35 citations · 44 across the 8 of their papers we have counts for
10 papers
Multiple Testing Of Composite Null Hypotheses With High Dimensional Count Data: A Local False Discovery Rate Approach
Emmanuel Asare, Pratyaydipta Rudra, Joshua Habiger
High throughput sequencing technology is routinely used to generate high dimensional (HD) count data. One objective is to determine which variables are associated with a covariate…
Sensitivity Analysis for False Discovery Rate Estimation with Published p-Values
Tianyu Cao, Sangyoon Yi, Joshua Habiger
There is recent interest in estimating the false discovery rate (FDR) with published p-values. However, there is little formal research that addresses the manner and extent to whic…
Minimally Discrete and Minimally Randomized p-Values
Joshua Habiger, Pratyaydipta Rudra
In meta analysis, multiple hypothesis testing and many other methods, p-values are utilized as inputs and assumed to be uniformly distributed over the unit interval under the null…
False Discovery Rate Control for Lesion-Symptom Mapping with Heterogeneous data via Weighted P-values
Siyu Zheng, Alexander C. McLain, Joshua Habiger +2
Lesion-symptom mapping studies provide insight into what areas of the brain are involved in different aspects of cognition. This is commonly done via behavioral testing in patients…
The Inuence of Misspecified Covariance on False Discovery Control when Using Posterior Probabilities
Ye Liang, Joshua D. Habiger, Xiaoyi Min
This paper focuses on the influence of a misspecified covariance structure on false discovery rate for the large scale multiple testing problem. Specifically, we evaluate the influ…
Adaptive False Discovery Rate Control for Heterogeneous Data
Joshua D. Habiger
Efforts to develop more efficient multiple hypothesis testing procedures for false discovery rate (FDR) control have focused on incorporating an estimate of the proportion of true…
Multiple Test Functions and Adjusted p-Values for Test Statistics with Discrete Distributions
Joshua D Habiger
The randomized -value, (nonrandomized) mid--value and abstract randomized -value have all been recommended for testing a null hypothesis whenever the test statistic has a…
Compound p-Value Statistics for Multiple Testing Procedures
Joshua D. Habiger, Edsel A. Pena
Many multiple testing procedures make use of the p-values from the individual pairs of hypothesis tests, and are valid if the p-value statistics are independent and uniformly distr…
Classes of Multiple Decision Functions Strongly Controlling FWER and FDR
Edsel A. Pena, Joshua D. Habiger, Wensong Wu
This paper provides two general classes of multiple decision functions where each member of the first class strongly controls the family-wise error rate (FWER), while each member o…
Power-enhanced multiple decision functions controlling family-wise error and false discovery rates
Edsel A. Peña, Joshua D. Habiger, Wensong Wu
Improved procedures, in terms of smaller missed discovery rates (MDR), for performing multiple hypotheses testing with weak and strong control of the family-wise error rate (FWER)…