remove_outliers: Remove outliers using mixed models

In inti: Tools and Statistical Procedures in Plant Science

Remove outliers using mixed models

Description

Use the method M4 in Bernal Vasquez (2016). Bonferroni Holm test to judge residuals standardized by the re scaled MAD (BH MADR).

Usage

remove_outliers(data, formula, drop_na = FALSE, plot_diag = FALSE)

Arguments

data	Experimental design data frame with the factors and traits.
formula	mixed model formula.
drop_na	drop NA values from the data.frame
plot_diag	Diagnostic plot based in the raw and clean data

Details

Function to remove outliers in MET experiments

Value

list. 1. Table with date without outliers. 2. The outliers in the dataset.

References

Bernal Vasquez, Angela Maria, et al. “Outlier Detection Methods for Generalized Lattices: A Case Study on the Transition from ANOVA to REML.” Theoretical and Applied Genetics, vol. 129, no. 4, Apr. 2016.

Examples

library(inti)

rmout <- potato %>%
  remove_outliers(data = .
  , formula = stemdw ~ 0 + (1|bloque) + treat*geno
  , plot_diag = FALSE
  , drop_na = FALSE
  )

rmout
  

inti documentation built on Sept. 11, 2024, 8:04 p.m.