查询Oracle Clob数据类型(Querying Oracle Clob datatype)

 数据框中的对象名称与函数中的环境名称有冲突。 这是你的数据： 
 
org <- data.frame(
    X = rep(1:10+rnorm(10,mean=1,sd=0.5),2),
    cX = rep(1:10+rnorm(10,mean=1,sd=0.5),2),
    Y = rep(1:10+rnorm(10,mean=1,sd=0.5), 2),
    cY = rep(1:10-rnorm(10,mean=1,sd=0.5),2),
    Frame = rep(1:5, 4),
    JN = rep(1:2, each=5),
    ID = rep(1:2, each=10))
 
 我选择只将一个字符串传递给VAR参数，而不是像你那样去掉。 然后检查VAR和cVAR是否在数据帧中。 然后我减少数据帧并将VAR和cVAR重命名为Y和X，以便在调用lmer（）时确保公式所指的是data.frame中的变量，而不是函数环境中的对象。 
 
library(lme4)
FUNC <- function(VAR = "VAR", df) {
    cVAR <- paste0("c", VAR)
    stopifnot(all(c(VAR, cVAR) %in% names(df)))
    df <- df[,c("ID", "JN", "Frame", VAR, cVAR)]
    names(df) <- c(c("ID", "JN", "Frame", "Y", "X"))
    df <- df[complete.cases(df),]
    MixedModel <- lme4::lmer(Y ~ X + (1|ID), data=df)
    plot(MixedModel)
}

FUNC(VAR = "X", df = org)

You have some conflicting names of objects in your dataframe and the environment in your function. Here's your data:
 
org <- data.frame(
    X = rep(1:10+rnorm(10,mean=1,sd=0.5),2),
    cX = rep(1:10+rnorm(10,mean=1,sd=0.5),2),
    Y = rep(1:10+rnorm(10,mean=1,sd=0.5), 2),
    cY = rep(1:10-rnorm(10,mean=1,sd=0.5),2),
    Frame = rep(1:5, 4),
    JN = rep(1:2, each=5),
    ID = rep(1:2, each=10))
 
I choose to just pass a string to the VAR argument instead of deparsing like you did. Then check if VAR and cVAR are in the dataframe. Then I reduce the dataframe and rename VAR and cVAR to Y and X so that when you call lmer() you're sure that the formula is referring to the variables in the data.frame and not the objects in the function environment.
 
library(lme4)
FUNC <- function(VAR = "VAR", df) {
    cVAR <- paste0("c", VAR)
    stopifnot(all(c(VAR, cVAR) %in% names(df)))
    df <- df[,c("ID", "JN", "Frame", VAR, cVAR)]
    names(df) <- c(c("ID", "JN", "Frame", "Y", "X"))
    df <- df[complete.cases(df),]
    MixedModel <- lme4::lmer(Y ~ X + (1|ID), data=df)
    plot(MixedModel)
}

FUNC(VAR = "X", df = org)