Evidence map›Paper›PMID 25705065›Full record

ArticleJournal of the American Statistical Association2004

Methodology for Evaluating a Partially Controlled Longitudinal Treatment Using Principal Stratification, With Application to a Needle Exchange Program.

Constantine E Frangakis, Ronald S Brookmeyer, Ravi Varadhan, Mahboobeh Safaeian, David Vlahov, Steffanie A Strathdee

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the American Statistical Association, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Trial
  2. Principal stratification with U-statistics under principal ignorability.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
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  11. Article
  12. Article
  13. Article
  14. Adaptive designs for randomized trials in public health.Annual review of public health · 2009
    Review
  15. Causal Mediation Analyses for Randomized Trials.Health services & outcomes research methodology · 2008
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Constantine E FrangakisDepartment of Biostatistics, Bloomberg School of Public Health of the Johns Hopkins University, Baltimore, MD 21205.
Ronald S BrookmeyerDepartment of Biostatistics, Bloomberg School of Public Health of the Johns Hopkins University, Baltimore, MD 21205.
Ravi VaradhanDepartments of Biostatistics and Epidemiology, Bloomberg School of Public Health of the Johns Hopkins University, Baltimore, MD 21205.
Mahboobeh SafaeianDepartments of Biostatistics and Epidemiology, Bloomberg School of Public Health of the Johns Hopkins University, Baltimore, MD 21205.
David VlahovCenter for Urban Epidemiologic Studies, New York Academy of Medicine, New York, NY.
Steffanie A StrathdeeDepartment of Epidemiology, Bloomberg School of Public Health of the Johns Hopkins University, Baltimore, MD 21205.

Funding

Statistical Methods for Partially Controlled StudiesR01EY014314 · NEI · JOHNS HOPKINS UNIVERSITY · PI FRANGAKIS, CONSTANTINE E · 2002 to 2005
$975k
NEI NIH HHS R01 EY014314
6 · The paper itself

Abstract

We consider studies for evaluating the short-term effect of a treatment of interest on a time-to-event outcome. The studies we consider are only partially controlled in the following sense: (1) Subjects' exposure to the treatment of interest can vary over time, but this exposure is not directly controlled by the study; (2) subjects' follow-up time is not directly controlled by the study; and (3) the study directly controls another factor that can affect subjects' exposure to the treatment of interest as well as subjects' follow-up time. When factors 1 and 2 are both present in the study, evaluating the treatment of interest using standard methods, including instrumental variables, does not generally estimate treatment effects. We develop the methodology for estimating the effect of treatment 1 in this setting of partially controlled studies under explicit assumptions using the framework for principal stratification for causal inference. We illustrate our methods by a study to evaluate the efficacy of the Baltimore Needle Exchange Program to reduce the risk of human immunodeficiency virus (HIV) transmission, using data on distance of the program's sites from the subjects.

Indexed as

Causal inferenceHIVNeedle exchangePartially controlled studiesPotential outcomesPrincipal stratification

Identifiers

PMID25705065
PMCPMC4332568

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.