add_stats is used to add the output of a statistical test to a
tidystats list. While adding the output, additional information about the
test can be added, including the type of test (primary, secondary, or
exploratory), whether the test was preregistered, and additional notes.
Please note that not all statistical tests are supported. See 'Details' below
for a list of supported statistical tests.
add_stats(
results,
output,
identifier = NULL,
type = NULL,
preregistered = NULL,
notes = NULL
)A tidystats list.
Output of a statistical test.
A character string identifying the model. Automatically created if not provided.
A character string specifying the type of analysis: primary, secondary, or exploratory.
A boolean specifying whether the analysis was preregistered or not.
A character string specifying additional information.
Currently supported functions:
stats:
lme4/lmerTest:
lmer()
BayesFactor:
generalTestBF()
lmBF()
regressionBF()
ttestBF()
anovaBF()
correlationBF()
contingencyTableBF()
proportionBF()
meta.ttestBF()
tidystats:
# Load dplyr for access to the piping operator
library(dplyr)
#>
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#>
#> filter, lag
#> The following objects are masked from ‘package:base’:
#>
#> intersect, setdiff, setequal, union
# 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)
#' # Create an empty list
results <- list()
# Add output to the results list
results <- results %>%
add_stats(sleep_test) %>%
add_stats(lm_D9, type = "primary", preregistered = TRUE) %>%
add_stats(npk_aov, notes = "An ANOVA example")