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Multiple Regression Analysis/Evidence
Method evidence record

Multiple Regression Analysis

Multiple regression analysis is a statistical method for modeling the relationship between a continuous dependent variable and two or more independent variables (predictors). Originating from Gauss's early 19th-century work and formalized by Draper and Smith (1966), it estimates linear equations predicting outcomes from multiple predictors while accounting for confounding relationships, making it indispensable in epidemiology, economics, psychology, and clinical research.

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Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Multiple Linear Regression
Taxonomic method record · process-pipeline / research-statistics
  • Draper, N. R., & Smith, H. (1966). Applied Regression Analysis. John Wiley & Sons. · URL
  • Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (1992). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum. · URL
  • Marquardt, D. W. (1980). You should standardize the independent variables in your regression models. Discussion of a paper by G. David Knottnerus. Journal of the American Statistical Association, 75(369), 87–91. · URL
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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyAnalysis of Variance (ANOVA)machine-suggested · Relational suggestion, not evidence.Same method familyFactor Analysismachine-suggested · Relational suggestion, not evidence.Same method familyLogistic Regressionmachine-suggested · Relational suggestion, not evidence.Same method familyStructural Equation Modelingmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

3 recorded citations, copied from the method source record.

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