tidystats (version 0.5)

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. 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 peek at how the output of a specific analysis will be organized.

Usage

tidy_stats(x)
# S3 method for htest
tidy_stats(x)
# S3 method for lm
tidy_stats(x)
# S3 method for glm
tidy_stats(x)
# S3 method for anova
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 lmerMod
tidy_stats(x)
# S3 method for lmerModLmerTest
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'

• glm: tidy_stats method for class 'glm'

• anova: tidy_stats method for class 'anova'

• 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'

• lmerMod: tidy_stats method for class 'lmerMod'

• lmerModLmerTest: tidy_stats method for class 'lmerModLmerTest'

• BFBayesFactor: tidy_stats method for class 'BayesFactor'

• afex_aov: tidy_stats method for class 'afex_aov'

Details

Please note that not all statistical tests are supported. See 'Details' below for a list of supported statistical tests.

Currently supported functions:

stats:

• t.test()

• cor.test()

• chisq.test()

• wilcox.test()

• fisher.test()

• oneway.test()

• lm()

• glm()

• aov()

• anova()

lme4/lmerTest:

• lmer()

BayesFactor:

• generalTestBF()

• lmBF()

• regressionBF()

• ttestBF()

• anovaBF()

• correlationBF()

• contingencyTableBF()

• proportionBF()

• meta.ttestBF()

tidystats:

• describe_data()

• count_data()

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)

# }