Demographics visualizations
Child age
Child age in months (age_group
) by child_sex
.
Note: The child’s exact age in months is part of the Databrary-related data. That is on the work plan.
xtabs(formula = ~ age_group + child_sex,
data = home_visit_filtered)
## child_sex
## age_group female male
## 12mo 144 122
## 18mo 129 149
## 24mo 109 113
A total of \(n=\) 766 mother-infant dyads have been tested. This includes training and pilot visits.
home_visit_filtered |>
ggplot() +
aes(age_group, fill = child_sex) +
geom_bar() +
theme(legend.position = "bottom") +
theme(legend.title = element_blank())
![Participants by age group and sex](include/img/fig-age-grp-by-sex-1.png)
Figure 4: Participants by age group and sex
Time series
To calculate cumulative visits, we have to add an index variable
df <- home_visit_filtered |>
dplyr::select(test_date, site_id) |>
dplyr::mutate(test_date = as.Date(test_date)) |>
dplyr::arrange(test_date) |>
dplyr::mutate(n_visits = seq_along(test_date))
df |>
dplyr::filter(!is.na(test_date),
!is.na(n_visits),
!is.na(site_id)) |>
ggplot() +
aes(test_date, n_visits) +
geom_point()
![Cumulative home visits by year](include/img/fig-home-visit-time-series-1.png)
Figure 5: Cumulative home visits by year