Using a for loop to extract coefficients from multiple models - r

Question

I have multiple cox models (with one variable static in all models) and am trying to extract the coefficient for that variable.
In all models the coefficient is indexed as follows: for example in model1 it is model1[[8]][1] ; for model2 it is model2[[8]][1] etc. I attempted to create a for loop but R as shown below but its not working.
Could someone help me why I am getting an error when running the following code
for (i in 1:5) {
coef[i] <- exp(summary(model[i])[[8]][1])
}
I get the following error "object 'model' not found".
Many thanks in advance
A

Answer 1

Here is an example of what I meant in my comment
data(iris)
model1 <- lm(data = iris, Sepal.Length ~ Sepal.Width + Species)
model2 <- lm(data = iris, Sepal.Length ~ Sepal.Width)
You can do this so you don't have to type all the models.
model.list<-mget(grep("model[0-9]+$", ls(),value=T))
ls() lists all the object you have and grep() is taking all the objects that have names "model" followed by a number.
coefs<-lapply(model.list,function(x)coef(x)[2])
unlist(coefs)
Sepal.Width Sepal.Width
0.8035609 -0.2233611

Answer 2

Here's a generalized example:
model1 <- 1:5
model2 <- 2:6
I can execute a function like mean to find the average of each vector with a for loop:
for(i in 1:2) print(mean(get(paste0('model', i))))
#[1] 3
#[1] 4
It works. But the a more standard approach is to use the list object. Then I can execute the desired function with built-in functions like sapply:
lst <- list(model1, model2)
sapply(lst, mean)
#[1] 3 4