Differences between the critical points for two factor's levels

Differences between the estimation of critical for two factor's levels.

Usage

criticaldiff(model, level1 = NULL, level2 = NULL, der = NULL)

Arguments

model: Parametric or nonparametric regression model obtained by frfast function.
level1: First factor's level at which to perform the differences between critical points.
level2: Second factor's level at which to perform the differences between critical points.
der: Number which determines any inference process. By default der is NULL. If this term is 0, the calculate of the differences for the critical point is for the estimate. If it is 1 or 2, it is designed for the first or second derivative, respectively.

Value

An object is returned with the following elements:

critical.diff: a table with a couple of factor's level where it is used to calculate the differences between the critical points, and their 95% confidence interval (for the estimation, first and second derivative).

Details

Differences are calculated by subtracting a factor relative to another (\(level2 - level1\)). By default level2 and level1 are NULL, so the differences calculated are for all possible combinations between two factors. Additionally, it is obtained the 95% confidence interval for this difference which let us to make inference about them.

References

Sestelo, M. (2013). Development and computational implementation of estimation and inference methods in flexible regression models. Applications in Biology, Engineering and Environment. PhD Thesis, Department of Statistics and O.R. University of Vigo.

Sestelo, M., Villanueva, N.M., Meira-Machado, L., Roca-Pardinas, J. (2017). npregfast: An R Package for Nonparametric Estimation and Inference in Life Sciences. Journal of Statistical Software, 82(12), 1-27.

Author

Marta Sestelo, Nora M. Villanueva and Javier Roca-Pardinas.

Examples

library(npregfast)
data(barnacle)
fit2 <- frfast(DW ~ RC : F, data = barnacle, seed = 130853, nboot = 100) # with interactions
criticaldiff(fit2)
#> [[1]]
#>              L2    L1   Diff    Lwr    Upr
#> Estimation lens barca   -1.6   -1.6 -0.265
#> First_der  lens barca -0.217 -5.298  0.356
#> Second_der lens barca -0.174   <NA>   <NA>
#> 
criticaldiff(fit2, der = 1)
#> [[1]]
#>             L2    L1   Diff    Lwr   Upr
#> First_der lens barca -0.217 -5.298 0.356
#> 
criticaldiff(fit2, der = 1, level1 = "lens", level2 = "barca")
#>              L2   L1  Diff    Lwr   Upr
#> First_der barca lens 0.217 -0.356 5.298