tidystats (version 0.4.1)

tidy_stats: Tidy the output of a statistics object

Description

tidy_stats is used to convert the output of a statistical object to a list of organized statistics. This output can then be added to a list using the add_stats function of this package. The tidy_stats function is automatically run when add_stats is used, so there is generally no need to use this function explicitly. It can be used, however, to quickly peek at how the output of a specific analysis will be organized.Please note that not all statistical tests are supported. See 'Details' below for a list of supported statistical tests.

Usage

tidy_stats(x)
# S3 method for htest
tidy_stats(x)
# S3 method for lm
tidy_stats(x)
# S3 method for lmerMod
tidy_stats(x)
# S3 method for lmerModLmerTest
tidy_stats(x)
# S3 method for aov
tidy_stats(x)
# S3 method for aovlist
tidy_stats(x)
# S3 method for tidystats_descriptives
tidy_stats(x)
# S3 method for tidystats_counts
tidy_stats(x)
# S3 method for anova
tidy_stats(x)
# S3 method for BFBayesFactor
tidy_stats(x)
# S3 method for afex_aov
tidy_stats(x)

Arguments

x

The output of a statistical test.

Methods (by class)

• htest: tidy_stats method for class 'htest'

• lm: tidy_stats method for class 'lm'

• lmerMod: tidy_stats method for class 'lmerMod'

• lmerModLmerTest: tidy_stats method for class 'lmerModLmerTest'

• aov: tidy_stats method for class 'aov'

• aovlist: tidy_stats method for class 'aovlist'

• tidystats_descriptives: tidy_stats method for class 'tidystats_descriptives'

• tidystats_counts: tidy_stats method for class 'tidystats_counts'

• anova: tidy_stats method for class 'anova'

• BFBayesFactor: tidy_stats method for class 'BayesFactor'

• afex_aov: tidy_stats method for class 'afex_aov'

Details

Currently supported functions:

• t.test()

• cor.test()

• chisq.test()

• wilcox.test()

• fisher.test()

• oneway.test()

• aov()

• lm()

Examples

# NOT RUN {
# Conduct statistical tests
# t-test:
sleep_test <- t.test(extra ~ group, data = sleep, paired = TRUE)

# lm:
ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
group <- gl(2, 10, 20, labels = c("Ctl","Trt"))
weight <- c(ctl, trt)
lm_D9 <- lm(weight ~ group)

# ANOVA:
npk_aov <- aov(yield ~ block + N*P*K, npk)

# Tidy the statistics and store each analysis in a separate variable
list_sleep_test <- tidy_stats(sleep_test)
list_lm_D9 <- tidy_stats(lm_D9)
list_npk_aov <- tidy_stats(npk_aov)

# Now you can inspect each of these variables, e.g.,:
names(list_sleep_test)
str(list_sleep_test)

# }