文章基本信息

标题：Logistic Growth Modeling with Markov Chain Monte Carlo Estimation
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作者：Choi, Jaehwa ; Chen, Jinsong ; Harring, Jeffrey R. 等
期刊名称：Journal of Modern Applied Statistical Methods
出版年度：2019
卷号：18
期号：1
页码：22-39
DOI：10.22237/jmasm/1556669820
出版社：Wayne State University
摘要：A new growth modeling approach is proposed to can fit inherently nonlinear (i.e., logistic) function without constraint nor reparameterization. A simulation study is employed to investigate the feasibility and performance of a Markov chain Monte Carlo method within Bayesian estimation framework to estimate a fully random version of a logistic growth curve model under manipulated conditions such as the number and timing of measurement occasions and sample sizes.
关键词：Growth modeling; latent growth modeling; nonlinear growth models; logistic functions; Markov chain Monte Carlo; Bayesian inference