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phantSEM  

Create Phantom Variables in Structural Equation Models for Sensitivity Analyses
View on CRAN: Click here


Download and install phantSEM package within the R console
Install from CRAN:
install.packages("phantSEM")

Install from Github:
library("remotes")
install_github("cran/phantSEM")

Install by package version:
library("remotes")
install_version("phantSEM", "1.0.0.0")



Attach the package and use:
library("phantSEM")
Maintained by
Alexis Georgeson
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-09-07
Latest Update: 2023-09-07
Description:
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.
How to cite:
Alexis Georgeson (2023). phantSEM: Create Phantom Variables in Structural Equation Models for Sensitivity Analyses. R package version 1.0.0.0, https://cran.r-project.org/web/packages/phantSEM. Accessed 22 Dec. 2024.
Previous versions and publish date:
No previous versions
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Complete documentation for phantSEM
Functions, R codes and Examples using the phantSEM R package
Some associated functions: SA_lookup . SA_step1 . SA_step2 . SA_step3 . ghost_par_ests . phantSEM-package . 
Some associated R codes: SA_lookup.R . SA_step1.R . SA_step2.R . SA_step3.R . ghost_par_ests.R . phantSEM-package.R .  Full phantSEM package functions and examples
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