조사연구 권 호 특집논문 1) 탐색적요인분석의오 남용문제와교정 * Misuse of Exploratory Factor Analysis and Its Remedies 2) a) 주제어 탐색적요인분석 주성분분석 구성체 설명분산 요인의수 요인회전 방법 Though the f

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1 조사연구 권 호 특집논문 1) 탐색적요인분석의오 남용문제와교정 * Misuse of Exploratory Factor Analysis and Its Remedies 2) a) 주제어 탐색적요인분석 주성분분석 구성체 설명분산 요인의수 요인회전 방법 Though the factor analysis is widely used in social science research, researchers make frequently unreasonable decisions when conducting these analyses. The study reviews and recommends which decisions must be made when conducting factor analyses.

2 조사연구 This study contends that one of the main reasons of the misuse is because researchers understand exploratory factor analysis(efa) in the frame of principal component analysis(pca). The paper provides methodological and statistical comparisons between two methods and the consequences of interpreting EFA results in the frame of PCA. This article also address the issues of data fitting method, fit indices, choosing number of factors, and treating missing data and categorical data. Key words : exploratory factor analysis, principal component analysis, explained variance, number of factors, factor rotation methods Ⅰ. 서론

3 탐색적요인분석의오남용문제와교정

4 조사연구 II. 요인분석의원리

5 탐색적요인분석의오남용문제와교정 그림 요인분석모형의경로도 측정변수 공통요인 공통요인

6 조사연구

7 탐색적요인분석의오남용문제와교정 Ⅲ. 선택 1: 주성분분석대요인분석 1. 주성분분석

8 조사연구

9 탐색적요인분석의오남용문제와교정 2. 잠재변수 ( 요인 ) 와성분점수 3. 요인분석과주성분분석의비교

10 조사연구

11 탐색적요인분석의오남용문제와교정 Ⅳ. 선택 2: 요인분석의자료적합방법 log log

12 조사연구 1. 서열척도의요인분석

13 탐색적요인분석의오남용문제와교정

14 조사연구 Ⅴ. 선택 3: 모형의양호도판단

15 탐색적요인분석의오남용문제와교정 설명분산

16 조사연구 설명분산

17 탐색적요인분석의오남용문제와교정

18 조사연구 Ⅵ. 선택 4: 요인부하량행렬의회전방법

19 탐색적요인분석의오남용문제와교정

20 조사연구 Ⅶ. 선택 5: 요인의수의결정

21 탐색적요인분석의오남용문제와교정

22 조사연구 Ⅷ. 선택 6: 결측치처리방법의선택

23 탐색적요인분석의오남용문제와교정 Ⅸ. 선택 7: 소프트웨어의선택

24 조사연구 Ⅹ. 맺는말

25 탐색적요인분석의오남용문제와교정 참고문헌 : 7: Amemiya, Y. and T.W. Anderson Asymptotic Chi-Square Tests for a Large Class of Factor Analysis Models. Annals of Statistics 18: Anderson, T.W. and Y. Amemiya The Asymptotic Normal Distribution of Estimators in Factor Analysis under General Conditions. Annals of Statistics 16: Bartholomew, D.J History of Factor Analysis: A Statistical Perspective. Encyclopedia of Statistics in Behavioural Science Vol.2.: , John Wiley and Sons Limited. Browne, M.W. 1972a. Orthogonal Rotation to a Partially Specified Target. British Journal of Mathematical and Statistical Psychology 25: Browne, M.W. 1972b. Oblique Rotation to a Partially Specified Target. British Journal of Mathematical and Statistical Psychology 25: Browne, M.W Generalized Least Squares Estimators in the Analysis

26 조사연구 of Covariance Structures. ETS Research Bulletin Series 1973: Browne, M.W Covariance Structure. In D.M. Hawkins(ed.). Topics in Applied Multivariate Analysis : Cambridge: Cambridge University Press. Browne, M.W Asymtotically DistributionFree Methods for the Analysis of Covariance Structures. British Journal of Mathematical and Statistical Psychology 37: Browne, M.W., and R. Cudeck Alternative Ways of Assessing Model Fit. In K.A. Bollen & J.S. Long(eds.). Testing structural equation models(pp ). Beverly Hills, CA: SAGE Browne, M.W., R. Cudeck, K. Tateneni, and G. Mels CEFA: Comprehensive Exploratory Factor Analysis, Version 2.00 [Computer software and manual]. Retrieved from Browne, M.W., R.C. MacCallum, C. Kim, B.L. Anderson, and R. Glaser When Fit Indices and Residuals Are Incompatible. Psychological Methods 7: Browne, M.W. and A. Shapiro Robustness of Normal Theory Methods in the Analysis of Linear Latent Variate Models. British Journal of Mathematical and Statistical Psychology 41: Cattell, R.B The Scree Test for the Number of Factors. Multivariate Behavioral Research 1: Cattell, R.B. and S. Vogelmann A Comprehensive Trial of the Scree and KG Criteria for Determining the Number of Factors. Journal of Educational Measurement 14: Cronbach, L.J. and P. Meehl Construct Validity in Psychological Tests. Psychological Bulletin 52: Fabrigar, L.R., D.T. Wegener, R.C. MacCallum, and E.J. Strahan Evaluating the Use of Exploratory Factor Analysis in Psychological Research. Psychological Methods 4:

27 탐색적요인분석의오남용문제와교정 Floyd, F.J. and K.F. Widaman Factor Analysis in the Development and Refinement of Clinical Assessment Instruments. Psychological Assessment 7: Graham, J.W., P.E. Cumsille, and E. Elek-Fisk Methods for Handling Missing Data. In J.A. Schinka & W.F. Velicer(eds.). Research Methods in Psychology(pp ). Volume 2 of Handbook of Psychology (I.B. Weiner, EditorinChief). New York: John Wiley & Sons. Guttman, L Some Necessary Conditions for Common Factor Analysis. Psychometrika 19: Hakstian, A.R., W.T. Rogers, and R.B. Cattell The Behavior of Number offactors Rules with Simulated Data. Multivariate Behavioral Research 17: Hart, B. and C. Spearman General Ability, Its Existence and Nature. British Journal of Psychology 5: Hayton, J.C., D.G. Allen, and V. Scarpello "Factor Retention Decisions in Exploratory Factor analysis: A Tutorial on Parallel Analysis." Organizational Research Methods 7: Hotelling, H Analysis of a Complex of Statistical Variables into Principal Components. Journal of Educational Psychology 24: Horn, J.L A Rationale and Test for the Number of Factors in Factor Analysis. Psychometrika 30: Hu, L.T. and P.M. Bentler Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria versus New Alternatives. Structural Equation Modeling 6: Kaiser, H.F The Application of Electronic Computers to Factor Analysis. Educational and Psychological Measurement 20: Kaiser, H.F A Note on Guttman's Lower Bound for the Number of Common Factors. British Journal of Statistical Psychology 14: 1-2.

28 조사연구 Ledesma, R.D. and P. Valero-Mora Determining the Number of Factors to Retain in EFA: An Easy-to-use Computer Program for Carrying out Parallel Analysis. Practical Assessment, Research & Evaluation 12: Linn, R.L A Monte Carlo Approach to the Number of Factors Problem. Psychometrika 33: Little, R.J.A. and D.B. Rubin Statistical Analysis with Missing Data (2nd ed.). New York: Wiley. Margenau, H The Competence and Limitations of Scientific Method. Journal of Operations Research Society of America 3: Pearson, K On Lines and Planes of Closest Fit to Systems of Points in Space. The London, Edinburgh and Dublin Philosophical Magazine and Journal of Science, Sixth Series 2: Pigott, T.D A Review of Methods for Missing Data. Educational Research and Evaluation 7: Preacher, K.J. and R.C. MacCallum Repairing Tom Swift s Electric Factor Analysis Machine. Understanding Statistics 2: Preacher, K.J., G. Zhang, C. Kim, and G. Mels Choosing the Optimal Number of Factors in Exploratory Factor Analysis: A Model Selection Perspective. Multivariate Behavioral Research 48: Rubin, D.B Inference and Missing Data. Biometrika 63: Schafer, J.L. and J.W. Graham Missing Data: Our View of the State of the Art. Psychological Methods 7: Shapiro, A Robustness Properties of the MDF Analysis of Moment Structures. South African Statistical Journal 21: Spearman, C General Intelligence: Objectively Determined and Measured. American Journal of Psychology 15: Thurstone, L.L The Vectors of Mind: MultipleFactor Analysis for the Isolation of Primary Traits. Chicago: University of Chicago Press. Thurstone, L.L Primary Mental Abilities. Psychometric Monograph 1. Chicago: University of Chicago Press.

29 탐색적요인분석의오남용문제와교정 Yuan, K-H and P.M. Bentler On Asymptotic Distributions of Normal Theory MLE in Covariance Structure Analysis under Some Nonnormal Distributions. Statistics and Probability Letters 42: Zwick, W.R. and W.F. Velicer Factors Influencing Four Rules for Determining the Number of Components to Retain. Multivariate Behavioral Research 17: Zwick, W.R. and W.F. Velicer Comparison of Five Rules for Determining the Number of Components to Retain. Psychological Bulletin 99: < 2016/1/31, 2016/2/17, 2016/2/22>

조사연구 권 호 연구논문 한국노동패널조사자료의분석을위한패널가중치산출및사용방안사례연구 A Case Study on Construction and Use of Longitudinal Weights for Korea Labor Income Panel Survey 2)3) a

조사연구 권 호 연구논문 한국노동패널조사자료의분석을위한패널가중치산출및사용방안사례연구 A Case Study on Construction and Use of Longitudinal Weights for Korea Labor Income Panel Survey 2)3) a) b) 조사연구 주제어 패널조사 횡단면가중치 종단면가중치 선형혼합모형 일반화선형혼 합모형