lmer anova effect sizes

Question

I would like to compute the marginal R squared for the whole factors from an anova table. This post shows how to get the effect size for each fixed effect based on the r2glmm package but it does not seem to work to get the whole factor.

Here is an example:

library(lmerTest)
library(r2glmm)
set.seed(1)
df <- data.frame(id = rep(1:3, 5),
                 score = sample(15),
                 gender = rep(c("male", "female", "other"), 5),
                 age = rep(c("teenager", "adult", "old"), each = 5))
mdl <- lmer(score ~ gender + age + (1|id), data = df)
df
id    score   gender  age
1   1     9       male    teenager
2   2     4       female  teenager
3   3     7       other   teenager
4   1     1       male    teenager
5   2     2       female  teenager
6   3    13       other   adult
7   1    11       male    adult
8   2     3       female  adult
9   3     8       other   adult
10  1    12       male    adult
11  2     5       female  old
12  3     6       other   old
13  1    15       male    old
14  2    10       female  old
15  3    14       other   old

Compute the anova table:

anova(mdl)
# Type III Analysis of Variance Table with Satterthwaite's method
#        Sum Sq Mean Sq NumDF DenDF F value  Pr(>F)  
# gender  24.75  12.375     2    10  1.0081 0.39916  
# age     80.45  40.225     2    10  3.2770 0.08044 .
# ---
# Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

I would like to compute the effect sizes for gender and age factors from the above anova table.

I tried:

r2beta(mdl, partial = TRUE)
#        Effect   Rsq upper.CL lower.CL
# 1       Model 0.407    0.761    0.172
# 2  gendermale 0.215    0.601    0.003
# 3 genderother 0.143    0.537    0.001
# 5 ageteenager 0.143    0.537    0.001
# 4      ageold 0.027    0.377    0.000

But none is giving me what I am looking for.

Is there any solution?

---

Edit

So with the development version from GitHub it does compute the effect sizes for the whole factor:

r2beta(mdl, partial = TRUE)
#   Effect   Rsq upper.CL lower.CL
# 1  Model 0.407    0.761    0.172
# 3    age 0.260    0.656    0.034
# 2 gender 0.233    0.638    0.026

The problem now is that I need both: for the whole factor and for the break down with dummy codes (or any other code). Is there a way to achieve this or do I need to manually create dummy codes? it would be nice to have an option in the function to specify which output we wish.