I'm trying to use the package fifer with command install.packages("fifer") with R 3.5.0. However, R tells me that it is not available. This webpage tells me that it has been removed from CRAN. Alternatively is there another function / package in R that allows to do a post hoc chi squared?
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Is there any reason why you can't download and install the archived version? – Rui Barradas Sep 23 '18 at 09:42
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Thank you. @RuiBarradas. I successfully downloaded the archived version! However why has it been remove from CRAN? – ecjb Sep 23 '18 at 10:49
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I don't know. Usually this means that the maintainer no longer wants or can support it. Contributed packages are the developers' and maintainer's responsability, not CRAN's. – Rui Barradas Sep 23 '18 at 10:51
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Ok @RuiBarradas thank you for the comments – ecjb Sep 23 '18 at 10:59
5 Answers
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Alternatively, you can install the package using devtools
install.packages("devtools")
library(devtools)
install_github("dustinfife/fifer")
Based on the activity on Github, it looks like it's still being maintained/developed.
However, I don't manage to install it this way or using the archive in R 3.5.1 (but it seems to work for R 3.5.0 and older). Good luck.
David
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Additionally, there is the chisq.posthoc.test package.
https://www.rdocumentation.org/packages/chisq.posthoc.test/versions/0.1.2/topics/chisq.posthoc.test
test.df <- as.table(cbind(c(30,40,60,120), c(50,70,60,80)))
library(chisq.posthoc.test)
chisq.posthoc.test(test.df)
# Dimension Value A B
#1 A Residuals -2.2446418 2.2446418
#2 A p values 0.1983290 0.1983290
#3 B Residuals -2.9981988 2.9981988
#4 B p values 0.0217260 0.0217260
#5 C Residuals 0.2456726 -0.2456726
#6 C p values 1.0000000 1.0000000
#7 D Residuals 3.9842868 -3.9842868
#8 D p values 0.0005410 0.0005410
Evelyn Mac
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The package fifer is no longer maintained, here is a solution with RVAideMemoire (described in more detail here https://rdrr.io/cran/RVAideMemoire/src/R/chisq.multcomp.R), using an example from Post-Hoc tests for chi-sq in R:
install.packages("RVAideMemoire")
library(RVAideMemoire)
theft_loc<-as.table(c(13704L, 14059L, 14263L, 14450L, 14057L, 15503L, 14230L,
16758L, 15289L, 15499L, 16066L, 15905L, 18531L, 19217L, 12410L,
13398L, 13308L, 13455L, 13083L, 14111L, 13068L, 19569L, 18771L,
19626L, 20290L, 19816L, 20923L, 20466L, 20517L, 19377L, 20035L,
20504L, 20393L, 22409L, 22289L, 7997L, 8106L, 7971L, 8437L, 8246L,
9090L, 8363L, 7934L, 7874L, 7909L, 8150L, 8191L, 8746L, 8277L,
27194L, 25220L, 26034L, 27080L, 27334L, 30819L, 30633L, 10452L,
10848L, 11301L, 11494L, 11265L, 11985L, 11038L, 12104L, 13368L,
14594L, 14702L, 13891L, 12891L, 12939L), .Dim = c(7L, 10L), .Dimnames = structure(list(
c("Sunday", "Monday", "Tuesday", "Wednesday", "Thursday",
"Friday", "Saturday"), c("BAYVIEW", "CENTRAL", "INGLESIDE",
"MISSION", "NORTHERN", "PARK", "RICHMOND", "SOUTHERN", "TARAVAL",
"TENDERLOIN")), .Names = c("", "")), class = "table")
chisq.multcomp(theft_loc, p.method = "none")
> 7874 7909 7934 7971 7997 8106 8150 8191 8246 8277 8363 8437 8746 9090 10452 10848 11038 11265 11301
7909 0.78056 - - - - - - - - - - - - - - - - - -
7934 0.63321 0.84256 - - - - - - - - - - - - - - - - -
7971 0.44095 0.62272 0.76923 - - - - - - - - - - - - - - - -
7997 0.32889 0.48533 0.61768 0.83698 - - - - - - - - - - - - - - -
8106 0.06647 0.11954 0.17444 0.28701 0.39036 - - - - - - - - - - - - - -
8150 0.02923 0.05720 0.08854 0.15860 0.22857 0.73002 - - - - - - - - - - - - -
8191 0.01238 0.02625 0.04298 0.08354 0.12732 0.50552 0.74841 - - - - - - - - - - - -
8246 0.00339 0.00802 0.01417 0.03081 0.05073 0.27360 0.45342 0.66793 - - - - - - - - - - -
8277 0.00152 0.00382 0.00706 0.01637 0.02817 0.18156 0.32174 0.50276 0.80943 - - - - - - - - - -
8363 0.00012 0.00037 0.00078 0.00216 0.00422 0.04522 0.09741 0.18128 0.36396 0.50497 - - - - - - - - -
8437 1.0e-05 3.6e-05 8.5e-05 0.00027 0.00060 0.01007 0.02585 0.05643 0.13921 0.21586 0.56805 - - - - - - - -
8746 1.3e-11 8.8e-11 3.2e-10 2.0e-09 7.1e-09 8.2e-07 4.5e-06 2.0e-05 0.00013 0.00032 0.00341 0.01841 - - - - - - -
9090 < 2e-16 < 2e-16 < 2e-16 < 2e-16 < 2e-16 6.2e-14 8.1e-13 8.0e-12 1.5e-10 6.9e-10 3.7e-08 8.1e-07 0.01000 - - - - - -
10452 < 2e-16 < 2e-16 < 2e-16 < 2e-16 < 2e-16 < 2e-16 < 2e-16 < 2e-16 < 2e-16 < 2e-16 < 2e-16 < 2e-16 < 2e-16 < 2e-16 - - - - -
Unfortunately the category names are lost and replaced by the counts of each category.
I don't like corrections for multiple comparisons (see [Moran 2003][1] for a discussion), but fdr is available.
> install.packages("fifer")
Installing package into ‘C:/Users/admin/Documents/R/win-library/3.5’
(as ‘lib’ is unspecified)
Warning in install.packages :
package ‘fifer’ is not available (for R version 3.5.0)
[1]: Moran, M. D. (2003). Arguments for rejecting the sequential Bonferroni in ecological studies. Oikos, 100(2), 403-405.
Nakx
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Having use the 'fifer' package in the past, I also saw this:
chisq.test(Matriz)
X-squared = 7.7832, df = 3, p-value = 0.05071
FUN = function(i,j){
chisq.test(matrix(c(Matriz[i,1], Matriz[i,2],
Matriz[j,1], Matriz[j,2]),
nrow=2,
byrow=TRUE))$ p.value
}
pairwise.table(FUN,
rownames(Matriz),
p.adjust.method="fdr")
Found at https://rcompanion.org/rcompanion/b_05.html -- this gives answers similar to fifer. The p.adjust.method can be changed.
tripleee
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Alternatively, you can downloads source bundle and install using remote packages.
library(remotes)
install_version("fifer", "1.0")
# Import
library(fifer)
# Run Post Hoc Test of Proportion
chisq.post.hoc(table(data))
Works on R version 4.1.2
Moiz Ali Syed
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