Class Evolution Tree: A graphical tool to support decisions on the number of classes in exploratory categorical latent variable modeling for rehabilitation research

International Journal of Rehabilitation Research

Volumn 34, Issue 2, 2011, Pages 181-185

  Kriston, Levente ^a   Melchior, Hanne ^a   Hergert, Anika ^a   Bergelt, Corinna ^a   Watzke, Birgit ^a   Schulz, Holger ^a   Von Wolff, Alessa ^a  

^a UNIVERSITY MEDICAL CENTER HAMBURG EPPENDORF   (Germany)

Author keywords

Classification; latent class analysis; medical illustration; multivariate analysis; rehabilitation

Indexed keywords

CLASSIFICATION; LATENT CLASS ANALYSIS; MEDICAL ILLUSTRATION; MULTI VARIATE ANALYSIS; REHABILITATION;

MULTIVARIANT ANALYSIS; PATIENT TREATMENT; PLANT EXTRACTS; RESEARCH;

PATIENT REHABILITATION;

ARTICLE; COMPUTER GRAPHICS; COOPERATION; CROSS-SECTIONAL STUDY; DECISION SUPPORT SYSTEM; DECISION TREE; GERMANY; HEALTH SERVICES RESEARCH; HOSPITAL ADMISSION; HUMAN; INTERDISCIPLINARY COMMUNICATION; LONGITUDINAL STUDY; MENTAL DISEASE; MULTIMODALITY CANCER THERAPY; NEOPLASM; PATIENT CARE; REHABILITATION; REHABILITATION CENTER; RESEARCH; STATISTICAL MODEL; STATISTICS; TREATMENT OUTCOME;

COMBINED MODALITY THERAPY; COMPUTER GRAPHICS; COOPERATIVE BEHAVIOR; CROSS-SECTIONAL STUDIES; DECISION SUPPORT TECHNIQUES; DECISION TREES; GERMANY; HEALTH SERVICES RESEARCH; HUMANS; INTERDISCIPLINARY COMMUNICATION; LONGITUDINAL STUDIES; MENTAL DISORDERS; MODELS, STATISTICAL; NEOPLASMS; OUTCOME AND PROCESS ASSESSMENT (HEALTH CARE); PATIENT ADMISSION; PATIENT CARE TEAM; REHABILITATION; REHABILITATION CENTERS; RESEARCH;

EID: 79955828902     PISSN: 03425282     EISSN: None     Source Type: Journal    
DOI: 10.1097/MRR.0b013e3283460e7d     Document Type: Article

References (20)

1. Akaike H (1987). Factor analysis and AIC. Psychometrika 52:317-332.
2. Bauer DJ, Curran PJ (2003). Distributional assumptions of growth mixture models: implications for overextraction of latent trajectory classes. Psychol Methods 8:338-363. (Pubitemid 37268950)
3. Bürge E, Cieza A, Allet L, Finger ME, Stucki G, Huber EO (2008). Intervention categories for physiotherapists treating patients with internal medicine conditions on the basis of the International Classification of Functioning Disability and Health. Int J Rehabil Res 31:43-50. (Pubitemid 351263235)
4. Cattell R (1966). The scree test for the number of factors. Multivariate Behav Res 1:245-276.
5. Dean N, Raftery AE (2010). Latent class analysis variable selection. Ann Inst Stat Math 62:11-35.
6. Fulton C (1999). Patients with metastatic breast cancer: their physical and psychological rehabilitation needs. Int J Rehabil Res 22:291-301.
7. Goodman LA (1974). Exploratory latent structure analysis using both identifiable and unidentifiable models. Biometrika 61:215-231.
8. Huang G (2005). Selecting the number of classes under latent class regression: a factor analytic analogue. Psychometrika 70:325-345. (Pubitemid 41251215)
9. Jung T,Wickrama KAS (2008). An introduction to latent class growth analysis and growth mixture modeling. Soc Personal Psychol Compass 2:302-317.
10. Kass RE, Raftery AE (1995). Bayes factors. J Am Stat Assoc 90:773-795.
11. Lo Y, Mendell NR, Rubin DB (2001). Testing the number of components in a normal mixture. Biometrika 88:767-778. (Pubitemid 33771022)
12. Marcoulides GA, Moustaki I (2002). Latent variable and latent structure models. Mahwah, NJ: Lawrence Erlbaum Associates.
13. McLachlan G, Peel D (2000). Finite mixture models. New York: Wiley.
14. Muthén BO, Muthén LK (2000). Integrating person-centered and variablecentered analyses: growth mixture modeling with latent trajectory classes. Alcohol Clin Exp Res 24:882-891. (Pubitemid 30421740)
15. Nylund KL, Asparouhov T, Muthen BO (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Struct Equ Modeling 14:535-569.
16. Schwarz G (1978). Estimating the dimension of a model. Ann Stat 6:461-464.
17. Van Harten WH, Van Noort O, Warmerdam R, Hendricks H, Seidel E (1998). Assessment of rehabilitation needs in cancer patients. Int J Rehabil Res 21:247-257. (Pubitemid 28508925)
18. Van Weert E, Hoekstra-Weebers JEHM, Grol BMF, Otter R, Arendzen JH, Postema K, van der Schans (2004). Physical functioning and quality of life after cancer rehabilitation. Int J Rehabil Res 27:27-35. (Pubitemid 38393498)
19. Vogel H, Zdrahal-Urbanek J (2004). Rehabilitation in Germany: new challenges of a structured social security scheme. Int J Rehabil Res 27:93-98. (Pubitemid 38903396)
20. Vuong QH (1989). Likelihood ratio tests for model selection and non-nested hypotheses. Econometrica 57:307-333.