autoFC: Automatic Toolkit for Construction, Optimization, Scoring and
Simulation of Forced-Choice Tests
Forced-choice (FC) response has gained increasing popularity
and interest for its resistance to faking when well-designed (Cao &
Drasgow, 2019 <doi:10.1037/apl0000414>). To established well-designed
FC scales, typically each item within a block should measure different
trait and have similar level of social desirability (Zhang et al.,
2020 <doi:10.1177/1094428119836486>). Recent study also suggests the
importance of high inter-item agreement of social desirability between
items within a block (Pavlov et al., 2021
<doi:10.31234/osf.io/hmnrc>). In addition to this, FC developers may
also need to maximize factor loading differences (Brown &
Maydeu-Olivares, 2011 <doi:10.1177/0013164410375112>) or minimize item
location differences (Cao & Drasgow, 2019 <doi:10.1037/apl0000414>)
depending on scoring models. Decision of which items should be
assigned to the same block, also called as item pairing, is thus critical
to the quality of an FC test. Because such pairing process often requires
researchers to meet multiple objectives, manual pairing becomes impractical
or even not feasible once the number of latent traits and/or number of items
per elevates. To address these problems, autoFC is developed as a
automatic and efficient tool for facilitating the automatic construction of
FC tests (Li et al., 2022 <doi:10.1177/01466216211051726>), essentially
exempting users from the burden of manual item pairing.
Given characteristics of each item (and item responses), FC measures
can be constructed either automatically based on user-defined pairing
criteria and weights, or based on exact specifications of each block
(i.e., blueprint; see Li et al., 2025
<doi:10.1177/10944281241229784>). Users can also generate simulated
responses based on the Thurstonian Item Response Theory model (Brown &
Maydeu-Olivares, 2011 <doi:10.1177/0013164410375112>) and predict
trait scores of simulated/actual respondents based on an estimated
model.
| Version: |
1.0.0.1000 |
| Depends: |
R (≥ 3.5) |
| Imports: |
lavaan, MASS, MplusAutomation, pbapply, rstan, stats |
| Suggests: |
knitr, rmarkdown, cmdstanr |
| Published: |
2026-05-27 |
| DOI: |
10.32614/CRAN.package.autoFC |
| Author: |
Mengtong Li  [cre,
aut],
Tianjun Sun [aut],
Bo Zhang [aut] |
| Maintainer: |
Mengtong Li <mt_li at fudan.edu.cn> |
| License: |
GPL (≥ 3) |
| NeedsCompilation: |
no |
| Additional_repositories: |
https://stan-dev.r-universe.dev |
| Materials: |
README |
| CRAN checks: |
autoFC results |
Documentation:
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