δ₂); and H₃: d ∈ [δ₁, δ₂] vs. K₃: d ? [δ₁, δ₂], where H_i is the null hypothesis and K_i is the alternative hypothesis. These tests are useful in clinical trials, pharmacological and vaccine studies and in statistics generally. The three problems may be investigated by exact unconditional tests when the sample sizes are moderate. Otherwise, one should use approximate (or asymptotical) tests generally based on a Z‐statistics like those suggested in the paper. The article defines a new procedure for testing H₂ or H₃, demonstrates that this is more powerful than tests based on confidence intervals (the classic TOST – two one sided tests – test), defines two corrections for continuity which reduce the liberality of the three tests, and selects the one that behaves better. The programs for executing the unconditional exact and asymptotic tests described in the paper can be loaded at http://www.ugr.es/~bioest/software.htm. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

The Relationship Between Two Statistical Tests for the Comparison of Two Exponential Distributions

To compare two exponential distributions with or without censoring, two different statistics are often used; one is the F test proposed by COX (1953) and the other is based on the efficient score procedure. In this paper, the relationship between these tests is investigated and it is shown that the efficient score test is a large-sample approximation of the F test.     

Stereoselective pharmacokinetics of stable isotope (+/−)‐[13C]‐pantoprazole: Implications for a rapid screening phenotype test of CYP2C19 activity

Aims: We have previously shown that the (±)‐[¹³C]‐pantoprazole breath test is a promising noninvasive probe of CYP2C19 activity. As part of that trial, plasma, breath test indices and CYP2C19 (*2, *3, and *17) genotype were collected. Here, we examined whether [¹³C]‐pantoprazole exhibits enantioselective pharmacokinetics and whether this enantioselectivity is correlated with indices of breath test. Methods: Plasma (−)‐ and (+)‐[¹³C]‐pantoprazole that were measured using a chiral HPLC were compared between CYP2C19 genotypes and correlated with breath test indices. Results: The AUC_(0‐∞) of (+)‐[¹³C]‐pantoprazole in PM (*2/*2, n = 4) was 10.1‐ and 5.6‐fold higher that EM (*1/*1or *17, n = 10) and IM (*1/*2or *3, n = 10) of CYP2C19, respectively (P < 0.001). The AUC_(0‐∞) of (−)‐[¹³C]‐pantoprazole only significantly differed between PMs and EMs (1.98‐fold; P = 0.05). The AUC_(0‐∞) ratio of (+)‐/(−)‐[¹³C]‐pantoprazole was 3.45, 0.77, and 0.67 in PM, IM, and EM genotypes, respectively. Breath test index, delta over baseline show significant correlation with AUC_(0‐∞) of (+)‐[¹³C]‐pantoprazole (Pearson's r = 0.62; P < 0.001). Conclusions: [¹³C]‐pantoprazole exhibits enantioselective elimination. (+)‐[¹³C]‐pantoprazole is more dependent on CYP2C19 metabolic status and may serve as a more attractive probe of CYP2C19 activity than (−)‐[¹³C]‐pantoprazole or the racemic mixture. Chirality, 2011. © 2011 Wiley‐Liss, Inc.