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目录.html
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<!DOCTYPE html>
<html lang="en">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
<title>目录 | 纵向与事件时间数据的联合模型及其在 R 中的应用</title>
<meta name="author" content="Wang Zhen">
<meta name="description" content="介绍 1.1 目标 1.2 激励性研究 1.2.1 原发性胆汁性肝硬化 (PBC) 数据 1.2.2 艾滋病数据 1.2.3 肝硬化数据 1.2.4 主动脉瓣数据 1.2.5 其他应用 1.3 纵向研究中的推断目标 1.3.1 协变量对单一结果的效应 1.3.2 结果之间的关联 1.3.3 复杂的假设检验 1.3.4 预测 1.3.5 隐式结果的统计分析 1.4 概述 纵向数据分析...">
<meta name="generator" content="bookdown 0.38 with bs4_book()">
<meta property="og:title" content="目录 | 纵向与事件时间数据的联合模型及其在 R 中的应用">
<meta property="og:type" content="book">
<meta property="og:description" content="介绍 1.1 目标 1.2 激励性研究 1.2.1 原发性胆汁性肝硬化 (PBC) 数据 1.2.2 艾滋病数据 1.2.3 肝硬化数据 1.2.4 主动脉瓣数据 1.2.5 其他应用 1.3 纵向研究中的推断目标 1.3.1 协变量对单一结果的效应 1.3.2 结果之间的关联 1.3.3 复杂的假设检验 1.3.4 预测 1.3.5 隐式结果的统计分析 1.4 概述 纵向数据分析...">
<meta name="twitter:card" content="summary">
<meta name="twitter:title" content="目录 | 纵向与事件时间数据的联合模型及其在 R 中的应用">
<meta name="twitter:description" content="介绍 1.1 目标 1.2 激励性研究 1.2.1 原发性胆汁性肝硬化 (PBC) 数据 1.2.2 艾滋病数据 1.2.3 肝硬化数据 1.2.4 主动脉瓣数据 1.2.5 其他应用 1.3 纵向研究中的推断目标 1.3.1 协变量对单一结果的效应 1.3.2 结果之间的关联 1.3.3 复杂的假设检验 1.3.4 预测 1.3.5 隐式结果的统计分析 1.4 概述 纵向数据分析...">
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<ul class="book-toc list-unstyled">
<li><a class="" href="index.html">前言</a></li>
<li><a class="active" href="%E7%9B%AE%E5%BD%95.html">目录</a></li>
<li class="book-part">正文</li>
<li><a class="" href="chap1.html"><span class="header-section-number">1</span> 介绍</a></li>
<li><a class="" href="chap2.html"><span class="header-section-number">2</span> 纵向数据分析</a></li>
<li><a class="" href="chap3.html"><span class="header-section-number">3</span> 事件时间数据分析</a></li>
<li><a class="" href="chap4.html"><span class="header-section-number">4</span> 纵向与事件时间数据的联合模型</a></li>
<li><a class="" href="chap5.html"><span class="header-section-number">5</span> 标准联合模型的扩展</a></li>
<li><a class="" href="chap6.html"><span class="header-section-number">6</span> 联合模型诊断</a></li>
<li><a class="" href="chap7.html"><span class="header-section-number">7</span> 联合模型的预测和准确性</a></li>
<li class="book-part">附录</li>
<li><a class="" href="A.html"><span class="header-section-number">A</span> R 的简要介绍</a></li>
<li class="book-part">—</li>
<li><a class="" href="bib.html">参考文献</a></li>
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<h1>目录<a class="anchor" aria-label="anchor" href="#%E7%9B%AE%E5%BD%95"><i class="fas fa-link"></i></a>
</h1>
<ol style="list-style-type: decimal">
<li>
<a href="chap1.html#chap1">介绍</a>
<ul>
<li>1.1 <a href="chap1.html#sec1-1">目标</a>
</li>
<li>1.2 <a href="chap1.html#sec1-2">激励性研究</a>
<ul>
<li>1.2.1 <a href="chap1.html#sec1-2-1">原发性胆汁性肝硬化 (PBC) 数据</a>
</li>
<li>1.2.2 <a href="chap1.html#sec1-2-2">艾滋病数据</a>
</li>
<li>1.2.3 <a href="chap1.html#sec1-2-3">肝硬化数据</a>
</li>
<li>1.2.4 <a href="chap1.html#sec1-2-4">主动脉瓣数据</a>
</li>
<li>1.2.5 <a href="chap1.html#sec1-2-5">其他应用</a>
</li>
</ul>
</li>
<li>1.3 <a href="chap1.html#sec1-3">纵向研究中的推断目标</a>
<ul>
<li>1.3.1 <a href="chap1.html#sec1-3-1">协变量对单一结果的效应</a>
</li>
<li>1.3.2 <a href="chap1.html#sec1-3-2">结果之间的关联</a>
</li>
<li>1.3.3 <a href="chap1.html#sec1-3-3">复杂的假设检验</a>
</li>
<li>1.3.4 <a href="chap1.html#sec1-3-4">预测</a>
</li>
<li>1.3.5 <a href="chap1.html#sec1-3-5">隐式结果的统计分析</a>
</li>
</ul>
</li>
<li>1.4 <a href="chap1.html#sec1-4">概述</a>
</li>
</ul>
</li>
<li>
<a href="chap2.html#chap2">纵向数据分析</a>
<ul>
<li>2.1 <a href="chap2.html#sec2-1">纵向数据的特征</a>
</li>
<li>2.2 <a href="chap2.html#sec2-2">线性混合效应模型</a>
<ul>
<li>2.2.1 <a href="chap2.html#sec2-2-1">估计</a>
</li>
<li>2.2.2 <a href="chap2.html#sec2-2-2">在 R 中的实现</a><br>
</li>
</ul>
</li>
<li>2.3 <a href="chap2.html#sec2-3">纵向研究中的缺失数据</a>
<ul>
<li>2.3.1 <a href="chap2.html#sec2-3-1">缺失数据机制</a>
</li>
<li>2.3.2 <a href="chap2.html#sec2-3-2">非随机缺失模型族</a>
</li>
</ul>
</li>
<li>2.4 <a href="chap2.html#sec2-4">延伸阅读</a>
</li>
</ul>
</li>
<li>
<a href="chap3.html#chap3">事件时间数据分析</a>
<ul>
<li>3.1 <a href="chap3.html#sec3-1">事件时间数据的特征</a>
</li>
<li>3.2 <a href="chap3.html#sec3-2">生存分析的基本函数</a>
<ul>
<li>3.2.1 <a href="chap3.html#sec3-2-1">删失数据的似然构造</a>
</li>
</ul>
</li>
<li>3.3 <a href="chap3.html#sec3-3">相对风险回归模型</a>
<ul>
<li>3.3.1 <a href="#sec3-3-1">在 R 中的实现</a>
</li>
</ul>
</li>
<li>3.4 <a href="chap3.html#sec3-4">时依协变量</a>
</li>
<li>3.5 <a href="chap3.html#sec3-5">扩展的 Cox 模型</a>
</li>
<li>3.6 <a href="chap3.html#sec3-6">延伸阅读</a>
</li>
</ul>
</li>
<li>
<a href="chap4.html#chap4">纵向与事件时间数据的联合模型</a>
<ul>
<li>4.1 <a href="chap4.html#sec4-1">基本联合模型</a>
<ul>
<li>4.1.1 <a href="chap4.html#sec4-1-1">生存子模型</a>
</li>
<li>4.1.2 <a href="chap4.html#sec4-1-2">纵向子模型</a>
</li>
</ul>
</li>
<li>4.2 <a href="chap4.html#sec4-2">R 中的联合建模:与扩展的 Cox 模型比较</a>
</li>
<li>4.3 <a href="chap4.html#sec4-3">联合模型的估计</a>
<ul>
<li>4.3.1 <a href="chap4.html#sec4-3-1">两阶段法</a>
</li>
<li>4.3.2 <a href="chap4.html#sec4-3-2">联合似然公式</a>
</li>
<li>4.3.3 <a href="chap4.html#sec4-3-3">具有未指定基线风险函数的标准误</a>
</li>
<li>4.3.4 <a href="chap4.html#sec4-3-4"><code>JM</code> 中的优化控制</a>
</li>
<li>4.3.5 <a href="chap4.html#sec4-3-5">数值积分</a>
</li>
<li>4.3.6 <a href="chap4.html#sec4-3-6"><code>JM</code> 中的数值积分控制</a>
</li>
<li>4.3.7 <a href="chap4.html#sec4-3-7">收敛问题</a>
</li>
</ul>
</li>
<li>4.4 <a href="chap4.html#sec4-4">联合模型的渐近推断</a>
<ul>
<li>4.4.1 <a href="chap4.html#sec4-4-1">假设检验</a>
</li>
<li>4.4.2 <a href="chap4.html#sec4-4-2">置信区间</a>
</li>
<li>4.4.3 <a href="chap4.html#sec4-4-3">设计考虑</a>
</li>
</ul>
</li>
<li>4.5 <a href="chap4.html#sec4-5">随机效应的估计</a>
</li>
<li>4.6 <a href="chap4.html#sec4-6">与缺失数据框架的连接</a>
</li>
<li>4.7 <a href="chap4.html#sec4-7">联合模型的敏感性分析</a>
</li>
</ul>
</li>
<li>
<a href="chap5.html#chap5">标准联合模型的扩展</a>
<ul>
<li>5.1 <a href="chap5.html#sec5-1">参数化</a>
<ul>
<li>5.1.1 <a href="chap5.html#sec5-1-1">交互效应</a>
</li>
<li>5.1.2 <a href="chap5.html#sec5-1-2">滞后效应</a>
</li>
<li>5.1.3 <a href="chap5.html#sec5-1-3">滞后效应</a>
</li>
<li>5.1.4 <a href="chap5.html#sec5-1-4">时依斜率参数化</a>
</li>
<li>5.1.5 <a href="chap5.html#sec5-1-5">累积效应参数化</a>
</li>
<li>5.1.6 <a href="#sec5-1-6">随机效应参数化</a>
</li>
</ul>
</li>
<li>5.2 <a href="chap5.html#sec5-2">处理外源时依协变量</a>
</li>
<li>5.3 <a href="chap5.html#sec5-3">分层相对风险模型</a>
</li>
<li>5.4 <a href="chap5.html#sec5-4">潜类别联合模型</a>
</li>
<li>5.5 <a href="chap5.html#sec5-5">多个事件</a>
<ul>
<li>5.5.1 <a href="chap5.html#sec5-5-1">竞争风险</a>
</li>
<li>5.5.2 <a href="chap5.html#sec5-5-2">复发事件</a>
</li>
</ul>
</li>
<li>5.6 <a href="chap5.html#sec5-6">加速失效时间模型</a>
</li>
<li>5.7 <a href="chap5.html#sec5-7">分类纵向结果的联合模型</a>
<ul>
<li>5.7.1 <a href="chap5.html#sec5-7-1">广义线性混合模型 (GLMM)</a>
</li>
<li>5.7.2 <a href="chap5.html#sec5-7-2">将离散重复测量与生存结合</a>
</li>
</ul>
</li>
<li>5.8 <a href="chap5.html#sec5-8">多个纵向结果的联合模型</a>
</li>
</ul>
</li>
<li>
<a href="chap6.html#chap6">标准联合模型的扩展</a>
<ul>
<li>6.1 <a href="chap6.html#sec6-1">联合模型的残差</a>
<ul>
<li>6.1.1 <a href="chap6.html#sec6-1-1">纵向部分的残差</a>
</li>
<li>6.1.2 <a href="chap6.html#sec6-1-2">生存部分的残差</a>
</li>
</ul>
</li>
<li>6.2 <a href="chap6.html#sec6-2">脱落和残差</a>
</li>
<li>6.3 <a href="chap6.html#sec6-3">多重插补残差</a>
<ul>
<li>6.3.1 <a href="chap6.html#sec6-3-1">固定就诊时间</a>
</li>
<li>6.3.2 <a href="chap6.html#sec6-3-2">随机就诊时间</a>
</li>
</ul>
</li>
<li>6.4 <a href="chap6.html#sec6-4">随机效应分布</a>
</li>
</ul>
</li>
<li>
<a href="chap7.html#chap7">联合模型的预测和准确性</a>
<ul>
<li>7.1 <a href="chap7.html#sec7-1">生存概率的动态预测</a>
<ul>
<li>7.1.1 <a href="chap7.html#sec7-1-1">定义</a>
</li>
<li>7.1.2 <a href="chap7.html#sec7-1-2">估计</a>
</li>
<li>7.1.3 <a href="chap7.html#sec7-1-3">在 R 中的实现</a>
</li>
</ul>
</li>
<li>7.2 <a href="chap7.html#sec7-2">纵向结果的动态预测</a>
</li>
<li>7.3 <a href="chap7.html#sec7-3">参数化对预测的影响</a>
</li>
<li>7.4 <a href="chap7.html#sec7-4">联合模型的前瞻准确性</a>
<ul>
<li>7.4.1 <a href="chap7.html#sec7-4-1">二项结果的判别度量</a>
</li>
<li>7.4.2 <a href="chap7.html#sec7-4-2">生存结果的判别度量</a>
</li>
<li>7.4.3 <a href="chap7.html#sec7-4-3">纵向标志物的预测规则</a>
</li>
<li>7.4.4 <a href="chap7.html#sec7-4-4">判别指数</a>
</li>
<li>7.4.5 <a href="chap7.html#sec7-4-5">联合建模框架下的估计</a>
</li>
<li>7.4.6 <a href="chap7.html#sec7-4-6">在 R 中的实现</a>
</li>
</ul>
</li>
</ul>
</li>
</ol>
<ul>
<li>附录 A <a href="A.html#A">R 的简要介绍</a>
<ul>
<li>A.1 <a href="#secA-1">获取并安装 R 和 R 包</a>
</li>
</ul>
</li>
<li>附录 B <a href="#B">联合模型的 EM 算法</a>
</li>
<li>附录 C <a href="#C">JM 包的结构</a>
</li>
<li><a href="bib.html#bib">参考书目</a></li>
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