Literature DB >> 24926156

The use of propensity scores to assess the generalizability of results from randomized trials.

Elizabeth A Stuart1, Stephen R Cole2, Catherine P Bradshaw3, Philip J Leaf3.   

Abstract

Randomized trials remain the most accepted design for estimating the effects of interventions, but they do not necessarily answer a question of primary interest: Will the program be effective in a target population in which it may be implemented? In other words, are the results generalizable? There has been very little statistical research on how to assess the generalizability, or "external validity," of randomized trials. We propose the use of propensity-score-based metrics to quantify the similarity of the participants in a randomized trial and a target population. In this setting the propensity score model predicts participation in the randomized trial, given a set of covariates. The resulting propensity scores are used first to quantify the difference between the trial participants and the target population, and then to match, subclassify, or weight the control group outcomes to the population, assessing how well the propensity score-adjusted outcomes track the outcomes actually observed in the population. These metrics can serve as a first step in assessing the generalizability of results from randomized trials to target populations. This paper lays out these ideas, discusses the assumptions underlying the approach, and illustrates the metrics using data on the evaluation of a schoolwide prevention program called Positive Behavioral Interventions and Supports.

Entities:  

Keywords:  Causal inference; External validity; Positive Behavioral Interventions and Supports; Research synthesis

Year:  2001        PMID: 24926156      PMCID: PMC4051511          DOI: 10.1111/j.1467-985X.2010.00673.x

Source DB:  PubMed          Journal:  J R Stat Soc Ser A Stat Soc        ISSN: 0964-1998            Impact factor:   2.483


  29 in total

1.  Hierarchical models in generalized synthesis of evidence: an example based on studies of breast cancer screening.

Authors:  T C Prevost; K R Abrams; D R Jones
Journal:  Stat Med       Date:  2000-12-30       Impact factor: 2.373

2.  Stratification and weighting via the propensity score in estimation of causal treatment effects: a comparative study.

Authors:  Jared K Lunceford; Marie Davidian
Journal:  Stat Med       Date:  2004-10-15       Impact factor: 2.373

3.  External validity of randomised controlled trials: "to whom do the results of this trial apply?".

Authors:  Peter M Rothwell
Journal:  Lancet       Date:  2005 Jan 1-7       Impact factor: 79.321

4.  Treating individuals 2. Subgroup analysis in randomised controlled trials: importance, indications, and interpretation.

Authors:  Peter M Rothwell
Journal:  Lancet       Date:  2005 Jan 8-14       Impact factor: 79.321

5.  Selection criteria and generalizability within the counterfactual framework: explaining the paradox of antidepressant-induced suicidality?

Authors:  Herbert I Weisberg; Vanessa C Hayden; Victor P Pontes
Journal:  Clin Trials       Date:  2009-04       Impact factor: 2.486

6.  Altering school climate through school-wide Positive Behavioral Interventions and Supports: findings from a group-randomized effectiveness trial.

Authors:  Catherine P Bradshaw; Christine W Koth; Leslie A Thornton; Philip J Leaf
Journal:  Prev Sci       Date:  2009-06

7.  Comment: Demystifying Double Robustness: A Comparison of Alternative Strategies for Estimating a Population Mean from Incomplete Data.

Authors:  Anastasios A Tsiatis; Marie Davidian
Journal:  Stat Sci       Date:  2007       Impact factor: 2.901

Review 8.  Large-scale randomized evidence: large, simple trials and overviews of trials.

Authors:  R Peto; R Collins; R Gray
Journal:  J Clin Epidemiol       Date:  1995-01       Impact factor: 6.437

9.  Adjustment for selection bias in observational studies with application to the analysis of autopsy data.

Authors:  S Haneuse; J Schildcrout; P Crane; J Sonnen; J Breitner; E Larson
Journal:  Neuroepidemiology       Date:  2009-01-29       Impact factor: 3.282

10.  Constructing inverse probability weights for marginal structural models.

Authors:  Stephen R Cole; Miguel A Hernán
Journal:  Am J Epidemiol       Date:  2008-08-05       Impact factor: 4.897

View more
  87 in total

1.  External Validity in Policy Evaluations that Choose Sites Purposively.

Authors:  Robert B Olsen; Larry L Orr; Stephen H Bell; Elizabeth A Stuart
Journal:  J Policy Anal Manage       Date:  2013

2.  Generalizability of findings from randomized controlled trials: application to the National Institute of Drug Abuse Clinical Trials Network.

Authors:  Ryoko Susukida; Rosa M Crum; Cyrus Ebnesajjad; Elizabeth A Stuart; Ramin Mojtabai
Journal:  Addiction       Date:  2017-03-16       Impact factor: 6.526

3.  Sample Selection for Medicare Risk Adjustment Due to Systematically Missing Data.

Authors:  Savannah L Bergquist; Thomas G McGuire; Timothy J Layton; Sherri Rose
Journal:  Health Serv Res       Date:  2018-09-11       Impact factor: 3.402

4.  Epidemiology at a time for unity.

Authors:  Bryan Lau; Priya Duggal; Stephan Ehrhardt
Journal:  Int J Epidemiol       Date:  2018-10-01       Impact factor: 7.196

5.  A scenario-based, randomized trial of patient values and functional prognosis on intensivist intent to discuss withdrawing life support.

Authors:  Alison E Turnbull; Jenna R Krall; A Parker Ruhl; J Randall Curtis; Scott D Halpern; Bryan M Lau; Dale M Needham
Journal:  Crit Care Med       Date:  2014-06       Impact factor: 7.598

6.  Assessing methods for generalizing experimental impact estimates to target populations.

Authors:  Holger L Kern; Elizabeth A Stuart; Jennifer Hill; Donald P Green
Journal:  J Res Educ Eff       Date:  2016-01-14

7.  An Algorithm for Creating Virtual Controls Using Integrated and Harmonized Longitudinal Data.

Authors:  William B Hansen; Shyh-Huei Chen; Santiago Saldana; Edward H Ip
Journal:  Eval Health Prof       Date:  2018-05-03       Impact factor: 2.651

8.  Estimating the health benefit of reducing indoor air pollution in a randomized environmental intervention.

Authors:  Roger D Peng; Arlene M Butz; Amber J Hackstadt; D'Ann L Williams; Gregory B Diette; Patrick N Breysse; Elizabeth C Matsui
Journal:  J R Stat Soc Ser A Stat Soc       Date:  2014-07-15       Impact factor: 2.483

9.  Constrained Maximum Likelihood Estimation for Model Calibration Using Summary-level Information from External Big Data Sources.

Authors:  Nilanjan Chatterjee; Yi-Hau Chen; Paige Maas; Raymond J Carroll
Journal:  J Am Stat Assoc       Date:  2016-05-05       Impact factor: 5.033

10.  Effects of school-wide positive behavioral interventions and supports on child behavior problems.

Authors:  Catherine P Bradshaw; Tracy E Waasdorp; Philip J Leaf
Journal:  Pediatrics       Date:  2012-10-15       Impact factor: 7.124

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.