这种情况下,使用潜增长曲线模型拟合我们的数据,或者说在我们的数据中建立潜增长模型将不合适,应该考虑到样本异质性问题,而能解决这一问题的模型之一便是潜类别增长模型(Latent Class Growth Model, LCGM)。 潜类别增长模型可以简单理解为:先将样本分成不同的潜类别组,然后在每个潜类别组中建立潜增长曲线模型去描述...
Next, I delineate the specification and statistical inference of the latent growth model (LGM). It is emphasized that in many ways, LGM is an SEM expression of linear mixed modeling in the context of longitudinal analysis. The latent growth mixture model (LGMM) is an extension of LGM with ...
Fig. 4. Growth Mixture Modeling (GMM). k latent classes are estimated, each having class-specific growth parameters. In GMM, any part of the model can be class-specific (including the means and variances of the latent growth parameters, the indicator variances, etc.). (10)yit=∑k=1Kpkα...
Latent growth mixture modeling (LGMM) was utilized to identify subpopulations with similar longitudinal trajectories. LGMM models both linear and non-linear trajectories and allows for individuals to vary on growth factors (i.e., intercept and slope) [82,83]; thus, is appropriate for modeling ev...
I am conducting the latent class growth mixture model for my study .This study uses data from the longitudinal cohort. Data includes 4 different phases.Phase 1 has a span of (2003-2006) and is following at 3 subsequent phases.we aimed to identify different patterns of BMI I WANTto describe...
I am thinking of a random intercepts and slopes model (for longitudinal data), but would like to have random slopes follow a mixture normal (latent class), while keep random intercept a regular normal. Can growth mixture model be applied in this situation?
second-order latent growth modelThis Monte Carlo study investigated the impacts of measurement noninvariance across groups on major parameter estimates in latent growth modeling when researchers test group differences in initial status and latent growth. The average initial status and latent growth and ...
In this paper, we consider the use of the latent growth curve model to analyze longitudinal ordinal categorical data that involve measurements at different... TY Lu,WY Poon,YF Tsang - 《Computational Statistics & Data Analysis》 被引量: 26发表: 2011年 A Latent Growth Mixture Modeling Approach...
We look at the performance of these tests and indexes for 3 types of mixture models: latent class analysis (LCA), a factor mixture model (FMA), and a growth mixture models (GMM). We evaluate the ability of the tests and indexes to correctly identify the number of classes at three ...
, 2002), where latent factor models are an alternative to the shared-parameter model approach to censored or missing data. Growth Mixture Models LGMs can be broadened to include subject-specific random effects. Such models are called growth mixture models (Muthén et al., 2002) or heterogeneity...