Ignore my previous comment. It applies only to the incomplete code in your first example.

Here's a working example that's analogous to the complete code in your response:

```
library(tidyverse)
library(broom)
# Set up three regression models
modelo_dp2 = lm(mpg ~ hp, data=mtcars)
modelo_dasr2 = lm(mpg ~ wt, data=mtcars)
modelo_tc2 = lm(mpg ~ cyl, data=mtcars)
modelo_dp2 %>%
glance() %>%
mutate(var = "DP") %>%
bind_rows(modelo_dasr2 %>%
glance() %>%
mutate(var = "DASR_log")) %>%
bind_rows(modelo_tc2 %>%
glance() %>%
mutate(var = "TC_log")) %>%
select(var, r.squared:nobs) %>%
pivot_longer(-var) %>%
filter(name %in% c("r.squared", "statistic", "df",
"df.residual", "p.value")) %>%
mutate(value = round(value, 3)) %>%
pivot_wider(names_from = var,
values_from = value) %>%
mutate(name = factor(c("R²", "F", "P valor",
"Grados de libertad",
"Grados de libertad residual")))
#> # A tibble: 5 x 4
#> name DP DASR_log TC_log
#> <fct> <dbl> <dbl> <dbl>
#> 1 R² 0.602 0.753 0.726
#> 2 F 45.5 91.4 79.6
#> 3 P valor 0 0 0
#> 4 Grados de libertad 1 1 1
#> 5 Grados de libertad residual 30 30 30
```

^{Created on 2020-10-19 by the reprex package (v0.3.0)}