Literature DB >> 34349611

LocalControl: An R Package for Comparative Safety and Effectiveness Research.

Nicolas R Lauve1, Stuart J Nelson1, S Stanley Young2, Robert L Obenchain3, Christophe G Lambert1.   

Abstract

The LocalControl R package implements novel approaches to address biases and confounding when comparing treatments or exposures in observational studies of outcomes. While designed and appropriate for use in comparative safety and effectiveness research involving medicine and the life sciences, the package can be used in other situations involving outcomes with multiple confounders. LocalControl is an open-source tool for researchers whose aim is to generate high quality evidence using observational data. The package implements a family of methods for non-parametric bias correction when comparing treatments in observational studies, including survival analysis settings, where competing risks and/or censoring may be present. The approach extends to bias-corrected personalized predictions of treatment outcome differences, and analysis of heterogeneity of treatment effect-sizes across patient subgroups.

Entities:  

Keywords:  Kaplan-Meier; R; bias; competing risks; survival

Year:  2020        PMID: 34349611      PMCID: PMC8330612          DOI: 10.18637/jss.v096.i04

Source DB:  PubMed          Journal:  J Stat Softw        ISSN: 1548-7660            Impact factor:   6.440


  13 in total

1.  Non-parametric confidence interval estimation for competing risks analysis: application to contraceptive data.

Authors:  Jahar B Choudhury
Journal:  Stat Med       Date:  2002-04-30       Impact factor: 2.373

2.  Propensity score applied to survival data analysis through proportional hazards models: a Monte Carlo study.

Authors:  Etienne Gayat; Matthieu Resche-Rigon; Jean-Yves Mary; Raphaël Porcher
Journal:  Pharm Stat       Date:  2012-03-12       Impact factor: 1.894

3.  Empirical assessment of methods for risk identification in healthcare data: results from the experiments of the Observational Medical Outcomes Partnership.

Authors:  Patrick B Ryan; David Madigan; Paul E Stang; J Marc Overhage; Judith A Racoosin; Abraham G Hartzema
Journal:  Stat Med       Date:  2012-09-27       Impact factor: 2.373

4.  Effect of smoking on blood pressure.

Authors:  C C Seltzer
Journal:  Am Heart J       Date:  1974-05       Impact factor: 4.749

5.  Kaplan-Meier, marginal or conditional probability curves in summarizing competing risks failure time data?

Authors:  M S Pepe; M Mori
Journal:  Stat Med       Date:  1993-04-30       Impact factor: 2.373

6.  Local control for identifying subgroups of interest in observational research: persistence of treatment for major depressive disorder.

Authors:  Douglas E Faries; Yi Chen; Ilya Lipkovich; Anthony Zagar; Xianchen Liu; Robert L Obenchain
Journal:  Int J Methods Psychiatr Res       Date:  2013-08-18       Impact factor: 4.035

Review 7.  Cigarette smoking and hypertension.

Authors:  A Virdis; C Giannarelli; M Fritsch Neves; S Taddei; L Ghiadoni
Journal:  Curr Pharm Des       Date:  2010       Impact factor: 3.116

8.  Abciximab provides cost-effective survival advantage in high-volume interventional practice.

Authors:  D J Kereiakes; R L Obenchain; B L Barber; A Smith; M McDonald; T M Broderick; J P Runyon; T M Shimshak; J F Schneider; C R Hattemer; E M Roth; D D Whang; D Cocks; C W Abbottsmith
Journal:  Am Heart J       Date:  2000-10       Impact factor: 4.749

9.  The use of propensity score methods with survival or time-to-event outcomes: reporting measures of effect similar to those used in randomized experiments.

Authors:  Peter C Austin
Journal:  Stat Med       Date:  2013-09-30       Impact factor: 2.373

10.  The performance of different propensity score methods for estimating absolute effects of treatments on survival outcomes: A simulation study.

Authors:  Peter C Austin; Tibor Schuster
Journal:  Stat Methods Med Res       Date:  2014-01-23       Impact factor: 3.021

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