assess_cvpat_compare {seminrExtras}R Documentation

SEMinR function to compare CV-PAT loss of two models

Description

'assess_cvpat_compare' conducts a CV-PAT significance test of loss between two models.

Usage

assess_cvpat_compare(
  established_model,
  alternative_model,
  testtype = "two.sided",
  nboot = 2000,
  seed = 123,
  technique = predict_DA,
  noFolds = NULL,
  reps = NULL,
  cores = NULL
)

Arguments

established_model

The base seminr model for CV-PAT comparison.

alternative_model

The alternate seminr model for CV-PAT comparison.

testtype

Either "two.sided" (default) or "greater".

nboot

The number of bootstrap subsamples to execute (defaults to 2000).

seed

The seed for reproducibility (defaults to 123).

technique

predict_EA or predict_DA (default).

noFolds

Mumber of folds for k-fold cross validation.

reps

Number of repetitions for cross validation.

cores

Number of cores for parallelization.

Value

A matrix of the estimated loss and results of significance testing.

References

Sharma, P. N., Liengaard, B. D., Hair, J. F., Sarstedt, M., & Ringle, C. M. (2022). Predictive model assessment and selection in composite-based modeling using PLS-SEM: extensions and guidelines for using CVPAT. European journal of marketing, 57(6), 1662-1677.

Liengaard, B. D., Sharma, P. N., Hult, G. T. M., Jensen, M. B., Sarstedt, M., Hair, J. F., & Ringle, C. M. (2021). Prediction: coveted, yet forsaken? Introducing a cross‐validated predictive ability test in partial least squares path modeling. Decision Sciences, 52(2), 362-392.

Examples

# Load libraries
library(seminr)



[Package seminrExtras version 0.1.0 Index]