如何更改papaja :: apa_print中的十进制标记？

发布于 2025-01-23 06:56:41 字数 951 浏览 2 评论 0原文

我想使用papaja :: apa_print（）使我的报告更容易，但是我需要调整语言的APA样式适应的输出。这意味着显示领先的零并将逗号设置为十进制标记。大多数papaja函数的大多数不是问题，而是apa_print（）并不是那么简单。

library(papaja)
model <- lm(Sepal.Length ~ Species, data = iris)
anova(model) |> apa_print(decimal.mark = ",", gt1 = TRUE)

这些选项应用于大多数输出，但不适用于p值和F-Ratios（至少在ANOVA中）。我认为它可能适用于输出的所有乳胶部分，但ETA方似乎还可以。我相信这可能是一个错误。那么我该如何处理呢？我应该将其报告为错误吗？输出的一部分供参考：

$estimate
$estimate$Species
[1] "$\\hat{\\eta}^2_G = 0,401$, 90\\% CI $[0,300, 0,485]$"


$statistic
$statistic$Species
[1] "$F(2, 147) = 49.16$, $p < .001$"


$full_result
$full_result$Species
[1] "$F(2, 147) = 49.16$, $p < .001$, $\\hat{\\eta}^2_G = 0,401$, 90\\% CI $[0,300, 0,485]$"


$table
A data.frame with 7 labelled columns:

     term estimate       conf.int statistic df df.residual p.value
1 Species    0,401 [0,300, 0,485]     49.16  2         147  < .001

原文

I wanted to use papaja::apa_print() to make things easier in my report but I need to adjust the output for my language's APA style adaptation. It means displaying leading zeros and setting comma as the decimal mark. It's not a problem with most of papaja functions but with apa_print() is not that straightforward.

library(papaja)
model <- lm(Sepal.Length ~ Species, data = iris)
anova(model) |> apa_print(decimal.mark = ",", gt1 = TRUE)

The options are applied to most of the output but not to p-values and F-ratios (at least in ANOVA). I thought it might apply to all LaTeX parts of the output but eta-squared seems to be OK. I believe it might be a bug. So how do I deal with it? Should I report it as a bug? Part of the output for reference:

$estimate
$estimate$Species
[1] "$\\hat{\\eta}^2_G = 0,401$, 90\\% CI $[0,300, 0,485]quot;


$statistic
$statistic$Species
[1] "$F(2, 147) = 49.16$, $p < .001quot;


$full_result
$full_result$Species
[1] "$F(2, 147) = 49.16$, $p < .001$, $\\hat{\\eta}^2_G = 0,401$, 90\\% CI $[0,300, 0,485]quot;


$table
A data.frame with 7 labelled columns:

     term estimate       conf.int statistic df df.residual p.value
1 Species    0,401 [0,300, 0,485]     49.16  2         147  < .001

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