Abstract
In the context of intervention research, it is always important to ask whether the growth of the participants in the intervention group is superior to that of the control group participants. Although this question can be answered by analyses based on traditional generalized linear models, there are many problems associated with such analyses. Alternatively, individual growth curve (IGC) modeling analyses based on linear mixed methods (LMM) are proposed. Although LMM are available in generic computer software, such as SPSS, there is a paucity of user-friendly manuals and illustrations. To help researchers utilize SPSS in creating IGC models, we present in this paper the basic concepts of IGC modeling and of the process of using SPSS to conduct IGC.
Original language | English |
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Pages (from-to) | 169-182 |
Number of pages | 14 |
Journal | International Journal on Disability and Human Development |
Volume | 13 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1 May 2014 |
Keywords
- human development
- individual growth curve modeling
- linear mixed methods
- SPSS
ASJC Scopus subject areas
- Rehabilitation
- Sensory Systems
- Geriatrics and Gerontology
- Psychiatry and Mental health
- Advanced and Specialised Nursing
- Speech and Hearing