Pengaplikasian Multiple Indicator Multiple Causes (MIMIC) Model dalam Mendeteksi Differential Item Functioning (DIF) pada Alat Ukur Social Quality of Life

Hasbi Wahyudi

Abstract


Abstract

This study aims to detect DIF (differential item functioning) on a quality of life measurement tool that measures one aspect, namely social quality of life. Social quality of life contains 24 items developed from the Patient Reported Outcomes Measurement Information System (PROMIS) by a National Institutes of Health (NIH). This measuring tool measures the quality of life in the social function domain of adolescent patients suffering from diseases or chronic medical conditions. Detection of DIF in this study uses a special case approach from CFA, namely CFA with covariate or multiple indicator multiple causes (MIMIC) models. This study involved 322 participants, 117 (36%) male participants and 205 (64%) female participants, with an age range between 13-23 years in Riau Province. Based on the results of the first order CFA on a set of social quality of life items there are 22 valid items. Then the MIMIC model analysis results found that the model is fit with data where the value of RMSEA = 0.048, so it is known two items that contain DIF, namely item 5 (0.135, P = 0.002) "I have a close friend" and item 23 (0.308, P = 0.002 ) "I hope to have lots of friends".

Keywords: Social quality of life, MIMIC model, differential item functioning

Abstrak

Penelitian ini bertujuan untuk mendeteksi DIF (differential item functioning) pada alat ukur quality of life yang mengukur salah satu aspek yaitu social quality of life. Social quality of life berisi 24 item yang dikembangkan dari Patient Reported Outcomes Measurement Information System (PROMIS) oleh sebuah badan National Institutes of Health (NIH). Alaalat ukur ini mengukur kualitas hidup pada domain fungsi sosial pasien remaja yang menderita penyakit atau kondisi medis kronis. Pendeteksian DIF pada penelitian ini menggunakan pendekatan kasus khusus dari CFA, yakni CFA with covariate atau multiple indicator multiple causes (MIMIC) model. Penelitian ini melibatkan 322 partisipan, yakni sebanyak 117 (36%) partisipan laki-laki dan 205 (64%) partisipan perempuan, dengan rentang usia antara 13-23 tahun di Propinsi Riau. Berdasarkan hasil first order CFA pada sekumpulan item-item social quality of life terdapat 22 item yang valid. Kemudian hasil analisis model MIMIC ditemukan bahwa model fit dengan data dimana nilai RMSEA = 0.048, sehingga diketahui dua item yang mengandung DIF, yaitu item 5 (0.135, P = 0.002) “saya memiliki teman dekat” dan item 23 (0.308, P = 0.002) “saya berharap mempunyai banyak teman”.

Kata kunci: Social quality of life, MIMIC model, differential item functioning


Keywords


Social quality of life; MIMIC model; differential item functioning

References


Allen, M.J. & Yen, W.M. (1979). Introduction to measurement theory. Monterey: Brooks Cole.

Anastasi, A. Dan Urbina, U., 1997, Psychological testing (seventh edition), Prentice- all Inc, New Jersey.

Bollen, K. A. (1989). Structural equations with latent variables. New York, NY: John Wiley & Sons, Inc.

Brown, A Timothy. (2006). Confirmatory factor analysis for research. New York: The Guilford Press.

Cai, L. (2010). Metropolis-hastings robbins-monro algorithm for confirmatory item factor analysis. Journal of Educational and Behavioral Statistics, 35, 3, 307-335.

Cai, L. (2010b). High-dimensional exploratory item factor analysis by a Metropolis-Hastings Robbins-Monro algorithm. Psychometrika, 75, 33-57.

Camilli, G., & Shepard, L. A. (1994). Methods for identifying biased test items. Thousand Oaks, CA: Sage.

Carr, A. (2004). Positive psychology: the science of happiness and human strengths. New York, NY: Brunner-Routledge.

Cheng, Y., Shao, C. & Lathrop, Q. N. (2015). The mediated MIMIC model for understanding the underlying mechanism of DIF. Educational and Psychological Measurement, 76, 1, 43-63.

Crane, Gibbons, Narasimhalu, Lai & Cella. (2007). Rapid detection of differential item functioning in assessments of health-related quality of life: The functional assessment of cancer therapy. Quality Life Research,, 16, 101-114.

Felce, D.,& Perry, J. (2005). Exploring current conceptions of quality of life: a model for people with and without disabilities. Dalam Renwick, I. Brown, & M. Nagler (Eds.), Quality of life in health promotion and rehabilitation: conceptual approaches, issues, and applications. California: SAGE Publication.

Finch, Holmes. (2012). The MIMIC model as a method for detecting DIF: comparison with mantel-haenszel, SIBTEST, and the IRT likelihood ratio. Applied Psychological Measurement, 278-294

Fox, Jean-Paul. (2010). Bayesian item response modeling: Theory and applications. New York: Springer.

Gallo, J. J., Anthony, J. C., & Muthen, B. O. (1994). Age differences in the symptoms of depression: A latent trait analysis. Journal of Gerontology: Psychological Sciences, 49, 251-264.

Heck, H. R., & Thomas, L. S. 2005. An introduction to multilevel modeling techniques. New York: Routledge Taylor & Prancis Group

Kaplan, R. M. & Saccuzzo. (2005). Psychological Testing: principles, application, and issues (6th ed.). Belmont : Thomson Wadsworth.

Lee, S. Y. (2007). Structural equation modeling: a bayesian approach. Chicester: John Wiley & Sons Ltd.

Muthen, B. O. 1989. Latent variable modeling in heterogenous populations. Psychometrika, 54, No. 4, 557-585

Power, M. J. (20013).Quality of Life.dalam Lopez, S. J., & Synder, C. R. (Ed). Positive psychological assessment: a handbook of models and measures. Washington: American Psychological Association.

Reeve, B. B., Hays, R. D., Bjorner, J. B., Cook, K. F., Crane, P. K., Teresi, J. A., et al. (2007). Psychometric evaluation and calibration of health-related quality of life items banks: Plans for the patient-reported outcome measurement information system (PROMIS). Medical Care, 45, S22–S31.

Sarafino, E. P. & Smith, T. W. (2011). Health psychology: biopsychosocial interactions (7th edition), Hoboken, NJ: John Wiley & Sons, Inc.

Scot, W Neil. Fayers, M Peter. Aaronson, K Neil. Bottomey, Andrew. Graeff, de Alexander. Groenvold, Mogens. Gundy, Chad. Koller, Michael. Pettersen, A Morten. & Sprangers, AG Mirjam. (2010). Differential item functioning (DIF) analyses of health-related quality of life instruments using logistic regression. Health and Quality of Life Outcomes, 8, 1-9

Sills, L.C., & Brown, T.A. (2006). Research considerations: latent variable approaches to studying the classification and psychopathology of mental disorders. In M. Hersen, J. C. Thomas & F. Andrasik (Eds.), Comprehensive Handbook of Personality and Psychopathology. Volume 2. Hoboken, N.J.: John Wiley & Sons.

Simon, M. K. & Goes, J. (2013). Dissertattion and scholarly research: recipes for success. Seattle, WA: Dissertation Success LLC.

Taylor, S.E., Peplau, L.A., Sears, D.O. 2000. Social psychology, 10th edition. USA : Prentice Hall

Wang, W. C., Shih, C. L., & Yang, C. C. (2009). The MIMIC method with scale purification for detecting differential item functioning. Educational and Psychological Measurement, 69, 713-731.

Wang, Jichuan. & Wang, Xiaoqian. (2012). Structural equation modelling: application using Mplus. United Kingdom: A John Wiley & Sons

Umar, J. (2011). Bahan ajar statistik. Fakultas Psikologi UIN Jakarta. Tidak dipublikasikan.

Woods, Oltmanns& Turkheimer. (2008). Illustration of MIMIC-Model DIF testing with the schedule for nonadaptive and adaptive personality. Journal Psychopatologi Behaviour Assessment, 31, 320-330.


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DOI: 10.15408/jp3i.v8i1.12851

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