Literature DB >> 26293167

Falsification Testing of Instrumental Variables Methods for Comparative Effectiveness Research.

Steven D Pizer1.   

Abstract

OBJECTIVES: To demonstrate how falsification tests can be used to evaluate instrumental variables methods applicable to a wide variety of comparative effectiveness research questions. STUDY
DESIGN: Brief conceptual review of instrumental variables and falsification testing principles and techniques accompanied by an empirical application. Sample STATA code related to the empirical application is provided in the Appendix. EMPIRICAL APPLICATION: Comparative long-term risks of sulfonylureas and thiazolidinediones for management of type 2 diabetes. Outcomes include mortality and hospitalization for an ambulatory care-sensitive condition. Prescribing pattern variations are used as instrumental variables.
CONCLUSIONS: Falsification testing is an easily computed and powerful way to evaluate the validity of the key assumption underlying instrumental variables analysis. If falsification tests are used, instrumental variables techniques can help answer a multitude of important clinical questions. © Health Research and Educational Trust.

Entities:  

Keywords:  Comparative effectiveness research; big data; causal inference; falsification testing; instrumental variables

Mesh:

Substances:

Year:  2015        PMID: 26293167      PMCID: PMC4799892          DOI: 10.1111/1475-6773.12355

Source DB:  PubMed          Journal:  Health Serv Res        ISSN: 0017-9124            Impact factor:   3.402


  32 in total

1.  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

2.  Two-stage residual inclusion estimation: addressing endogeneity in health econometric modeling.

Authors:  Joseph V Terza; Anirban Basu; Paul J Rathouz
Journal:  J Health Econ       Date:  2007-12-04       Impact factor: 3.883

3.  The hazards of stroke case selection using administrative data.

Authors:  Dean M Reker; Amy K Rosen; Helen Hoenig; Dan R Berlowitz; Judith Laughlin; Leigh Anderson; Clifford R Marshall; Maude Rittman
Journal:  Med Care       Date:  2002-02       Impact factor: 2.983

4.  Who is the marginal patient? Understanding instrumental variables estimates of treatment effects.

Authors:  K M Harris; D K Remler
Journal:  Health Serv Res       Date:  1998-12       Impact factor: 3.402

5.  Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group.

Authors:  R B D'Agostino
Journal:  Stat Med       Date:  1998-10-15       Impact factor: 2.373

6.  Credible Mendelian randomization studies: approaches for evaluating the instrumental variable assumptions.

Authors:  M Maria Glymour; Eric J Tchetgen Tchetgen; James M Robins
Journal:  Am J Epidemiol       Date:  2012-01-12       Impact factor: 4.897

7.  Positive predictive value of the diagnosis of acute myocardial infarction in an administrative database.

Authors:  L A Petersen; S Wright; S L Normand; J Daley
Journal:  J Gen Intern Med       Date:  1999-09       Impact factor: 5.128

Review 8.  Sulfonylureas in NIDDM.

Authors:  L C Groop
Journal:  Diabetes Care       Date:  1992-06       Impact factor: 19.112

9.  Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). UK Prospective Diabetes Study (UKPDS) Group.

Authors: 
Journal:  Lancet       Date:  1998-09-12       Impact factor: 79.321

10.  Effect of rosiglitazone on the risk of myocardial infarction and death from cardiovascular causes.

Authors:  Steven E Nissen; Kathy Wolski
Journal:  N Engl J Med       Date:  2007-05-21       Impact factor: 91.245

View more
  13 in total

1.  Rural-Urban Differences in the Effect of Follow-Up Care on Postdischarge Outcomes.

Authors:  Matthew Toth; Mark Holmes; Courtney Van Houtven; Mark Toles; Morris Weinberger; Pam Silberman
Journal:  Health Serv Res       Date:  2016-08-08       Impact factor: 3.402

2.  Discontinuity of Medicaid Coverage: Impact on Cost and Utilization Among Adult Medicaid Beneficiaries With Major Depression.

Authors:  Xu Ji; Adam S Wilk; Benjamin G Druss; Cathy Lally; Janet R Cummings
Journal:  Med Care       Date:  2017-08       Impact factor: 2.983

3.  Falsification Tests for Instrumental Variable Designs With an Application to Tendency to Operate.

Authors:  Luke Keele; Qingyuan Zhao; Rachel R Kelz; Dylan Small
Journal:  Med Care       Date:  2019-02       Impact factor: 2.983

4.  School racial segregation and long-term cardiovascular health among Black adults in the US: A quasi-experimental study.

Authors:  Min Hee Kim; Gabriel L Schwartz; Justin S White; M Maria Glymour; Sean F Reardon; Kiarri N Kershaw; Scarlett Lin Gomez; Daniel F Collin; Pushkar P Inamdar; Guangyi Wang; Rita Hamad
Journal:  PLoS Med       Date:  2022-06-21       Impact factor: 11.613

5.  Empirical Anti-MRSA vs Standard Antibiotic Therapy and Risk of 30-Day Mortality in Patients Hospitalized for Pneumonia.

Authors:  Barbara Ellen Jones; Jian Ying; Vanessa Stevens; Candace Haroldsen; Tao He; McKenna Nevers; Matthew A Christensen; Richard E Nelson; Gregory J Stoddard; Brian C Sauer; Peter M Yarbrough; Makoto M Jones; Matthew Bidwell Goetz; Tom Greene; Matthew H Samore
Journal:  JAMA Intern Med       Date:  2020-04-01       Impact factor: 21.873

6.  The Price Elasticity of Specialty Drug Use: Evidence from Cancer Patients in Medicare Part D.

Authors:  Jeah Kyoungrae Jung; Roger Feldman; A Marshall McBean
Journal:  Forum Health Econ Policy       Date:  2017-05-26

7.  Outcomes of primary care delivery by nurse practitioners: Utilization, cost, and quality of care.

Authors:  Chuan-Fen Liu; Paul L Hebert; Jamie H Douglas; Emily L Neely; Christine A Sulc; Ashok Reddy; Anne E Sales; Edwin S Wong
Journal:  Health Serv Res       Date:  2020-01-13       Impact factor: 3.402

8.  Instrumental variables: Don't throw the baby out with the bathwater.

Authors:  Luke Keele; Dylan Small
Journal:  Health Serv Res       Date:  2019-03-11       Impact factor: 3.402

9.  The promise and perils of big data in healthcare.

Authors:  Austin B Frakt; Steven D Pizer
Journal:  Am J Manag Care       Date:  2016-02       Impact factor: 3.247

10.  Comparative Outcomes of Percutaneous Coronary Intervention for ST-Segment-Elevation Myocardial Infarction Among Medicare Beneficiaries With Multivessel Coronary Artery Disease: An National Cardiovascular Data Registry Research to Practice Project.

Authors:  Eric A Secemsky; Neel Butala; Aishwarya Raja; Rohan Khera; Yongfei Wang; Jeptha P Curtis; Thomas M Maddox; Salim S Virani; Ehrin J Armstrong; Kendrick A Shunk; Ralph G Brindis; Deepak Bhatt; Robert W Yeh
Journal:  Circ Cardiovasc Interv       Date:  2021-08-10       Impact factor: 7.514

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.