pastaPlot {pastaPlot}

Spaghetti-plot fixed and random effects of linear mixed models

Description

pastaPlot() plots slopes for both fixed and random effects of linear mixed models from 'lme4' or 'glmmTMB' packages as a single spaghetti plot, optionally between conditions including confidence bands for fixed effects.

Usage

pastaPlot(
  model = NULL,
  predictor = NULL,
  nested.in = NULL,
  group = NULL,
  legend.title = "Legend",
  group.labels = NULL,
  xlab = NULL,
  ylab = NULL,
  font.family = NULL,
  colors = NULL,
  ci.lvl = 0.95,
  ci.int = FALSE,
  ci.linetype = 0,
  lwd.fix = 1,
  lwd.ran = 0.5,
  xlab.inc = 0,
  xlab.int = NULL,
  ylim = NULL,
  opacity.ci = 0.25,
  opacity.ran = 0.3,
  colors.ci = NULL
)

Arguments

model

lme4 or glmmTMB model object

predictor

(Character) Name of predictor (e.g., "time" or "math_score"), as it is present in the model

nested.in

(Character) Name of the variable your time points or subjects are nested in (e.g.,"school" or "id")

group

(Optional, character) The name of your grouping variable (e.g., "condition" or "gender")

legend.title

(Optional, character) Name of legend in plot (e.g., "Condition", or "Gender")

group.labels

(Optional, vector of characters) Names of group labels to be displayed in the plot (e.g., c("Control", "Intervention"))

xlab

(Optional, character) Label of x-axis (predictor) (e.g., "Time (days)")

ylab

(Optional, character) Label of y-axis (dependant variable) (e.g., "GAF")

font.family

(Optional, character) Name of the font family (e.g. "serif")

colors

(Optional, vector of characters) Set color of slopes. Length of vector should correspond to number of values in group variable (e.g., c("#5e9aff", "blue")). If no group variable is specified, pass a single color.

ci.lvl

(Optional, numeric) Set confidence interval (default: 0.95)

ci.int

(Optional, logical) Enable confidence (prediction) intervals, disabled by default

ci.linetype

(Optional, numeric) Set linetype of confidence bands outline (default: 0)

lwd.fix

(Optional, numeric) Line width of fixed effects (default: 1)

lwd.ran

(Optional, numeric) Line width of random effects (default: 0.5)

xlab.inc

(Optional, numeric) Increment the displayed values of your predictor (e.g., xlab_int = 1 changes range of x from 0-29 to 1-30), set to 0 by default

xlab.int

(Optional, numeric) Interval between displayed predictor values on x-axis (e.g., "1"), disabled by default

ylim

(Optional, numeric vector) Limited range of values on y-axis (e.g. c(1,5.5))

opacity.ci

(Optional, numeric) Set opacity of confidence bands in the range of 0 to 1 (default = 0.1)

opacity.ran

(Optional, numeric) Set opacity of random slopes in the range of 0 to 1 (default = 0.4)

colors.ci

(Optional, vector of characters) Set color of confidence bands. Length of vector should correspond to number of values in group variable (e.g., c("#5e9aff", "blue")). If no group variable is specified, pass a single color.

Value

Returns a ggplot2 plot object to further be modified

Examples

lme4_model <- lme4::lmer(CO2 ~ 1 + time*condition + (1 + time | id),
data=ecovia_data, REML = FALSE, control = lme4::lmerControl(optimizer = "bobyqa"))
pastaPlot(lme4_model, "time", "id", group = "condition", legend.title = "Condition",
group.labels = c("Control", "Intervention"), ci.int = TRUE, xlab = "Time (days)",
ylab = "CO2")

glmmTMB_model <- glmmTMB::glmmTMB(math_score_y3 ~ 1 + math_score_y1*gender +
(1 + math_score_y1 | school), data=jsp_data, REML = FALSE)
pastaPlot(glmmTMB_model, "math_score_y1", "school", group = "gender",
legend.title = "Gender", group.labels = c("Male", "Female"), ci.int = FALSE,
xlab = "Math score (year 1)", ylab = "Math score (year 3)")