Literature DB >> 20563313

Using Non-experimental Data to Estimate Treatment Effects.

Elizabeth A Stuart1, Sue M Marcus, Marcela V Horvitz-Lennon, Robert D Gibbons, Sharon-Lise T Normand.   

Abstract

While much psychiatric research is based on randomized controlled trials (RCTs), where patients are randomly assigned to treatments, sometimes RCTs are not feasible. This paper describes propensity score approaches, which are increasingly used for estimating treatment effects in non-experimental settings. The primary goal of propensity score methods is to create sets of treated and comparison subjects who look as similar as possible, in essence replicating a randomized experiment, at least with respect to observed patient characteristics. A study to estimate the metabolic effects of antipsychotic medication in a sample of Florida Medicaid beneficiaries with schizophrenia illustrates methods.

Entities:  

Year:  2009        PMID: 20563313      PMCID: PMC2886294          DOI: 10.3928/00485713-20090625-07

Source DB:  PubMed          Journal:  Psychiatr Ann        ISSN: 0048-5713


  17 in total

1.  Principal stratification in causal inference.

Authors:  Constantine E Frangakis; Donald B Rubin
Journal:  Biometrics       Date:  2002-03       Impact factor: 2.571

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.  Propensity score estimation with boosted regression for evaluating causal effects in observational studies.

Authors:  Daniel F McCaffrey; Greg Ridgeway; Andrew R Morral
Journal:  Psychol Methods       Date:  2004-12

Review 4.  Reader's guide to critical appraisal of cohort studies: 1. Role and design.

Authors:  Paula A Rochon; Jerry H Gurwitz; Kathy Sykora; Muhammad Mamdani; David L Streiner; Susan Garfinkel; Sharon-Lise T Normand; Geoffrey M Anderson
Journal:  BMJ       Date:  2005-04-16

5.  On the use of discrete choice models for causal inference.

Authors:  Rusty Tchernis; Marcela Horvitz-Lennon; Sharon-Lise T Normand
Journal:  Stat Med       Date:  2005-07-30       Impact factor: 2.373

6.  Estimating causal effects from epidemiological data.

Authors:  Miguel A Hernán; James M Robins
Journal:  J Epidemiol Community Health       Date:  2006-07       Impact factor: 3.710

7.  The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials.

Authors:  Donald B Rubin
Journal:  Stat Med       Date:  2007-01-15       Impact factor: 2.373

8.  The role of model selection in causal inference from nonexperimental data.

Authors:  J M Robins; S Greenland
Journal:  Am J Epidemiol       Date:  1986-03       Impact factor: 4.897

9.  Balancing Treatment Comparisons in Longitudinal Studies.

Authors:  Sue M Marcus; Juned Siddique; Thomas R Ten Have; Robert D Gibbons; Elizabeth Stuart; Sharon-Lise T Normand
Journal:  Psychiatr Ann       Date:  2008-12-01

10.  Changes in glucose and cholesterol levels in patients with schizophrenia treated with typical or atypical antipsychotics.

Authors:  Jean-Pierre Lindenmayer; Pal Czobor; Jan Volavka; Leslie Citrome; Brian Sheitman; Joseph P McEvoy; Thomas B Cooper; Miranda Chakos; Jeffrey A Lieberman
Journal:  Am J Psychiatry       Date:  2003-02       Impact factor: 18.112

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  16 in total

1.  Online community use predicts abstinence in combined Internet/phone intervention for smoking cessation.

Authors:  George D Papandonatos; Bahar Erar; Cassandra A Stanton; Amanda L Graham
Journal:  J Consult Clin Psychol       Date:  2016-04-21

2.  Statistics in Brief: An Introduction to the Use of Propensity Scores.

Authors:  Maria C S Inacio; Yuexin Chen; Elizabeth W Paxton; Robert S Namba; Steven M Kurtz; Guy Cafri
Journal:  Clin Orthop Relat Res       Date:  2015-03-13       Impact factor: 4.176

3.  Metal-on-conventional polyethylene total hip arthroplasty bearing surfaces have a higher risk of revision than metal-on-highly crosslinked polyethylene: results from a US registry.

Authors:  Elizabeth W Paxton; Maria C S Inacio; Robert S Namba; Rebecca Love; Steven M Kurtz
Journal:  Clin Orthop Relat Res       Date:  2015-03       Impact factor: 4.176

Review 4.  Propensity Score: an Alternative Method of Analyzing Treatment Effects.

Authors:  Oliver Kuss; Maria Blettner; Jochen Börgermann
Journal:  Dtsch Arztebl Int       Date:  2016-09-05       Impact factor: 5.594

5.  Attention-deficit/hyperactivity disorder severity, diagnosis, & later academic achievement in a national sample.

Authors:  Jayanti Owens; Heide Jackson
Journal:  Soc Sci Res       Date:  2016-06-25

6.  Adolescent drinking and motivated decision-making: a cotwin-control investigation with monozygotic twins.

Authors:  Stephen M Malone; Monica Luciana; Sylia Wilson; Jordan C Sparks; Ruskin H Hunt; Kathleen M Thomas; William G Iacono
Journal:  Behav Genet       Date:  2014-03-28       Impact factor: 2.805

7.  Reciprocal relations between coalition functioning and the provision of implementation support.

Authors:  Louis D Brown; Mark E Feinberg; Valerie B Shapiro; Mark T Greenberg
Journal:  Prev Sci       Date:  2015-01

8.  Alcohol Use and Food Insecurity Among People Living with HIV in Mbarara, Uganda and St. Petersburg, Russia.

Authors:  Gregory J Patts; Debbie M Cheng; Nneka Emenyonu; Carly Bridden; Natalia Gnatienko; Christine A Lloyd-Travaglini; Christine Ngabirano; Tatiana Yaroslavtseva; Winnie R Muyindike; Sheri D Weiser; Evgeny M Krupitsky; Judith A Hahn; Jeffrey H Samet
Journal:  AIDS Behav       Date:  2017-03

9.  Use of an online smoking cessation community promotes abstinence: Results of propensity score weighting.

Authors:  Amanda L Graham; George D Papandonatos; Bahar Erar; Cassandra A Stanton
Journal:  Health Psychol       Date:  2015-12       Impact factor: 4.267

Review 10.  Brains, bones, and aging: psychotropic medications and bone health among older adults.

Authors:  Monique J Brown; Briana Mezuk
Journal:  Curr Osteoporos Rep       Date:  2012-12       Impact factor: 5.096

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