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Sem Paths to Networks Westland

A critical survey of the history, methods, and practical application of structural equation modeling, guiding researchers from the origins of path analysis to the future of network science.

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What it’s about

This book provides a comprehensive and critical guide to the world of structural equation modeling (SEM) for researchers and doctoral students. It traces the evolution of path analysis methodologies from their roots in genetics with Sewall Wright, through the divergent developments of the Scandinavian school (PLS-PA, LISREL) and the Chicago school (systems of regression equations). The author demystifies the statistical underpinnings of each approach, highlighting their unique strengths, weaknesses, and the often-misrepresented controversies surrounding them. It offers indispensable practical advice on crucial research design aspects, including data collection, calculating adequate sample size, and the proper treatment of survey data, particularly the pitfalls of Likert scales. By equipping readers with a deep understanding of the assumptions and limitations of these powerful tools, the book aims to prevent common errors and elevate the quality of quantitative research, ultimately showing how the path-based thinking of SEM is merging into the broader, more powerful domain of network analysis.

The through-line

Who it’s for
A quantitative social science researcher or doctoral student who needs to test complex theoretical models involving unobservable concepts like 'trust' or 'satisfaction'. They want to produce rigorous, defensible, and publishable findings.
The problem
The researcher is confronted with a confusing landscape of SEM methodologies (PLS-PA, LISREL, etc.) and software, each with conflicting claims, arcane assumptions, and inadequate guidance on critical issues like sample size calculation and handling survey data. They feel uncertain about their methodological choices, anxious that their results might be invalid or rejected by reviewers, and fearful of inadvertently contributing to the proliferation of 'bad science'.
The plan
  1. Understand the historical context and statistical underpinnings of different SEM methods.
  2. Learn the specific strengths and weaknesses of PLS-PA, LISREL, and Systems of Regression to choose the right tool for your research.
  3. Master the principles of calculating adequate sample size and properly handling Likert scale data.
  4. Adopt a rigorous paradigm for model specification, testing, and interpretation.
  5. See how path modeling is evolving into the broader science of network analysis.
The payoff
The researcher confidently designs robust studies, justifies their methodological choices, and produces valid, defensible results. · Their work is published in high-impact journals and contributes meaningfully to their field. · They are recognized as a methodologically rigorous and thoughtful scholar.

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