r-分组和整理是否可以用于将多层次模型(lme)与重复测量/纵向数据拟合

Question

考虑以下纵向/重复测量数据集示例

library(tidyverse)
library(broom)
library(nlme)
data <- read.csv("https://stats.idre.ucla.edu/stat/data/study2.csv")
data <- data %>% mutate(dbp =rnorm(120, 30:150), sbp = rnorm(120, 50:200),bmi 
= rnorm(120,15:40), chol = rnorm(120,50:350), insulin = rnorm(120,2:40), educ = rnorm(120,5:10))

我可以使用group_by %>% do(tidy(*))运行几个未调整和调整的单级回归模型(循环通过结果和暴露列表(，并将模型结果提取到数据帧中，如下所示

out <-c("pulse","insulin","chol")
exp <- c("factor(exertype)","sbp","dbp")
conf <- c("bmi","factor(diet)")
#Unadjusted models - single level regression (lm)
#################################################
Unadjusted <- expand.grid(out, exp) %>%
group_by(Var1) %>% rowwise() %>%
summarise(frm = paste0(Var1, "~", Var2)) %>%
group_by(model_id = row_number(),frm) %>%
do(tidy(lm(.$frm, data = data))) %>%
mutate(lci = estimate-(1.96*std.error)) %>%
mutate(uci = estimate+(1.96*std.error))
#Adjusted models - single level regression (lm)
###############################################
Adjusted <- expand.grid(out, exp, conf) %>%
group_by(Var1, Var2) %>%
summarise(Var3 = paste0(Var3, collapse = "+")) %>%
rowwise() %>%
summarise(frm = paste0(Var1, "~", Var2, "+", Var3)) %>%
group_by(model_id = row_number(), frm) %>%
do(tidy(lm(.$frm, data = data))) %>%
mutate(lci = estimate-(1.96*std.error)) %>%
mutate(uci = estimate+(1.96*std.error))

我想使用相同的过程来拟合多级模型，以解释重复的数据。使用示例代码：

lme(sbp ~ pulse+factor(diet)+time, data=data, random= ~time|id, method ="ML")

然而，当我尝试这样做时，例如使用：

#Unadjusted models - multi-level regression (lme)
#################################################
Unadjusted <- expand.grid(out, exp) %>%
group_by(Var1) %>% rowwise() %>%
summarise(frm = paste0(Var1, "~", Var2)) %>%
group_by(model_id = row_number(),frm) %>%
do(tidy(lme(.$frm, data = data, random= ~time|id, method = "ML"))) %>%
mutate(lci = estimate-(1.96*std.error)) %>%
mutate(uci = estimate+(1.96*std.error))

我收到以下错误消息：

Error in UseMethod("lme") : no applicable method for 'lme' applied to an object of class "character"

关于如何让lme类型的模型工作，有什么想法吗？

Answer 1

与lm不同，lme不会接受公式作为字符值。您需要将其显式转换为公式。尝试仅添加as.formula()

do(tidy(lme(as.formula(.$frm), ...))) %>%