2019-01-11 20:37:23 +01:00
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# ==================================================================== #
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# TITLE #
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2021-02-02 23:57:35 +01:00
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# Antimicrobial Resistance (AMR) Data Analysis for R #
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2019-01-11 20:37:23 +01:00
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# #
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# SOURCE #
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2020-07-08 14:48:06 +02:00
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# https://github.com/msberends/AMR #
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2019-01-11 20:37:23 +01:00
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# #
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# LICENCE #
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2020-12-27 00:30:28 +01:00
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# (c) 2018-2021 Berends MS, Luz CF et al. #
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2020-10-08 11:16:03 +02:00
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# Developed at the University of Groningen, the Netherlands, in #
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# collaboration with non-profit organisations Certe Medical #
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# Diagnostics & Advice, and University Medical Center Groningen. #
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2019-01-11 20:37:23 +01:00
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# #
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# This R package is free software; you can freely use and distribute #
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# it for both personal and commercial purposes under the terms of the #
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# GNU General Public License version 2.0 (GNU GPL-2), as published by #
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# the Free Software Foundation. #
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2020-01-05 17:22:09 +01:00
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# We created this package for both routine data analysis and academic #
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# research and it was publicly released in the hope that it will be #
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# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
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2020-10-08 11:16:03 +02:00
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# #
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# Visit our website for the full manual and a complete tutorial about #
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2021-02-02 23:57:35 +01:00
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# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
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2019-01-11 20:37:23 +01:00
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# ==================================================================== #
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2021-05-15 21:36:22 +02:00
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# GOODNESS-OF-FIT
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# example 1: clearfield rice vs. red rice
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x <- c(772, 1611, 737)
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expect_equal(g.test(x, p = c(0.25, 0.50, 0.25))$p.value,
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0.12574,
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tolerance = 0.0001)
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# example 2: red crossbills
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x <- c(1752, 1895)
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expect_equal(g.test(x)$p.value,
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0.017873,
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tolerance = 0.0001)
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expect_error(g.test(0))
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expect_error(g.test(c(0, 1), 0))
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expect_error(g.test(c(1, 2, 3, 4), p = c(0.25, 0.25)))
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expect_error(g.test(c(1, 2, 3, 4), p = c(0.25, 0.25, 0.25, 0.24)))
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expect_warning(g.test(c(1, 2, 3, 4), p = c(0.25, 0.25, 0.25, 0.24), rescale.p = TRUE))
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# INDEPENDENCE
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x <- as.data.frame(
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matrix(data = round(runif(4) * 100000, 0),
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ncol = 2,
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byrow = TRUE)
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)
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# fisher.test() is always better for 2x2 tables:
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expect_warning(g.test(x))
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expect_true(suppressWarnings(g.test(x)$p.value) < 1)
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expect_warning(g.test(x = c(772, 1611, 737),
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y = c(780, 1560, 780),
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rescale.p = TRUE))
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expect_error(g.test(matrix(data = c(-1, -2, -3, -4), ncol = 2, byrow = TRUE)))
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expect_error(g.test(matrix(data = c(0, 0, 0, 0), ncol = 2, byrow = TRUE)))
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