Estimation of Extended Mixed Models Using Latent Classes and Latent Processes: The R Package lcmm
Estimation of Extended Mixed Models Using Latent Classes and Latent Processes: The R Package lcmm
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DOI：
10.18637/jss.v078.i02
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发表时间：
2017-06-01
影响因子：
5.8
通讯作者：
Liquet, Benoit
中科院分区：
文献类型：
--
作者：
Proust-Lima, Cecile;Philipps, Viviane;Liquet, Benoit
R包lcmm提供了一系列函数来估计基于线性混合模型理论的统计模型。它包括高斯纵向结果（hlme）、曲线和有序单变量纵向结果（lcmm）以及曲线多变量纵向结果的混合模型和潜在类混合模型的估计（multlcmm），以及联合潜在类混合模型（联合国）（高斯或曲线）纵向结局和可能左截断右截断的至事件发生时间结局-在竞争环境中审查和定义。最大似然估计器是使用修改后的马夸特算法与严格的收敛标准的基础上的参数和似然稳定性，和负的二阶导数。该软件包还提供各种拟合后功能，包括拟合优度分析、分类、绘图、预测轨迹、事件的个体动态预测和预测准确性评估。本文构成了配套文件包通过介绍每个家庭的模型，估计技术，一些实施细节，并通过一个数据集的认知老化的例子。
The R package lcmm provides a series of functions to estimate statistical models based on linear mixed model theory. It includes the estimation of mixed models and latent class mixed models for Gaussian longitudinal outcomes (hlme), curvilinear and ordinal univariate longitudinal outcomes (lcmm) and curvilinear multivariate outcomes (multlcmm), as well as joint latent class mixed models (Jointlcmm) for a (Gaussian or curvilinear) longitudinal outcome and a time-to-event outcome that can be possibly left-truncated right-censored and defined in a competing setting. Maximum likelihood esimators are obtained using a modified Marquardt algorithm with strict convergence criteria based on the parameters and likelihood stability, and on the negativity of the second derivatives. The package also provides various post-fit functions including goodness-of-fit analyses, classification, plots, predicted trajectories, individual dynamic prediction of the event and predictive accuracy assessment. This paper constitutes a companion paper to the package by introducing each family of models, the estimation technique, some implementation details and giving examples through a dataset on cognitive aging.