## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----basic--------------------------------------------------------------------
library(effectcheck)

# Check a single APA-style result
result <- check_text("t(28) = 2.21, p = .035, d = 0.80")
print(result)

## ----multiple-----------------------------------------------------------------
text <- "
Study 1 found a significant effect, t(45) = 3.12, p = .003, d = 0.91.
The ANOVA revealed a main effect, F(2, 87) = 5.44, p = .006.
The correlation was significant, r(48) = .42, p = .003.
"

results <- check_text(text)
summary(results)

## ----filter-------------------------------------------------------------------
# Filter by status
errors <- get_errors(results)
warnings <- get_warnings(results)

# Filter by test type
t_tests <- filter_by_test_type(results, "t")

# Get counts
count_by(results, "test_type")

## ----variants-----------------------------------------------------------------
result <- check_text("t(28) = 2.21, p = .035, d = 0.80")

# See all computed variants for the first result
format_variants(result, 1)

# Get metadata about a specific variant type
get_variant_metadata("d_ind")

## ----files, eval=FALSE--------------------------------------------------------
# # Single file
# result <- check_file("manuscript.pdf")
# 
# # Multiple files
# results <- check_files(c("study1.pdf", "study2.html"))
# 
# # Entire directory
# results <- check_dir("manuscripts/")

## ----export, eval=FALSE-------------------------------------------------------
# results <- check_text("t(28) = 2.21, p = .035, d = 0.80")
# 
# # HTML report
# generate_report(results, out = file.path(tempdir(), "report.html"))
# 
# # CSV/JSON export
# export_csv(results, out = file.path(tempdir(), "results.csv"))
# export_json(results, out = file.path(tempdir(), "results.json"))

## ----statcheck, eval=FALSE----------------------------------------------------
# comp <- compare_with_statcheck("t(28) = 2.21, p = .035, d = 0.80")
# print(comp)

