nparLD: An R Software Package for the Nonparametric Analysis of Longitudinal Data in Factorial Experiments
nparLD: An R Software Package for the Nonparametric Analysis of Longitudinal Data in Factorial Experiments
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DOI：
10.18637/jss.v050.i12
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发表时间：
2012-09-01
影响因子：
5.8
通讯作者：
Konietschke, Frank
中科院分区：
文献类型：
--
作者：
Noguchi, Kimihiro;Gel, Yulia R.;Konietschke, Frank
析因实验的纵向数据经常出现在各个研究领域，从医学和生物学到公共政策和社会学。在大多数实际情况下，观测数据的分布是未知的，并且可能存在许多非典型测量值和异常值。因此，使用参数和半参数程序对观察到的纵向样本施加限制性分布假设变得值得怀疑。这反过来又导致了对统计程序的大量需求，使我们能够在可用数据的最小条件下准确可靠地分析析因实验中的纵向测量，而提供这种可能性的强大非参数方法变得特别具有实际重要性。在本文中，我们介绍了一个新的 R 包 nparLD，它为来自其他学科的统计学家和研究人员提供了一种简单且用户友好的方式来访问最新的稳健的基于排名的方法，用于分析因子设置中的纵向数据。我们通过牙科、生物学和医学的案例研究来说明所实施的程序。
Longitudinal data from factorial experiments frequently arise in various fields of study, ranging from medicine and biology to public policy and sociology. In most practical situations, the distribution of observed data is unknown and there may exist a number of atypical measurements and outliers. Hence, use of parametric and semiparametric procedures that impose restrictive distributional assumptions on observed longitudinal samples becomes questionable. This, in turn, has led to a substantial demand for statistical procedures that enable us to accurately and reliably analyze longitudinal measurements in factorial experiments with minimal conditions on available data, and robust nonparametric methodology offering such a possibility becomes of particular practical importance. In this article, we introduce a new R package nparLD which provides statisticians and researchers from other disciplines an easy and user-friendly access to the most up-to-date robust rank-based methods for the analysis of longitudinal data in factorial settings. We illustrate the implemented procedures by case studies from dentistry, biology, and medicine.