Search Results - subject:"Multiple Hypothesis Testing"

Multiple hypothesis testing and clustering with mixtures of non-central t-distributions applied in microarray data analysis

Marín, J.M.; Rodríguez-Bernal, M.T. - In: Computational Statistics & Data Analysis 56 (2012) 6, pp. 1898-1907

Multiple testing analysis and clustering methodologies are usually applied in microarray data analysis. A combination of both methods to deal with multiple comparisons among groups obtained from microarray expressions of genes is proposed. Assuming normal data, a statistic which depends on...

Persistent link: https://www.econbiz.de/10011056509

International price and earnings momentum

Leippold, Markus; Lohre, Harald - In: The European journal of finance 18 (2012) 5/6, pp. 535-573

Persistent link: https://www.econbiz.de/10009615713

Evaluations of FWER-controlling methods in multiple hypothesis testing

Hwang, Yi-Ting; Lai, Jia-Jung; Ou, Shyh-Tyan - In: Journal of Applied Statistics 37 (2010) 10, pp. 1681-1694

hypothesis testing is to control Type-I error. The probability of at least one false rejection referred to as the familywise …Simultaneously testing a family of n null hypotheses can arise in many applications. A common problem in multiple …

Persistent link: https://www.econbiz.de/10008674984

Weighted Multiple Hypothesis Testing Procedures

Kang, Guolian; Ye, Keying; Liu, Nianjun; Allison, David; … - In: Statistical Applications in Genetics and Molecular Biology 8 (2009) 1, pp. 23-23

Multiple hypothesis testing is commonly used in genome research such as genome-wide studies and gene expression data … analysis (Lin, 2005). The widely used Bonferroni procedure controls the family-wise error rate (FWER) for multiple hypothesis … testing, but has limited statistical power as the number of hypotheses tested increases. The power of multiple testing …

Persistent link: https://www.econbiz.de/10005046591

The Two Sample Problem for Multiple Categorical Variables

DiRienzo, A. - In: International Journal of Biostatistics 2 (2006) 1, pp. 1019-1019

Comparing two large multivariate distributions is potentially complicated at least for the following reasons. First, some variable/level combinations may have a redundant difference in prevalence between groups in the sense that the difference can be completely explained in terms of lower-order...

Persistent link: https://www.econbiz.de/10005752612

Calibrating Observed Differential Gene Expression for the Multiplicity of Genes on the Array

Zheng, Yingye; Pepe, Margaret - Berkeley Electronic Press - 2004

In a gene expression array study, the expression levels of thousands of genes are monitored simultaneously across various biological conditions on a small set of subjects. One goal of such studies is to explore a large pool of genes in order to select a subset of genes that appear to be...

Persistent link: https://www.econbiz.de/10005579372

Multiple hypothesis test for parameter constancy based on recursive residuals

Chu, Chia-Shang James - In: Econometric Reviews 16 (1997) 3, pp. 353-360

This article presents a multiple hypothesis test procedure that combines two well known tests for structural change in the linear regression model, the CUSUM test and the recursive t test. The CUSUM test is run through the sequence of recursive residuals as usual; if the CUSUM plot does not...

Persistent link: https://www.econbiz.de/10005476050