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Plots of Case Influence on Parameter Estimates

Source: R/est_change_plot.R
est_change_plot.Rd

Gets the output of functions such as est_change() and est_change_approx() and plots case influence on selected parameters.

Usage

est_change_plot(
  change,
  parameters,
  cutoff_change = NULL,
  largest_change = 1,
  title = TRUE,
  point_aes = list(),
  vline_aes = list(),
  hline_aes = list(),
  cutoff_line_aes = list(),
  case_label_aes = list(),
  wrap_aes = list()
)

est_change_gcd_plot(
  change,
  parameters,
  cutoff_gcd = NULL,
  largest_gcd = 1,
  cutoff_change = NULL,
  largest_change = 1,
  title = TRUE,
  point_aes = list(),
  hline_aes = list(),
  cutoff_line_aes = list(),
  case_label_aes = list(),
  wrap_aes = list()
)

Arguments

change

The output from est_change(), est_change_raw(), est_change_approx(), or est_change_raw_approx().

parameters

If it is a character vector, it specifies the selected parameters. Each parameter is named as in lavaan syntax, e.g., x ~ y or x ~~ y, as appeared in the columns lhs, op, and rhs in the output of lavaan::parameterEstimates(). Supports specifying an operator to select all parameters with this operators: ~, ~~, =~, and ~1. This vector can contain both parameter names and operators. If it is a numeric vector, it specifies the columns to be used. If omitted or NULL, the default, changes on all parameters in change. will be used.

cutoff_change

Cases with absolute changes larger than this value will be labeled. Default is NULL. If NULL, no cutoff line will be drawn.

largest_change

The number of cases with the largest absolute changes to be labelled. Default is

  1. If not an integer, it will be rounded to the nearest integer.

title

If TRUE, the default, a default title will be added to the plot. If it is a string, it will be used as the title. If FALSE, no title will be added to the plot.

point_aes

A named list of arguments to be passed to ggplot2::geom_point() to modify how to draw the points. Default is list() and internal default settings will be used.

vline_aes

A named list of arguments to be passed to ggplot2::geom_segment() to modify how to draw the line for each case in the index plot by est_change_plot(). Default is list() and internal default settings will be used.

hline_aes

A named list of arguments to be passed to ggplot2::geom_hline() to modify how to draw the horizontal line for zero case influence. Default is list() and internal default settings will be used.

cutoff_line_aes

A named list of arguments to be passed to ggplot2::geom_hline() in est_change_plot() or ggplot2::geom_vline() in est_change_gcd_plot() to modify how to draw the line for user cutoff value (cutoff_change or cutoff_gcd). Default is list() and internal default settings will be used.

case_label_aes

A named list of arguments to be passed to ggrepel::geom_label_repel() to modify how to draw the labels for cases marked (based on cutoff_change, cutoff_gcd, largest_change, or largest_gcd). Default is list() and internal default settings will be used.

wrap_aes

A named list of arguments to be passed to ggplot2::facet_wrap() to modify how the plots are organized. Default is list() and internal default settings will be used.

cutoff_gcd

Cases with generalized Cook's distance or approximate generalized Cook's distance larger than this value will be labeled. Default is NULL. If NULL, no cutoff line will be drawn.

largest_gcd

The number of cases with the largest generalized Cook's distance or approximate generalized Cook's distance to be labelled. Default is 1. If not an integer, it will be rounded to the nearest integer.

Value

A ggplot2 plot. Plotted by default. If assigned to a variable or called inside a function, it will not be plotted. Use plot() to plot it.

Details

The output of est_change(), est_change_raw(), est_change_approx(), and est_change_raw_approx() is simply a matrix. Therefore, these functions will work for any matrix provided. Row number will be used on the x-axis if applicable. However, case identification values will be used for labeling individual cases if they are stored as row names.

The default settings for the plots should be good enough for diagnostic purpose. If so desired, users can use the *_aes arguments to nearly fully customize all the major elements of the plots, as they would do for building a ggplot2 plot.

Functions

  • est_change_plot(): Index plot of case influence on parameters.

  • est_change_gcd_plot(): Plot case influence on parameter estimates against generalized Cook's distance.

References

Pek, J., & MacCallum, R. (2011). Sensitivity analysis in structural equation models: Cases and their influence. Multivariate Behavioral Research, 46(2), 202-228. doi:10.1080/00273171.2011.561068

See also

est_change(), est_change_raw(), est_change_approx(), and est_change_raw_approx().

Author

Shu Fai Cheung https://orcid.org/0000-0002-9871-9448.

Examples


library(lavaan)

# A path model

dat <- pa_dat
mod <-
"
m1 ~ a1 * iv1 + a2 * iv2
dv ~ b * m1
a1b := a1 * b
a2b := a2 * b
"
# Fit the model
fit <- lavaan::sem(mod, dat)
summary(fit)
#> lavaan 0.6.17 ended normally after 1 iteration
#> 
#>   Estimator                                         ML
#>   Optimization method                           NLMINB
#>   Number of model parameters                         5
#> 
#>   Number of observations                           100
#> 
#> Model Test User Model:
#>                                                       
#>   Test statistic                                 6.711
#>   Degrees of freedom                                 2
#>   P-value (Chi-square)                           0.035
#> 
#> Parameter Estimates:
#> 
#>   Standard errors                             Standard
#>   Information                                 Expected
#>   Information saturated (h1) model          Structured
#> 
#> Regressions:
#>                    Estimate  Std.Err  z-value  P(>|z|)
#>   m1 ~                                                
#>     iv1       (a1)    0.215    0.106    2.036    0.042
#>     iv2       (a2)    0.522    0.099    5.253    0.000
#>   dv ~                                                
#>     m1         (b)    0.517    0.106    4.895    0.000
#> 
#> Variances:
#>                    Estimate  Std.Err  z-value  P(>|z|)
#>    .m1                0.903    0.128    7.071    0.000
#>    .dv                1.321    0.187    7.071    0.000
#> 
#> Defined Parameters:
#>                    Estimate  Std.Err  z-value  P(>|z|)
#>     a1b               0.111    0.059    1.880    0.060
#>     a2b               0.270    0.075    3.581    0.000
#> 

# Compute approximate case influence on parameters estimates
out <- est_change_approx(fit)

# Plot case influence for all regression coefficients
est_change_plot(out,
                parameters = "~",
                largest_change = 2)


# Plot case influence against approximated gCD for all
# regression coefficients
# Label top 5 cases with largest approximated gCD
est_change_gcd_plot(out,
                    parameters = "~",
                    largest_gcd = 5)


# Customize elements in a plot.
# For example, change the color and shape of the points.

est_change_plot(out,
                parameters = "~",
                largest_change = 2,
                point_aes = list(shape = 5,
                                 color = "red"))