Diagnostic plots of fitted 2S-PA model

Usage

tspa_plot(
  tspa_fit,
  title = NULL,
  label_x = NULL,
  label_y = NULL,
  abbreviation = TRUE,
  fscores_type = c("original", "lavaan"),
  ask = FALSE,
  ...
)

Arguments

tspa_fit: An object of class lavaan, representing the output generated from the tspa() function.
title: Character. Set the name of scatter plot. The default value is "Scatterplot".
label_x: Character. Set the name of the x-axis. The default value is "fs_" followed by variable names.
label_y: Character. Set the name of the y-axis. The default value is "fs_" followed by variable names.
abbreviation: Logic input. If FALSE is indicated, the group name will be shown in full. The default setting is TRUE.
fscores_type: Character. Set the type of factor score for input. The default setting is using factor score from observed data (i.e., output from get_fs()). If fscore_type = "est", then it will use output from lavaan::lavPredict().
ask: Logic input. If TRUE is indicated, the user will be asked before before each plot is generated. The default setting is 'False'.
...: Additional arguments passed to plot. See plot for a list.

Value

A scatterplot between factor scores, and a residual plot.

Examples

library(lavaan)
model <- "
# latent variable definitions
ind60 =~ x1 + x2 + x3
dem60 =~ y1 + a*y2 + b*y3 + c*y4
# regressions
dem60 ~ ind60
"
fs_dat_ind60 <- get_fs(
  data = PoliticalDemocracy,
  model = "ind60 =~ x1 + x2 + x3"
)
fs_dat_dem60 <- get_fs(
  data = PoliticalDemocracy,
  model = "dem60 =~ y1 + y2 + y3 + y4"
)
fs_dat <- cbind(fs_dat_ind60, fs_dat_dem60)

tspa_fit <- tspa(
  model = "dem60 ~ ind60",
  data = fs_dat,
  se_fs = list(ind60 = 0.1213615, dem60 = 0.6756472)
)
tspa_plot(tspa_fit)