Quantitative Methods Guide

A skill for designing and executing rigorous quantitative analyses in academic research. Covers the full pipeline from research question formulation through variable operationalization, model specification, estimation, diagnostics, and interpretation, with emphasis on regression modeling as the workhorse of empirical research.

Overview

Quantitative methods form the foundation of empirical research across the social sciences, health sciences, economics, education, and many STEM fields. This skill provides a structured approach to the entire quantitative analysis workflow, ensuring that researchers make methodologically sound choices at each stage. It treats regression analysis as the central tool, covering ordinary least squares (OLS), logistic regression, Poisson regression, and multilevel models, while also addressing the broader issues of research design, measurement, and causal inference that determine whether regression results are meaningful.

The skill is designed for graduate students and researchers who have basic statistics knowledge but need guidance on applying methods correctly in their own research contexts.

Research Design and Variable Specification

From Question to Model

Research Question: "Does mentoring frequency affect publication output among
                    junior faculty, controlling for department size and funding?"

Step 1: Identify variables