Evaluate College Impact on Income: Address Bias and Validity

Q: Evaluate College Impact on Income: Address Bias and Validity

This question evaluates competency in critiquing observational study design and analysis, including recognition of sampling bias and external validity issues, regression model assumptions, confounding, diagnostic reasoning, and the distinction between descriptive and causal inference.

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Question

Study Setup

You have an observational, cross-sectional dataset of 1,000 adult Mountain View residents. The outcome is individual annual income (pre-tax). The exposure is a binary indicator of having completed a 4-year college degree (College = 1 if yes, 0 otherwise).

Question

Is fitting a simple linear regression of income on a binary college indicator appropriate for this data? Discuss:

Sampling bias and external validity.
Model validity and assumptions (distributional form, confounding, diagnostics).
Better analytic alternatives for both descriptive and causal goals.

Evaluate College Impact on Income: Address Bias and Validity

Study Setup

Question

Solution

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