参考文献

Adachi, K. (2020). Matrix-based introduction to multivariate data analysis (2nd ed.). Springer. https://doi.org/10.1007/978-981-15-4103-2

Akaike, H. (1998–1969). Information theory and an extension of the maximum likelihood principle. In E. Parzen, K. Tanabe, & G. Kitagawa (Eds.), Selected papers of Hirotugu Akaike (pp. 199–213). Springer (Original work published 1969). https://doi.org/10.1007/978-1-4612-1694-0_15(Original work published 1969)

Albers, S. (2010). PLS and success factor studies in marketing. In V. Esposito Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of partial least squares: concepts, methods and applications (pp. 409–425). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-32827-8

American Educational Research Association, American Psychological Association, & National Council on Measurement in Education (Eds.). (2011). Standards for educational and psychological testing. American Educational Research Association.

Asparouhov, T., & Muthén, B. (2009). Exploratory structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal, 16(3), 397–438. https://doi.org/10.1080/10705510903008204

Austin, P. C., & Merlo, J. (2017). Intermediate and advanced topics in multilevel logistic regression analysis. Statistics in Medicine, 36(20), 3257–3277. https://doi.org/10.1002/sim.7336

Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94. https://doi.org/10.1007/BF02723327

Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182. https://doi.org/10.1037/0022-3514.51.6.1173

Bartlett, M. S. (1950). Tests of significance in factor analysis. British Journal of Statistical Psychology, 3(2), 77–85. https://doi.org/10.1111/j.2044-8317.1950.tb00285.x

Bartlett, M. S. (1951). The effect of standardization on a χ2 approximation in factor analysis. Biometrika, 38(3/4), 337–344. https://doi.org/10.2307/2332580

Bauer, D. J., & Curran, P. J. (2005). Probing interactions in fixed and multilevel regression: inferential and graphical techniques. Multivariate Behavioral Research, 40(3), 373–400. https://doi.org/10.1207/s15327906mbr4003_5

Bayonne, E., Marin-Garcia, J. A., & Alfalla-Luque, R. (2020). Partial least squares (PLS) in operations management research: insights from a systematic literature review. Journal of Industrial Engineering and Management, 13(3), 565–597. https://doi.org/10.3926/jiem.3416

Beatty, P. C., & Willis, G. B. (2007). Research synthesis: the practice of cognitive interviewing. Public Opinion Quarterly, 71(2), 287–311. https://doi.org/10.1093/poq/nfm006

Bentler, P. M. (1983). Some contributions to efficient statistics in structural models: Specification and estimation of moment structures. Psychometrika, 48(4), 493–517. https://doi.org/10.1007/BF02293875

Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246. https://doi.org/10.1037/0033-2909.107.2.238

Berrío, Á. I., Gómez-Benito, J., & Arias-Patiño, E. M. (2020). Developments and trends in research on methods of detecting differential item functioning. Educational Research Review, 31, 100340. https://doi.org/10.1016/j.edurev.2020.100340

Böckenholt, U. (2017). Measuring response styles in Likert items. Psychological Methods, 22(1), 69–83. https://doi.org/10.1037/met0000106

Borsboom, D. (2005). Measuring the mind: conceptual issues in contemporary psychometrics. Cambridge University Press.

（ボースブーム，D.　仲嶺 真（監訳）仲嶺 真・下司 忠大・三枝 高大・須藤 竜之介・武藤 拓之（訳）（2022）．心を測る: 現代の心理測定における諸問題　金子書房）

Borsboom, D., Mellenbergh, G. J., & van Heerden, J. (2004). The concept of validity. Psychological Review, 111(4), 1061–1071. https://doi.org/10.1037/0033-295X.111.4.1061

Bowling, S. R., Khasawneh, M. T., Kaewkuekool, S., & Cho, B. R. (2009). A logistic approximation to the cumulative normal distribution. Journal of Industrial Engineering and Management, 2(1), 114–127. https://doi.org/10.3926/jiem.2009.v2n1.p114-127

Brown, A., & Maydeu-Olivares, A. (2011). Item response modeling of forced-choice questionnaires. Educational and Psychological Measurement, 71(3), 460–502. https://doi.org/10.1177/0013164410375112

Browne, M. W. (1968). A comparison of factor analytic techniques. Psychometrika, 33(3), 267–334. https://doi.org/10.1007/BF02289327

Browne, M. W. (2001). An overview of analytic rotation in exploratory factor analysis. Multivariate Behavioral Research, 36(1), 111–150. https://doi.org/10.1207/S15327906MBR3601_05

Chalmers, R. P. (2018). Model-based measures for detecting and quantifying response bias. Psychometrika, 83(3), 696–732. https://doi.org/10.1007/s11336-018-9626-9

Chen, W.-H., & Thissen, D. (1997). Local dependence indexes for item pairs using item response theory. Journal of Educational and Behavioral Statistics, 22(3), 265–289. https://doi.org/10.2307/1165285

Cho, E. (2023). Interchangeability between factor analysis, logistic IRT, and normal ogive IRT. Frontiers in Psychology, 14, 1267219. https://doi.org/10.3389/fpsyg.2023.1267219

Choi, Y.-J., & Asilkalkan, A. (2019). R packages for item response theory analysis: descriptions and features. Measurement: Interdisciplinary Research and Perspectives, 17(3), 168–175. https://doi.org/10.1080/15366367.2019.1586404

Cliff, N. (1988). The eigenvalues-greater-than-one rule and the reliability of components. Psychological Bulletin, 103(2), 276–279. https://doi.org/10.1037/0033-2909.103.2.276

Conners, C. K., Erhardt, D., & Sparrow, E. P. (1999). Conners’ adult ADHD rating scales (CAARS): technical manual. Multi-Health Systems North Tonawanda, NY.

Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334. https://doi.org/10.1007/BF02310555

Curran, P. G. (2016). Methods for the detection of carelessly invalid responses in survey data. Journal of Experimental Social Psychology, 66, 4–19. https://doi.org/10.1016/j.jesp.2015.07.006

Demerouti, E., Bakker, A. B., Vardakou, I., & Kantas, A. (2003). The convergent validity of two burnout instruments: A multitrait-multimethod analysis. European Journal of Psychological Assessment, 19(1), 12–23. https://doi.org/10.1027//1015-5759.19.1.12

Devine, S., Uanhoro, J. O., Otto, A. R., & Flake, J. K. (2024). Approaches for quantifying the ICC in multilevel logistic models: a didactic demonstration. Collabra: Psychology, 10(1), 94263. https://doi.org/10.1525/collabra.94263

Drasgow, F., Levine, M. V., & Williams, E. A. (1984). Appropriateness measurement with polychotomous item response models and standardized indices (Issue ADA141365). Model Based Measurement Laboratory, University of Illinois.

Dunn, A. M., Heggestad, E. D., Shanock, L. R., & Theilgard, N. (2018). Intra-individual response variability as an indicator of insufficient effort responding: comparison to other indicators and relationships with individual differences. Journal of Business and Psychology, 33(1), 105–121. https://doi.org/10.1007/s10869-016-9479-0

Ferrando, P. J., & Lorenzo-Seva, U. (2007). An item response theory model for incorporating response time data in binary personality items. Applied Psychological Measurement, 31(6), 525–543. https://doi.org/10.1177/0146621606295197

Flora, D. B. (2020). Your coefficient alpha is probably wrong, but which coefficient omega is right? A tutorial on using R to obtain better reliability estimates. Advances in Methods and Practices in Psychological Science, 3(4), 484–501. https://doi.org/10.1177/2515245920951747

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312

Gessaroli, M. E., & De Champlain, A. F. (1996). Using an approximate chi-square statistic to test the number of dimensions underlying the responses to a set of items. Journal of Educational Measurement, 33(2), 157–179.

Goldberg, L. R. (1993). The structure of phenotypic personality traits. American Psychologist, 48(1), 26–34. https://doi.org/10.1037/0003-066X.48.1.26

Guttman, L. (1945). A basis for analyzing test-retest reliability. Psychometrika, 10(4), 255–282. https://doi.org/10.1007/BF02288892

Guttman, L. (1953). Image theory for the structure of quantitative variates. Psychometrika, 18(4), 277–296. https://doi.org/10.1007/BF02289264

Guttman, L. (1954). Some necessary conditions for common-factor analysis. Psychometrika, 19(2), 149–161. https://doi.org/10.1007/BF02289162

Haebara, T. (1980). Equating logistic ability scales by a weighted least squares method. Japanese Psychological Research, 22(3), 144–149. https://doi.org/10.4992/psycholres1954.22.144

南風原 朝和（2000）．局所独立性　　Retrieved July 4, 2022 from https://www.p.u-tokyo.ac.jp/~haebara/local_ind/

Haenlein, M., & Kaplan, A. M. (2004). A beginner’s guide to partial least squares analysis. Understanding Statistics, 3(4), 283–297. https://doi.org/10.1207/s15328031us0304_4

萩生田 伸子・繁桝 算男（1996）．順序付きカテゴリカルデータへの因子分析の適用に関するいくつかの注意点　心理学研究，67(1), 1–8. https://doi.org/10.4992/jjpsy.67.1

Hair, J. F. (Ed.). (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (Second edition). Sage.

Hair, J. F., Hult, T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: a workbook. Classroom Companion: Business. Springer.

Hancock, G. R., Stapleton, L. M., & Mueller, R. O. (2019). Structural equation modeling. In The reviewer’s guide to quantitative methods in the social sciences (2nd ed., pp. 445–456). Routledge.

Harrison, X. A. (2014). Using observation-level random effects to model overdispersion in count data in ecology and evolution. PeerJ, 2, e616. https://doi.org/10.7717/peerj.616

林 邦好・冨田 誠・田中 豊（2008）．主成分分析における軸の回転について　計算機統計学，19(2), 89–101. https://doi.org/10.20551/jscswabun.19.2_89

Henseler, J., Ringle, C. M., & Sarstedt, M. (2012). Using partial least squares path modeling in advertising research: basic concepts and recent issues. In S. Okazaki (Ed.), Handbook of research on international advertising (pp. 252–276). E. Elgar.

Höhne, J. K., & Schlosser, S. (2018). Investigating the adequacy of response time outlier definitions in computer-based web surveys using paradata SurveyFocus. Social Science Computer Review, 36(3), 369–378. https://doi.org/10.1177/0894439317710450

堀 一輝・牧野 直道（2024）．測定モデルユーザーのための次元性評価法総論　日本テスト学会誌，20, 135–167. https://doi.org/10.24690/jart.20.1_135

堀 啓造（2005）．因子分析における因子数決定法――並行分析を中心にして――　香川大学経済論叢，77(4), 35–70.

星野 崇宏・岡田 謙介・前田 忠彦（2005）．構造方程式モデリングにおける適合度指標とモデル改善について : 展望とシミュレーション研究による新たな知見　行動計量学，32(2), 209–235. https://doi.org/10.2333/jbhmk.32.209

Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118

Huang, J. L., Curran, P. G., Keeney, J., Poposki, E. M., & DeShon, R. P. (2012). Detecting and deterring insufficient effort responding to surveys. Journal of Business and Psychology, 27(1), 99–114. https://doi.org/10.1007/s10869-011-9231-8

Hwang, H., Sarstedt, M., Cheah, J. H., & Ringle, C. M. (2020). A concept analysis of methodological research on composite-based structural equation modeling: bridging PLSPM and GSCA. Behaviormetrika, 47(1), 219–241. https://doi.org/10.1007/s41237-019-00085-5

Jackson, D. N., Wroblewski, V. R., & Ashton, M. C. (2000). The impact of faking on employment tests: does forced choice offer a solution? Human Performance, 13(4), 371–388. https://doi.org/10.1207/S15327043HUP1304_3

Johnson, P. O., & Fay, L. C. (1950). The Johnson-Neyman technique, its theory and application. Psychometrika, 15(4), 349–367. https://doi.org/10.1007/BF02288864

Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20(1), 141–151. https://doi.org/10.1177/001316446002000116

Kaiser, H. F. (1970). A second generation little jiffy. Psychometrika, 35(4), 401–415. https://doi.org/10.1007/BF02291817

Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31–36. https://doi.org/10.1007/BF02291575

Kaiser, H. F. (1981). A revised measure of sampling adequacy for factor-analytic data matrices. Educational and Psychological Measurement, 41(2), 379–381. https://doi.org/10.1177/001316448104100216

Kaiser, H. F., & Rice, J. (1974). Little jiffy, mark IV. Educational and Psychological Measurement, 34(1), 111–117. https://doi.org/10.1177/001316447403400115

Kang, H., & Ahn, J.-W. (2021). Model setting and interpretation of results in research using structural equation modeling: a checklist with guiding questions for reporting. Asian Nursing Research, 15(3), 157–162. https://doi.org/10.1016/j.anr.2021.06.001

Karabatsos, G. (2003). Comparing the aberrant response detection performance of thirty-six person-fit statistics. Applied Measurement in Education, 16(4), 277–298. https://doi.org/10.1207/S15324818AME1604_2

加藤 健太郎・山田 剛史・川端 一光（2014）．Rによる項目反応理論　オーム社

川端 一光（2019）．パラメータ推定　Rで学ぶマルチレベルモデル［実践編］（pp. 145--178）　朝倉書店

Kenny, D. A., & La Voie, L. (1985). Separating individual and group effects. Journal of Personality and Social Psychology, 48(2), 339–348. https://doi.org/10.1037/0022-3514.48.2.339

Kiers, H. A. L., & Ten Berge, J. M. F. (1994). The Harris-Kaiser independent cluster rotation as a method for rotation to simple component weights. Psychometrika, 59(1), 81–90. https://doi.org/10.1007/BF02294267

King, G. (1986). How not to lie with statistics: avoiding common mistakes in quantitative political science. American Journal of Political Science, 30(3), 666. https://doi.org/10.2307/2111095

北岡 和代・増田 真也・荻野 佳代子・中川 秀昭（2011）．バーンアウト測定尺度 Maslach Burnout Inventory-General Survey(MBI-GS)の概要と日本版について　北陸公衆衛生学会誌，37, 34–40.

Kleinman, M., & Teresi, J. A. (2016). Differential item functioning magnitude and impact measures from item response theory models. Psychological Test and Assessment Modeling, 58(1), 79–98.

Kolen, M. J., & Brennan, R. L. (2014). Test equating, scaling, and linking (3rd ed.). Springer.

Kong, X. J., Wise, S. L., & Bhola, D. S. (2007). Setting the response time threshold parameter to differentiate solution behavior from rapid-guessing behavior. Educational and Psychological Measurement, 67(4), 606–619. https://doi.org/10.1177/0013164406294779

Kopf, J., Zeileis, A., & Strobl, C. (2015). Anchor selection strategies for DIF analysis. Educational and Psychological Measurement, 75(1), 22–56. https://doi.org/10.1177/0013164414529792

小杉 考司（2018）．言葉と数式で理解する多変量解析入門　北大路書房

Kreuter, F. (Ed.). (2013). Improving surveys with paradata: analytic use of process information. Wiley series in survey methodology. John Wiley & Sons.

Krosnick, J. A. (1991). Response strategies for coping with the cognitive demands of attitude measures in surveys. Applied Cognitive Psychology, 5(3), 213–236. https://doi.org/10.1002/acp.2350050305

Kuder, G. F., & Richardson, M. W. (1937). The theory of the estimation of test reliability. Psychometrika, 2(3), 151–160. https://doi.org/10.1007/BF02288391

Landy, F. J. (1986). Stamp collecting versus science: Validation as hypothesis testing. American Psychologist, 41(11), 1183–1192. https://doi.org/10.1037/0003-066X.41.11.1183

Likert, R. (1932). A technique for the measurement of attitudes. Archives of psychology. New York.

Lin, H.-M., Lee, M.-H., Liang, J.-C., Chang, H.-Y., Huang, P., & Tsai, C.-C. (2020). A review of using partial least square structural equation modeling in e-learning research. British Journal of Educational Technology, 51(4), 1354–1372. https://doi.org/10.1111/bjet.12890

Little, R. J. A. (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83(404), 1198–1202. https://doi.org/10.1080/01621459.1988.10478722

Lord, F. M. (1980). Applications of item response theory to practical testing problems. L. Erlbaum Associates.

Lord, F. M., & Novick, M. R. (1968). Statistical theories of mental test scores. Addison-Wesley series in behavioral science quantitative methods. Addison-Wesley.

Magno, F., Cassia, F., & Ringle, C. M. (2022). A brief review of partial least squares structural equation modeling (PLS-SEM) use in quality management studies. The TQM Journal, ahead-of-print(ahead-of-print). https://doi.org/10.1108/TQM-06-2022-0197

Mantel, N., & Haenszel, W. (1959). Statistical aspects of the analysis of data from retrospective studies of disease. Journal of the National Cancer Institute. https://doi.org/10.1093/jnci/22.4.719

Maruyama, G., & Ryan, C. S. (2014). Research methods in social relations (8th ed.). John Wiley & Sons Inc.

Maslach, C., & Jackson, S. E. (1981). The measurement of experienced burnout. Journal of Organizational Behavior, 2(2), 99–113. https://doi.org/10.1002/job.4030020205

Maslach, C., Jackson, S. E., & Leiter, M. (1996). Maslach Burnout Inventory Manual (3rd ed.). Consulting Psychologists Press.

増田 真也（1997）．日本語版 Maslach Burnout Inventory の妥当性の検討　健康心理学研究，10(2), 44–53. https://doi.org/10.11560/jahp.10.2_44

Maydeu-olivares, A., Hernández, A., & Mcdonald, R. P. (2006). A multidimensional ideal point item response theory model for binary data. Multivariate Behavioral Research, 41(4), 445–472. https://doi.org/10.1207/s15327906mbr4104_2

Mayekawa, S. (1994). Equivalent path models in linear structural equation models. Behaviormetrika, 21(1), 79–96. https://doi.org/10.2333/bhmk.21.79

McDonald, R. P. (1978). Generalizability in factorable domains: “domain validity and generalizability.” Educational and Psychological Measurement, 38(1), 75–79. https://doi.org/10.1177/001316447803800111

McDonald, R. P. (1999). Test theory: a unified treatment (0th ed.). Psychology Press. https://doi.org/10.4324/9781410601087

McGraw, K. O., & Wong, S. P. (1996). Forming inferences about some intraclass correlation coefficients. Psychological Methods, 1(1), 30–46. https://doi.org/10.1037/1082-989x.1.1.30

McKinley, R. L., & Mills, C. N. (1985). A comparison of several goodness-of-fit statistics. Applied Psychological Measurement, 9(1), 49–57. https://doi.org/10.1177/014662168500900105

McNeish, D., & Wolf, M. G. (2020). Thinking twice about sum scores. Behavior Research Methods, 52(6), 2287–2305. https://doi.org/10.3758/s13428-020-01398-0

Mehta, P. D., & Neale, M. C. (2005). People are variables too: Multilevel structural equations modeling. Psychological Methods, 10(3), 259–284. https://doi.org/10.1037/1082-989X.10.3.259

Meijer, R. R., Niessen, A. S. M., & Tendeiro, J. N. (2016). A practical guide to check the consistency of item response patterns in clinical research through person-fit statistics: examples and a computer program. Assessment, 23(1), 52–62. https://doi.org/10.1177/1073191115577800

Meijer, R. R., & Sijtsma, K. (2001). Methodology review: evaluating person fit. Applied Psychological Measurement, 25(2), 107–135. https://doi.org/10.1177/01466210122031957

Messick, S. (1995). Validity of psychological assessment. American Psychologist, 50(9), 741–749. https://doi.org/10.1037/0003-066X.50.9.741

三浦 麻子・小林 哲郎（2016）．オンライン調査における努力の最小限化（Satisfice）傾向の比較 : IMC違反率を指標として　メディア・情報・コミュニケーション研究，1, 27–42.

Mulaik, S. A., James, L. R., Van Alstine, J., Bennett, N., Lind, S., & Stilwell, C. D. (1989). Evaluation of goodness-of-fit indices for structural equation models. Psychological Bulletin, 105(3), 430–445. https://doi.org/10.1037/0033-2909.105.3.430

Muraki, E. (1992). A generalized partial credit model: application of an EM algorithm. Applied Psychological Measurement, 16(2), 159–176. https://doi.org/10.1177/014662169201600206

村山 航（2012）．妥当性：概念の歴史的変遷と心理測定学的観点からの考察　教育心理学年報，51, 118–130. https://doi.org/10.5926/arepj.51.118

岡田 謙介（2011）．クロンバックのαに代わる信頼性の推定法について――構造方程式モデリングによる方法・McDonaldのωの比較――　日本テスト学会誌，7, 37–50. https://doi.org/10.24690/jart.7.1_37

岡田 謙介（2015）．心理学と心理測定における信頼性について――Cronbachのα係数とは何なのか，何でないのか――　教育心理学年報，54, 71–83. https://doi.org/10.5926/arepj.54.71

Oppenheimer, D. M., Meyvis, T., & Davidenko, N. (2009). Instructional manipulation checks: Detecting satisficing to increase statistical power. Journal of Experimental Social Psychology, 45(4), 867–872. https://doi.org/10.1016/j.jesp.2009.03.009

Orlando, M., & Thissen, D. (2000). Likelihood-based item-fit indices for dichotomous item response theory models. Applied Psychological Measurement, 24(1), 50–64. https://doi.org/10.1177/01466216000241003

尾崎 幸謙・川端 一光・山田 剛史（2018）．Rで学ぶマルチレベルモデル［入門編］　朝倉書店

尾崎 幸謙・川端 一光・山田 剛史（2019）．Rで学ぶマルチレベルモデル［実践編］　朝倉書店

Padilla, M. A., & Divers, J. (2016). A comparison of composite reliability estimators: coefficient omega confidence intervals in the current literature. Educational and Psychological Measurement, 76(3), 436–453. https://doi.org/10.1177/0013164415593776

Peterson, C. H., Peterson, N. A., & Powell, K. G. (2017). Cognitive interviewing for item development: validity evidence based on content and response processes. Measurement and Evaluation in Counseling and Development, 50(4), 217–223. https://doi.org/10.1080/07481756.2017.1339564

Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879

Raju, N. S. (1988). The area between two item characteristic curves. Psychometrika, 53(4), 495–502. https://doi.org/10.1007/BF02294403

Raju, N. S., van der Linden, W. J., & Fleer, P. F. (1995). IRT-based internal measures of differential functioning of items and tests. Applied Psychological Measurement, 19(4), 353–368. https://doi.org/10.1177/014662169501900405

Rasch, G. (1980). Probabilistic models for some intelligence and attainment tests. University of Chicago Press. (Original work published 1960)

Reckase, M. D. (2019). Logistic multidimensional models. In W. J. van der Linden (Ed.), Handbook of item response theory: Volume one, models (pp. 189–209). CRC Press.

Reise, S. P. (2012). The rediscovery of bifactor measurement models. Multivariate Behavioral Research, 47(5), 667–696. https://doi.org/10.1080/00273171.2012.715555

Revelle, W., & Rocklin, T. (1979). Very simple structure: an alternative procedure for estimating the optimal number of interpretable factors. Multivariate Behavioral Research, 14(4), 403–414. https://doi.org/10.1207/s15327906mbr1404_2

Roberts, J. S. (2019). Generalized graded unfolding model. In W. J. van der Linden (Ed.), Handbook of item response theory: Volume one, models (pp. 369–392). CRC Press.

Robinson, W. S. (1950). Ecological correlations and the behavior of individuals. American Sociological Review, 15(3), 351. https://doi.org/10.2307/2087176

Rönkkö, M., McIntosh, C. N., & Antonakis, J. (2015). On the adoption of partial least squares in psychological research: Caveat emptor. Personality and Individual Differences, 87, 76–84. https://doi.org/10.1016/j.paid.2015.07.019

Roussos, L. A., & Ozbek, O. Y. (2006). Formulation of the DETECT Population Parameter and Evaluation of DETECT Estimator Bias. Journal of Educational Measurement, 43(3), 215–243. https://doi.org/10.1111/j.1745-3984.2006.00014.x

Samejima, F. (1969). Estimation of latent ability using a response pattern of graded scores. Psychometrika, 34(S1), 1–97. https://doi.org/10.1007/BF03372160

Schafer, J. L., & Graham, J. W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7(2), 147–177. https://doi.org/10.1037/1082-989X.7.2.147

Schaufeli, W. B., Salanova, M., Lez-Roma, V. G., & Bakker, A. B. (2002). The measurement of engagement and burnout: a two sample confirmatory factor analytic approach. Journal of Happiness Studies, 3, 71–92. https://doi.org/10.1023/A:1015630930326

Schaufeli, W. B., Shimazu, A., Hakanen, J., Salanova, M., & De Witte, H. (2019). An ultra-short measure for work engagement: the UWES-3 validation across five countries. European Journal of Psychological Assessment, 35(4), 577–591. https://doi.org/10.1027/1015-5759/a000430

Schmid, J., & Leiman, J. M. (1957). The development of hierarchical factor solutions. Psychometrika, 22(1), 53–61. https://doi.org/10.1007/BF02289209

Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461–464. https://doi.org/10.1214/aos/1176344136

Shimazu, A., Schaufeli, W. B., Kosugi, S., Suzuki, A., Nashiwa, H., Kato, A., Sakamoto, M., Irimajiri, H., Amano, S., Hirohata, K., Goto, R., & Kitaoka-Higashiguchi, K. (2008). Work engagement in Japan: validation of the Japanese version of the Utrecht Work Engagement Scale. Applied Psychology, 57(3), 510–523. https://doi.org/10.1111/j.1464-0597.2008.00333.x

清水 裕士（2014）．個人と集団のマルチレベル分析　ナカニシヤ出版

Shirkey, E. C., & Dziuban, C. D. (1976). A note on some sampling characteristics of the measure of sampling adequacy (MSA). Multivariate Behavioral Research, 11(1), 125–128. https://doi.org/10.1207/s15327906mbr1101_9

Simpson, E. H. (1951). The interpretation of interaction in contingency tables. Journal of the Royal Statistical Society Series B: Statistical Methodology, 13(2), 238–241. https://doi.org/10.1111/j.2517-6161.1951.tb00088.x

Sitarenios, G. (2022). Short versions of tests: best practices and potential pitfalls. Journal of Pediatric Neuropsychology, 8, 101–115. https://doi.org/10.1007/s40817-022-00126-0

Smith, R. M., Schumacker, R. E., & Busch, M. J. (1995). Using item mean squares to evaluate fit to the rasch model. A paper presented at the Annual Meeting of the American Educational Research Association, San Francisco, CA.

Snijders, T. A. B., & Bosker, R. J. (2012). Multilevel analysis: an introduction to basic and advanced multilevel modeling (2nd ed). Sage.

Stark, S., Chernyshenko, O. S., Drasgow, F., & Williams, B. A. (2006). Examining assumptions about item responding in personality assessment: Should ideal point methods be considered for scale development and scoring? Journal of Applied Psychology, 91(1), 25. https://doi.org/10.1037/0021-9010.91.1.25

Steiger, J. H., & Lind, J. C. (1980). Statistically based tests for the number of common factors. Paper Presented at the Psychometric Society Annual Meeting.

Stocking, M. L., & Lord, F. M. (1983). Developing a common metric in item response theory. Applied Psychological Measurement, 7(2), 201–210. https://doi.org/10.1177/014662168300700208

Stout, W. (1987). A nonparametric approach for assessing latent trait unidimensionality. Psychometrika, 52(4), 589–617. https://doi.org/10.1007/BF02294821

Stout, W., Habing, B., Douglas, J., Hae Rim Kim, Roussos, L., & Jinming Zhang. (1996). Conditional covariance-based nonparametric multidimensionality assessment. Applied Psychological Measurement, 20(4), 331–354. https://doi.org/10.1177/014662169602000403

Streiner, D. L., & Norman, G. R. (2008). Health measurement scales: a practical guide to their development and use (4th ed). Oxford University Press.

Sturges, H. A. (1926). The choice of a class interval. Journal of the American Statistical Association, 21(153), 65–66. https://doi.org/10.1080/01621459.1926.10502161

高橋 将宜・渡辺 美智子（2017）．欠測データ処理: Rによる単一代入法と多重代入法　共立出版

Takane, Y., & de Leeuw, J. (1987). On the relationship between item response theory and factor analysis of discretized variables. Psychometrika, 52(3), 393–408. https://doi.org/10.1007/BF02294363

Thurstone, L. L. (1927). A law of comparative judgment. Psychological Review, 34(4), 273–286. https://doi.org/10.1037/h0070288

Thurstone, L. L. (1947). Multiple-factor analysis: a development and expansion of the vectors of mind. University of Chicago Press.

豊田 秀樹（編）（2013）．項目反応理論［中級編］　統計ライブラリー　朝倉書店

豊田 秀樹（2014）．共分散構造分析 [R編]　東京図書

Tucker, L. R., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38(1), 1–10. https://doi.org/10.1007/BF02291170

Yen, W. M. (1981). Using simulation results to choose a latent trait model. Applied Psychological Measurement, 5(2), 245–262. https://doi.org/10.1177/014662168100500212

Yen, W. M. (1984). Effects of local item dependence on the fit and equating performance of the three-parameter logistic model. Applied Psychological Measurement, 8(2), 125–145. https://doi.org/10.1177/014662168400800201

Zhang, J. (2007). Conditional covariance theory and detect for polytomous items. Psychometrika, 72(1), 69–91. https://doi.org/10.1007/s11336-004-1257-7

Zhang, J., & Stout, W. (1999). The theoretical DETECT index of dimensionality and its application to approximate simple structure. Psychometrika, 64(2), 213–249. https://doi.org/10.1007/BF02294536

Zwick, W. R., & Velicer, W. F. (1986). Comparison of five rules for determining the number of components to retain. Psychological Bulletin, 99(3), 432–442. https://doi.org/10.1037/0033-2909.99.3.432