plot_growth: Plot growth trajectories

In tidySEM: Tidy Structural Equation Modeling

Plot growth trajectories

Description

Plots latent and observed trajectories for latent growth models.

Usage

plot_growth(
  x,
  items = NULL,
  growth_variables = NULL,
  time_scale = NULL,
  bw = FALSE,
  rawdata = FALSE,
  estimated = TRUE,
  alpha_range = c(0, 0.1),
  jitter_lines = NULL
)

Arguments

x	An oject for which a method exists.
items	Character vector. Indicate the names of the observed variables for the growth trajectory to plot. If NULL (default), all observed variables are used. Use this option to plot one trajectory when a model contains multiple latent growth trajectories.
growth_variables	Character vector. Indicate the names of the latent variables for the growth trajectory to plot. If NULL (default), all latent growth variables are used. Use this option to plot one trajectory when a model contains multiple latent growth trajectories.
time_scale	Numeric vector. In case some of the loadings of the growth model are freely estimated, provide the correct time scale here (e.g., c(0, 1, 2)).
bw	Logical. Should the plot be black and white (for print), or color?
rawdata	Logical. Should raw data (observed trajectories) be plotted in the background? Setting this to TRUE might result in long plotting times. Requires including the Mplus syntax 'SAVEDATA: FILE IS "filename"; SAVE = cprobabilities' in the Mplus input.
estimated	Logical. Should the Mplus estimates growth trajectories be displayed? Defaults to TRUE.
alpha_range	Numeric vector. The minimum and maximum values of alpha (transparency) for the raw data. Minimum should be 0; lower maximum values of alpha can help reduce overplotting.
jitter_lines	Numeric. Indicate the amount (expressed in fractions of a standard deviation of all observed data) by which the observed trajectories should be vertically jittered. Like alpha_range, this parameter helps control overplotting.

Value

An object of class 'ggplot'.

Author(s)

Caspar J. van Lissa

Examples

## Not run: 
data("empathy")
df <- empathy[1:6]
mx_growth_mixture(model = "i =~ 1*ec1 + 1*ec2 + 1*ec3 +1*ec4 +1*ec5 +1*ec6
                           s =~ 0*ec1 + 1*ec2 + 2*ec3 +3*ec4 +4*ec5 +5*ec6
                           ec1 ~~ vec1*ec1
                           ec2 ~~ vec2*ec2
                           ec3 ~~ vec3*ec3
                           ec4 ~~ vec4*ec4
                           ec5 ~~ vec5*ec5
                           ec6 ~~ vec6*ec6
                           i ~~ 0*i
                           s ~~ 0*s
                           i ~~ 0*s",
                  classes = 2,
                  data = df) -> res
plot_growth(res, rawdata = FALSE)

## End(Not run)

tidySEM documentation built on Oct. 25, 2023, 1:06 a.m.