https://wiki.statsape.com/index.php?action=history&feed=atom&title=%E5%B9%BF%E4%B9%89%E4%BC%B0%E8%AE%A1%E6%96%B9%E7%A8%8B_%E6%B3%8A%E6%9D%BE 2026-05-15T16:10:45Z 本wiki上该页面的版本历史 MediaWiki 1.39.6 https://wiki.statsape.com/index.php?title=%E5%B9%BF%E4%B9%89%E4%BC%B0%E8%AE%A1%E6%96%B9%E7%A8%8B_%E6%B3%8A%E6%9D%BE&diff=6086&oldid=prev 2024-01-19T11:11:40Z

<p></p> <table style="background-color: #fff; color: #202122;" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="zh-Hans-CN"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">←上一版本</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">2024年1月19日 (五) 19:11的版本</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l7">第7行：</td> <td colspan="2" class="diff-lineno">第7行：</td></tr> <tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|productionstate={{图标文件|Win}} / {{图标文件|W10}} Win10及以上可用</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; 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border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>|nodeenglishname=<del style="font-weight: bold; text-decoration: none;">[[Has english name::</del>Generalized Estimating Equation_Poisson<del style="font-weight: bold; text-decoration: none;">]]</del></div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>|nodeenglishname=Generalized Estimating Equation_Poisson</div></td></tr> <tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>|abbreviation=<del style="font-weight: bold; text-decoration: none;">[[Has abbreviation::</del>GEEPoisson<del style="font-weight: bold; text-decoration: none;">]]</del></div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>|abbreviation=GEEPoisson</div></td></tr> <tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|funcmaincategory=数据分析</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|funcmaincategory=数据分析</div></td></tr> <tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|funcsubcategory=[[DataAGM Lv1 Cat::回归分析]]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; 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<p>创建页面，内容为“{{Infobox nodebasic |nodename=广义估计方程_泊松 |nodeimage=Generalized Estimating Equation_Poisson.png |icon=Generalized Estimating Equation_Poisson.svg |simpleicon=Generalized Estimating Equation_Poisson_Pure.svg |developer=Dev.Team-DPS |productionstate={{图标文件|Win}} / {{图标文件|W10}} Win10及以上可用 |productionstatedesc=在<a href="/index.php?title=Update:DecisionLinnc_1.0.2.0&amp;action=edit&amp;redlink=1" class="new" title="Update:DecisionLinnc 1.0.2.0（页面不存在）">V1.0.2</a>部署 |nodeenglishname=Has english name::Generalized Estimating Equati…”</p> <p><b>新页面</b></p><div>{{Infobox nodebasic <br /> |nodename=广义估计方程_泊松<br /> |nodeimage=Generalized Estimating Equation_Poisson.png<br /> |icon=Generalized Estimating Equation_Poisson.svg<br /> |simpleicon=Generalized Estimating Equation_Poisson_Pure.svg<br /> |developer=Dev.Team-DPS<br /> |productionstate={{图标文件|Win}} / {{图标文件|W10}} Win10及以上可用<br /> |productionstatedesc=在[[Update:DecisionLinnc 1.0.2.0|V1.0.2]]部署<br /> |nodeenglishname=[[Has english name::Generalized Estimating Equation_Poisson]]<br /> |abbreviation=[[Has abbreviation::GEEPoisson]]<br /> |funcmaincategory=数据分析<br /> |funcsubcategory=[[DataAGM Lv1 Cat::回归分析]]<br /> |nodecategory=数据挖掘<br /> |nodeinterpretor=R<br /> |nodeshortdescription=&lt;p&gt;广义估计方程是一种研究纵向数据(比如重复测量数据,面板数据)的方法。用于估计广义线性模型的参数,其中线性模型的结果之间可能存在未知的相关性, 对于纵向数据,不满足方差分析条件的重复测量设计资料可以采用广义估计方程来进行分析。纵向数据是按时间顺序对个体进行重复测量得到的资料泊松回归是用来为计数资料和列联表建模的一种回归分析,因变量为计数变量,解决的问题是在特定时间内发生n个事件的概率。回归需要满足以下条件:一个事件的发生不影响其它事件的发生,即事件独立发生,不存在传染性、聚集性的事件。因变量Y服从泊松分布,总体均数等于总体方差。&lt;/p&gt;&lt;p&gt;用途：用于分析计数数据的统计方法，尤其适用于处理相关或群集数据。GEE方法考虑了数据中可能存在的观测间相关性，并且可以用于纵向数据或重复测量数据分析。&lt;/p&gt;&lt;p&gt;参数：选择泊松分布因变量，ID变量，和自变量。&lt;/p&gt;<br /> |nodeinputnumber=5<br /> |nodeoutputnumber=2<br /> |nodeloopsupport=是<br /> |nodeifswitchsupport=否<br /> |nodeavailableplotlist=FR_Curve_Plot;RegressionCoefficientPlot<br /> |nodeavailabletablelist=Coeff-Value;SE;Stats-Value;P-Value;CI<br /> |nodeconfiguration=VariableList;DropMenu<br /> |nodeinputports=WorkFlow-Control ➤;Transfer-Variable ◆;Transfer-Table ■<br /> |nodeoutputports=WorkFlow-Control ➤;Transfer-Table ■<br /> |statsapewikiurl=https://wiki.statsape.com/广义估计方程_泊松<br /> |previousnode=[[广义估计方程_负二项]]<br /> |nextnode=[[广义相加混合模型_伽玛]]<br /> }}<br /> <br /> <br /> {{Navplate AlgorithmNodeList}}<br /> <br /> [[Category:回归分析]]</div>

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