Data Interview Question

Incorporating Additional Variables in Regression Analysis

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Requirements Clarification & Assessment

  1. Understanding the Problem Context

    • Determine the primary objective of the regression model. Is it for prediction, inference, or both?
    • Identify the dependent variable and the existing independent variables (m variables).

  2. Data Exploration for New Variables

    • Analyze the source and nature of the additional n variables.
    • Evaluate the frequency and accuracy of data collection for these variables.
    • Assess the completeness and quality of the data.

  3. Relevance and Theoretical Justification

    • Ensure the new variables have theoretical backing or empirical evidence supporting their inclusion.
    • Determine how these variables relate to the dependent variable and existing variables.

  4. Preliminary Data Analysis

    • Perform exploratory data analysis (EDA) to understand distributions, outliers, and potential relationships.
    • Check for missing values and plan for imputation if necessary.