cvlldiff: Cross-Validated Difference in Means (CVDM) Test with Vector...

In modeLLtest: Compare Models with Cross-Validated Log-Likelihood

Cross-Validated Difference in Means (CVDM) Test with Vector Imputs

Description

Applies cross-validated log-likelihood to test between two methods of estimating a formula. The output identifies the vector from the more appropriate model.

Please cite:

Desmarais, B. A., & Harden, J. J. (2014). An Unbiased Model Comparison Test Using Cross-Validation. Quality & Quantity, 48(4), 2155-2173. doi: 10.1007/s11135-013-9884-7

Usage

cvlldiff(vector1, vector2, df)

Arguments

vector1	A numeric vector of cross-validated log-likelihoods.
vector2	A numeric vector of cross-validated log-likelihoods.
df	A value of the degrees of freedom in the models.

Details

This function implements the cross-validated difference in means (CVDM) test between two vectors of cross-validated log-likelihoods. A positive test statistic supports the method that produced the first vector and a negative test statistic supports the second.

Value

An object of class cvlldiff computed by the cross-validated log likelihood difference in means test (CVDM). The test statistic object is the Cross-Validated Johnson's t-test. A positive test statistic supports the first method and a negative test statistic supports the second.See cvdm_object for more details.

References

Desmarais, B. A., & Harden, J. J. (2014). An Unbiased Model Comparison Test Using Cross-Validation. Quality & Quantity, 48(4), 2155-2173. doi: 10.1007/s11135-013-9884-7

Examples

  set.seed(123456)
  b0 <- .2 # True value for the intercept
  b1 <- .5 # True value for the slope
  n <- 500 # Sample size
  X <- runif(n, -1, 1)

  Y <- b0 + b1 * X + rnorm(n, 0, 1) # N(0, 1 error)
  cvll_ols <- cvll(Y ~ X, data.frame(cbind(Y, X)), method = "OLS")
  cvll_mr <- cvll(Y ~ X, data.frame(cbind(Y, X)), method = "MR")
  obj_compare <- cvlldiff(cvll_ols$cvll, cvll_mr$cvll, cvll_ols$df)

modeLLtest documentation built on May 6, 2022, 1:05 a.m.