activity
20132024
most citedRegularized Ordinal Regression and the ordinalNet R Package

86 citations · 117 across the 9 of their papers we have counts for

collaborators

10 papers

stat.ME2024

Dir-SPGLM: A Bayesian semiparametric GLM with data-driven reference distribution

Entejar Alam, Peter Müller, Paul J. Rathouz

The recently developed semi-parametric generalized linear model (SPGLM) offers more flexibility as compared to the classical GLM by including the baseline or reference distribution…

stat.CO2022★ 2 cited

%CRTFASTGEEPWR: a SAS macro for power of the generalized estimating equations of multi-period cluster randomized trials with application to stepped wedge designs

Ying Zhang, John S. Preisser, Fan Li +2

Multi-period cluster randomized trials (CRTs) are increasingly used for the evaluation of interventions delivered at the group level. While generalized estimating equations (GEE) a…

stat.ME2021★ 5 cited

Marginal modeling of cluster-period means and intraclass correlations in stepped wedge designs with binary outcomes

Fan Li, Hengshi Yu, Paul J. Rathouz +2

Stepped wedge cluster randomized trials (SW-CRTs) with binary outcomes are increasingly used in prevention and implementation studies. Marginal models represent a flexible tool for…

stat.ME2020

Generalized Linear Models for Longitudinal Data with Biased Sampling Designs: A Sequential Offsetted Regressions Approach

Lee S. McDaniel, Jonathan S. Schildcrout, Enrique F. Schisterman +1

Biased sampling designs can be highly efficient when studying rare (binary) or low variability (continuous) endpoints. We consider longitudinal data settings in which the probabili…

stat.CO2017★ 86 cited

Regularized Ordinal Regression and the ordinalNet R Package

Michael J. Wurm, Paul J. Rathouz, Bret M. Hanlon

Regularization techniques such as the lasso (Tibshirani 1996) and elastic net (Zou and Hastie 2005) can be used to improve regression model coefficient estimation and prediction ac…

stat.ME2016★ 8 cited

Orthogonality of the mean and error distribution in generalized linear models

Alan Huang, Paul J. Rathouz

We show that the mean-model parameter is always orthogonal to the error distribution in generalized linear models. Thus, the maximum likelihood estimator of the mean-model paramete…

stat.AP2015★ 15 cited

Biased sampling designs to improve research efficiency: Factors influencing pulmonary function over time in children with asthma

Jonathan S. Schildcrout, Paul J. Rathouz, Leila R. Zelnick +2

Substudies of the Childhood Asthma Management Program [Control. Clin. Trials 20 (1999) 91-120; N. Engl. J. Med. 343 (2000) 1054-1063] seek to identify patient characteristics assoc…

cs.AI2015

Mapping Heritability of Large-Scale Brain Networks with a Billion Connections {\em via} Persistent Homology

Moo K. Chung, Victoria Vilalta-Gil, Paul J. Rathouz +2

In many human brain network studies, we do not have sufficient number (n) of images relative to the number (p) of voxels due to the prohibitively expensive cost of scanning enough…

stat.ME2015

AR(1) Latent Class Models for Longitudinal Count Data

Nicholas C. Henderson, Paul J. Rathouz

In a variety of applications involving longitudinal or repeated-measurements data, it is desired to uncover natural groupings or clusters which exist among study subjects. Motivate…

stat.AP2013★ 1 cited

Prediction and replication from case-control sequencing studies using custom genotyping and additional sequencing

C. Ryan King, Paul J. Rathouz, Dan L. Nicolae

We present two results about using allele-count (AC) burdens of rare SNPs discovered in a case-control sequencing study for prediction or validation in an external prospective stud…