Description Usage Arguments Value Examples
Simulate EMA data
1 2 3 |
plan |
a sample plan, as generated by |
mm_par |
a list, defining the parameters of a mixed effects model; the list should contain elements "fixed", "random", "error" and "phi". |
lim |
optional upper and lower limits of data (defaults to NULL, in which case data values are unbounded). |
a data.frame
, containing the simulated data:
id |
Participant id (numeric) |
observation |
observation counter (within participant; numeric) |
day |
day counter (numeric) |
beep |
beep counter, within day (numeric) |
t |
time of day (string, in "%H:%M" format) |
Y |
Simulated EMA value |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 | sample_plan <- sample_plan(n_participants = 20, n_days = 7)
mm_par_a <- list(
fixed = c(intercept = 0,
time = 0),
random = c(intercept = 0.1,
time = 0.005),
error = 0.2,
phi = 0.5
)
a <- sim_ema(plan = sample_plan,
mm_par = mm_par_a)
mm_par_b <- mm_par_a
mm_par_b$fixed['time'] <- -0.5
mm_par_b$random['time'] <- 0.005
b <- sim_ema(plan = sample_plan,
mm_par = mm_par_b)
b$id <- b$id + max(a$id)
c <- rbind(a, b)
c$group <- c(rep(0, nrow(a)), rep(1, nrow(b)))
# plot
library(ggplot2)
ggplot(data = c, aes(x = time, y = Y)) +
geom_line(aes(group = id, colour = factor(group))) +
geom_point(size = .8) +
geom_smooth(aes(group = factor(group), colour = factor(group)),
method = "loess", se = FALSE, size = 2) +
xlab("Time")
# test
library(nlme)
fm <- lme(Y ~ 1 + time * group ,
random = ~ 1 + time | id,
data = c,
correlation = corAR1())
summary(fm)
|
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