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Quantitative Research Methods

Elsevier Inc.
DOI: 10.1016/b978-0-12-373951-3.00034-x
  • Causal Inference
  • Classification
  • Experimental Design
  • General Linear Model
  • Generalizability
  • Generalized Linear Model
  • Longitudinal Data Analysis
  • Measurement
  • Missing Data
  • Multilevel Modeling
  • Path Analysis
  • Quantitative Research
  • Quasi-Experimental Design
  • Reliability
  • Structural Equation Modeling
  • Validity
  • Design
  • Logic


Abstract Scientific knowledge is only as sound as the research methods used to obtain it. Quantitative research methods encompass three broad categories: design, measurement, and analysis issues. The key features and elements within each of these three areas are outlined in the article. For design issues, sampling and generalizabilty as well as randomized and quasi-experimental designs for causal inference are discussed. For measurement issues, different types of reliability and validity of measurement are presented. For analysis issues, the commonly used analysis techniques to quantify the relationships among variables are introduced, including the techniques for different types of outcome, the techniques for cross-sectional and longitudinal data, the techniques to deal with measurement error and missing data, the techniques to take into account dependency among observations, and the techniques to classify subjects. The article concludes with general recommendations to researchers.

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