scholarly journals Bias toward the Null Hypothesis in Model-Free Linkage Analysis Is Highly Dependent on the Test Statistic Used

2004 ◽  
Vol 74 (6) ◽  
pp. 1294-1302 ◽  
Author(s):  
Heather J. Cordell
Keyword(s):  
Linkage Analysis ◽  
Null Hypothesis ◽  
Test Statistic ◽  
Model Free

scholarly journals REMAXINT: a two-mode clustering-based method for statistical inference on two-way interaction

2021 ◽  
Author(s):  
Zaheer Ahmed ◽  
Alberto Cassese ◽  
Gerard van Breukelen ◽  
Jan Schepers
Keyword(s):  
Null Hypothesis ◽  
Type I Error ◽  
Type I ◽  
The Novel ◽  
Simulation Studies ◽  
Test Statistic ◽  
Clustering Model ◽  
Novel Method ◽  
Main Effects ◽  
Empirical Case Studies

AbstractWe present a novel method, REMAXINT, that captures the gist of two-way interaction in row by column (i.e., two-mode) data, with one observation per cell. REMAXINT is a probabilistic two-mode clustering model that yields two-mode partitions with maximal interaction between row and column clusters. For estimation of the parameters of REMAXINT, we maximize a conditional classification likelihood in which the random row (or column) main effects are conditioned out. For testing the null hypothesis of no interaction between row and column clusters, we propose a $$max-F$$ m a x - F test statistic and discuss its properties. We develop a Monte Carlo approach to obtain its sampling distribution under the null hypothesis. We evaluate the performance of the method through simulation studies. Specifically, for selected values of data size and (true) numbers of clusters, we obtain critical values of the $$max-F$$ m a x - F statistic, determine empirical Type I error rate of the proposed inferential procedure and study its power to reject the null hypothesis. Next, we show that the novel method is useful in a variety of applications by presenting two empirical case studies and end with some concluding remarks.

An Omnibus Test for Systematic Changes in Judges’ Rankings

1992 ◽  
Vol 17 (1) ◽  
pp. 1-26
Author(s):  
Douglas E. Critchlow ◽  
Joseph S. Verducci
Keyword(s):  
Literary Criticism ◽  
Null Hypothesis ◽  
Statistical Test ◽  
Post Treatment ◽  
Graphical Methods ◽  
Test Results ◽  
Test Statistic ◽  
Omnibus Test ◽  
Null Distributions ◽  
Power Of The Test

Paired rankings arise when each subject in a study independently ranks a set of items, undergoes a treatment, and afterwards ranks the same set of items. For such data, a statistical test is proposed to detect if the subjects’ posttreatment rankings have moved systematically toward some unknown ranking or set of rankings. The null hypothesis for this test is that each subject’s post-treatment ranking is symmetrically distributed about his pretreatment ranking. The exact and asymptotic null distributions of the test statistic are simulated and compared, and the power of the test is studied. Using paired rankings from an experimental course in literary criticism, we also offer some graphical methods for representing such data that help us to interpret the test results.

A Computer Program to Estimate Power and Relative Efficiency of Flexibly Matched Case-control Studies

2005 ◽  
Vol 44 (05) ◽  
pp. 693-696 ◽  
Author(s):  
O. Gefeller ◽  
H. Brenner ◽  
T. Stürmer
Keyword(s):  
Computer Program ◽  
Relative Efficiency ◽  
Odds Ratio ◽  
Null Hypothesis ◽  
Case Control ◽  
Case Control Studies ◽  
Test Statistic ◽  
Matched Case ◽  
Haenszel Test ◽  
Flexible Matching

Summary Objectives: We recently introduced the concept of flexible matching strategies with varying proportions of a dichotomous matching factor among controls to increase power and efficiency of case-control studies. We now present a method and a computer program to calculate power and relative efficiency compared to an unmatched design varying the proportion of the matching factor in controls over all possible values from 0 to 100 percent. Methods: For all these values, the program calculates the expected variance of the combined Mantel-Haenszel odds ratio and determines the power using the standard error of the expected combined Mantel-Haenszel odds ratio under the null hypothesis as derived from the Mantel-Haenszel test statistic without continuity correction. Results: Thereby, the program allows estimating the optimal prevalence of the matching factor in selected controls for a given scenario which often differs from the prevalence in cases. It furthermore allows to estimate loss in power and efficiency compared to optimal matching by suboptimal matching. Conclusions: Estimations like these are helpful with respect to the decision when to stop efforts to optimize the degree of matching during the recruitment of controls. Our program will strongly facilitate assessing the benefits of flexible matching strategies.

scholarly journals Weighted Kolmogorov Smirnov testing: an alternative for Gene Set Enrichment Analysis

2015 ◽  
Vol 14 (3) ◽  
Author(s):  
Konstantina Charmpi ◽  
Bernard Ycart
Keyword(s):  
Weight Function ◽  
Null Hypothesis ◽  
Computing Time ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Test Statistic ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Gene Sets ◽  
Kolmogorov Smirnov

AbstractGene Set Enrichment Analysis (GSEA) is a basic tool for genomic data treatment. Its test statistic is based on a cumulated weight function, and its distribution under the null hypothesis is evaluated by Monte-Carlo simulation. Here, it is proposed to subtract to the cumulated weight function its asymptotic expectation, then scale it. Under the null hypothesis, the convergence in distribution of the new test statistic is proved, using the theory of empirical processes. The limiting distribution needs to be computed only once, and can then be used for many different gene sets. This results in large savings in computing time. The test defined in this way has been called Weighted Kolmogorov Smirnov (WKS) test. Using expression data from the GEO repository, tested against the MSig Database C2, a comparison between the classical GSEA test and the new procedure has been conducted. Our conclusion is that, beyond its mathematical and algorithmic advantages, the WKS test could be more informative in many cases, than the classical GSEA test.

scholarly journals Inclusion of unaffected sibs increases power in model-free linkage analysis of a behavioral trait

BMC Genetics ◽  
2005 ◽  
Vol 6 (Suppl 1) ◽  
pp. S22 ◽  
Author(s):  
Sabine Plancoulaine ◽  
Alexandre Alcaïs ◽  
Yue Chen ◽  
Laurent Abel ◽  
France Gagnon
Keyword(s):  
Linkage Analysis ◽  
Behavioral Trait ◽  
Model Free

THE LIMITING PROPERTIES OF THE CANOVA AND HANSEN TEST UNDER LOCAL ALTERNATIVES

2002 ◽  
Vol 18 (5) ◽  
pp. 1197-1220
Author(s):  
Eiji Kurozumi
Keyword(s):  
Monte Carlo ◽  
Characteristic Function ◽  
Spectral Density ◽  
Unit Root ◽  
Null Hypothesis ◽  
Inverse Function ◽  
Unit Roots ◽  
Local Alternatives ◽  
Test Statistic ◽  
Economic Statistics

This paper investigates the limiting properties of the Canova and Hansen test, testing for the null hypothesis of no unit root against seasonal unit roots, under a sequence of local alternatives with the model extended to have seasonal dummies and trends or no deterministic term and also only seasonal dummies. We derive the limiting distribution of the test statistic and its characteristic function under local alternatives. We find that the local limiting power is an inverse function of the spectral density at frequency π (π/2) when we test against a negative unit root (annual unit roots). We also theoretically show that the local limiting power of the Canova and Hansen test against a negative unit root (annual unit roots) does not increase when the true process has annual unit roots (a negative unit root) but not a negative unit root (annual unit roots), which has been observed in Monte Carlo simulations in such research as Caner (1998, Journal of Business and Economic Statistics 16, 349–356), Canova and Hansen (1995, Journal of Business and Economic Statistics 13, 237–252), and Hylleberg (1995, Journal of Econometrics 69, 5–25).

On some properties of the scan statistic on the circle and the line

1977 ◽  
Vol 14 (2) ◽  
pp. 272-283 ◽  
Author(s):  
Noel Cressie
Keyword(s):  
Stochastic Process ◽  
Continuous Time ◽  
Null Hypothesis ◽  
Nuisance Parameter ◽  
Test Statistic ◽  
Scan Statistic ◽  
Asymptotic Power ◽  
Power Comparisons ◽  
Continuous Time Stochastic Process ◽  
Parameter Distributions

The scan statistic is defined as the supremum of a particular continuous-time stochastic process, and is used as a test statistic for testing uniformity against a simple clustering type of alternative. Its distribution under the null hypothesis is investigated and weak convergence of the stochastic process to the appropriate Gaussian process is proved. An interesting link is forged between the circular scan statistic and Kuiper's statistic, which rids us of the trouble of estimating a nuisance parameter. Distributions under the alternative are then derived, and asymptotic power comparisons are made.

Sign in / Sign up

Export Citation Format

Share Document