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Report R environment (packages, system, etc.)

Usage

# S3 method for sessionInfo
report(x, ...)

report_packages(session = NULL, include_R = TRUE, ...)

cite_packages(session = NULL, include_R = TRUE, ...)

report_system(session = NULL)

Arguments

x

The R object that you want to report (see list of of supported objects above).

...

Arguments passed to or from other methods.

session

A sessionInfo object.

include_R

Include R in the citations.

Value

For report_packages, a data frame of class with information on package name, version and citation.

An object of class report().

Examples


library(report)

session <- sessionInfo()

r <- report(session)
r
#> Analyses were conducted using the R Statistical language (version 4.2.0; R Core Team, 2022) on Ubuntu 20.04.4 LTS, using the packages performance (version 0.9.1; Lüdecke et al., 2021), bayestestR (version 0.12.1; Makowski et al., 2019), report (version 0.5.1.2; Makowski et al., 2020), lavaan (version 0.6.12; Yves Rosseel, 2012), Matrix (version 1.4.1; NA), dplyr (version 1.0.9; NA) and lme4 (version 1.1.29; NA).
#> 
#> References
#> ----------
#>   - Lüdecke et al., (2021). performance: An R Package for Assessment, Comparison and Testing of Statistical Models. Journal of Open Source Software, 6(60), 3139. https://doi.org/10.21105/joss.03139
#>   - Makowski, D., Ben-Shachar, M., & Lüdecke, D. (2019). bayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Framework. Journal of Open Source Software, 4(40), 1541. doi:10.21105/joss.01541
#>   - Makowski, D., Ben-Shachar, M.S., Patil, I. & Lüdecke, D. (2020). Automated Results Reporting as a Practical Tool to Improve Reproducibility and Methodological Best Practices Adoption. CRAN. Available from https://github.com/easystats/report. doi: .
#>   - R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
#>   - Yves Rosseel (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36. https://doi.org/10.18637/jss.v048.i02
#>   - NA
#>   - NA
#>   - NA
summary(r)
#> The analysis was done using the R Statistical language (v4.2.0; R Core Team, 2022) on Ubuntu 20.04.4 LTS, using the packages performance (v0.9.1), bayestestR (v0.12.1), report (v0.5.1.2), lavaan (v0.6.12), Matrix (v1.4.1), dplyr (v1.0.9) and lme4 (v1.1.29).
as.data.frame(r)
#> Package     | Version |                                                                                                                                                                                                                                                Reference
#> --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
#> Matrix      |   1.4.1 |                                                                                                                                                                                                                                                         
#> R           |   4.2.0 |                                                                                    R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
#> bayestestR  |  0.12.1 |               Makowski, D., Ben-Shachar, M., & Lüdecke, D. (2019). bayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Framework. Journal of Open Source Software, 4(40), 1541. doi:10.21105/joss.01541
#> dplyr       |   1.0.9 |                                                                                                                                                                                                                                                         
#> lavaan      |  0.6.12 |                                                                                          Yves Rosseel (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36. https://doi.org/10.18637/jss.v048.i02
#> lme4        |  1.1.29 |                                                                                                                                                                                                                                                         
#> performance |   0.9.1 |                                                        Lüdecke et al., (2021). performance: An R Package for Assessment, Comparison and Testing of Statistical Models. Journal of Open Source Software, 6(60), 3139. https://doi.org/10.21105/joss.03139
#> report      | 0.5.1.2 | Makowski, D., Ben-Shachar, M.S., Patil, I. & Lüdecke, D. (2020). Automated Results Reporting as a Practical Tool to Improve Reproducibility and Methodological Best Practices Adoption. CRAN. Available from https://github.com/easystats/report. doi: .
summary(as.data.frame(r))
#> Package     | Version
#> ---------------------
#> Matrix      |   1.4.1
#> R           |   4.2.0
#> bayestestR  |  0.12.1
#> dplyr       |   1.0.9
#> lavaan      |  0.6.12
#> lme4        |  1.1.29
#> performance |   0.9.1
#> report      | 0.5.1.2

# Convenience functions
report_packages(include_R = FALSE)
#>   - performance (version 0.9.1; Lüdecke et al., 2021)
#>   - bayestestR (version 0.12.1; Makowski et al., 2019)
#>   - report (version 0.5.1.2; Makowski et al., 2020)
#>   - lavaan (version 0.6.12; Yves Rosseel, 2012)
#>   - Matrix (version 1.4.1; NA)
#>   - dplyr (version 1.0.9; NA)
#>   - lme4 (version 1.1.29; NA)
cite_packages(prefix = "> ")
#> > Lüdecke et al., (2021). performance: An R Package for Assessment, Comparison and Testing of Statistical Models. Journal of Open Source Software, 6(60), 3139. https://doi.org/10.21105/joss.03139
#> > Makowski, D., Ben-Shachar, M., & Lüdecke, D. (2019). bayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Framework. Journal of Open Source Software, 4(40), 1541. doi:10.21105/joss.01541
#> > Makowski, D., Ben-Shachar, M.S., Patil, I. & Lüdecke, D. (2020). Automated Results Reporting as a Practical Tool to Improve Reproducibility and Methodological Best Practices Adoption. CRAN. Available from https://github.com/easystats/report. doi: .
#> > R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
#> > Yves Rosseel (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36. https://doi.org/10.18637/jss.v048.i02
#> > NA
#> > NA
#> > NA
report_system()
#> Analyses were conducted using the R Statistical language (version 4.2.0; R Core Team, 2022) on Ubuntu 20.04.4 LTS