Flexible weighted log-rank tests optimal for detecting early and/or late survival differences

At the present time, many AIDS clinical trials compare drug therapies by a time-to-event primary endpoint that measures the durability of suppression of HIV replication. For such studies, survival differences tend to occur early and/or late in the follow-up period due to drug differences in initial potency and/or durability of efficacy, and detecting these differences is of primary interest. We propose a weighted log-rank statistic that emphasizes early and/or late survival differences. We also consider some versatile tests that also emphasize these differences but are sensitive to a wider range of alternatives. The performances of the new tests are evaluated in numerical studies. For the alternatives of interest, the new tests show greater power and flexibility than commonly used weighted log-rank tests and related versatile tests. When the main interest is in detecting early and/or late survival differences, these tests may be preferable to the other versatile and weighted log-rank tests that have been studied.     

Taste sensitivities to PROP and PTC vary independently in mice

Mammals use common mechanisms to detect, transduce and process taste stimulus information. For example, they share families of receptors that respond to amino acids, and sweet- and bitter-tasting stimuli. Nonetheless, it also clear that different species exhibit unique taste sensitivities that may reflect specific genetic variations. In humans, sensitivities to the chemically similar, bitter-tasting compounds 6-n-propylthiouracil (PROP) and phenylthiocarbamide (PTC) are heritable and strongly correlated, suggesting a common genetic basis. However, it is unknown whether PROP and PTC taste sensitivities are similarly correlated in mice. Here we report that PROP and PTC taste sensitivities vary independently between two inbred strains of mice. In brief-access taste tests C3HeB/FeJ (C3) and SWR/J (SW) mice possess similar taste sensitivity to PTC, while SW mice are significantly more sensitive to PROP than are C3 mice. In two-bottle preference tests, however, SW mice display greater aversion to both compounds. This discrepancy may be explained by the observation that SW mice consumed taste solutions at a greater rate during the intake test than did C3 mice. Therefore, PTC avoidance is correlated with the amount of PTC consumed in the intake tests rather than the concentration of PTC tested. These findings suggest that post-ingestive factors play a significant role in PTC avoidance during intake tests and highlight an important advantage of brief-access tests over intake tests in resolving the gustatory and post-ingestive contributions to taste-related behaviors. Most strikingly, these results demonstrate that in mice, unlike in humans, PTC and PROP taste sensitivities vary independently, thereby suggesting a subtle functional diversity of bitter-taste mechanisms across mammalian species.     

Analysis of Randomized Dose-Finding-Studies: Closure Test Modifications Based on Multiple Contrast Tests

The power of single contrast tests strongly depends on the a priori unknown shape of the dose response relationship. Two approaches can be used to overcome this major disadvantage: the likelihood ratio test for order restriction or multiple contrast tests. Within the closure principle, the shape for the different hyptheses varies. Therefore multiple contrast tests are used as trend tests. Based on a simulation study the power advantage of this approach in comparison with single contrast tests is demonstrated.     

UMPU and Alternative Tests for Association in 2 × 2 Tables

The use of the uniformly most powerful among the unbiased (UMPU) test was recently suggested for the study of gametic association between two polymorphic loci as an alternative to the Fisher's exact test (Zapata and Alvarez, 1997, Annals of Human Genetics 61, 71-77). However, the proposed test is not UMPU for two-sided alternatives. In this study, we present the UMPU test, discuss criticisms against the use of randomized tests, and compare the power of several tests. We show that, in many practical cases, the use of the UMPU test is less than desirable and propose the alternative adjusted-more extreme tables (A-MET) and the equal-tails (ET) tests. We suggest that some of the general arguments against the use of randomized tests can be alleviated by a newly proposed extended p-value definition.     

Adjusting O'Brien's test to control type I error for the generalized nonparametric Behrens-Fisher problem

O'Brien (1984, Biometrics 40, 1079-1087) introduced a simple nonparametric test procedure for testing whether multiple outcomes in one treatment group have consistently larger values than outcomes in the other treatment group. We first explore the theoretical properties of O'Brien's test. We then extend it to the general nonparametric Behrens-Fisher hypothesis problem when no assumption is made regarding the shape of the distributions. We provide conditions when O'Brien's test controls its error probability asymptotically and when it fails. We also provide adjusted tests when the conditions do not hold. Throughout this article, we do not assume that all outcomes are continuous. Simulations are performed to compare the adjusted tests to O'Brien's test. The difference is also illustrated using data from a Parkinson's disease clinical trial.     

Is the Exact Test Better than the Asymptotic Test for Testing Marginal Homogeneity in 2 × 2 Tables?

McNemar test is commonly used to test for the marginal homogeneity in 2 × 2 contingency tables. McNemar test is an asymptotic test based either on standard normal distribution or on the chi‐square distribution. When the total sample size is small, an exact version of McNemar test is available based on the binomial probabilities. The example in the paper came from a clinical study to investigate the effect of epidermal growth factor for children who had microvillus inclusion diseases. There were only six observations available. The test results differ between the exact test and the asymptotic test. It is a common belief that with this small sample size the exact test be used. However, we claim that McNemar test performs better than the exact test even when the sample size is small. In order to investigate the performances of McNemar test and the exact test, we identify the parameters that affect the test results and then perform sensitivity analysis. In addition, through Monte Carlo simulation studies we compare the empirical sizes and powers of these tests as well as other asymptotic tests such as Wald test and the likelihood ratio test.     

The use of score tests for inference on variance components

Whenever inference for variance components is required, the choice between one-sided and two-sided tests is crucial. This choice is usually driven by whether or not negative variance components are permitted. For two-sided tests, classical inferential procedures can be followed, based on likelihood ratios, score statistics, or Wald statistics. For one-sided tests, however, one-sided test statistics need to be developed, and their null distribution derived. While this has received considerable attention in the context of the likelihood ratio test, there appears to be much confusion about the related problem for the score test. The aim of this paper is to illustrate that classical (two-sided) score test statistics, frequently advocated in practice, cannot be used in this context, but that well-chosen one-sided counterparts could be used instead. The relation with likelihood ratio tests will be established, and all results are illustrated in an analysis of continuous longitudinal data using linear mixed models.     

A class of permutation tests for stratified survival data

We propose a class of permutation tests for stratified survival data. The tests are derived using the framework of Fay and Shih (1998, Journal of the American Statistical Association 93, 387-396), which creates tests by permuting scores based on a functional of estimated distribution functions. Here the estimated distribution function for each possibly right-, left-, or interval-censored observation is based on a shrinkage estimator similar to the nonparametric empirical estimator of Ghosh, Lahiri, and Tiwari (1989, Communications in Statistics--Theory and Methods 18, 121-146), and permutation is carried out within strata. The proposed test with a weighted Mann-Whitney functional is similar to the permutation form of the stratified log-rank test when there is a large strata effect or the sample size in each stratum is large and is similar to the permutation form of the ordinary log-rank test when there is little strata effect. Thus, the proposed test unifies the advantages of both the stratified and ordinary log-rank tests. By changing the functional, we may obtain a stratified Prentice-Wilcoxon test or a difference in means test with similar unifying properties. We show through simulations the advantage of the proposed test over existing tests for uncensored and right-censored data.     

Wald Tests of Location for Symmetric Nonnormal Data

For nonnormal data we suggest a test of location based on a broader family of distributions than normality. Such a test will in a sense fall between the standard parametric and non parametric tests. We see that the Wald tests based on this family of distributions have some advantages over the score tests and that they perform well in comparison to standard parametric and nonparametric tests in a variety of situations. We also consider when and how to apply such tests in practice.     

Trend Test for Overdispersed Proportions

The Cochran-Armitage test has commonly been used for a trend test in binomial proportions. The quasi-likelihood method provides a simple approach to model extra-binomial proportions. Two versions of the score and Wald tests using different parameterizations for the extra-binomial variance were investigated: one in terms of intercluster correlation, and another in terms of variance. The Monte Carlo simulation was used to evaluate the performance of the each version of the score test and the Wald test, and the Cochran-Armitage test. The simulation shows that the Cochran-Armitage test has the proper size only for the binomial sample data, and the test is no longer valid when applied to the extra-binomial data. The Wald test is more likely to exceed the nominal level than the score test under either intercluster correlation model or variance model. Both score tests performed very well even with the binomial data; the tests control the type I error and in the meantime maintain the power of detecting the dose effects. Based on the design considered in this paper, the two scores test are comparable. The score test based on the intercluster correlations model seems better controlling the Type I error but appears less powerful than that based on the variance model. An example from a developmental toxicity experiment is given.     

Comparing Trials with Multiple Outcomes: The Multivariate One-Sided Hypothesis with Unknown Covariances

The paper deals with a problem arising for tests in clinical trials. The outcomes of a standard and a new treatment to be compared are multivariate normally distributed with common but unknown covariance matrix. Under the null hypothesis the means of the outcomes are equal, under the alternative the new treatment is assumed to be superior, i.e. the means are larger without further quantification. For known covariance matrix there is a variety of tests for this problem. Some of these procedures can be extended to the case of unknown covariances if one is willing to accept a bias. There is, however, also an efficient unbiased test. The paper contains some numerical comparisons of these different procedures and takes a look on the minimax properties of the unbiased test.     

A Comparison of the Three Conditional Exact Tests in Two‐way Contingency Tables Using the Unconditional Exact Power

The conditional exact tests of homogeneity of two binomial proportions are often used in small samples, because the exact tests guarantee to keep the size under the nominal level. The Fisher's exact test, the exact chi‐squared test and the exact likelihood ratio test are popular and can be implemented in software StatXact. In this paper we investigate which test is the best in small samples in terms of the unconditional exact power. In equal sample cases it is proved that the three tests produce the same unconditional exact power. A symmetry of the unconditional exact power is also found. In unequal sample cases the unconditional exact powers of the three tests are computed and compared. In most cases the Fisher's exact test turns out to be best, but we characterize some cases in which the exact likelihood ratio test has the highest unconditional exact power. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Smooth tests for the zero-inflated poisson distribution

In this article we construct three smooth goodness-of-fit tests for testing for the zero-inflated Poisson (ZIP) distribution against general smooth alternatives in the sense of Neyman. We apply our tests to a data set previously claimed to be ZIP distributed, and show that the ZIP is not a good model to describe the data. At rejection of the null hypothesis of ZIP, the individual components of the test statistic, which are directly related to interpretable parameters in a smooth model, may be used to gain insight into an alternative distribution.     

Review: Diagnosis of Helicobacter pylori infection

New imaging techniques are still the topic of many evaluations for both the diagnosis of Helicobacter pylori gastritis and the detection of early gastric cancer. Concerning invasive tests, there were studies on the reuse of the rapid urease test material for other tests, and a novel fluorescent method to be used for histology but with limited sensitivity. Progress occurred essentially in the molecular methods area, especially next‐generation sequencing which is applied to detect both H pylori and the mutations associated with antibiotic resistance. For non‐invasive tests, a few studies have been published on the validity of breath collection bags, the shortening of the testing time, the performance of different analysers or the added value of citric acid in the protocol. The accuracy of serological immunochromatographic tests is also improving. Multiplex serology detecting antibodies to certain proteins allows confirmation of a current infection. Dried blood spots can be used to collect and store blood without a loss of accuracy. Finally, the serum antibody titer can be useful in predicting the risk of gastric cancer. Several stool antigen tests were evaluated with good results, and a novel test using immunomagnetic beads coated with monoclonal antibodies is potentially interesting. PCR detection in stools can also be effective but needs an efficient DNA extraction method. The use of easyMAG^® (bioMérieux) combined with Amplidiag® H pylori + ClariR (Mobidiag) appears to be powerful.     

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*.     

A Powerful and Adaptive Association Test for Rare Variants

This article focuses on conducting global testing for association between a binary trait and a set of rare variants (RVs), although its application can be much broader to other types of traits, common variants (CVs), and gene set or pathway analysis. We show that many of the existing tests have deteriorating performance in the presence of many nonassociated RVs: their power can dramatically drop as the proportion of nonassociated RVs in the group to be tested increases. We propose a class of so-called sum of powered score (SPU) tests, each of which is based on the score vector from a general regression model and hence can deal with different types of traits and adjust for covariates, e.g., principal components accounting for population stratification. The SPU tests generalize the sum test, a representative burden test based on pooling or collapsing genotypes of RVs, and a sum of squared score (SSU) test that is closely related to several other powerful variance component tests; a previous study (Basu and Pan 2011) has demonstrated good performance of one, but not both, of the Sum and SSU tests in many situations. The SPU tests are versatile in the sense that one of them is often powerful, although its identity varies with the unknown true association parameters. We propose an adaptive SPU (aSPU) test to approximate the most powerful SPU test for a given scenario, consequently maintaining high power and being highly adaptive across various scenarios. We conducted extensive simulations to show superior performance of the aSPU test over several state-of-the-art association tests in the presence of many nonassociated RVs. Finally we applied the SPU and aSPU tests to the GAW17 mini-exome sequence data to compare its practical performance with some existing tests, demonstrating their potential usefulness.     

抗菌整理织物的抗菌效力测试

本文对大连印染厂试产的X—Si—4有机硅等抗菌整理布进行了抗菌效力检测,显示对细菌具100％的抑菌率,而且有较强皮肤癣菌和污染性霉菌的效力,同时具耐紫外线照射,耐高温高压,耐洗涤等优良性能。试验均达预期效果,表明方法简易,重复性好,结果可信。本文并从菌种的选择,试验方法的配合使用,抗菌整理布的优良性能测试等诸方面进行了探讨。     

Drawbacks to Integer Scoring for Ordered Categorical Data

Linear rank tests are widely used when testing for independence against stochastic order in a 2 x J contingency table with two treatments and J ordered outcome levels. For this purpose, numerical scores are assigned, possibly by default, to the J outcome levels. When the choice of scores is not apparent, integer (equally spaced) scores are often assigned. We show that this practice generally leads to unnecessarily conservative tests. The use of slightly perturbed scores will result in a less conservative and uniformly more powerful test.     

Analysis of Profiles Based on Ordinal Classification Functions and Rank Tests

In this article a test for the comparison of K groups of independent profiles is suggested. It is based on rank tests, in which the criterion is obtained by using a suitably chosen ordinal classification function. This function represents a specific view on the profiles. The test, which is easy to use, can be regarded as a generalisation of other well known tests and can be applied within a variety of situations. The relationships to other procedures for the analysis of profiles are described. Some properties are discussed.     

小鼠脑缺血神经功能障碍行为学评价的研究进展

在脑缺血及脑缺血-再灌注损伤的研究中,小鼠的可逆性大脑中动脉阻塞（middle cerebral artery occlusion,MCAO）模型应用广泛。除了测量脑梗死体积外,神经功能缺损的行为学评价也是判定脑缺血严重程度的重要指标。其评价指标大多移植于大鼠的评价体系,方法较多,没有统一的评价标准,本文对小鼠脑缺血后神经功能损伤的行为学评价方法及各自的优缺点及侧重点做一综述。