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A Step-by-Step Guide to Exploratory Factor Analysis with SPSS

A practical, formula-light, step-by-step guide to conducting exploratory factor analysis (EFA) in SPSS using evidence-based best practices.

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What it’s about

Exploratory factor analysis is over a century old and ubiquitous across the behavioral, medical, and social sciences, yet surveys repeatedly show it is routinely misapplied because researchers receive little formal training and lean on poor software defaults. Marley Watkins answers this gap with a concise, accessible, applied manual that walks the reader through every decision step of an EFA—choosing variables and participants, screening data, judging whether EFA is appropriate, selecting the model, extraction method, number of factors, rotation, interpretation, and reporting—each illustrated with annotated SPSS screenshots, syntax, downloadable datasets, and scholarly citations. With minimal mathematics and a calm, jargon-light tone, the book equips students and seasoned researchers alike to produce defensible, replicable factor-analytic results and to respond confidently to editorial reviews.

The through-line

Who it’s for
An applied researcher or graduate student who wants to conduct a credible, publishable exploratory factor analysis in SPSS.
The problem
They must make many technical EFA decisions in SPSS with little training and unsound software defaults. They feel uncertain, intimidated by the math, and worried their analysis is wrong or indefensible.
The plan
  1. Follow the ten-step EFA decision checklist in order.
  2. Screen data and verify EFA is appropriate before analyzing.
  3. Choose the common factor model with a justified extraction method.
  4. Use multiple criteria (parallel analysis, MAP, scree, theory) to decide factor number.
  5. Apply oblique rotation, interpret competing models, and report every decision transparently.
The payoff
The reader produces defensible, replicable EFA results. · They can justify every analytic choice to reviewers with citations. · They confidently interpret, name, and report factors and understand when to use EFA versus CFA.

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