Change class types in a list-CodePudding

I have run a series of "lmerModLmerTest" class-type models, which I have saved in a list. I would like to change the class of these models from "lmerModLmerTest" to "lmerTest".

For one model, I would change it like this, which works nicely:

class(model_1) <- "lmerMod"

However as I have many models I would ideally like to loop through the list in which I have saved all these models (old_models).

However when I run this code:

mylist.df <- lapply(names(old_models),
                   function(x){
                   b <- as(old_models[[x]],"lmerMod")
                   b
                   })

the resulting new list (mylist.df) has 0 elements. Any ideas as to why this is the case? Many thanks!

CodePudding user response：

Do not use names:

library(lmerTest)
#> Loading required package: lme4
#> Loading required package: Matrix
#> 
#> Attaching package: 'lmerTest'
#> The following object is masked from 'package:lme4':
#> 
#>     lmer
#> The following object is masked from 'package:stats':
#> 
#>     step
library(lme4)

old_models <- list(
  lmerTest::lmer(Sepal.Length ~ Sepal.Width   (1|Species) , data = iris),
  lmerTest::lmer(Sepal.Width ~ Sepal.Length   (1|Species) , data = iris)
)

old_models
#> [[1]]
#> Linear mixed model fit by REML ['lmerModLmerTest']
#> Formula: Sepal.Length ~ Sepal.Width   (1 | Species)
#>    Data: iris
#> REML criterion at convergence: 194.6361
#> Random effects:
#>  Groups   Name        Std.Dev.
#>  Species  (Intercept) 1.010   
#>  Residual             0.438   
#> Number of obs: 150, groups:  Species, 3
#> Fixed Effects:
#> (Intercept)  Sepal.Width  
#>      3.4062       0.7972  
#> 
#> [[2]]
#> Linear mixed model fit by REML ['lmerModLmerTest']
#> Formula: Sepal.Width ~ Sepal.Length   (1 | Species)
#>    Data: iris
#> REML criterion at convergence: 71.8035
#> Random effects:
#>  Groups   Name        Std.Dev.
#>  Species  (Intercept) 0.5706  
#>  Residual             0.2890  
#> Number of obs: 150, groups:  Species, 3
#> Fixed Effects:
#>  (Intercept)  Sepal.Length  
#>       1.0448        0.3444
sapply(old_models, class)
#> [1] "lmerModLmerTest" "lmerModLmerTest"

new_models <- lapply(old_models, function(x) as(x, "lmerMod"))
new_models
#> [[1]]
#> Linear mixed model fit by REML ['lmerMod']
#> Formula: Sepal.Length ~ Sepal.Width   (1 | Species)
#>    Data: iris
#> REML criterion at convergence: 194.6361
#> Random effects:
#>  Groups   Name        Std.Dev.
#>  Species  (Intercept) 1.010   
#>  Residual             0.438   
#> Number of obs: 150, groups:  Species, 3
#> Fixed Effects:
#> (Intercept)  Sepal.Width  
#>      3.4062       0.7972  
#> 
#> [[2]]
#> Linear mixed model fit by REML ['lmerMod']
#> Formula: Sepal.Width ~ Sepal.Length   (1 | Species)
#>    Data: iris
#> REML criterion at convergence: 71.8035
#> Random effects:
#>  Groups   Name        Std.Dev.
#>  Species  (Intercept) 0.5706  
#>  Residual             0.2890  
#> Number of obs: 150, groups:  Species, 3
#> Fixed Effects:
#>  (Intercept)  Sepal.Length  
#>       1.0448        0.3444
sapply(new_models, class)
#> [1] "lmerMod" "lmerMod"

^{Created on 2022-02-09 by the reprex package (v2.0.1)}