Error in 1 | country : operations are possible only for numeric, logical or complex types

[Arial]

I have imputed missing data using mice, and run the first multilevel model (empty model):

tom <- with(imputer, lm(attitude ~ 1 + (1 | country)))

But, I get the following error:

Error in 1 | country : operations are possible only for numeric, logical or complex types

Country is a character variable. I have tried to set it as.factor, but this creates another type of error.. What can the problem be?

[pieterjanvc]

Hi,

Welcome to the RStudio community!

The problem is that a linear regression model can only work with numeric data and not categorical (it can with logical i.e. 0 - 1). A way around it so convert a categorical variable into a one-hot representation, i.e. one column per value with 0 or 1. Normally the lm() function should be able to do this automatically like so:

lm(Sepal.Length ~ Species + Petal.Width, data = iris)
#> 
#> Call:
#> lm(formula = Sepal.Length ~ Species + Petal.Width, data = iris)
#> 
#> Coefficients:
#>       (Intercept)  Speciesversicolor   Speciesvirginica        Petal.Width  
#>           4.78044           -0.06025           -0.05009            0.91690

^{Created on 2021-07-09 by the reprex package (v2.0.0)}
You can see that the Species variable gets split into n - 1 new inputs

There seems to be an issue with your data preventing this, but it's hard to say without being able to run the code. So I suggest you create a reprex and share that so we can figure this out. A reprex consists of the minimal code and data needed to recreate the issue/question you're having. You can find instructions how to build and share one here:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

Hope this helps,
PJ