如何编写一个用于创建模型并具有引用同一模型的函数的 for 循环 [英] How to write a for loop which creates a model and has a function which references that same model

问题描述

我正在尝试使用 rstatix 包中的 anova_test 函数对不平衡的双向方差分析运行事后分析.我需要迭代地运行这个事后测试，因为我有大约 26 个响应 (y) 变量.我的第一步是创建与 group 和 treatment 相关的所有 y 变量的模型.我已经成功地做到了这一点，创建了一个包含 26 个模型的列表:

I am trying to run a post hoc analysis on an unbalanced two way anova using the anova_test funciton in the rstatix package. I need to run this post hoc test iteratively, as I have ~26 response (y) variables. My first step is to create models of all my y variables with relation to group and treatment. I have successfully managed to do this, creating a single list with 26 models:

models <- map(data[,y1:y26], ~(lm(.x ~data$group*data$treatment)))

现在是我坚持的部分.反复引用这些模型.我想为我拥有的 每个 y 变量运行以下代码:

Now comes the part I'm stuck on. Referring to these models iteratively. I would like to run the following code for every y variable I have:

group_by(group) %>%
anova_test(y ~ treatment, error = models(y), type = 3)

在我的 y 每次都发生变化的地方，模型"(在 error = 术语中引用)相应地更新.我正在努力解决这一问题，因为我制作的第一组模型用于通知第二组模型.

where my y changes every time and as it does, the "model" (referred to in the error = term) is updated accordingly. I'm struggling with this bit since first set of models I make is used to inform the second set of models.

然而，如果我一次只在整个代码中运行一个 y 变量，我会得到适当的结果.

However, if I run just one y variable through this whole bit of code at one time, I get the appropriate results.

model <- lm(y ~ group*treatment, data = data)

data %>%
group_by(group) %>%
anova_test(y ~ treatment, error = model, type = 3)

我曾尝试创建一个 for 循环以及使用 purrr 包中的 map 函数，但我没有成功.我是 for 循环和 purrr 的新手，所以我确定这是一个简单的修复，我只是看不到它.

I have tried creating a for loop as well as using the map function in the purrr package but I have been unsuccessful. I am new to for loops and purrr so I am sure it's a simple fix I just can't see it.

基本上我想要一种运行方式

Basically I want a way to run

data %>%
group_by(group) %>%
anova_test(y ~ treatment, error = model, type = 3)

对不同的 y 变量(y1, y2, ..., y26)进行迭代，同时也引用适当的 model(model$y1，模型 $y2，...，模型 $26).

iteratively for different y variables (y1, y2, ..., y26) while also referring to the approprite model (model$y1, model$y2, ..., model$26).

感谢您的帮助！

推荐答案

感谢来自 rstudio 社区论坛的 Nirgrahamuk 的回答:

Thanks to Nirgrahamuk from the rstudio community forum for this answer:

map(names(models_1) ,
    ~ anova_test(data=group_by(df,edge),
                 formula = as.formula(paste0(.x,"~ trt")),
                 error = models_1[[.x]],
                 type = 3))

(请参阅他们的完整答案:https://community.rstudio.com/t/trouble-using-group-by-and-map2-together/66730/8?u=mvula)

(see their full answer at: https://community.rstudio.com/t/trouble-using-group-by-and-map2-together/66730/8?u=mvula)

^{由 reprex 包 (v0.3.0) 于 2020 年 5 月 20 日创建}

^{Created on 2020-05-20 by the reprex package (v0.3.0)}

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