lead_longitudinal/figures/hdrs-plots.R
2026-04-20 17:51:32 +02:00

198 lines
5.7 KiB
R

# hdrs-plots.R
#
# Example on growth curve models for Reisby et al. (1977)
#
# content: (1) Read data
# (2) Linear analysis
# (3) Fitting quadratic model
# (3) Centering of variables
# (4) Check random effects structure
# (5) Check model assumptions
#
# input: resiby.txt
# output: hdrs-ind_pred-randomslope.pdf
# hdrs-ind_pred-quad.pdf
# hdrs-caterpillar.pdf
# hdrs_shrinkage_int-week.pdf
# hdrs_shrinkage_int-weeksq.pdf
# hdrs_shrinkage_week-weeksq.pdf
#
# last mod: 2026-04-20, NW
library("lme4")
library("lattice")
#--------------- (1) Read data ------------------------------------------------
dat <- read.table("../data/reisby.txt", header = TRUE)
dat$id <- factor(dat$id)
dat$diag <- factor(dat$diag, levels = c("nonen", "endog"))
dat <- na.omit(dat) # drop missing values
pdf("hdrs-box.pdf", height = 3.375, width = 3.375, pointsize = 10)
par(mai = c(.6, .6, .1, .1), mgp = c(2, .4, 0))
boxplot(hamd ~ week, dat,
col = "#3CB4DC",
ylab = "HDRS score",
xlab = "Time (week)")
dev.off()
#--------------- (2) Linear analysis ------------------------------------------
# random slope model
lme2 <- lmer(hamd ~ week + (week | id), dat, REML = FALSE)
pdf("hdrs-ind_pred-randomslope.pdf", height = 6, width = 6)
xyplot(hamd + predict(lme2) ~ week | id, data = dat,
type = c("p", "l", "g"),
#pch = 16,
ratio = "xy",
col = c("#3CB4DC", "#FF6900"),
distribute.type = TRUE,
layout = c(11, 6),
ylab = "HDRS score",
xlab = "Time (week)")
dev.off()
#--------------- (3) Fitting quadratic model ----------------------------------
# model with quadratic time trend
lme3 <- lmer(hamd ~ week + I(week^2) + (week + I(week^2) | id), dat,
REML = FALSE)
pdf("hdrs-ind_pred-quad.pdf", height = 6, width = 6)
xyplot(hamd + predict(lme3) ~ week | id, data = dat,
type = c("p", "l", "g"),
#pch = 16,
ratio = "xy",
col = c("#3CB4DC", "#FF6900"),
distribute.type = TRUE,
layout = c(11, 6),
ylab = "HDRS score",
xlab = "Time (week)")
dev.off()
#--------------- (4) Check random effects structure ---------------
pdf("hdrs-caterpillar.pdf", height = 8, width = 20)
dotplot(ranef(lme3), col = "#3CB4DC",
scales = list(x = list(relation = "free")))[[1]]
dev.off()
# Shrinkage plots
df <- coef(lmList(hamd ~ week_c + I(week_c^2) | id, dat))
cc1 <- as.data.frame(coef(lme3reml)$id)
names(cc1) <- c("A", "B", "C")
df <- cbind(df, cc1)
ff <- fixef(lme3reml)
pdf("hdrs_shrinkage_int-week.pdf", height = 6, width = 6, pointsize = 10)
with(df,
xyplot(`(Intercept)` ~ week_c, aspect = 1,
x1 = B, y1 = A,
panel = function(x, y, x1, y1, subscripts, ...) {
panel.grid(h = -1, v = -1)
x1 <- x1[subscripts]
y1 <- y1[subscripts]
larrows(x, y, x1, y1, type = "closed", length = 0.1, fill = "black",
angle = 15, ...)
lpoints(x, y,
pch = 16,
col = trellis.par.get("superpose.symbol")$col[2])
lpoints(x1, y1,
pch = 16,
col = trellis.par.get("superpose.symbol")$col[1])
lpoints(ff[2], ff[1],
pch = 16,
col = trellis.par.get("superpose.symbol")$col[3])
},
xlab = "week_c",
ylab = "(Intercept)",
key = list(space = "top", columns = 3,
text = list(c("Mixed model", "Within-subject", "Population")),
points = list(col = trellis.par.get("superpose.symbol")$col[1:3],
pch = 16))
)
)
dev.off()
pdf("hdrs_shrinkage_int-weeksq.pdf", height = 6, width = 6, pointsize = 10)
with(df,
xyplot(`(Intercept)` ~ `I(week_c^2)`, aspect = 1,
x1 = C, y1 = A,
panel = function(x, y, x1, y1, subscripts, ...) {
panel.grid(h = -1, v = -1)
x1 <- x1[subscripts]
y1 <- y1[subscripts]
larrows(x, y, x1, y1, type = "closed", length = 0.1, fill = "black",
angle = 15, ...)
lpoints(x, y,
pch = 16,
col = trellis.par.get("superpose.symbol")$col[2])
lpoints(x1, y1,
pch = 16,
col = trellis.par.get("superpose.symbol")$col[1])
lpoints(ff[3], ff[1],
pch = 16,
col = trellis.par.get("superpose.symbol")$col[3])
},
xlab = expression(week_c^2),
ylab = "(Intercept)",
key = list(space = "top", columns = 3,
text = list(c("Mixed model", "Within-subject", "Population")),
points = list(col = trellis.par.get("superpose.symbol")$col[1:3],
pch = 16))
)
)
dev.off()
pdf("hdrs_shrinkage_week-weeksq.pdf", height = 6, width = 6, pointsize = 10)
with(df,
xyplot(week_c ~ `I(week_c^2)`, aspect = 1,
x1 = C, y1 = B,
panel = function(x, y, x1, y1, subscripts, ...) {
panel.grid(h = -1, v = -1)
x1 <- x1[subscripts]
y1 <- y1[subscripts]
larrows(x, y, x1, y1, type = "closed", length = 0.1, fill = "black",
angle = 15, ...)
lpoints(x, y,
pch = 16,
col = trellis.par.get("superpose.symbol")$col[2])
lpoints(x1, y1,
pch = 16,
col = trellis.par.get("superpose.symbol")$col[1])
lpoints(ff[3], ff[2],
pch = 16,
col = trellis.par.get("superpose.symbol")$col[3])
},
xlab = expression(week_c^2),
ylab = "week_c",
key = list(space = "top", columns = 3,
text = list(c("Mixed model", "Within-subject", "Population")),
points = list(col = trellis.par.get("superpose.symbol")$col[1:3],
pch = 16))
)
)
dev.off()