Evidence map›Paper›PMID 34445914›Full record

ArticleStatistical methods in medical research2021

Additive rates model for recurrent event data with intermittently observed time-dependent covariates.

Tianmeng Lyu, Xianghua Luo, Chiung-Yu Huang, Yifei Sun

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In one paragraph

Article in Statistical methods in medical research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Tianmeng LyuClinical Development & Analytics, Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA.
Xianghua LuoDivision of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA.ORCID 0000-0001-7501-6582
Chiung-Yu HuangDepartment of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA.
Yifei SunDepartment of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA.ORCID 0000-0002-6961-5500

Funding

Women's CancerP30CA077598 · NCI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI Douglas Yee · 1998 to 2026
$100.4M
University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UL1TR000114 · NCATS · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R · 2012 to 2015
$35.0M
University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UL1TR002494 · NCATS · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R, WEISDORF, DANIEL J · 2018 to 2022
$34.9M
Statistical Methods for Survival and Recurrent Event Data in Clinical ResearchR01CA193888 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HUANG, CHIUNG-YU · 2015 to 2019
$1.7M
Statistical methods for bivariate alternating recurrent event dataR03MH112895 · NIMH · UNIVERSITY OF MINNESOTA · PI LUO, XIANGHUA · 2017 to 2018
$143k
Statistical Methods for Analyzing Data of Recurrent Infections after HematopoietiR03CA187991 · NCI · UNIVERSITY OF MINNESOTA · PI LUO, XIANGHUA · 2014 to 2015
$143k
NCATS NIH HHS UL1 TR000114NCATS NIH HHS UL1 TR002494NCI NIH HHS P30 CA077598NCI NIH HHS R01 CA193888NCI NIH HHS R03 CA187991NIMH NIH HHS R03 MH112895
6 · The paper itself

Abstract

Various regression methods have been proposed for analyzing recurrent event data. Among them, the semiparametric additive rates model is particularly appealing because the regression coefficients quantify the absolute difference in the occurrence rate of the recurrent events between different groups. Estimation of the additive rates model requires the values of time-dependent covariates being observed throughout the entire follow-up period. In practice, however, the time-dependent covariates are usually only measured at intermittent follow-up visits. In this paper, we propose to kernel smooth functions involving time-dependent covariates across subjects in the estimating function, as opposed to imputing individual covariate trajectories. Simulation studies show that the proposed method outperforms simple imputation methods. The proposed method is illustrated with data from an epidemiologic study of the effect of streptococcal infections on recurrent pharyngitis episodes.

Indexed as

Models, StatisticalComputer SimulationEpidemiologic StudiesHumansRecurrenceRegression Analysisadditive rates modelsestimating equationsKernel smoothingrecurrent eventstime-dependent covariates

Identifiers

PMID34445914
PMCPMC8608417

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.