## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse  = TRUE,
  comment   = "#>",
  message   = FALSE,
  warning   = FALSE
)

## ----load---------------------------------------------------------------------
library(statAPA)

## ----descriptives-------------------------------------------------------------
result <- apa_descriptives(
  mtcars,
  vars  = c("mpg", "wt", "hp"),
  group = "cyl"
)

## ----ttest--------------------------------------------------------------------
# Two-sample Welch t-test: mpg by transmission type
auto   <- mtcars$mpg[mtcars$am == 0]
manual <- mtcars$mpg[mtcars$am == 1]

res <- apa_t_test(auto, manual, output = "console")

## ----anova--------------------------------------------------------------------
mtcars2       <- mtcars
mtcars2$cyl   <- factor(mtcars2$cyl)

res <- apa_anova(lm(mpg ~ cyl, data = mtcars2), es = "partial_eta2")

## ----twoway-------------------------------------------------------------------
mtcars2$gear <- factor(mtcars2$gear)

res <- apa_twoway_anova(
  mpg ~ cyl * gear,
  data    = mtcars2,
  factorA = "cyl",
  factorB = "gear",
  simple_effects = TRUE
)

## ----ancova-------------------------------------------------------------------
res <- apa_ancova(
  formula   = mpg ~ cyl + wt,
  data      = mtcars2,
  covariate = "wt",
  focal     = "cyl",
  es        = "partial_eta2"
)

## ----manova-------------------------------------------------------------------
res <- apa_manova(
  cbind(Sepal.Length, Petal.Length) ~ Species,
  data = iris
)

## ----posthoc------------------------------------------------------------------
fit <- aov(mpg ~ cyl, data = mtcars2)
res <- apa_posthoc(fit, by = "cyl", adjust = "tukey")

## ----chisq--------------------------------------------------------------------
# Independence test
m <- matrix(c(30, 10, 20, 40), nrow = 2,
            dimnames = list(c("Group A", "Group B"),
                            c("Yes",    "No")))
res <- apa_chisq(m)

## ----proptest-----------------------------------------------------------------
res <- apa_prop_test(x = c(30, 20), n = c(50, 50), output = "console")

## ----regression---------------------------------------------------------------
fit <- lm(mpg ~ wt + hp + factor(cyl), data = mtcars)
res <- apa_table(fit)

## ----robust-------------------------------------------------------------------
res <- apa_robust(fit, type = "HC3")

## ----hetero-------------------------------------------------------------------
res <- apa_hetero(fit)
res <- apa_homoskedasticity(fit)

## ----multilevel, eval = requireNamespace("lme4", quietly = TRUE)--------------
library(lme4)
data(ECLS_demo)

m0 <- lmer(math ~ 1 + (1 | schid),        data = ECLS_demo, REML = FALSE)
m1 <- lmer(math ~ SES + (1 | schid),      data = ECLS_demo, REML = FALSE)
m2 <- lmer(math ~ SES + gender + (1 | schid), data = ECLS_demo, REML = FALSE)

res <- apa_multilevel(
  m0, m1, m2,
  model_names = c("Null", "+ SES", "+ SES + Gender")
)

## ----word, eval = FALSE-------------------------------------------------------
# ft <- apa_to_flextable(res)
# 
# doc <- officer::read_docx()
# doc <- flextable::body_add_flextable(doc, ft)
# print(doc, target = "my_table.docx")

## ----word2, eval = FALSE------------------------------------------------------
# apa_table(fit, output = "word", file = "regression_table.docx")

## ----plots, fig.width = 6, fig.height = 4-------------------------------------
apa_plot_descriptives(mtcars2, y = "mpg", group = "cyl", show_points = TRUE)

## ----plots2, fig.width = 6, fig.height = 4------------------------------------
apa_plot_anova(aov(mpg ~ cyl, data = mtcars2), by = "cyl")