From e8f793927e490bf327e3c9656328c7aa7bf9cb57 Mon Sep 17 00:00:00 2001 From: nathante Date: Thu, 23 Feb 2023 22:52:44 +0000 Subject: [PATCH] Update on Overleaf. --- article.Rtex | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/article.Rtex b/article.Rtex index f9e3243..01f55fb 100644 --- a/article.Rtex +++ b/article.Rtex @@ -1027,7 +1027,7 @@ grid.draw(p) \subsection{Simulating misclassification in skewed variables} -For simplicity, our main simulations have balanced classified variables. But classifiers are often used to measure imbalanced or skewed variables, which can be more difficult to predict. Here, we show that MLE correction performs similarly well as with skewned classified variables. Although the Fischer approximation for confidence intervals performs poorly, the profile likelihood method works well. +For simplicity, our main simulations have balanced classified variables. But classifiers are often used to measure imbalanced or skewed variables, which can be more difficult to predict. Here, we show that MLE correction performs similarly well as with skewed classified variables. Although the Fischer approximation for confidence intervals performs poorly, the profile likelihood method works well. %However, if one can assume the model for $Y$, then one believes that $Y$ and $X$ are conditionally independent given other observed variables.