Cumulative Link Models for Ordinal Regression with the R Package ordinal

Cumulative Link Models for Ordinal Regression with the R Package ordinal
复制标题

使用 R 包序数进行序数回归的累积链接模型

DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
B. Christensen
B. Christensen
中科院分区：
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文献类型：
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作者：
Rune Haubo;B. Christensen

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本文介绍了使用累积链接模型分析有序数据的R-包有序。模型框架包括部分比例优势、结构化阈值、尺度效应和可伸缩连接函数。该软件包还支持具有随机效应的累积链接模型，这将在未来的论文中介绍。一个快速和可靠的正则化牛顿估计方案，使用解析导数提供了最大似然估计的模型类。本文描述了包中的实现以及如何使用包中的功能来分析有序数据，包括模型可识别性和自定义建模的主题。该软件包实现了轮廓似然置信区间的方法，I型，II型和III型检验的偏差表分析，各种预测以及检查拟合模型收敛性的方法
This paper introduces the R-package ordinal for the analysis of ordinal data using cumulative link models. The model framework implemented in ordinal includes partial proportional odds, structured thresholds, scale effects and flexible link functions. The package also support cumulative link models with random effects which are covered in a future paper. A speedy and reliable regularized Newton estimation scheme using analytical derivatives provides maximum likelihood estimation of the model class. The paper describes the implementation in the package as well as how to use the functionality in the package for analysis of ordinal data including topics on model identifiability and customized modelling. The package implements methods for profile likelihood confidence intervals, analysis of deviance tables with type I, II and III tests, predictions of various kinds as well as methods for checking the convergence of the fitted models