| Author |
Publication year |
Journal name |
Title |
Main features |
| Greenland |
2000 |
International Journal of Epidemiology |
An introduction to instrumental variables for epidemiologists |
-basic introduction with an empirical example
-link with randomized studies with non-compliance
-estimated bound for the exposure effects |
| Martens et al. |
2006 |
Epidemiology |
Instrumental variables: application and limitations |
-fundamental issues are described with several practical details using graphical representation |
| Hernan and Robins |
2006 |
Epidemiology |
Instruments for causal inference: an epidemiologists dream? |
-overview of IV analysis with explanation of several key assumptions
-highlights limitations and emphasis on estimating parameters of IV analysis |
| Rassen et al. |
2009 |
Journal of Clinical Epidemiology |
Instrumental variables I: instrumental variables exploit natural variation in nonexperimental data to estimate causal relationships |
-demonstrates how IV analysis arises from an analogous but potentially impossible RCT design
-shows estimation of effects with an empirical example |
| Rassen et al. |
2009 |
Journal of Clinical Epidemiology |
Instrumental variables II: instrumental variable application—in 25 variations, the physician prescribing preference generally was strong and reduced covariate imbalance |
-assesses the overall relationship between strength and imbalance of confounders between IV categories with an empirical example
-assesses several possible IVs |
| Rassen et al. |
2009 |
American Journal of Epidemiology |
Instrumental variable analysis for estimation of treatment effects with dichotomous outcomes |
-reviews commonly used IV estimation methods for binary outcome and compared them in empirical examples |
| Brookhart et al. |
2010 |
Pharmacoepidemiology and Drug Safety |
Instrumental variable methods in comparative safety and effectiveness research |
-guidance on reporting of IV analysis with an empirical example |
| Clarke and Windmeijer |
2010 |
Journal of American Statistical Association |
Instrumental variable estimators for binary outcomes |
-estimation methods of IV analysis for binary outcome with mathematical descriptions |
| Chen and Briesacher |
2011 |
Journal of Clinical Epidemiology |
Use of instrumental variable in prescription drug research with observational data: a systematic review |
-review of practice of IV analysis in epidemiology
|
| Palmer et al. |
2011 |
American Journal of Epidemiology |
Instrumental variable estimation of causal risk ratios and causal odds ratios in Mendelian randomization |
-overview of commonly used IV estimation methods for continuous exposure
-empirical example of Mendelian randomization study |
| Davies et al. |
2013 |
Epidemiology |
Issues in the reporting and conduct of instrumental variable studies: a systematic review |
- review of practice of IV analysis in epidemiology -focus on target parameter (e.g. RD, OR)
-reviews methods used to estimate standard errors
- proposes a checklist of information to be reported by studies using instrumental variables |
| Swanson and Hernan |
2013 |
Epidemiology |
Commentary: How to report instrumental variable analyses (suggestions welcome) |
-provided flow chart for reporting of IV analyses
|
| Baiocchi et al. |
2014 |
Statistics in Med |
Instrumental variable methods for causal inference |
-generic tutorial and guidelines of IV analysis with an empirical example |
| Garabedian et al. |
2014 |
Annals of Internal Medicine |
Potential Bias of Instrumental Variable Analyses for Observational Comparative Effectiveness Research |
-this review found that the results of IV analyses may be biased substantially if the IV and outcome are related through an unadjusted third variable: an “IV–outcome confounder”
- the authors caution against overreliance on IV studies comparative effectiveness research |
