R Observatory: Metrics for ItemRest version 1.0.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

ItemRest

1.0.0Package record

Automated Item Removal Strategies for Exploratory Factor Analysis

1packages depend

3.6Kdownloads / year

92.8%test coverage

13/13flavors OK

Overview

About

Maintained by Ahmet ÇalışkanCRAN page ↗GitHub ↗Issues ↗

Identifies candidate item sets through threshold-driven iterative removal searches in exploratory factor analysis. Provides a no-removal baseline, numerical diagnostics, factor reliability, holdout evaluation, and bootstrap search stability to support transparent screening and documented content review rather than automatic measurement decisions. The loading criteria are based on best practices and established heuristics (e.g., Costello & Osborne (2005) doi:10.7275/jyj1-4868, Howard (2016) doi:10.1080/10447318.2015.1087664). Includes flexible thresholds for factor loadings (min_loading) and cross-loading differences (loading_diff).

Changes in 1.0.0

Record informational estimator messages without disqualifying candidates. Silently preload GPArotation for rotations and restrict message-driven review to explicit convergence, rotation, variance, and matrix-repair problems.
Scope validation correlations to requested item sets and isolate constant-item failures. Suppress diagnostic variable tables printed on correlation errors.
Record source correlation warnings/messages once per analysis, rather than attributing them to every subset. Detect identical validation response values after row reordering; retain order-sensitive bootstrap input checks.
Label unassessed whole-set alpha as Not_assessed and remove unused combination generation, sorting helpers, and the obsolete internal combs argument.
Validate extraction and rotation names before analysis, canonicalize supported capitalization, and declare the default rotation's GPArotation dependency. Record estimator messages and flag reported nonconvergence.

Show all changes in 1.0.0Hide the rest of the changes in 1.0.0

Label Howard primary loadings below .40 as low loadings, and match holdout factors and signs using linear assignment rather than factorial enumeration. Add Min_Congruence and scaled CFA fit indices.
Fingerprint numeric values and item names independently of row names and integer/double storage. Explain that protected flagged items can prevent candidate solutions and that unknown convergence remains Not_reported.
Keep fa parallel analysis as default and add parallel_method = "pc". Ordinal reference samples preserve observed category margins and missing positions and use the same mixed/polychoric correlation estimator as the observed data. Add configurable ordinal_categories, excluding NA from category counts.
Add bootstrap frequencies across all attempts as a conservative sensitivity summary, predraw replicate rows and seeds, and provide a progress bar.
Label whole-set alpha as descriptive in multifactor models; factor-specific reliability remains available. Store compact EFA results by default, with store_fits = TRUE for full psych fit objects.
Compute the original correlation matrix and pairwise observation counts once per dataset and reuse submatrices in parallel analysis and removal searches. Check positive definiteness and apply requested smoothing per retained set. Validation EFA uses its own matrix; each bootstrap replicate uses a new matrix. Expose correlation_matrix and pairwise_n in discovery results.
Replace the single optimal_strategy field with all screened candidate_solutions. Candidate reporting is the default; report = "optimal" is a deprecated alias.
Reassess remaining items after removal, cache identical item sets, retain the no-removal baseline, and label bounded searches as incomplete.
Add numerical admissibility, correlation positive-definiteness and explicit smoothing, convergence status, factor correlations, factor support, warnings, and branch-specific failure records. Unidentified subsets are skipped.
Add explicit missing-data handling, effective pair counts, parameter checks, protected items, content notes, and scoring keys.
Default ordering is discovery order; optional removal-count/variance ordering never selects a winner. Oblique explained variance uses mean model communality.
Add factor-level alpha and model omega total, with separate raw, standardized, and selected-correlation alpha labels. Preserve signed loading ranges and add absolute ranges. Capture Howard failures below the secondary .30 threshold.
Add holdout EFA, optional lavaan CFA, disjoint sample splitting, and bootstrap stability of the entire search with explicit failure/incompleteness denominators.
Add DDMMYYYY date-based default seeds (e.g. label 05102026 / seed 5102026), caller RNG restoration, configurable parallel-analysis replications, and recorded settings and software provenance.
Provide a reproducible simulated vignette and complete executable workflow.
Restore "Let algorithms be your compass, not your captain." as the final line of every printed analysis summary.

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("ItemRest", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("ahmetcaliskan1987/ItemRest")

Development version from ahmetcaliskan1987/ItemRest. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-itemrest

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-ItemRest

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-ItemRest

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 3.7 min · r-release-macos-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-06-09
ERROR12 OK, 1 ERROR2026-06-08
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 1.0.0

READMEYes · 1,102 wordsVignettesYes · 1 · dynamicNEWSYes · 100% structured · mentions 1.0.0Citation fileNoWebsitenot declared in DESCRIPTION

Help pages: 12 (7 internal)
Examples that run: 50%1 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples: 50%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 0%

Vignettes (1)

Candidate Item Sets, Diagnostics, and Independent Evaluation HTML

How these are measured

Downloads

3.6K

CRAN downloads in the past year

Rank #8,950 · ~10/day · ~303/mo

Releases R versions

Daily download trend is not available in this view yet.

45130 days

1K90 days

3.6K1 year

Compare downloads with other packages →

Also on86 r2u8 autocran

How downloads are counted

Repository

ahmetcaliskan1987/itemrest ↗Account: ahmetcaliskan1987

0Stars

0Forks

0Open issues

0Open PRs

0Releases

efafactor-analysisitem-analysisrr-packageitem-removal

Last activity 2026-10-06

Responsiveness

not measured

How these are measured

PracticesBeta

5 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/ahmetcaliskan1987/itemrest on 2026-10-11.

Continuous integration (1)

GitHub Actions

Docs source (1)

README.Rmd

CRAN release process (2)

cran-comments.mdCRAN-SUBMISSION

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies

9 external dependencies (excludes base and recommended)

Installing ItemRest adds 73 packages (40 with compiled code, 65 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.

Depends (1)

R >= 4.1

Imports (8)

clue GPArotation gtools psych qgraphstatstoolsutils

LinkingTo (0)

none

Suggests (4)

testthat knitr rmarkdown lavaan

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

1direct

0indirect

Imports 1

Depends, Imports or LinkingTo, most downloaded first

FAfA

How these are counted

Code & Tests

People & History

People (2)

Ahmet Çalışkan

Author, Maintainer since 0.2.3 (2025)

Abdullah Faruk Kılıç

Author

Releases (4)

Pick two releases to compare their code metrics.

1.0.0Latest
record
2026-10-05 · current release · diff ↗ ·
added 3 exports
itemrest_bootstrap, itemrest_split, itemrest_validate
R
R 4.6.0 released · 2026-04-24
0.2.5
record
2026-04-14 · diff ↗
0.2.4
record
2026-04-13 · diff ↗
0.2.3
record
2025-10-09
R
R 4.5.0 released · 2025-04-11

Package metadata

First published: 2025-10-09
Total releases: 4 / 1 yrs
License: MIT + file LICENSE OSI
Minimum R: ≥ 4.1
Download size: 54 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("ItemRest")

Format

Çalışkan, A., & Kılıç, A. F. (2026). ItemRest: Automated Item Removal Strategies for Exploratory Factor Analysis (Version 1.0.0) [Computer software]. https://doi.org/10.32614/CRAN.package.ItemRest

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for ItemRest version 1.0.0 [Data set]. HJJB, LLC. Data release v2026-10-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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