Bireysel Farklılıkların Kategorik Değişkenler Olarak Modellenmesinde Örtük Sınıf Analizi Kullanımı için Uygulama Kılavuzu: Psikolojik Dayanıklılık Örneği

Eğitim programlarının hedeflerine ulaşmadaki başarıları, içerdikleri izleme, koruma ve müdahale, plan ve uygulamaların, bu programlardaki öğrencilerin ilgi ve ihtiyaçlarını karşılamadaki başarıları ile doğru orantılı olacaktır. Öğrencilerin farklı gereksinimlere sahip olmalarından kaynaklanan kategorik farklılıkları yansıtabilecek grup değişkenlerinin tanımlanması ve içerdikleri alt grupların belirlenmesi bu anlamda oldukça önemlidir. Bu çalışmada, öğrenci gruplarında oluşabilecek olan niteliksel farklılıkların kategorik değişkenler olarak tanımlanmasında ve test edilmesinde kullanılabilecek istatistiksel bir yöntem olan örtük sınıf analizine odaklanılmıştır. Öğretmen adaylarının psikolojik dayanıklılık alt gruplarının çalışıldığı bir araştırma üzerinden, öğrenci gruplarında var olduğu düşünülen ancak henüz tanımlanmamış kategorik farklılıkların örtük sınıf analizi modelleri ile nasıl çalışılabileceği uygulamalı olarak örneklendirilmiştir. Örtük sınıf analizinin nasıl yapılabileceği, (1) analiz öncesi, (2) analiz ve (3) analiz sonrası olmak üzere üç parçaya ayrılarak aşamalı olarak anlatılmıştır. Son aşamada, elde edilen bulguların teorik bilgiler ile birlikte yorumlanmasının öneminin altı çizilmiş ve örnek uygulama verileri için bulunan dört alt dayanıklılık grubunun, ilgili literatürde geçen ve bireylerin dayanıklılık türlerini savunmasızlık, yeterlik, dayanıklılık ve uyumsuzluk olarak dört ayrı kategoride ele alan teorik bakış açısı ile beraber tartışılmasının getirdiği yorumsal derinliğe vurgu yapılmıştır. Bulguların geçerlilik argümanlarının desteklemesi açısından ikincil değişkenlerin kullanılmasının getireceği potansiyel katkı, sosyal desteği daha yüksek olan bireylerin psikolojik dayanıklılık bakımından daha güçlü bir profil çizen dayanıklılık ve yeterlik gruplarında yer almalarının daha olası olduğu bulgusu ile örneklendirilmiştir. Bu çalışma, hem örtük sınıf analizinin ölçme ve değerlendirme araştırmalarında daha çok yer alabilmesi için araştırmacılara kısa bir kullanım rehberi sunmakta, hem de elde edilecek bulguların kuramsal bilgilerle sentezlenerek, yapılacak geçerlilik argümanlarını zenginleştirmede nasıl kullanılabileceğini örneklendirmektedir.

A Primer on Applied Latent Class Analysis for Modeling Qualitative Differences: An Application on Resilience Data

The efficiency of an educational program is closely related to the quality of its monitoring, prevention and treatment strategies that are most suited for students’ characteristics and needs. Group differences reflecting inter-individual differences are needed to be defined as well as the characteristics of the groups reflecting distinct needs of students comprising them. This study focuses on latent class analysis which is a statistical method used for defining and analyzing inter-individual differences as categorical variables. How to conduct a latent class analysis is illustrated via an application that focused on studying qualitative differences in resilience levels of pre-service teachers. The illustration presents the steps of conducting a latent class analysis using three stages: pre-analysis, analysis and post-analysis. The application nicely illustrates the importance of utilizing a theoretical base when providing a validity argument for that it reveals a four categorically different subgroups of resilience which aligns with the vulnerability, competence, resiliency and maladaptation subgroups as suggested by some viable resilience theory. To illustrate how researchers can further enhance the validity of the findings from a latent class analysis, the last section provides an extended application where an external variable, i.e., social support received, is used as a covariate showing that students whose social support was higher in fact more likely to be in “resilience” and “competence” subgroups. The ultimate purpose of this paper is to provide researchers with a brief guide to latent class analysis using a real data illustration.

PDF

___

Agresti, A. (1990). Categorical data analysis. New York: Wiley.
Akaike, H. (1987). Factor analysis and AIC. Psychometrika, 52, 317-332.
American Psychological Association (2014). The road to resilience. 10.12.2018 tarihinde http://www.apa.org/helpcenter/road-resilience.aspx adresinden alındı.
Åsenlöf, P., Denison, E., & Lindberg, P. (2005). Individually tailored treatment targeting activity, motor behavior, and cognition reduces pain–related disability: a randomized controlled trial in patients with musculoskeletal pain. The Journal of Pain, 6(9), 588-603.
Baruth, K. E., & Caroll, J. J. (2002). A formal assessment of resilience: The Baruth Protective Factors Inventory. The Journal of Individual Psychology, 58(3), 235-244.
Beck, A. T., Ward, C., & Mendelson, M. (1961). An ınventory for measuring depression. Archives of General Psychiatry Journal, 4(6), 561-571.
Berlin, K. S., Williams, N. A., & Parra, G. R. (2014). An introduction to latent variable mixture modeling (part 1): Overview and cross-sectional latent class and latent profile analyses. Journal of Pediatric Psychology, 39(2), 174-187.
Bobek, B. L. (2002). Teacher resiliency: A key to career longevity. The Clearing House, 75(4), 202-205.
Burnham, J. J. (2009). Contemporary fears of children and adolescents: Coping and resiliency in the 21st century. Journal of Counseling & Development, 87(1), 28-35.
Carlbring, P., Maurin, L., Törngren, C., Linna, E., Eriksson, T., Sparthan, E., Strååt, M., Marquez von Hage, C., Bergman- Nordgren, L. & Andersson, G. (2011). Individually-tailored, Internet-based treatment for anxiety disorders: A randomized controlled trial. Behaviour Research and Therapy, 49(1), 18-24.
Castro, A. J., Kelly, J., & Shih, M. (2010). Resilience strategies for new teachers in high-needs areas. Teaching and Teacher Education, 26(3), 622-629.
Cheng, Z. (2012). The Relation between uncertainty in latent class membership and outcomes in a latent class signal detection model. Columbia University.
Collins, L. M., & Flaherty, B. P. (2002). Latent class models for longitudinal data. Jacques A. Hagenaars & Allan L. McCutcheon (Eds.), in Applied latent class analysis (pp. 7-303). Cambridge, UK: Cambridge University Press.
Collins, L.M., & Lanza, S. T. (2010). Latent class and latent transition analysis: with applications in the social, behavioral, and health sciences. New Jersey: John Wiley & Sons.
Collins, L. M., Lanza, S. T., Schafer, J. L., & Flaherty, B. P. (2002). WinLTA user’s guide. State College, PA: Pennsylvania State University, University Park Campus, Methodology Center.
Connor, K. M., & Davidson, J. R. (2003). Development of a new resilience scale: The Connor‐Davidson resilience scale (CD‐RISC). Depression and anxiety, 18(2), 76-82.
Cooper, B. R., & Lanza, S. T. (2014). Who benefits most from Head Start? Using latent class moderation to examine differential treatment effects. Child development, 85(6), 2317-2338.
Egli, D. S. (2013). Beyond the storms: Strengthening preparedness, response, & resilience in the 21st century. Journal of Strategic Security, 6(2), 32-45.
Fedorowicz, A. E. (1995). Children's coping questionnaire (CCQ): development and factor structure (Doctoral dissertation, Arts and Social Sciences: Psychology).
Fergus, S., & Zimmerman, M. A. (2005). Adolescent resilience: A framework for understanding healthy development in the face of risk. Annual Review of Public Health, 26, 399-419.
Fleming, J. L., Mackrain, M., & LeBuffe, P. A. (2013). Caring for the caregiver: Promoting the resilience of teachers. Goldstein S. & Brooks R. (Eds.), in Handbook of resilience in children (pp. 387-397). Springer, Boston, MA.
Friborg, O., Hjemdal, O., Rosenvinge, J. H., & Martinussen, M. (2003). A new rating scale for adult resilience: What are the central protective resources behind healthy adjustment?. International Journal of Methods in Psychiatric Research, 12(2), 65-76.
Gu, Q., & Day, C. (2007). Teachers resilience: A necessary condition for effectiveness. Teaching and Teacher education, 23(8), 1302-1316.
Hagenaars, J. A., & McCutcheon, A. L. (Eds.). (2002). Applied latent class analysis. Cambridge University Press.
Hisli, N. (1989). Beck Depresyon Envanterinin üniversite öğrencileri için geçerliği, güvenirliği. Psikoloji Dergisi, 7(23), 3-13.
Howard, S., & Johnson, B. (2004). Resilient teachers: Resisting stress and burnout. Social Psychology of Education, 7(4), 399-420.
Lanza, S. T., Collins, L. M., Lemmon, D. R., & Schafer, J. L. (2007). PROC LCA: A SAS procedure for latent class analysis. Structural Equation Modeling, 14(4), 671-694.
Lanza, S. T., Flaherty, B. P., & Collins, L. M. (2003). Latent class and latent transition analysis. John A. Schinka & Wayne F. Velicer (Eds.), in Handbook of psychology, (pp.663-685). New Jersey: John Wiley & Sons, Inc.
Lanza, S. T., & Rhoades, B. L. (2013). Latent class analysis: An alternative perspective on subgroup analysis in prevention and treatment. Prevention Science, 14(2), 157-168.
Lazarsfeld, P. F., & Henry, N. W. (1968). Latent structure analysis. Boston: Houghton Mifflin.
Le Cornu, R. (2009). Building resilience in pre-service teachers. Teaching and Teacher Education, 25(5), 717-723.
Lo, Y., Mendell, N. R., & Rubin, D. B. (2001). Testing the number of components in a normal mixture. Biometrika, 88(3), 767-778.
Luthar, S. S. (2015). Resilience in development: A synthesis of research across five decades. Dante Cicchetti & Donald J. Cohen (Eds.), in Developmental psychopathology: volume three: risk, disorder, and adaptation, (pp.739-795). John Wiley & Sons, Inc.
Masten, A. S. (2015). Ordinary magic: Resilience in development. Guilford Publications.
Masten, A. S., Burt, K. B., Roisman, G. I., Obradović, J., Long, J. D., & Tellegen, A. (2004). Resources and resilience in the transition to adulthood: Continuity and change. Development and psychopathology, 16(4), 1071-1094.
Masten, A. S., & Tellegen, A. (2012). Resilience in developmental psychopathology: Contributions of the project competence longitudinal study. Development and psychopathology, 24(2), 345-361.
Masyn, K. E. (2013). Latent class analysis and finite mixture modeling. Todd D. Little (Eds.), in The Oxford Handbook of Quantitative Methods, (pp. 551-611). Oxford University Press.
McCutcheon, A. L. (2002). Basic concepts and procedures in single-and multiple-group latent class analysis. Applied latent class analysis, 56-88.
McLachlan, G., & Peel, D. (2000). Finite mixture modeling. New York, NY: Wiley.
Morin, A. J., Meyer, J. P., Creusier, J., & Bi try, F. (2016). Multiple-group analysis of similarity in latent profile solutions. Organizational Research Methods, 19(2), 231-254.
Muth n, L. K., & Muth n, B. O. (1998-2011). Mplus User's Guide. Los Angeles, CA: Muth n & Muth n.
Nylund, K. L., Asparouhov, T., & Muth n, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling, 14(4), 535-569.
Oberski, D. (2016). Mixture models: Latent profile and latent class analysis. Judy Robertson & Maurits Kaptein (Eds.), in Modern statistical methods for HCI (pp. 275-287). Springer, Cham.
Oshio, A., Kaneko, H., Nagamıne, S., & Nakaya, M. (2003). Construct validity of the adolescent resilience scale. Psychological Reports, 93, 1217-1222.
Prince-Embury, S.(2007, 2006). Resiliency scales for children and adolescents: a profile of personal strengths. Canadian Journal of School Psychology, 22(2), 255-261.
Rabe-Hesketh, S, Skrondal, A, & Pickles, A. (2004). GLLAMM manual. U.C. Berkeley Division of Biostatistics Working Paper Series. Berkeley, CA: Berkeley Electronic Press.
Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2).
Rutter M. (1993). Resilience: some conceptual considerations. Journal of Adolescent Health, 14, 598–611. Schwarz, G. (1978). Estimating the dimension of a model. The Annuals of Statistics, 6(2), 461-464.
Sinclair, V. G., & Wallston, K. A. (2004). The development and psychometric evaluation of the Brief Resilient Coping Scale. Assessment, 11(1), 94-101.
Smith, B. W., Dalen, J., Wiggins, K., Tooley, E., Christopher, P., & Bernard, J. (2008). The brief resilience scale: assessing the ability to bounce back. International Journal Of Behavioral Medicine, 15(3), 194-200.
Tait, M. (2008). Resilience as a contributor to novice teacher success, commitment, and retention. Teacher Education Quarterly, 35(4), 57-75.
Uebersax, J. (2009). A Practical Guide to Conditional Dependence in Latent Class Models. 21.12.2018 tarihinde https://www.john-uebersax.com/stat/condep.htm sayfasından alındı.
van de Pol, F., Langeheine, R. & De Jong, W. (1998). PANMARK User Manual, Version 3, Netherlands Central Bureau of Statistics, Voorburg.
Vermunt, J.K (1997). LEM 1.0: A general program for the analysis of categorical data. Tilburg: Tilburg University.
Vermunt, J. K., & Magidson, J. (2004). Latent class analysis. The Sage Encyclopedia of Social Sciences Research Methods, 549, 553.
Vermunt, J.K. (2010). Latent class modeling with covariates: Two improved three-step approaches. Political Analysis, 18, 450-469.
Vermunt, J. K. and Magidson, J. (2005). Technical guide for latent GOLD 4.0: Basic and advanced. Belmont Massachusetts: Statistical Innovations Inc.
Vermunt, J. K., Tran, B., & Magidson, J. (2008). Latent class models in longitudinal research. Scott Menard (Eds.), in Handbook of longitudinal research: Design, measurement, and analysis, (pp.373- 385). London: Elsevier.
Wagnild, G. M., & Young, H. M. (1993). Development and psychometric evaluation of the Resilience Scale. Journal of Nursing Measurement, 1(2), 165-178.
Werner, E. E. (2000). Protective factors and individual resilience. Jack P. Shonkoff & Samuel J. Meisels (Eds.), in Handbook of early childhood intervention, (pp.115-132). Cambridge: Cambridge University Press.
Yang, R. (2014). The role of non-cognitive skills in students’ academic performance and life satisfaction: a longitudınal study of resilience. (Unpublished doctoral dissertation). University of Pennsylvania.