Journal maintained by Dylan Small. Site hosted by University of Pennsylvania.
Issue Browser
2017 all »
art. 2 Review of "Observation and Experiment"
(author Paul Rosenbaum)
Book review by Dylan Small

art. 1 Study Protocol for the Evaluation of a
Vocational Rehabilitation
by Philip Fowler, Xavier de Luna, Per Johansson,
Petra Ornstein, Sofia Bill and Peje Bengtsson

2016 all »
art. 9 Reprint "Regression-Discontinuity Analysis:
An Alternative to the Ex-Post Facto Experiment"
by Donald Thistlewaite and Donald Campbell
followed by comments by
Peter Aronow, Nicole Basta, M. Elizabeth Halloran;
Matias Cattaneo and Gonzalo Vazquez-Bare;
Guido Imbens;
Alessandra Mattei and Fabrizia Mealli;
Jasjeet Sekhon and Rocío Titiunik;
and Vivian Wong and Coady Wing

art. 8 Assessing the Dose-Response Relationship
Between Maternal Use of Inhaled Corticosteroids
Therapy and Birth Weight: A Generalized
Propensity Score Approach
by Mariia Samoilenko, Lucie Blais, Benoît
Cossette, Amélie Forget, & Geneviève Lefebvre

art. 7 Review of "Causality in a Social World"
(author Guanglei Hong)
Book review by Ken Frank, Guan Kung Saw
and Ran Xu

art. 6 An Interim Sample Size Recalculation
for Observational Studies
by Sergey Tarima, Peng He, Tao Wang
and Aniko Szabo

art. 5 Cohort Restriction Based on Prior
Enrollment: Examining Potential Biases in
Estimating Cancer and Mortality Risk
by Susan Shortreed, Eric Johnson, Carolyn Rutter,
Aruna Kamineni, Karen Wernli & Jessica Chubak

art. 4 Patient Centered Hazard Ratio Estimation
Using Principal Strati cation Weights:
Application to the NORCCAP Randomized Trial
of Colorectal Cancer Screening
by Todd MacKenzie, Magnus Loberg and
A. James O'Malley

art. 3 Electronic Health Records to Evaluate
and Account for Non-response Bias: A Survey
of Patients Using Chronic Opioid Therapy
by Susan Shortreed, Michael Von Korff, Stephen
Thielke, Linda LeResche, Kathleen Saunders,
Dori Rosenberg and Judith Turner

art. 2 Large Sparse Optimal Matching
with R package rcbalance
by Samuel Pimentel

art. 1 Review of "Explanation in Causal
Inference: Mediation and Interaction"
(author T.J. Vanderweele)
Book review by Luke Keele

2015 all »
art. 10 Targeted Learning for Pre-Analysis Plans
in Public Health and Health Policy Research
by Sherri Rose

art. 9 Review of "Causal Inference for Statistics,
Social, and Biomedical Sciences"
(authors: G.W. Imbens and D.B. Rubin)
Book review by Fabrizia Mealli

art. 8 Simulation-Extrapolation for Estimating
Means and Causal Effects with Mismeasured
by J.R. Lockwood and Daniel McCaffrey

art. 7 Reprint of "Observational Studies"
by William Cochran followed by comments
by current researchers in observational studies

art. 6 The non-zero mean SIMEX:
Improving estimation in the face of
measurement error
by Nabila Parveen, Erica Moodie
and Bluma Brenner

Editorial Board
Peter Austin
University of Toronto
Anirban Basu
University of Washington
Jake Bowers
University of Illinois
Alan Brookhart
University of North Carolina
Jing Cheng
University of California, San Francisco
Thomas Cook
Northwestern University
Xavier de Luna
Umea University
Beth Ann Griffin
RAND Corporation
Jens Hainmueller
Stanford University
Ben Hansen
University of Michigan
David Harding
University of California, Berkeley
Joseph Hogan
Brown University
Kosuke Imai
Princeton University
Guido Imbens
Stanford University
Luke Keele
Georgetown University
Genevieve Lefebvre
Universite du Quebec a Montreal
Stephen Morgan
Johns Hopkins University
Paul Rosenbaum
University of Pennsylvania
Jason Roy
University of Pennsylvania
Jas Sekhon
University of California, Berkeley
Susan Shortreed
Group Health Research Institute
Michael Sobel
Columbia University
Elizabeth Stuart
Johns Hopkins University
Eric Tchetgen Tchetgen
Harvard University
Mark van der Laan
University of California, Berkeley
Advisory Committee
David Banks
Duke University
Marie Davidian
North Carolina State University
Joel Greenhouse
Carnegie Mellon University
M. Elizabeth Halloran
Fred Hutchinson Cancer Research Center
University of Washington
Sharon-Lise Normand
Harvard University

Simulation-Extrapolation for Estimating
Means and Causal Effects with Mismeasured
by J.R. Lockwood and Daniel McCaffrey

Published on 08-07-2015
Regression, weighting and related approaches to estimating a population mean from a sample with nonrandom missing data often rely on the assumption that conditional on covariates, observed samples can be treated as random. Standard methods using this assumption generally will fail to yield consistent estimators when covariates are measured with error. We review approaches to consistent estimation of a population mean of an incompletely observed variable using error-prone covariates, noting difficulties with applying these methods. We consider the application of Simulation-Extrapolation (SIMEX) as a simple and effective alternative. We provide technical conditions under which SIMEX will lead to a consistent estimator of a population mean and argue why it may function well in common settings. We use a simulation study to demonstrate its potential for removing nearly all of the bias in regression, weighting and doubly robust estimators for a population mean while maintaining precision competitive with what would be obtained without measurement error. We also discuss and evaluate options for estimating the standard error of the SIMEX mean estimator. Finally, we present an empirical example of estimating middle school effects on student achievement.
This article contains file attachments. Click to download.

Contact | Please review these Journal Guidenlines prior to submitting a new entry.
Page maintained by Dylan Small. Site hosted by University of Pennsylvania.