Error: Variable in lenghts differ in R (but they do not..) - r

Question

This indeed looks like easy error message to solve, but I've been struggling with it the entire morning and I don't really see why I get this message, but maybe one of you is more familiar with this problem. I made a testdataset to illustrate my question:
> test
PatientID Age Gender Date Group var1 var2 var3
1 1 70 Male 1/1/2015 A_0 0.30 4 117
2 1 70 Male 1/6/2015 A_1 0.70 9 90
3 2 52 Female 1/1/2015 A_0 1.00 1 87
4 2 52 Female 1/8/2015 A_1 2.00 11 103
5 3 49 Male 1/3/2015 A_0 0.25 14 111
6 3 49 Male 1/8/2015 A_1 0.30 5 50
7 4 36 Female 1/3/2015 A_0 0.70 7 82
8 4 36 Female 1/6/2015 A_1 0.80 8 133
> library(broom)
> lapply(names(test)[6:9], function(n) {
+ linear <- lm(n ~ Group + Age + Gender + Date, data = test)
+ lapply(linear, glance)
+ })
Error in model.frame.default(formula = n ~ Group + Age + Gender + Date, :
variable lengths differ (found for 'Group')
When I try to run the same regression on one of the variables I don't get the error message:
> summary(lm(var1 ~ Group + Age + Gender + Date))
Call:
lm(formula = var1 ~ Group + Age + Gender + Date)
Residuals:
1 2 3 4 5 6 7 8
-0.03321 -0.06578 0.03321 0.09672 0.19571 -0.09672 -0.19571 0.06578
Coefficients: (1 not defined because of singularities)
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.19491 0.68201 -1.752 0.2219
GroupA_1 0.93650 0.26436 3.543 0.0713 .
Age 0.04157 0.01234 3.368 0.0780 .
GenderMale -1.38185 0.25128 -5.499 0.0315 *
Date1/3/2015 0.59406 0.32438 1.831 0.2085
Date1/6/2015 -0.50393 0.23247 -2.168 0.1625
Date1/8/2015 NA NA NA NA
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.2304 on 2 degrees of freedom
Multiple R-squared: 0.9536, Adjusted R-squared: 0.8375
F-statistic: 8.216 on 5 and 2 DF, p-value: 0.112
I did some diagnostics to check wether these factors really have only one level, but it seems not to be the case...
> l<-sapply(test,function(x)is.factor(x))
> l
PatientID Age Gender Date Group var1 var2 var3
FALSE FALSE TRUE TRUE TRUE FALSE FALSE FALSE
> m<-test[,names(which(l=="TRUE"))]
> m
Gender Date Group
1 Male 1/1/2015 A_0
2 Male 1/6/2015 A_1
3 Female 1/1/2015 A_0
4 Female 1/8/2015 A_1
5 Male 1/3/2015 A_0
6 Male 1/8/2015 A_1
7 Female 1/3/2015 A_0
8 Female 1/6/2015 A_1
> ifelse(n<-sapply(m,function(x)length(levels(x)))==1,"DROP","NODROP")
Gender Date Group
"NODROP" "NODROP" "NODROP"
So it would be really great if somebody has a suggestion to overcome this at first sight easy error?
New script after suggestion underneath:
attach(test)
lapply(names(test)[6:8], function(n) {
linear <-as.formula(paste(n, "~ Group + Age + Gender + Date"))
glance(lm(linear, na.action=na.omit))
})
I also incorporated now how to handle missing values.
Thank you very very much for the suggestion, because I wasn't seeing it clearly anymore this morning!!