Abstract
Recently, latent curve modelling (LCM) has received increasing attention in the analysis of longitudinal data. It is a method to model individual change and to assess the effects of co-variates and the relationship among multiple outcomes. It provides an integrated and flexible approach in modelling developmental processes from both inter- and intra-individual perspectives. Similar to conventional longitudinal analysis, the main objectives of this model are to characterise changes in the response of interest over time and to examine the selected covariates that contribute to those changes. In this article the fundamental principle of LCM is briefly introduced. Several important kinds of LCM, including linear LCM, non-linear LCM, multilevel LCM and mixture LCM, together with their applications in medical research, are reviewed. We believe that this statistical technique should become more popular in medical applications, and that the medical field would benefit from increased use of this powerful and flexible statistical method.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
