SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
One model to rule them all? Using machine learning algorithms to determine the number of factors in exploratory factor analysis.
16 references·4 citing·25 second hop
One model to rule them all? Using machine learning algorithms to determine the number of factors in exploratory factor analysis. (2020)One model to rule them all? Using machine…How to determine the number of factors to retain in exploratory factor analysis: A comparison of extraction methods under realistic conditions. (2019)How to determine the number o…Exploratory factor analysis: Current use, methodological developments and recommendations for good practice (2019)Exploratory factor analysis: …An empirical Kaiser criterion. (2016)An empirical Kaiser criterion.The Hull Method for Selecting the Number of Common Factors (2011)The Hull Method for Selecting…Factor recovery by principal axis factoring and maximum likelihood factor analysis as a function of factor pattern and sample size (2011)Factor recovery by principal …Determining the number of factors to retain in an exploratory factor analysis using comparison data of known factorial structure. (2011)Determining the number of fac…psych: Procedures for Psychological, Psychometric, and Personality Research (2007)psych: Procedures for Psychol…An Overview of Analytic Rotation in Exploratory Factor Analysis (2001)An Overview of Analytic Rotat…Evaluating the use of exploratory factor analysis in psychological research. (1999)Evaluating the use of explora…An alternative "description of personality": The Big-Five factor structure. (1990)An alternative "description o…Comparison of five rules for determining the number of components to retain. (1986)Comparison of five rules for …A Second Generation Little Jiffy (1970)A Second Generation Little Ji…The Scree Test For The Number Of Factors (1966)The Scree Test For The Number…A Rationale and Test for the Number of Factors in Factor Analysis (1965)A Rationale and Test for the …The Application of Electronic Computers to Factor Analysis (1960)The Application of Electronic…Measurement of Inequality of Incomes (1921)Measurement of Inequality of …Factor Retention Using Machine Learning With Ordinal Data (2022)Factor Retention Using Machin…Factor Retention in Exploratory Factor Analysis With Missing Data (2021)Factor Retention in Explorato…Exploratory Graph Analysis for Factor Retention: Simulation Results for Continuous and Binary Data (2021)Exploratory Graph Analysis fo…Determining the Number of Attributes in Cognitive Diagnosis Modeling (2021)Determining the Number of Att…The Handbook of Social Psychology (1969)Alternative Ways of Assessing Model Fit (1992)Handbook on Constructing Composite Indicators: Methodology and User Guide (2008)Bibliometric Methods in Management and Organization (2014)Assessing measurement model quality in PLS-SEM using confirmatory composite analysis (2019)The Varimax Criterion for Analytic Rotation in Factor Analysis (1958)Little Jiffy, Mark Iv (1974)Factor Retention Decisions in Exploratory Factor Analysis: a Tutorial on Parallel Analysis (2004)Sample size in factor analysis. (1999)Exploratory Structural Equation Modeling, Integrating CFA and EFA: Application to Students' Evaluations of University Teaching (2009)Initial construction of a maladaptive personality trait model and inventory for DSM-5 (2011)The Pittsburgh sleep quality index as a screening tool for sleep dysfunction in clinical and non-clinical samples: A systematic review and meta-analysis (2015)Relation of sample size to the stability of component patterns. (1988)Preliminary Psychometric Properties of the Acceptance and Action Questionnaire–II: A Revised Measure of Psychological Inflexibility and Experiential Avoidance (2011)Best Practices for Developing and Validating Scales for Health, Social, and Behavioral Research: A Primer (2018)The Eating Attitudes Test: psychometric features and clinical correlates (1982)A single-parameter generalization of the Gini indices of inequality (1980)A Generalization of the Quasilinear Mean with Applications to the Measurement of Income Inequality and Decision Theory Resolving the Allais Paradox (1983)Chapter 2 Measurement of inequality (2000)An Introduction to the Five‐Factor Model and Its Applications (1992)The Big Five Trait taxonomy: History, measurement, and theoretical perspectives. (1999)Grit: Perseverance and passion for long-term goals. (2007)Detecting Common Method Bias (2019)Initial validation of the general attitudes towards Artificial Intelligence Scale (2020)Profiling teachers' readiness for online teaching and learning in higher education: Who's ready? (2020)
this work references cited by second hop

References

  • 1966The Scree Test For The Number Of Factors13,549 cited
  • 1960The Application of Electronic Computers to Factor Analysis12,390 cited
  • 1999Evaluating the use of exploratory factor analysis in psychological research.9,564 cited
  • 1965A Rationale and Test for the Number of Factors in Factor Analysis8,818 cited
  • 1990An alternative "description of personality": The Big-Five factor structure.6,631 cited
  • 1970A Second Generation Little Jiffy4,816 cited
  • 1986Comparison of five rules for determining the number of components to retain.3,135 cited
  • 2007psych: Procedures for Psychological, Psychometric, and Personality Research2,973 cited
  • 1921Measurement of Inequality of Incomes1,729 cited
  • 2001An Overview of Analytic Rotation in Exploratory Factor Analysis1,140 cited
  • 2019Exploratory factor analysis: Current use, methodological developments and recommendations for good practice636 cited
  • 2011The Hull Method for Selecting the Number of Common Factors566 cited
  • 2011Determining the number of factors to retain in an exploratory factor analysis using comparison data of known factorial structure.533 cited
  • 2016An empirical Kaiser criterion.436 cited
  • 2011Factor recovery by principal axis factoring and maximum likelihood factor analysis as a function of factor pattern and sample size

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

385 cited
  • 2019How to determine the number of factors to retain in exploratory factor analysis: A comparison of extraction methods under realistic conditions.349 cited
  • Cited by

    • 2021Exploratory Graph Analysis for Factor Retention: Simulation Results for Continuous and Binary Data55 cited
    • 2021Factor Retention in Exploratory Factor Analysis With Missing Data53 cited
    • 2022Factor Retention Using Machine Learning With Ordinal Data41 cited
    • 2021Determining the Number of Attributes in Cognitive Diagnosis Modeling31 cited