Summaries

Last updated: 2026-04-04 18:00:21 using pinned data version from: 2026-03-27 12:57:56
Users can load data by running (requires one-time google drive authentication):

library(tidyverse)
library(pins)
library(nanoparquet)
library(googledrive)
ds <- board_gdrive(path = as_id("1OZlphhu6vYm1A2Bm2-zD7a4luS5nGWgS")) %>%
  pin_read("imu_raw_samples")

Usable data

usable_data <- ds %>% count(id, session) %>% mutate(usable_hours = n/3600)
recording_duration <- ds %>% group_by(id, session) %>% 
  mutate(recording_hours = as.numeric(time_leg_off - time_leg_on)) %>% 
  slice_head(n = 1) %>% ungroup
  
usable_data %>% left_join(recording_duration) %>% 
  get_summary_stats(usable_hours, recording_hours, show = c("mean", "sd","min","max")) %>% 
  flextable() %>% autofit()

Usable data and total recording length in hours

variable	n	mean	sd	min	max
usable_hours	17	6.687	1.60	4.432	9.466
recording_hours	17	10.408	1.43	7.533	12.317

usable_data  %>% 
  ggplot(aes(x = usable_hours)) + 
  geom_histogram() + 
  scale_x_binned(name = "Hours", limits = c(2,14))
recording_duration  %>% 
  ggplot(aes(x = recording_hours)) + 
  geom_histogram() + 
  scale_x_binned(name = "Hours", limits = c(2,14))

Usable hours after exclusions

Recording length in hours

Infant Position Frequency by Age (Overall)

ds_sum <- ds %>% group_by(id, session) %>% 
  mutate(total_samples = n()) %>% group_by(id, session, pos) %>% 
  summarize(pos_n  = n(), total_samples = mean(total_samples)) %>% ungroup
ds_sum <- ds_sum %>% complete(nesting(id, session), pos, fill = list(pos_n = 0, total_samples = 1))
ds_sum$pos_prop = ds_sum$pos_n/ds_sum$total_samples*100
ds_sum$session = as.numeric(ds_sum$session)

ds_sum %>% group_by(pos, session) %>% 
  get_summary_stats(pos_prop, show = c("mean", "sd","min","max")) %>% 
  select(-variable) %>% flextable() %>% autofit()

Position summary statistics

session	pos	n	mean	sd	min	max
1	Supine	10	20.955	14.312	8.322	56.079
2	Supine	6	11.692	8.366	3.956	26.262
3	Supine	1	1.922		1.922	1.922
1	Prone	10	21.892	15.089	2.168	53.195
2	Prone	6	10.231	4.244	3.257	15.002
3	Prone	1	10.127		10.127	10.127
1	Sitting	10	34.727	13.985	12.819	53.703
2	Sitting	6	43.629	10.534	32.400	60.394
3	Sitting	1	44.118		44.118	44.118
1	Standing	10	11.754	8.956	3.644	33.114
2	Standing	6	22.278	6.338	14.710	31.995
3	Standing	1	27.855		27.855	27.855
1	Held	10	10.672	4.112	3.704	18.293
2	Held	6	12.170	5.641	3.105	19.508
3	Held	1	15.978		15.978	15.978

ggplot(ds_sum, aes(x = session, y = pos_prop, color = pos)) + 
  stat_summary(position = position_dodge(.1)) + 
  stat_summary(geom = "line", position = position_dodge(.1)) + 
  ylim(0,101) + ylab("% of time") + xlab("Session") +
  scale_x_continuous(breaks = 1:3, labels = c("7 mo","9 mo","11 mo"), limits = c(0.5,3.5)) + 
  scale_color_manual(values = pal, name ="") + 
  theme(legend.position = "bottom")
ggplot(ds_sum, aes(x = session, y = pos_prop, fill = pos)) + 
  stat_summary(geom = "bar", position = "stack") + 
  ylim(0,101) + ylab("% of time") + xlab("Session") +
  scale_x_continuous(breaks = 1:3, labels = c("7 mo","9 mo","11 mo"), limits = c(0.5,3.5)) + 
  scale_fill_manual(values = pal, name ="") + 
  theme(legend.position = "bottom")

Position means and SE

Position distribution

Infant Position Frequency by Age (Individual)

ggplot(ds_sum, aes(x = session, y = pos_prop, color = pos, group = id)) + 
  facet_wrap(~ pos) + 
  geom_point() + geom_line() +  
  ylim(0,100) + ylab("% of time") + xlab("Session") +
  scale_x_continuous(breaks = 1:3, labels = c("7 mo","9 mo","11 mo"), limits = c(0.5,3.5)) + 
  scale_color_manual(values = pal, name ="") + 
  theme(legend.position = "none")

Usable hours after exclusions Recording length in hours Position means and SE Position distribution