| Type: | Package |
| Title: | Statistical Consistency Checker for Published Research Results |
| Version: | 0.2.3 |
| Description: | A conservative, assumption-aware statistical consistency checker for published research results. Parses test statistics, effect sizes, and confidence intervals from text, PDF, HTML, and Word documents across multiple citation styles including American Psychological Association (APA), Harvard, Frontiers, PLOS ONE, Scientific Reports, Nature Human Behaviour, PeerJ, eLife, PNAS, and others. Recomputes effect sizes using all plausible variants when design is ambiguous, and validates internal consistency. Supports t-tests, F-tests/ANOVA, correlations, chi-square, z-tests, regression, and nonparametric tests. Provides 'statcheck'-compatible API functions for batch processing of files and directories. Explicitly tracks all assumptions and uncertainty in output. Detects decision errors (significance reversals) similar to 'statcheck'. Note: this package is under active development and results should be independently verified. Use is at the sole responsibility of the user. Contributions and verification reports are welcome. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.3 |
| URL: | https://github.com/giladfeldman/escicheck |
| BugReports: | https://github.com/giladfeldman/escicheck/issues |
| SystemRequirements: | poppler-utils (pdftotext) for PDF text extraction |
| Imports: | stringr, stringi, dplyr, purrr, tibble, xml2, rvest, glue, logger, graphics, stats, utils |
| Suggests: | shiny, shinythemes, DT, knitr, rmarkdown, testthat (≥ 3.0.0), MBESS, effectsize, jsonlite, tesseract, magick, qpdf, statcheck |
| Depends: | R (≥ 4.1.0) |
| Config/testthat/edition: | 3 |
| VignetteBuilder: | knitr |
| NeedsCompilation: | no |
| Packaged: | 2026-03-20 16:41:04 UTC; filin |
| Author: | Gilad Feldman 
[aut, cre] |
| Maintainer: | Gilad Feldman <giladfel@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2026-03-25 10:50:02 UTC |
effectcheck: Statistical Consistency Checker for Published Research Results
Description
A conservative, assumption-aware statistical consistency checker for published research results. Parses test statistics, effect sizes, and confidence intervals from text, PDF, HTML, and Word documents across multiple citation styles including American Psychological Association (APA), Harvard, Frontiers, PLOS ONE, Scientific Reports, Nature Human Behaviour, PeerJ, eLife, PNAS, and others. Recomputes effect sizes using all plausible variants when design is ambiguous, and validates internal consistency. Supports t-tests, F-tests/ANOVA, correlations, chi-square, z-tests, regression, and nonparametric tests. Provides 'statcheck'-compatible API functions for batch processing of files and directories. Explicitly tracks all assumptions and uncertainty in output. Detects decision errors (significance reversals) similar to 'statcheck'. Note: this package is under active development and results should be independently verified. Use is at the sole responsibility of the user. Contributions and verification reports are welcome.
Author(s)
Maintainer: Gilad Feldman giladfel@gmail.com (ORCID)
See Also
Useful links:
Report bugs at https://github.com/giladfeldman/escicheck/issues
EffectCheck S3 Class Definition and Methods
Description
This file defines the effectcheck S3 class and its associated methods for printing, summarizing, and plotting results.
Usage
.effectcheck_version()
Constants for EffectCheck
Description
Default values and tolerances used across the package.
Usage
DEFAULT_TOL_EFFECT
Format
An object of class list of length 24.
Effect Size Type Definitions
Description
Maps reported effect size names to their family and variants. Based on Guide to Effect Sizes and Confidence Intervals (Jane et al., 2024) https://matthewbjane.quarto.pub/
Usage
EFFECT_SIZE_FAMILIES
Format
An object of class list of length 24.
Variant Metadata
Description
Provides assumptions and usage information for each effect size variant.
Usage
VARIANT_METADATA
Format
An object of class list of length 25.
Calculate Cramer's V from Chi-square
Description
Calculate Cramer's V from Chi-square
Usage
V_from_chisq(chisq, N, m)
Arguments
chisq |
Chi-square statistic |
N |
Total sample size |
m |
Smaller dimension - 1 (min(r-1, c-1)) |
Value
Cramer's V
Subset method for effectcheck objects
Description
Preserves effectcheck class when subsetting.
Usage
## S3 method for class 'effectcheck'
x[...]
Arguments
x |
An effectcheck object |
... |
Subsetting arguments |
Value
An effectcheck object
Examples
res <- check_text("t(28) = 2.21, p = .035. F(1, 50) = 4.03, p = .049")
res[1, ]
Compute adjusted R-squared
Description
Compute adjusted R-squared
Usage
adjusted_R2(R2, n, p)
Arguments
R2 |
R-squared value |
n |
Sample size |
p |
Number of predictors |
Value
Adjusted R-squared
Check Word documents in a directory
Description
Scans a directory for .docx files and checks all detected statistics.
Usage
checkDOCXdir(dir, subdir = TRUE, messages = TRUE, ...)
Arguments
dir |
Directory path to scan |
subdir |
Logical, recurse into subdirectories (default TRUE) |
messages |
Logical, show progress messages (default TRUE) |
... |
Additional arguments passed to check_text() |
Value
An effectcheck object with results
Examples
## Not run:
# Requires a directory with DOCX files
results <- checkDOCXdir("manuscripts/")
summary(results)
## End(Not run)
Check HTML files for statistical consistency
Description
Checks one or more HTML files for statistical consistency. This function is provided for compatibility with statcheck's checkHTML().
Usage
checkHTML(files, messages = TRUE, ...)
Arguments
files |
Character vector of HTML file paths |
messages |
Logical, show progress messages (default TRUE) |
... |
Additional arguments passed to check_text() |
Value
An effectcheck object with results
Examples
tmp <- tempfile(fileext = ".html")
writeLines("<p>t(28) = 2.21, p = .035, d = 0.80</p>", tmp)
results <- checkHTML(tmp)
summary(results)
unlink(tmp)
Check a directory of HTML files
Description
Scans a directory for HTML files and checks all detected statistics. This function is provided for compatibility with statcheck's checkHTMLdir().
Usage
checkHTMLdir(dir, subdir = TRUE, messages = TRUE, ...)
Arguments
dir |
Directory path to scan |
subdir |
Logical, recurse into subdirectories (default TRUE) |
messages |
Logical, show progress messages (default TRUE) |
... |
Additional arguments passed to check_text() |
Value
An effectcheck object with results
Examples
## Not run:
# Requires a directory with HTML files
results <- checkHTMLdir("manuscripts/")
summary(results)
## End(Not run)
Check PDF files for statistical consistency
Description
Checks one or more PDF files for statistical consistency. This function is provided for compatibility with statcheck's checkPDF().
Usage
checkPDF(files, try_tables = TRUE, try_ocr = FALSE, messages = TRUE, ...)
Arguments
files |
Character vector of PDF file paths |
try_tables |
Logical, attempt table extraction (default TRUE) |
try_ocr |
Logical, attempt OCR for scanned PDFs (default FALSE) |
messages |
Logical, show progress messages (default TRUE) |
... |
Additional arguments passed to check_text() |
Value
An effectcheck object with results
Examples
## Not run:
# Requires PDF files
results <- checkPDF(c("paper1.pdf", "paper2.pdf"))
summary(results)
## End(Not run)
Check a directory of PDF files
Description
Scans a directory for PDF files and checks all detected statistics. This function is provided for compatibility with statcheck's checkPDFdir().
Usage
checkPDFdir(
dir,
subdir = TRUE,
try_tables = TRUE,
try_ocr = FALSE,
messages = TRUE,
...
)
Arguments
dir |
Directory path to scan |
subdir |
Logical, recurse into subdirectories (default TRUE) |
try_tables |
Logical, attempt table extraction (default TRUE) |
try_ocr |
Logical, attempt OCR for scanned PDFs (default FALSE) |
messages |
Logical, show progress messages (default TRUE) |
... |
Additional arguments passed to check_text() |
Value
An effectcheck object with results
Examples
## Not run:
# Requires a directory with PDF files
results <- checkPDFdir("manuscripts/")
summary(results)
## End(Not run)
Check a directory for statistical consistency
Description
Recursively scans a directory for supported files and checks all detected statistics for consistency.
Usage
check_dir(
dir,
subdir = TRUE,
pattern = "\\.(pdf|html?|docx|txt)$",
try_tables = TRUE,
try_ocr = FALSE,
messages = TRUE,
allowed_base_dirs = NULL,
...
)
Arguments
dir |
Directory path to scan |
subdir |
Logical, recurse into subdirectories (default TRUE) |
pattern |
File pattern regex (default matches .pdf, .html, .htm, .docx, .txt) |
try_tables |
Logical, attempt table extraction from PDFs (default TRUE) |
try_ocr |
Logical, attempt OCR for scanned PDFs (default FALSE) |
messages |
Logical, show progress messages (default TRUE) |
allowed_base_dirs |
Optional character vector of allowed base directories for security |
... |
Additional arguments passed to check_text() |
Value
An effectcheck object with results from all files
Examples
d <- tempdir()
writeLines("t(28) = 2.21, p = .035, d = 0.80", file.path(d, "test.txt"))
results <- check_dir(d, pattern = "\\.txt$")
summary(results)
unlink(file.path(d, "test.txt"))
EffectCheck API Functions
Description
This file provides statcheck-compatible API functions for checking statistical consistency in APA-style results. Check a single file for statistical consistency
Usage
check_file(path, try_tables = TRUE, try_ocr = FALSE, ...)
Arguments
path |
Path to the file (.pdf, .html, .docx, or .txt) |
try_tables |
Logical, attempt table extraction from PDFs (default TRUE) |
try_ocr |
Logical, attempt OCR for scanned PDFs (default FALSE) |
... |
Additional arguments passed to check_text() |
Details
Reads a file and checks all detected statistics for consistency.
Value
An effectcheck object with results
Examples
tmp <- tempfile(fileext = ".txt")
writeLines("t(28) = 2.21, p = .035, d = 0.80", tmp)
result <- check_file(tmp)
print(result)
unlink(tmp)
Check files for statistical consistency
Description
Reads one or more files and checks all detected statistics for consistency.
Usage
check_files(paths, try_tables = TRUE, try_ocr = FALSE, messages = TRUE, ...)
Arguments
paths |
Character vector of file paths (.pdf, .html, .docx, or .txt) |
try_tables |
Logical, attempt table extraction from PDFs (default TRUE) |
try_ocr |
Logical, attempt OCR for scanned PDFs (default FALSE) |
messages |
Logical, show progress messages (default TRUE) |
... |
Additional arguments passed to check_text() |
Value
An effectcheck S3 object with consistency check results
Examples
tmp <- tempfile(fileext = ".txt")
writeLines("t(28) = 2.21, p = .035, d = 0.80", tmp)
results <- check_files(tmp)
print(results)
unlink(tmp)
Check raw text for statistical consistency
Description
Parses APA-style statistical results from text and checks for consistency between reported and computed values. Uses type-matched comparison to ensure reported effect sizes are compared against the same type of computed values.
Usage
check_text(
text,
stats = c("t", "F", "r", "chisq", "z", "U", "W", "H", "regression"),
ci_level = 0.95,
alpha = 0.05,
one_tailed = FALSE,
paired_r_grid = seq(0.1, 0.9, by = 0.1),
assume_equal_ns_when_missing = TRUE,
ci_method_phi = "bonett_price",
ci_method_V = "bonett_price",
tol_effect = list(d = 0.02, r = 0.005, phi = 0.02, V = 0.02),
tol_ci = 0.02,
tol_p = 0.001,
messages = FALSE,
max_text_length = 10^7,
max_stats_per_text = 10000,
cross_type_action = "NOTE",
ci_affects_status = TRUE,
plausibility_filter = TRUE,
sign_sensitive = FALSE
)
Arguments
text |
Character vector of text to check |
stats |
Character vector of test types to check (default: all supported types) |
ci_level |
Default confidence interval level (default 0.95) |
alpha |
Significance threshold for decision error detection (default 0.05) |
one_tailed |
Logical, assume one-tailed tests (default FALSE) |
paired_r_grid |
Numeric vector of correlation values for paired t-test grid search |
assume_equal_ns_when_missing |
Logical, assume equal group sizes when missing (default TRUE) |
ci_method_phi |
CI method for phi coefficient (default "bonett_price") |
ci_method_V |
CI method for Cramer's V (default "bonett_price") |
tol_effect |
List of tolerances for effect sizes by type |
tol_ci |
Tolerance for CI bounds (default 0.02) |
tol_p |
Tolerance for p-values (default 0.001) |
messages |
Logical, show progress messages (default FALSE) |
max_text_length |
Maximum total text length in characters (default 10^7) |
max_stats_per_text |
Maximum number of stats to process per text (default 10000) |
cross_type_action |
Action when cross-type match found ("NOTE", "WARN", or "ERROR"; default "NOTE") |
ci_affects_status |
Whether CI mismatches affect status (default TRUE) |
plausibility_filter |
Whether to apply plausibility bounds filter (default TRUE) |
sign_sensitive |
Whether sign differences affect status (default FALSE) |
Value
An effectcheck S3 object with consistency check results
Examples
result <- check_text("t(28) = 2.21, p = .035, d = 0.80")
print(result)
summary(result)
Calculate CI for Cohen's f
Description
Derived from Partial Eta-Squared CI.
Usage
ci_cohens_f(F_val, df1, df2, level = 0.95)
Arguments
F_val |
F statistic |
df1 |
df1 |
df2 |
df2 |
level |
CI level |
Value
ci_result list
Comprehensive CI computation for independent d
Description
Tries multiple methods in order of priority: effectsize -> noncentral t -> approximation.
Usage
ci_d_ind(d, n1, n2, level = 0.95, prefer_noncentral = TRUE)
Arguments
d |
Cohen's d |
n1 |
Sample size 1 |
n2 |
Sample size 2 |
level |
Confidence level (default 0.95) |
prefer_noncentral |
Logical, prefer noncentral t method |
Value
ci_result list
Approximate CI for independent d
Description
Uses Hedges/CMC large-sample approximation.
Usage
ci_d_ind_approx(d, n1, n2, level = 0.95)
Arguments
d |
Cohen's d |
n1 |
Sample size 1 |
n2 |
Sample size 2 |
level |
Confidence level (default 0.95) |
Value
Vector of bounds (lower, upper)
Noncentral t CI for independent d
Description
Uses noncentral t-distribution (via MBESS if available).
Usage
ci_d_ind_noncentral_t(d, n1, n2, level = 0.95)
Arguments
d |
Cohen's d |
n1 |
Sample size 1 |
n2 |
Sample size 2 |
level |
Confidence level (default 0.95) |
Value
Vector of bounds (lower, upper)
Calculate CI for Cohen's dz (paired design)
Description
Uses the noncentral t approach or large-sample approximation. SE(dz) = sqrt(1/n + dz^2 / (2*n)) for the normal approximation.
Usage
ci_dz(dz, n, level = 0.95)
Arguments
dz |
Cohen's dz |
n |
Sample size (number of pairs) |
level |
Confidence level (default 0.95) |
Value
ci_result list
Alias for ci_etap2 (used for eta2 when design implies equivalence or as approximation)
Description
Alias for ci_etap2 (used for eta2 when design implies equivalence or as approximation)
Usage
ci_eta2(F_val, df1, df2, level = 0.95)
Arguments
F_val |
F statistic |
df1 |
df1 |
df2 |
df2 |
level |
CI level |
Calculate CI for Partial Eta-Squared
Description
Calculate CI for Partial Eta-Squared
Usage
ci_etap2(F_val, df1, df2, level = 0.95)
Arguments
F_val |
F statistic |
df1 |
df1 |
df2 |
df2 |
level |
CI level |
Value
ci_result list
Comprehensive CI computation for correlation
Description
Comprehensive CI computation for correlation
Usage
ci_r(r, n, level = 0.95)
Arguments
r |
Correlation coefficient |
n |
Sample size |
level |
Confidence level |
Value
ci_result list
Compare effectcheck and statcheck results on a file
Description
Compare effectcheck and statcheck results on a file
Usage
compare_file_with_statcheck(path, ...)
Arguments
path |
Path to a file (PDF, HTML, DOCX, or text) |
... |
Additional arguments passed to check_file() |
Value
A tibble with source column
Examples
tmp <- tempfile(fileext = ".txt")
writeLines("t(28) = 2.21, p = .035, d = 0.80", tmp)
comp <- compare_file_with_statcheck(tmp)
unlink(tmp)
Compare reported value to all variants
Description
Creates a comparison table showing the reported value against all computed variants.
Usage
compare_to_variants(x, row_index = 1)
Arguments
x |
An effectcheck object |
row_index |
The row index |
Value
A data frame with variant comparisons
Examples
res <- check_text("t(28) = 2.21, p = .035, d = 0.80")
compare_to_variants(res, 1)
Compare effectcheck results with statcheck
Description
Runs both effectcheck and statcheck on the same text and returns a merged comparison tibble.
Usage
compare_with_statcheck(text, ...)
Arguments
text |
Character string containing APA-formatted statistics |
... |
Additional arguments passed to check_text() |
Value
A tibble with source column ("both", "effectcheck_only", "statcheck_only")
Examples
comp <- compare_with_statcheck("t(28) = 2.21, p = .035, d = 0.80")
print(comp)
Compute effects and compare to reported values for one parsed row
Description
This function implements type-matched comparison: it compares reported effect sizes against computed variants of the SAME type. When design is ambiguous, it computes all variants and finds the closest match among same-type variants.
Usage
compute_and_compare_one(
row,
ci_level = 0.95,
alpha = 0.05,
one_tailed = FALSE,
paired_r_grid = seq(0.1, 0.9, by = 0.1),
assume_equal_ns_when_missing = TRUE,
tol_effect = list(d = 0.02, r = 0.005, phi = 0.02, V = 0.02),
tol_ci = 0.02,
tol_p = 0.001,
cross_type_action = "NOTE",
ci_affects_status = TRUE,
plausibility_filter = TRUE,
sign_sensitive = FALSE
)
Arguments
row |
A single row from parsed data |
ci_level |
Default CI level |
alpha |
Significance threshold |
one_tailed |
Whether to use one-tailed tests |
paired_r_grid |
Grid of r values for paired t-test computations |
assume_equal_ns_when_missing |
Whether to assume equal n when missing |
tol_effect |
List of tolerances by effect type |
tol_ci |
Tolerance for CI bounds |
tol_p |
Tolerance for p-values |
cross_type_action |
Action when cross-type match found ("NOTE", "WARN", or "ERROR") |
ci_affects_status |
Whether CI mismatches affect status (default TRUE) |
plausibility_filter |
Whether to apply plausibility bounds filter (default TRUE) |
sign_sensitive |
Whether sign differences affect status (default FALSE) |
Value
A tibble with comparison results
Compute range of plausible dav values
Description
Calculates dav across a grid of possible correlations.
Usage
compute_dav_range(dz, r_grid = seq(0.1, 0.9, by = 0.1))
Arguments
dz |
Cohen's dz |
r_grid |
Vector of correlations to test |
Value
List with min, max, median, and values
Count statistics by category
Description
Provides counts of statistics grouped by various categories.
Usage
count_by(x, by = c("status", "test_type", "uncertainty", "design", "source"))
Arguments
x |
An effectcheck object |
by |
Character, grouping variable: "status", "test_type", "uncertainty", "design", or "source" |
Value
A data frame with counts
Examples
results <- check_text("t(28) = 2.21, p = .035. F(1, 50) = 4.03, p = .049")
count_by(results, "status")
count_by(results, "test_type")
Calculate Cohen's d from t-statistic (Independent Samples)
Description
Calculate Cohen's d from t-statistic (Independent Samples)
Usage
d_ind_from_t(t, n1, n2)
Arguments
t |
t-statistic |
n1 |
Sample size 1 |
n2 |
Sample size 2 |
Value
Cohen's d
Convert dz to dav (Cohen's d for average variance)
Description
Convert dz to dav (Cohen's d for average variance)
Usage
dav_from_dz(dz, r)
Arguments
dz |
Cohen's dz |
r |
Correlation between measures |
Value
Cohen's dav
Convert dz to drm (Cohen's d for raw means)
Description
Convert dz to drm (Cohen's d for raw means)
Usage
drm_from_dz(dz, r = NA_real_)
Arguments
dz |
Cohen's dz |
r |
Correlation (unused, for interface compatibility) |
Value
Cohen's drm
Calculate Cohen's dz from t-statistic (Paired)
Description
Calculate Cohen's dz from t-statistic (Paired)
Usage
dz_from_t(t, n)
Arguments
t |
t-statistic |
n |
Sample size (number of pairs) |
Value
Cohen's dz
Identify and Filter EffectCheck Results
Description
Functions for filtering and identifying problematic results in effectcheck output. Identify problematic results
Usage
ec_identify(
x,
what = c("errors", "warnings", "decision_errors", "high_uncertainty", "insufficient",
"all_problems"),
...
)
Arguments
x |
An effectcheck object |
what |
Character vector specifying what to identify:
|
... |
Additional arguments (ignored) |
Details
Filters effectcheck results to show only problematic cases based on specified criteria.
Value
An effectcheck object containing only the identified results
Examples
results <- check_text("t(28) = 2.21, p = .035, d = 0.80")
errors <- ec_identify(results, "errors")
Configuration Management for EffectCheck
Description
Retrieves configuration values from environment variables, options, or defaults.
Logging Infrastructure for EffectCheck
Description
Provides structured logging capabilities with fallback to standard R messaging.
Export results to CSV
Description
Exports check results to CSV format with proper handling of special characters and NA values.
Usage
export_csv(res, out, na = "", row.names = FALSE)
Arguments
res |
tibble returned by check_text() / check_files() |
out |
output file path (csv) |
na |
string to use for NA values (default: "") |
row.names |
logical, include row names (default: FALSE) |
Value
Invisible path to the generated CSV file.
Examples
res <- check_text("t(28) = 2.21, p = .035, d = 0.80")
export_csv(res, out = tempfile(fileext = ".csv"))
Export results to JSON
Description
Exports check results to JSON format with structured metadata.
Usage
export_json(res, out, pretty = TRUE)
Arguments
res |
tibble returned by check_text() / check_files() |
out |
output file path (json) |
pretty |
logical, pretty-print JSON (default: TRUE) |
Value
Invisible path to the generated JSON file.
Examples
res <- check_text("t(28) = 2.21, p = .035, d = 0.80")
export_json(res, out = tempfile(fileext = ".json"))
Extract context window around a sentence
Description
Gets n sentences around a given sentence index for design inference.
Usage
extract_context(chunks, idx, window_size = 2, extended = FALSE)
Arguments
chunks |
Character vector of sentence chunks |
idx |
Index of current sentence |
window_size |
Number of sentences before/after to include (default 2) |
extended |
Logical, return extended context (default FALSE) |
Value
Character vector of context sentences
Comprehensive PDF text extraction with fallbacks
Description
Tries multiple methods: regular text extraction, table extraction, and OCR.
Usage
extract_pdf_comprehensive(
pdf_path,
try_tables = TRUE,
try_ocr = TRUE,
min_text_length = 100
)
Arguments
pdf_path |
Path to PDF file |
try_tables |
Logical, attempt table extraction if regular text fails (default TRUE) |
try_ocr |
Logical, attempt OCR if text extraction yields little content (default TRUE) |
min_text_length |
Minimum text length to consider extraction successful (default 100) |
Value
List with 'text' (main text), 'tables' (table text), 'ocr' (OCR text), 'method' (method used)
Examples
## Not run:
# Requires a PDF file and poppler-utils (pdftotext)
result <- extract_pdf_comprehensive("paper.pdf")
cat(result$text)
## End(Not run)
Extract text from PDF using OCR (for scanned PDFs)
Description
Extract text from PDF using OCR (for scanned PDFs)
Usage
extract_pdf_ocr(pdf_path, language = "eng")
Arguments
pdf_path |
Path to PDF file |
language |
OCR language (default "eng") |
Value
Character vector of OCR'd text
Extract tables from PDF
Description
Attempts to extract tables from PDF using tabulizer, then converts to text format that can be parsed for statistics.
Usage
extract_pdf_tables(pdf_path)
Arguments
pdf_path |
Path to PDF file |
Value
Character vector of table text (one string per table)
Extract text from PDF using pdftotext
Description
Uses the pdftotext command-line tool (from poppler-utils) which correctly handles two-column academic papers. pdftools is NOT used as a fallback because it interleaves columns, corrupting statistical expressions.
Usage
extract_pdf_text_robust(pdf_path, suppress_warnings = TRUE)
Arguments
pdf_path |
Path to PDF file |
suppress_warnings |
Logical, suppress PDF font warnings (default TRUE) |
Value
Character vector of extracted text
Filter results by effect size delta
Description
Filters effectcheck results by the magnitude of effect size discrepancy.
Usage
filter_by_delta(x, min_delta = 0, max_delta = Inf)
Arguments
x |
An effectcheck object |
min_delta |
Minimum absolute delta to include (default 0) |
max_delta |
Maximum absolute delta to include (default Inf) |
Value
An effectcheck object containing only results within the delta range
Examples
results <- check_text("t(28) = 2.21, p = .035, d = 0.80")
filter_by_delta(results, min_delta = 0.1)
Filter results by source file
Description
Filters effectcheck results to show only results from specific files.
Usage
filter_by_source(x, files, pattern = FALSE)
Arguments
x |
An effectcheck object |
files |
Character vector of file names or patterns to include |
pattern |
Logical, if TRUE treat files as regex patterns (default FALSE) |
Value
An effectcheck object containing only results from specified files
Examples
results <- check_text("t(28) = 2.21, p = .035, d = 0.80")
filter_by_source(results, "text_input")
Filter results by test type
Description
Filters effectcheck results to show only specific test types.
Usage
filter_by_test_type(x, types)
Arguments
x |
An effectcheck object |
types |
Character vector of test types to include (e.g., "t", "F", "r", "chisq", "z") |
Value
An effectcheck object containing only the specified test types
Examples
results <- check_text("t(28) = 2.21, p = .035. F(1, 50) = 4.03, p = .049")
filter_by_test_type(results, "t")
Filter results by uncertainty level
Description
Filters effectcheck results by uncertainty level.
Usage
filter_by_uncertainty(x, levels)
Arguments
x |
An effectcheck object |
levels |
Character vector of uncertainty levels to include ("low", "medium", "high") |
Value
An effectcheck object containing only the specified uncertainty levels
Examples
results <- check_text("t(28) = 2.21, p = .035, d = 0.80")
filter_by_uncertainty(results, "high")
Fisher's z-transformation CI for correlation
Description
Fisher's z-transformation CI for correlation
Usage
fisher_ci_r(r, n, level = 0.95)
Arguments
r |
Correlation coefficient |
n |
Sample size |
level |
Confidence level |
Value
Vector of bounds (lower, upper)
Format variants for display
Description
Creates a formatted string representation of variants for a row.
Usage
format_variants(x, row_index = 1, include_alternatives = TRUE)
Arguments
x |
An effectcheck object |
row_index |
The row index |
include_alternatives |
Whether to include alternative suggestions |
Value
A character string with formatted variant information
Examples
res <- check_text("t(28) = 2.21, p = .035, d = 0.80")
cat(format_variants(res, 1))
Calculate Hedges' g from t-statistic
Description
Calculate Hedges' g from t-statistic
Usage
g_ind_from_t(t, n1, n2)
Arguments
t |
t-statistic |
n1 |
Sample size 1 |
n2 |
Sample size 2 |
Value
Hedges' g
Generate a submission-ready EffectCheck report
Description
Creates a self-contained HTML report with executive summary, color-coded results table, expandable details, reproducible R code, and footer stamp.
Usage
generate_report(
res,
out,
format = "html",
title = "EffectCheck Report",
author = NULL,
source_name = NULL,
include_repro_code = TRUE,
style = "beginner"
)
Arguments
res |
tibble returned by check_text() / check_files() |
out |
output file path (html) |
format |
Output format: "html" (default) or "pdf" (requires rmarkdown) |
title |
Report title (default: "EffectCheck Report") |
author |
Author name (optional) |
source_name |
Source file name (optional) |
include_repro_code |
Logical, include reproducible R code section (default TRUE) |
style |
Report style: "beginner" for plain English narrative (default), "expert" for the traditional technical table format |
Value
Invisible path to the generated report file
Examples
res <- check_text("t(28) = 2.21, p = .035, d = 0.80")
generate_report(res, out = tempfile(fileext = ".html"))
Get alternative suggestions for a row
Description
Get alternative suggestions for a row
Usage
get_alternatives(x, row_index = 1)
Arguments
x |
An effectcheck object |
row_index |
The row index |
Value
A list of alternative effect size suggestions
Examples
res <- check_text("t(28) = 2.21, p = .035, d = 0.80")
get_alternatives(res, 1)
Get Configuration Value
Description
Prioritizes:
R Options (effectcheck.key)
Environment Variables (EFFECTCHECK_KEY)
Default value
Usage
get_config(key, default = NULL)
Arguments
key |
Configuration key (lowercase) |
default |
Default value if not found |
Value
Configuration value
Get decision errors from effectcheck results
Description
Extracts results where the significance decision would be reversed (i.e., reported as significant when computed is not, or vice versa).
Usage
get_decision_errors(x)
Arguments
x |
An effectcheck object |
Value
An effectcheck object containing only decision errors
Examples
results <- check_text("t(28) = 2.21, p = .035, d = 0.80")
get_decision_errors(results)
Get effect size family information
Description
Returns information about an effect size family and its variants.
Usage
get_effect_family(effect_type)
Arguments
effect_type |
The effect size type (e.g., "d", "eta2", "r") |
Value
A list with family, variants, alternatives, and description
Examples
get_effect_family("d")
Get errors from effectcheck results
Description
Convenience function to extract only ERROR status results.
Usage
get_errors(x)
Arguments
x |
An effectcheck object |
Value
An effectcheck object containing only errors
Examples
results <- check_text("t(28) = 2.21, p = .035, d = 0.80")
get_errors(results)
Find Non-Centrality Parameter (NCP) Confidence Limits for F-distribution
Description
Uses uniroot to invert the non-central F CDF.
Usage
get_ncp_F(F_val, df1, df2, level = 0.95)
Arguments
F_val |
Observed F statistic |
df1 |
Numerator degrees of freedom |
df2 |
Denominator degrees of freedom |
level |
Confidence level (default 0.95) |
Value
Vector c(lambda_low, lambda_high)
Get same-type variants for a row
Description
Get same-type variants for a row
Usage
get_same_type_variants(x, row_index = 1)
Arguments
x |
An effectcheck object |
row_index |
The row index |
Value
A list of same-type variants with their values and metadata
Examples
res <- check_text("t(28) = 2.21, p = .035, d = 0.80")
get_same_type_variants(res, 1)
Get Tolerance Config
Description
Helper to get tolerances, falling back to constants.
Usage
get_tolerance(type = c("effect", "ci", "p"))
Arguments
type |
Type of tolerance ("effect", "ci", "p") |
Value
Named list of tolerance thresholds for the specified type.
Get variant metadata
Description
Returns metadata for a specific effect size variant type.
Usage
get_variant_metadata(variant_name)
Arguments
variant_name |
The name of the variant (e.g., "d_ind", "dz", "eta2") |
Value
A list with name, assumptions, when_to_use, and formula
Examples
get_variant_metadata("d_ind")
Get all variants for a specific row
Description
Extracts and parses the all_variants JSON structure for a given row.
Usage
get_variants(x, row_index = 1)
Arguments
x |
An effectcheck object |
row_index |
The row index to extract variants from |
Value
A list with same_type and alternatives sublists
Examples
res <- check_text("t(28) = 2.21, p = .035, d = 0.80")
get_variants(res, 1)
Get warnings from effectcheck results
Description
Convenience function to extract only WARN status results.
Usage
get_warnings(x)
Arguments
x |
An effectcheck object |
Value
An effectcheck object containing only warnings
Examples
results <- check_text("t(28) = 2.21, p = .035, d = 0.80")
get_warnings(results)
Calculate Hedges' J correction factor
Description
Calculate Hedges' J correction factor
Usage
hedges_J(df)
Arguments
df |
Degrees of freedom |
Value
Correction factor
Initialize Logger
Description
Sets up the logging configuration.
Usage
init_logger(
level = c("DEBUG", "INFO", "WARN", "ERROR"),
file = NULL,
console = TRUE
)
Arguments
level |
Logging level (default "INFO") |
file |
Optional file path to log to |
console |
Logical, whether to log to console (default TRUE) |
Value
Invisible NULL. Called for its side effect of configuring the logger.
Test if object is an effectcheck object
Description
Test if object is an effectcheck object
Usage
is.effectcheck(x)
Arguments
x |
Object to test |
Value
Logical
Examples
res <- check_text("t(28) = 2.21, p = .035, d = 0.80")
is.effectcheck(res)
Log Error Message
Description
Log Error Message
Usage
log_error(msg, ...)
Arguments
msg |
Message string |
... |
variables for interpolation |
Value
Invisible NULL. Called for its side effect of logging.
Log Information Message
Description
Log Information Message
Usage
log_info(msg, ...)
Arguments
msg |
Message string (supports glue-style interpolation) |
... |
variables for interpolation |
Value
Invisible NULL. Called for its side effect of logging.
Match effectcheck and statcheck results
Description
Uses fuzzy matching on test_type and stat_value to pair results from both tools.
Usage
match_results(ec, sc)
Arguments
ec |
effectcheck results tibble |
sc |
statcheck results data.frame (or NULL) |
Value
Merged tibble with source column
Create an effectcheck object
Description
Wraps a tibble of results with the effectcheck S3 class and metadata.
Usage
new_effectcheck(x, call = NULL, settings = list())
Arguments
x |
A tibble of check results |
call |
The original function call (for reproducibility) |
settings |
List of settings used for the check |
Value
An effectcheck S3 object
Normalize text for parsing
Description
Comprehensive normalization pipeline handling Unicode, decimals, whitespace, and CI delimiters. Designed to handle PDF extraction artifacts and locale variations.
Usage
normalize_text(x)
Arguments
x |
Character vector to normalize |
Value
Normalized character vector
Convert string to numeric with warning suppression
Description
Convert string to numeric with warning suppression
Usage
numify(x)
Arguments
x |
String or vector |
Value
Numeric value(s)
Convert string to integer, stripping thousands-separator commas
Description
Used ONLY for sample size values (N, n1, n2) where commas are always thousands separators, never decimal commas.
Usage
numify_int(x)
Arguments
x |
String or vector |
Value
Integer value(s)
Parse APA-style stats and effects from text
Description
Extracts test statistics, effect sizes, confidence intervals, and sample sizes from APA-style text. Includes context window extraction for design inference.
Usage
parse_text(text, context_window_size = 2)
Arguments
text |
Character vector of text to parse |
context_window_size |
Number of sentences before/after to capture (default 2) |
Value
Tibble with parsed elements including context windows
Examples
parsed <- parse_text("t(28) = 2.21, p = .035, d = 0.80")
parsed$test_type
parsed$stat_value
Calculate phi coefficient from Chi-square
Description
Calculate phi coefficient from Chi-square
Usage
phi_from_chisq(chisq, N)
Arguments
chisq |
Chi-square statistic |
N |
Total sample size |
Value
Phi coefficient
Plot method for effectcheck objects
Description
Creates visualizations of effectcheck results.
Usage
## S3 method for class 'effectcheck'
plot(x, type = c("status", "uncertainty", "test_type", "delta", "all"), ...)
Arguments
x |
An effectcheck object |
type |
Type of plot: "status", "uncertainty", "test_type", "delta", or "all" |
... |
Additional arguments passed to plotting functions |
Value
Invisibly returns x.
Examples
res <- check_text("t(28) = 2.21, p = .035, d = 0.80")
plot(res, type = "status")
Plot effect size delta distribution
Description
Plot effect size delta distribution
Usage
plot_delta(x)
Plot status distribution
Description
Plot status distribution
Usage
plot_status(x)
Plot test type distribution
Description
Plot test type distribution
Usage
plot_test_type(x)
Plot uncertainty distribution
Description
Plot uncertainty distribution
Usage
plot_uncertainty(x)
Print method for effectcheck objects
Description
Displays a formatted summary of effectcheck results.
Usage
## S3 method for class 'effectcheck'
print(x, short = TRUE, n = 10, ...)
Arguments
x |
An effectcheck object |
short |
Logical, if TRUE show abbreviated output (default TRUE) |
n |
Maximum number of rows to display (default 10) |
... |
Additional arguments (ignored) |
Value
Invisibly returns x.
Examples
res <- check_text("t(28) = 2.21, p = .035, d = 0.80")
print(res)
Print method for effectcheck comparison
Description
Print method for effectcheck comparison
Usage
## S3 method for class 'effectcheck_comparison'
print(x, ...)
Arguments
x |
An effectcheck_comparison object |
... |
Additional arguments (ignored) |
Value
Invisibly returns x.
Examples
comp <- compare_with_statcheck("t(28) = 2.21, p = .035, d = 0.80")
print(comp)
Print method for summary.effectcheck objects
Description
Print method for summary.effectcheck objects
Usage
## S3 method for class 'summary.effectcheck'
print(x, ...)
Arguments
x |
A summary.effectcheck object |
... |
Additional arguments (ignored) |
Value
Invisibly returns x.
Examples
res <- check_text("t(28) = 2.21, p = .035, d = 0.80")
s <- summary(res)
print(s)
Internal helper to process a list of files
Description
Internal helper to process a list of files
Usage
process_files_internal(
files,
read_args = list(),
check_args = list(),
messages = TRUE
)
Arguments
files |
Character vector of file paths to process |
read_args |
List of arguments for read_any_text() |
check_args |
List of arguments for check_text() |
messages |
Logical, show progress messages (default TRUE) |
Value
An effectcheck object with results from all files
Calculate correlation r from t-statistic
Description
Calculate correlation r from t-statistic
Usage
r_from_t(t, df)
Arguments
t |
t-statistic |
df |
Degrees of freedom |
Value
Correlation r
Combine effectcheck objects
Description
Combine effectcheck objects
Usage
## S3 method for class 'effectcheck'
rbind(...)
Arguments
... |
effectcheck objects to combine |
Value
Combined effectcheck object
Examples
res1 <- check_text("t(28) = 2.21, p = .035")
res2 <- check_text("F(1, 50) = 4.03, p = .049")
combined <- rbind(res1, res2)
Read text from .docx, .html, .txt, or .pdf
Description
Read text from .docx, .html, .txt, or .pdf
Usage
read_any_text(path, try_tables = TRUE, try_ocr = FALSE)
Arguments
path |
File path |
try_tables |
Logical, attempt table extraction from PDFs (default TRUE) |
try_ocr |
Logical, attempt OCR for scanned PDFs (default FALSE) |
Value
character vector of full text
Examples
tmp <- tempfile(fileext = ".txt")
writeLines("t(28) = 2.21, p = .035, d = 0.80", tmp)
text <- read_any_text(tmp)
unlink(tmp)
Render an enhanced HTML report
Description
Creates an HTML report with summary statistics, expandable sections, and uncertainty visualization.
Usage
render_report(res, out)
Arguments
res |
tibble returned by check_text() / check_files() |
out |
output file path (html) |
Value
Invisible path to the generated HTML report file.
Examples
res <- check_text("t(28) = 2.21, p = .035, d = 0.80")
render_report(res, out = tempfile(fileext = ".html"))
Render report as PDF via rmarkdown
Description
Falls back to HTML if rmarkdown is not available.
Usage
render_report_pdf(
res,
out,
title = "EffectCheck Report",
author = NULL,
source_name = NULL,
include_repro_code = TRUE
)
Arguments
res |
Results tibble |
out |
Output file path |
title |
Report title |
author |
Author name |
source_name |
Source file name |
include_repro_code |
Include reproducible code |
Value
Invisible path to generated file
Safe Stop
Description
Stops execution with a sanitized error message in production, or full details in development.
Usage
safe_stop(msg, public_msg = "An error occurred during processing.")
Arguments
msg |
Internal detailed error message |
public_msg |
Optional public-facing message (default: generic error) |
Value
Does not return; always calls stop().
Summary method for effectcheck objects
Description
Provides comprehensive summary statistics for effectcheck results.
Usage
## S3 method for class 'effectcheck'
summary(object, ...)
Arguments
object |
An effectcheck object |
... |
Additional arguments (ignored) |
Value
A list of class "summary.effectcheck" containing summary statistics
Examples
res <- check_text("t(28) = 2.21, p = .035, d = 0.80")
summary(res)
Verify adjusted R-squared consistency
Description
Verify adjusted R-squared consistency
Usage
verify_adj_R2(R2, adj_R2_reported, n, p, tol = 0.01)
Arguments
R2 |
R-squared value |
adj_R2_reported |
Reported adjusted R-squared |
n |
Sample size |
p |
Number of predictors |
tol |
Tolerance (default 0.01) |
Value
List with computed, delta, consistent
Verify t-statistic from regression coefficient and SE
Description
Checks if t = b/SE is consistent with the reported t-value.
Usage
verify_t_from_b_SE(b, SE, reported_t, tol = 0.01)
Arguments
b |
Regression coefficient |
SE |
Standard error of b |
reported_t |
Reported t-value |
tol |
Tolerance for matching (default 0.01) |
Value
List with computed_t, delta, and consistent (logical)