I'm struggling with a dataset where I have to identify certain traits from each family group. The following is a toy dataset. In the dataset, I can identify the person ID, family ID, which person is the head household for each family (HH), the age, income, and if the person has a disability or not:

```
Person Family HH AGE Income Disable
1 1 1 30 1000 0
2 1 0 28 1990 0
3 1 0 5 2000 0
4 2 1 20 2300 0
5 3 0 45 0 1
6 3 1 51 3200 0
7 3 0 23 1000 0
8 4 0 22 0 1
9 4 1 22 1200 0
10 5 1 65 2220 0

```

The objective is to create something like this:

```
Family Age_HH Family_income_percapita Disable
1 30 1663.3 0
2 20 2300 0
3 51 1400 1
4 22 600 1
5 65 2220 0

```

My try was to do something like this:

```
dt %>%
 group_by(Family) %>%
  summarise(
   Age_HH = case_when(HH == 1 ~ AGE, TRUE ~ 0), # Head household age
   Family_income_percapita = sum(Income)/n(), # Income per-capita
   Disable = max(Disable) # If there is any family member with a disability
  )

```

The original dataset is huge, so I don't know how to check if my method is right by hand. I wonder if there is a better way to compute `Age_HH`. Thank you!!