mirror of https://github.com/msberends/AMR
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
63 lines
2.8 KiB
63 lines
2.8 KiB
# ==================================================================== # |
|
# TITLE # |
|
# Antimicrobial Resistance (AMR) Data Analysis for R # |
|
# # |
|
# SOURCE # |
|
# https://github.com/msberends/AMR # |
|
# # |
|
# LICENCE # |
|
# (c) 2018-2021 Berends MS, Luz CF et al. # |
|
# Developed at the University of Groningen, the Netherlands, in # |
|
# collaboration with non-profit organisations Certe Medical # |
|
# Diagnostics & Advice, and University Medical Center Groningen. # |
|
# # |
|
# This R package is free software; you can freely use and distribute # |
|
# it for both personal and commercial purposes under the terms of the # |
|
# GNU General Public License version 2.0 (GNU GPL-2), as published by # |
|
# the Free Software Foundation. # |
|
# We created this package for both routine data analysis and academic # |
|
# research and it was publicly released in the hope that it will be # |
|
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. # |
|
# # |
|
# Visit our website for the full manual and a complete tutorial about # |
|
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ # |
|
# ==================================================================== # |
|
|
|
# GOODNESS-OF-FIT |
|
|
|
# example 1: clearfield rice vs. red rice |
|
x <- c(772, 1611, 737) |
|
expect_equal(g.test(x, p = c(0.25, 0.50, 0.25))$p.value, |
|
0.12574, |
|
tolerance = 0.0001) |
|
|
|
# example 2: red crossbills |
|
x <- c(1752, 1895) |
|
expect_equal(g.test(x)$p.value, |
|
0.017873, |
|
tolerance = 0.0001) |
|
|
|
expect_error(g.test(0)) |
|
expect_error(g.test(c(0, 1), 0)) |
|
expect_error(g.test(c(1, 2, 3, 4), p = c(0.25, 0.25))) |
|
expect_error(g.test(c(1, 2, 3, 4), p = c(0.25, 0.25, 0.25, 0.24))) |
|
expect_warning(g.test(c(1, 2, 3, 4), p = c(0.25, 0.25, 0.25, 0.24), rescale.p = TRUE)) |
|
|
|
# INDEPENDENCE |
|
|
|
x <- as.data.frame( |
|
matrix(data = round(runif(4) * 100000, 0), |
|
ncol = 2, |
|
byrow = TRUE) |
|
) |
|
|
|
# fisher.test() is always better for 2x2 tables: |
|
expect_warning(g.test(x)) |
|
expect_true(suppressWarnings(g.test(x)$p.value) < 1) |
|
|
|
expect_warning(g.test(x = c(772, 1611, 737), |
|
y = c(780, 1560, 780), |
|
rescale.p = TRUE)) |
|
|
|
expect_error(g.test(matrix(data = c(-1, -2, -3, -4), ncol = 2, byrow = TRUE))) |
|
expect_error(g.test(matrix(data = c(0, 0, 0, 0), ncol = 2, byrow = TRUE)))
|
|
|