Journal maintained by Dylan Small. Site hosted by University of Pennsylvania.
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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

The Statistical Modeling of Aging and
Risk of Transition Project: Data Collection and
Harmonization Across 11 Longitudinal Cohort
Studies of Aging, Cognition, and Dementia
by Erin Abner et al.

Published on 04-08-2015
Longitudinal cognitive trajectories and other factors associated with mixed neuropathologies (such as Alzheimer’s disease with co-occurring cerebrovascular disease) remain incompletely understood, despite being the rule and not the exception in older populations. The Statistical Modeling of Aging and Risk of Transition study (SMART) is a consortium of 11 different high-quality longitudinal studies of aging and cognition (N=11,541 participants) established for the purpose of characterizing risk and protective factors associated with subtypes of age-associated mixed neuropathologies (N=3,001 autopsies). While brain donation was not required for participation in all SMART cohorts, most achieved substantial autopsy rates (i.e., > 50%). Moreover, the studies comprising SMART have large numbers of participants who were followed from intact cognition and transitioned to cognitive impairment and dementia, as well as participants who remained cognitively intact until death. These data provide an exciting opportunity to apply sophisticated statistical methods, like Markov processes, that require large, well-characterized samples. Thus, SMART will serve as an important resource for the field of mixed dementia epidemiology and neuropathology.
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