Create Phantom Variables in Structural Equation Models for Sensitivity Analyses
Overview
Create phantom variables, which are variables that were not observed, for the purpose of sensitivity analyses for structural equation models. The package makes it easier for a user to test different combinations of covariances between the phantom variable(s) and observed variables. The package may be used to assess a model's or effect's sensitivity to temporal bias (e.g., if cross-sectional data were collected) or confounding bias.
- Added a
NEWS.mdfile to track changes to the package. - Updated lavaan compatibility for correlation-to-covariance conversion (prefers lav_cor2cov() when available).
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-07
- OK14 OK2026-03-10
Documentation
- Help pages
- 7 (2 internal)includes a package overview page
- Examples that run
- 100%5 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
- phantSEM HTML
Downloads
Dependencies
Code & Tests
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- 1.0.1Latest
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 1.0.0.02023-09-07
- RR 4.3.0 released · 2023-04-21
Package metadata
- First published
- 2023-09-07
- Total releases
- 2 / 3 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.5.1
- Download size
- 3.5 MB
Cite
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Run in R for the authors' preferred citation:
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