Home About us Contact
|
Home About us Contact | ||
|
|
||
Comparable Power (comparable + power)
Selected AbstractsPHYLOGENETICALLY NESTED COMPARISONS FOR TESTING CORRELATES OF SPECIES RICHNESS: A SIMULATION STUDY OF CONTINUOUS VARIABLESEVOLUTION, Issue 1 2003NICK J. B. ISAAC Abstract., Explaining the uneven distribution of species among lineages is one of the oldest questions in evolution. Proposed correlations between biological traits and species diversity are routinely tested by making comparisons between phylogenetic sister clades. Several recent studies have used nested sister-clade comparisons to test hypotheses linking continuously varying traits, such as body size, with diversity. Evaluating the findings of these studies is complicated because they differ in the index of species richness difference used, the way in which trait differences were treated, and the statistical tests employed. In this paper, we use simulations to compare the performance of four species richness indices, two choices about the branch lengths used to estimate trait values for internal nodes and two statistical tests under a range of models of clade growth and character evolution. All four indices returned appropriate Type I error rates when the assumptions of the method were met and when branch lengths were set proportional to time. Only two of the indices were robust to the different evolutionary models and to different choices of branch lengths and statistical tests. These robust indices had comparable power under one nonnull scenario. Regression through the origin was consistently more powerful than the t -test, and the choice of branch lengths exerts a strong effect on both the validity and power. In the light of our simulations, we re-evaluate the findings of those who have previously used nested comparisons in the context of species richness. We provide a set of simple guidelines to maximize the performance of phylogenetically nested comparisons in tests of putative correlates of species richness. [source] INTANGIBLE ASSETS, BOOK-TO-MARKET, AND COMMON STOCK RETURNSTHE JOURNAL OF FINANCIAL RESEARCH, Issue 1 2006James M. Nelson Abstract I examine two anomalies where the Fama and French three-factor model fails to adequately explain monthly industry and index returns. Both anomalies are consistent with a bad model problem where the book-to-market factor introduces a negative bias in the intercepts. I propose the intangibles model as an alternative where the three-factor model is known to have difficulty. This alternative model, which replaces the book-to-market factor with zero investment portfolio returns based on prior investments in intangible assets, is well specified in random samples, has comparable power, and fully explains both anomalies. [source] EMK: A Novel Program for Family-Based Allelic and Genotypic Association Tests on Quantitative TraitsANNALS OF HUMAN GENETICS, Issue 3 2008Y. W. Li Summary The QTDT program is a widely-used program for analyzing quantitative trait data, but the methods mainly test allelic association. Since the genotype of a marker is a direct observation for an individual, it is of interest to assess association at the genotypic level. In this study, we extended the allele-based association method developed by Monks and Kaplan (MK method) to genotype-based association tests for quantitative traits. We implemented a novel extended MK (EMK) program that can perform both allele- and genotype- based association tests in any pedigree structure. To evaluate the performance of EMK, we utilized simulated pedigree data and real data from our previous report of GSTO1 and GSTO2 genes in Alzheimer disease (AD). Both allele- and genotype-based EMK methods (allele-EMK and geno-EMK) showed correct type I error for various pedigree structures and admixture populations. The geno-EMK method showed comparable power to the allele-EMK test. By treating age-at-onset (AAO) as a quantitative trait, the EMK program was able to detect significant associations for rs4925 in GSTO1 (P= 0.006 for allele-EMK and P= 0.009 for geno-EMK), and rs2297235 in GSTO2 (P= 0.005 for allele-EMK and P= 0.009 for geno-EMK), which are consistent with our previous findings. [source] A Bayesian Chi-Squared Goodness-of-Fit Test for Censored Data ModelsBIOMETRICS, Issue 2 2010Jing Cao Summary We propose a Bayesian chi-squared model diagnostic for analysis of data subject to censoring. The test statistic has the form of Pearson's chi-squared test statistic and is easy to calculate from standard output of Markov chain Monte Carlo algorithms. The key innovation of this diagnostic is that it is based only on observed failure times. Because it does not rely on the imputation of failure times for observations that have been censored, we show that under heavy censoring it can have higher power for detecting model departures than a comparable test based on the complete data. In a simulation study, we show that tests based on this diagnostic exhibit comparable power and better nominal Type I error rates than a commonly used alternative test proposed by Akritas (1988,,Journal of the American Statistical Association,83, 222,230). An important advantage of the proposed diagnostic is that it can be applied to a broad class of censored data models, including generalized linear models and other models with nonidentically distributed and nonadditive error structures. We illustrate the proposed model diagnostic for testing the adequacy of two parametric survival models for Space Shuttle main engine failures. [source] | ||||||||||