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Number of households, and proportion headed by person with a disability

# Remove non-consenting participants
data <- data[data$consent == 'Yes' & !is.na(data$branch), ]

# Ns, by branch and disability status 
t1 <- data %>% 
  mutate(is_pwd = ifelse(pwd == 1, 1, 0), branch = as.character(branch)) %>%
  filter(!is.na(branch) & !is.na(is_pwd)) %>% 
  count(branch, is_pwd) %>% 
  group_by(branch) %>%
  mutate(N = sum(n), prop_pwd = paste0(round(100*n/N,0), '%')) %>%
  select(-N) %>%
  tidyr::pivot_wider(names_from = is_pwd, values_from = c(n, prop_pwd)) %>% 
  select(-prop_pwd_0)

knitr::kable(t1, digits = 2, col.names = c('Branch','N not pwd', 'N pwd', '% pwd'),
             caption = 'Households', align = 'lccc') %>%
  kable_styling(
      bootstrap_options = c("striped", "hover", "condensed", "responsive"),
                  font_size = 7, fixed_thead = T)

Households

Branch	N not pwd	N pwd	% pwd
Anaka	316	148	32%
Goma	320	127	28%
Gulu	331	163	33%
Kamdini	252	149	37%
Kigumba	285	79	22%
Lacor	231	142	38%
Loro	253	113	31%
Minakulu	351	127	27%

Number of individuals included in the survey (including secondary household members)

# Ns total people covered by the survey (listed in the rosters)
t2 <- data[, c('branch', 'res_gender', colnames(data)[grep("s23_", colnames(data))])] %>%
  tidyr::pivot_longer(cols = c(2:ncol(.)), names_to = 'HH_member', values_to = 'gender') %>%
  filter(!is.na(gender)) %>% 
  count(branch, gender) %>% 
  tidyr::pivot_wider(names_from = gender, values_from = n) %>% 
  group_by(branch) %>% 
  mutate(Females = paste0(Female,'/', (Male+Female), ' (', round(100*Female/(Male+Female)),'%)')) %>% 
  select(-Male)

knitr::kable(t2, digits = 2, caption = 'Individuals', align = 'lcc') %>%
  kable_styling(
      bootstrap_options = c("striped", "hover", "condensed", "responsive"),
                  font_size = 7, fixed_thead = T)

Individuals

branch	Female	Females
Gulu	1817	1817/2978 (61%)
Lacor	1470	1470/2434 (60%)
Anaka	1999	1999/3381 (59%)
Goma	1918	1918/3304 (58%)
Minakulu	1787	1787/3010 (59%)
Kamdini	1527	1527/2582 (59%)
Loro	1421	1421/2361 (60%)
Kigumba	1423	1423/2477 (57%)