使用rsq()函数时收到变量‘缺失’警告，是否需关注？

构建的GLM模型 #

model <- glm(
  data = df,
  family = binomial(link = 'logit'),
  formula = "Correct_Response ~ (Condition * TC_michelson_c * FC_michelson)",
  contrasts = list(
    Condition = contr.treatment(levels(df$Condition), base = TargIndex),
    FC_michelson = contr.sum(levels(df$FC_michelson)))
)

运行rsq()时的警告 #

执行rsq(model, type='n')（或rsq.n）后收到如下警告：

Warning: variable 'Condition' is absent, its contrast will be ignored
Warning: variable 'FC_michelson' is absent, its contrast will be ignored
[1] 0.243914

部分数据示例 #

Condition FC_michelson TC_michelson_c Correct_Response
1         C        0.111       0.033688                0
2  Straight         0.07       0.033688                1
3    Target        0.048       0.033688                0
4         C        0.048       0.033688                0
5        BC        0.091       0.033688                0
6        BC        0.048       0.033688                0
7    Target        0.091       0.033688                0

变量结构信息 #

> model$data$FC_michelson %>% str()
 Factor w/ 4 levels "0.048","0.07",..: 4 2 1 1 3 1 3 4 2 3 ...
> model$data$Condition %>% str()
 Factor w/ 4 levels "BC","C","Straight",..: 2 3 4 2 1 1 4 3 1 4 ...
> model$data$TC_michelson_c %>% str()
 num [1:10080] 0.0337 0.0337 0.0337 0.0337 0.0337 ...
> model$data$Correct_Response %>% str()
 int [1:10080] 0 1 0 0 0 0 0 0 0 0 ...

疑问 #

此前未使用过该函数/包，不清楚这类警告是否需要重视？

内容的提问来源于stack exchange，提问作者Harry S.