reveal.model.designs: Reveal model designs used in lm.rrpp fit

In RRPP: Linear Model Evaluation with Randomized Residuals in a Permutation Procedure

Reveal model designs used in lm.rrpp fit

Description

Function returns every full and reduced model for model terms used in lm.rrpp fits. This function is useful for revealing the null and full model that would be used in the pairwise function, if a specific null model is not declared as an argument (fit.null in the pairwise function). It also helps to demonstrate how sums of squares and cross-products (SSCP) are calculated in lm.rrpp permutations (iterations), from the difference between fitted values for null and full designs.

Usage

reveal.model.designs(fit)

Arguments

fit	A linear model fit from lm.rrpp.

Author(s)

Michael Collyer

Examples

data(Pupfish)
fit1 <- lm.rrpp(coords~ Pop*Sex, data = Pupfish, 
SS.type = "I", print.progress = FALSE, iter = 0)
fit2 <- lm.rrpp(coords~ Pop*Sex, data = Pupfish, 
SS.type = "II", print.progress = FALSE, iter = 0)
fit3 <- lm.rrpp(coords~ Pop*Sex, data = Pupfish, 
SS.type = "III", print.progress = FALSE, iter = 0)

reveal.model.designs(fit1)
reveal.model.designs(fit2)
reveal.model.designs(fit3)

RRPP documentation built on Aug. 16, 2023, 1:06 a.m.