Making inferences on treatment effects from real world data: propensity scores, confounding by indication, and other perils for the unwary in observational research

BMJ. 2013 Nov 11:347:f6409. doi: 10.1136/bmj.f6409.

Authors

Nick Freemantle¹, Louise Marston, Kate Walters, John Wood, Matthew R Reynolds, Irene Petersen

Affiliation

¹ Department of Primary Care and Population Health, UCL Medical School (Royal Free Campus), London NW3 2PF, UK.

PMID: 24217206
DOI: 10.1136/bmj.f6409

No abstract available

MeSH terms

Bias
Confounding Factors, Epidemiologic
Humans
Observational Studies as Topic / statistics & numerical data*
Propensity Score*
Randomized Controlled Trials as Topic / statistics & numerical data*
Reproducibility of Results
Research
Research Design / standards*
Treatment Outcome