How to compare instrumental variable and conventional regression analyses using negative controls and bias plots

Area of Science:

• Pharmacoepidemiology
• Biostatistics
• Observational Research

Background:

• Observational pharmacoepidemiology studies face challenges with unmeasured confounding.
• Instrumental variable (IV) analysis is a potential method to address confounding.
• However, IV analyses can be less precise and harder to interpret than conventional regression.

Purpose of the Study:

• To describe and illustrate techniques for assessing bias in instrumental variable analyses compared to conventional regression.
• To evaluate the performance of negative control outcomes, negative control populations, and covariate balance tests.

Main Methods:

• The study employed three bias assessment techniques: negative control outcomes, negative control populations, and covariate balance tests.
• These methods were applied to analyze the effects of varenicline, a smoking cessation therapy, in primary care data.

Main Results:

• The described techniques provide a framework for evaluating the validity of instrumental variable analyses.
• Application to smoking cessation therapies demonstrated the utility of these bias assessment methods.

Conclusions:

• Negative control outcomes, negative control populations, and covariate balance tests are valuable tools for assessing bias in pharmacoepidemiological studies.
• These methods aid in determining whether instrumental variable or conventional regression analyses yield less biased results.
• The findings support the appropriate application of instrumental variable analysis in real-world data research.