我试图在R中运行混合模型
result < lme(sleep ~ Age + BMI + Family_Type + Bedroom_Darkness + Race + Air_Condition + Bedroom_Sound, random = ~ Date_value | user_id, data = df)
但我收到错误
Error in lme.formula(sleep ~ Age + BMI + Family_Type + Bedroom_Darkness + :
nlminb problem, convergence error code = 1
message = iteration limit reached without convergence (10)
所以我希望测试共线性，所以我将预测变量放在一个看起来像（但有几百行或几行）的数据框中
Bedroom_Darkness Family_Type Air_Condition Bedroom_Sound Race BMI Age
Medium Dark (without eye mask) Married and No Child Yes Quiet Others 23.80540 41
Medium Dark (without eye mask) Married and No Child Yes Quiet Indian 20.66116 52
Medium Dark (with eye mask) Single No Quiet Chinese 21.35921 31
但是当我从usda包运行vif函数时
vif(df_predictors)
我得到了
Variables VIF
1 Bedroom_Darkness NA
2 Family_Type NA
3 Air_Condition NA
4 Bedroom_Sound NA
5 Race NA
6 BMI 1.267998
7 Age 3.170107
那么如何获得分类变量的VIF？