In this article, I extend the theory of added-variable plots to three panel-data estimation methods: fixed effects, between effects, and random effects. An added-variable plot is an effective way to show the correlation between an independent variable and a dependent variable conditional on other independent variables. In a multivariate context, a simple scatterplot showing x versus y is not adequate to show the relationship of x with y, because it ignores the impact of the other covariates. Added-variable plots are also useful for spotting influential outliers in the data that affect the estimated regression parameters. Stata can display added-variable plots with the command avplot, but it can be used only after regress. My new command, xtavplot, is a postestimation command that creates added-variable plots after xtreg estimates. Unlike avplot, xtavplot can display a confidence interval around the fitted regression line.

在本文中，我将可变变量图的理论扩展到三种面板数据估计方法：固定效应，效应之间和随机效应。加变量图是显示自变量与以其他自变量为条件的因变量之间的相关性的有效方法。在多变量情况下，一个简单的散点图表示X与ý不足以显示的关系X与ÿ，因为它忽略了其他协变量的影响。加变量图还可用于发现影响估计回归参数的数据中有影响的离群值。Stata可以使用命令avplot显示添加变量图，但只能在回归后使用。我的新命令xtavplot是后估计命令，该命令在xtreg估计后创建加变量图。与avplot不同，xtavplot可以在拟合的回归线周围显示置信区间。