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Exploratory Mediation Analysis via Regularization.

Sarfaraz Serang1, Ross Jacobucci1, Kim C Brimhall1

  • 1University of Southern California.

Structural Equation Modeling : a Multidisciplinary Journal
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Summary
This summary is machine-generated.

We introduce exploratory mediation analysis via regularization (XMed), a novel two-stage method for identifying mediators. XMed outperforms traditional techniques in accurately identifying mediators and provides unbiased estimates.

Keywords:
exploratory mediation analysislassomediationregularization

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Area of Science:

  • Psychological science
  • Statistical methodology
  • Social science research

Background:

  • Conventional mediation analysis methods are often rooted in confirmatory traditions, limiting their effectiveness in exploratory research.
  • Identifying potential mediators in complex processes requires flexible and robust analytical approaches.

Purpose of the Study:

  • To propose a novel two-stage approach, exploratory mediation analysis via regularization (XMed), designed for exploratory contexts.
  • To address the limitations of conventional methods in identifying mediators in exploratory mediation analysis.

Main Methods:

  • Developed a two-stage approach integrating regularization techniques for exploratory mediation analysis.
  • Evaluated the performance of XMed against conventional methods in identifying mediators.

Main Results:

  • Exploratory mediation analysis via regularization (XMed) correctly identifies mediators more frequently than conventional approaches.
  • XMed yields unbiased estimates of mediation effects, enhancing reliability.

Conclusions:

  • XMed offers a superior framework for exploratory mediation analysis, improving the accuracy and validity of mediator identification.
  • The proposed method is applicable to various research domains, as demonstrated by an example in college admissions and enrollment research.