Percent change for grouped subjects at multiple timepoints R - r

Question

id timepoint dv.a
1 baseline 100
1 1min 105
1 2min 90
2 baseline 70
2 1min 100
2 2min 80
3 baseline 80
3 1min 80
3 2min 90
I have repeated measures data for a given subject in long format as above. I'm looking to calculate percent change relative to baseline for each subject.
id timepoint dv pct.chg
1 baseline 100 100
1 1min 105 105
1 2min 90 90
2 baseline 70 100
2 1min 100 143
2 2min 80 114
3 baseline 80 100
3 1min 80 100
3 2min 90 113

Answer 1

df <- expand.grid( time=c("baseline","1","2"), id=1:4)
df$dv <- sample(100,12)
df %>% group_by(id) %>%
mutate(perc=dv*100/dv[time=="baseline"]) %>%
ungroup()
You're wanting to do something for each 'id' group, so that's the group_by, then you need to create a new column, so there's a mutate. That new variable is the old dv, scaled by the value that dv takes at the baseline - hence the inner part of the mutate. And finally it's to remove the grouping you'd applied.

Answer 2

Try creating a helper column, group and arrange on that. Then use the window function first in your mutate function:
df %>% mutate(clean_timepoint = str_remove(timepoint,"min") %>% if_else(. == "baseline", "0", .) %>% as.numeric()) %>%
group_by(id) %>%
arrange(id,clean_timepoint) %>%
mutate(pct.chg = (dv / first(dv)) * 100) %>%
select(-clean_timepoint)

Answer 3

in Base Ryou can do this
for(i in 1:(NROW(df)/3)){
df[1+3*(i-1),4] <- 100
df[2+3*(i-1),4] <- df[2+3*(i-1),3]/df[1+3*(i-1),3]*100
df[3+3*(i-1),4] <- df[3+3*(i-1),3]/df[1+3*(i-1),3]*100
}
colnames(df)[4] <- "pct.chg"
output:
> df
id timepoint dv.a pct.chg
1 1 baseline 100 100.0000
2 1 1min 105 105.0000
3 1 2min 90 90.0000
4 2 baseline 70 100.0000
5 2 1min 100 142.8571
6 2 2min 80 114.2857
7 3 baseline 80 100.0000
8 3 1min 80 100.0000
9 3 2min 90 112.5000

Answer 4

Base R solution: (assuming "baseline" always appears as first record per group)
data.frame(do.call("rbind", lapply(split(df, df$id),
function(x){x$pct.change <- x$dv/x$dv[1]; return(x)})), row.names = NULL)
Data:
df <- structure(
list(
id = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L),
timepoint = c(
"baseline",
"1min",
"2min",
"baseline",
"1min",
"2min",
"baseline",
"1min",
"2min"
),
dv = c(100L, 105L, 90L, 70L, 100L, 80L, 80L, 80L, 90L)
),
class = "data.frame",
row.names = c(NA,-9L)
)