report both change along with slope in mod_effect() output

[rpruim]

@dtkaplan, how does this look?

example(mod_effect)
## 
## md_ffc> mod1 <- lm(wage ~ age * sex * educ + sector, data = mosaicData::CPS85)
## 
## md_ffc> mod_effect(mod1, ~ sex)
## # A tibble: 1 x 6
##   change sex   to_sex   age  educ sector
##    <dbl> <fct> <fct>  <dbl> <dbl> <fct> 
## 1  -1.88 M     F         35    12 prof  
## 
## md_ffc> mod_effect(mod1, ~ sector)
## # A tibble: 1 x 6
##   change sector to_sector   age sex    educ
##    <dbl> <fct>  <fct>     <dbl> <fct> <dbl>
## 1  -2.23 prof   clerical     35 M        12
## 
## md_ffc> mod_effect(mod1, ~ age, sex = "M", educ = c(10, 12, 16), age = c(30, 40))
## # A tibble: 6 x 7
##   change slope   age to_age sex    educ sector
##    <dbl> <dbl> <dbl>  <dbl> <fct> <dbl> <fct> 
## 1   1.18 0.118    30     40 M        10 prof  
## 2   1.18 0.118    40     50 M        10 prof  
## 3   1.38 0.138    30     40 M        12 prof  
## 4   1.38 0.138    40     50 M        12 prof  
## 5   1.78 0.178    30     40 M        16 prof  
## 6   1.78 0.178    40     50 M        16 prof  
## 
## md_ffc> mod_effect(mod1, ~ age, sex = "F", age = 34, step = 1)
## # A tibble: 1 x 7
##   change  slope   age to_age sex    educ sector
##    <dbl>  <dbl> <dbl>  <dbl> <fct> <dbl> <fct> 
## 1 0.0549 0.0549    34     35 F        12 prof  
## 
## md_ffc> mod_effect(mod1, ~ sex, age = 35, sex = "M", to = "F" )
## # A tibble: 1 x 6
##   change sex   to_sex   age  educ sector
##    <dbl> <fct> <fct>  <dbl> <dbl> <fct> 
## 1  -1.88 M     F         35    12 prof  
## 
## md_ffc> # For classifiers, the change in *probability* of a level is reported.
## md_ffc> mod2 <- rpart::rpart(sector ~ age + sex + educ + wage, data = mosaicData::CPS85)
## 
## md_ffc> mod_effect(mod2, ~ educ)
## # A tibble: 1 x 7
##   change_clerical slope  educ to_educ   age sex    wage
##             <dbl> <dbl> <dbl>   <dbl> <dbl> <fct> <dbl>
## 1               0     0    12      14    35 M       7.8
## 
## md_ffc> mod_effect(mod2, ~ educ, class_level = "manag")
## # A tibble: 1 x 7
##   change_manag slope  educ to_educ   age sex    wage
##          <dbl> <dbl> <dbl>   <dbl> <dbl> <fct> <dbl>
## 1            0     0    12      14    35 M       7.8

[rpruim]

I see that sometimes the change column is inheriting a variable name. Do we want that? Should it be there in all cases?