SEMsensitivity (version 0.1.0)

Test61: Finding case deletions required to change fit metric using exact influences

Description

Remove a fixed percentage of samples (determined by the exact influence) at a time and refit the model to observe the change in the path of interest. Use method 1 - Naive Method with Exact Influence.

Usage

Test61(
  df,
  model,
  threshold,
  fit,
  max_final,
  N,
  measureTest = "cfi",
  fitThreshold = 0.9,
  highGood = TRUE,
  ...
)

Value

A list of class TestResult61 containing:

methodname

The name of the method used.

testindex

The index of the test performed.

original_fit_value

The original value of the fit measurement.

final_fit_value

The fit value after dropping the influential points.

num_drops

The number of data points dropped.

threshold_crossed

Logical indicating whether the threshold was crossed.

final_drops

The indices of the most influential data points dropped.

measureTest

The name of the fit measurement used.

fitThreshold

The threshold of the fit measurement used.

highGood

Logical indicating if a higher value is better for the fit measurement.

exact_threshold_tally

The tally value required to cross the threshold.

model_exact_threshold_final

The final fit value after dropping points sufficient to cross the threshold.

max_final

The maximum number of influential data points to consider.

N

The total number of data points.

Arguments

df

A data frame containing the dataset.

model

A specified SEM model.

threshold

The threshold for percentage of data dropped.

fit

The SEM object.

max_final

The maximum number of influential data points to consider.

N

The total number of data points.

measureTest

The fit measurement name. Can be "cfi", "chisq", "tli", "rmsea".

fitThreshold

The threshold of the fit measurement to be a "good" model. For example, for CFI (measureTest = "cfi), this threshold can be 0.9.

highGood

A boolean argument stating if the fit measurement is higher the better. For CFI, this argument is TRUE.

...

Other arguments.

Examples

# \donttest{
library(lavaan)
library(dplyr)
library(semfindr)
library(R.utils)


# Import data
df <- PoliticalDemocracy

# Build Model
model <- '
  # measurement model
  ind60 =~ x1 + x2 + x3
  dem60 =~ y1 + y2 + y3 + y4
  dem65 =~ y5 + y6 + y7 + y8
  # regressions
  dem60 ~ ind60
  dem65 ~ ind60 + dem60
  # residual correlations
  y1 ~~ y5
  y2 ~~ y4 + y6
  y3 ~~ y7
  y4 ~~ y8
  y6 ~~ y8
'

threshold <- 10

# Fit SEM model
fit <- lavaan::sem(model, data = df)
summary(fit)

# Compute max number of points to be dropped
max_final <- ceiling(threshold * nrow(df) / 100)
N <- nrow(df)

Test61_result <- Test61(df, model, threshold, fit, max_final, N,
 measureTest = "cfi", fitThreshold = 0.9, highGood = TRUE)
summary(Test61_result)
# }