Proxy Variables and the Generalizability of Study Results.

Area of Science:

• Epidemiology
• Biostatistics
• Health Services Research

Background:

• Self-selection into studies can bias results, limiting generalizability to the broader population.
• Standardization methods can adjust for biases but rely on observing common causes of participation and outcome, which are often unmeasured.
• Proxy variables offer an alternative when direct measurement of common causes is not feasible.

Purpose of the Study:

• To define and examine different types of proxy variables.
• To demonstrate how proxy variables can be utilized to achieve generalizable study results.
• To address the challenge of unobserved confounding in observational studies.

Main Methods:

• Exploiting proxies that independently influence participation or outcome to achieve conditional independence.
• Leveraging two proxies, each influencing either participation or outcome, to attain generalizability.
• Utilizing a single proxy that does not directly affect participation or outcome for approximate generalizability.

Main Results:

• Proxies influencing only participation or outcome can render these variables conditionally independent, ensuring perfect generalizability.
• Using two proxies, one for participation and one for outcome, can achieve generalizability even without conditional independence.
• A single proxy, not directly influencing participation or outcome, can yield approximate generalizability.

Conclusions:

• Proxy variables are valuable tools for enhancing the external validity of research findings.
• Different types of proxies offer varying degrees of generalizability, from perfect to approximate.
• The strategic use of proxies can overcome limitations posed by unobserved confounding in observational research.