MplusAutomation (version 1.1.1)

plotGrowthMixtures: Plot growth mixture models

Description

Plots latent and observed trajectories for a list of growth mixture models, specified using Mplus' '|' notation (e.g., i s | ).

Usage

plotGrowthMixtures(
  modelList,
  bw = FALSE,
  rawdata = FALSE,
  estimated = TRUE,
  poly = FALSE,
  alpha_range = c(0, 0.1),
  growth_variables = NULL,
  time_scale = NULL,
  jitter_lines = NULL,
  coefficients = "unstandardized"
)

Value

An object of class 'ggplot'.

Arguments

modelList

A list object of Mplus models, or a single Mplus model. This function additionally requires the models to be growth mixture models.

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.

poly

Logical. Should polynomial smooth lines be displayed for each group? Defaults to FALSE. If set to TRUE, the order of the polynomial is determined by taking the number of observed timepoints - 1 (e.g., 3 time points results in a quadratic polynomial). The data are weighted according to their posterior class probabilities. Note that rawdata must be TRUE in order to obtain polynomial smooth lines, because these are calculated on the raw data.

alpha_range

Numeric vector. The minimum and maximum values of alpha (transparancy) for the raw data. Minimum should be 0; lower maximum values of alpha can help reduce overplotting.

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)).

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.

Author

Caspar J. van Lissa

Examples

if (FALSE) {
mydat <- read.csv(
system.file("extdata", "ex8.2.csv", package = "MplusAutomation"))
res <- createMixtures(classes = 1:3, filename_stem = "ex8.2",
                      model_overall = 
                                    "i s | V1@0 V2@1 V3@2 V4@3;  i s on V5;",
                      rdata = mydat,
                      OUTPUT = "tech11 tech14;", 
                      usevariables = c("V1", "V2", "V3", "V4", "V5"),
                      run = 1L)
plotGrowthMixtures(res, estimated = TRUE, rawdata = TRUE, 
                   time_scale = c(0, 1, 2, 3))
plotGrowthMixtures(res, estimated = FALSE, rawdata = TRUE, poly = TRUE)

res <- createMixtures(classes = 1:3, filename_stem = "ex8.2_free",
                      model_overall = "i s | V1@0 V2* V3* V4@3;  i s on V5;",
                      rdata = mydat,
                      OUTPUT = "tech11 tech14;",
                      usevariables = c("V1", "V2", "V3", "V4", "V5"),
                      run = 1L)
plotMixtureDensities(res, variables = c("V1", "V2", "V3", "V4"))
plotGrowthMixtures(res, estimated = TRUE, rawdata = TRUE,
                   bw = TRUE, time_scale = c(0, 1, 2, 3),
                   alpha_range = c(0, .05))

plotGrowthMixtures(res, estimated = FALSE, rawdata = TRUE,
                   poly = TRUE, bw = TRUE, time_scale = c(0, 1, 2, 3))
}