Package: sensemakr 0.1.6

sensemakr: Sensitivity Analysis Tools for Regression Models

Implements a suite of sensitivity analysis tools that extends the traditional omitted variable bias framework and makes it easier to understand the impact of omitted variables in regression models, as discussed in Cinelli, C. and Hazlett, C. (2020), "Making Sense of Sensitivity: Extending Omitted Variable Bias." Journal of the Royal Statistical Society, Series B (Statistical Methodology) <doi:10.1111/rssb.12348>.

Authors:Carlos Cinelli [aut, cre], Jeremy Ferwerda [aut], Chad Hazlett [aut], Danielle Tsao [ctb], Aaron Rudkin [ctb], Grigorij Ljubownikow [ctb]

sensemakr_0.1.6.tar.gz
sensemakr_0.1.6.zip(r-4.7)sensemakr_0.1.6.zip(r-4.6)sensemakr_0.1.6.zip(r-4.5)
sensemakr_0.1.6.tgz(r-4.6-any)sensemakr_0.1.6.tgz(r-4.5-any)
sensemakr_0.1.6.tar.gz(r-4.7-any)sensemakr_0.1.6.tar.gz(r-4.6-any)
sensemakr_0.1.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
sensemakr/json (API)

# Install 'sensemakr' in R:
install.packages('sensemakr', repos = c('https://carloscinelli.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/carloscinelli/sensemakr/issues

Datasets:
  • colombia - Data from the 2016 referendum for peace with the FARC in Colombia.
  • darfur - Data from survey of Darfurian refugees in eastern Chad.

On CRAN:

Conda:

9.73 score 99 stars 4 packages 248 scripts 1.3k downloads 27 exports 0 dependencies

Last updated from:a5892aeb6e. Checks:7 ERROR, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64ERROR178
source / vignettesOK174
linux-release-x86_64ERROR199
macos-release-arm64ERROR271
macos-oldrel-arm64ERROR199
windows-develERROR218
windows-releaseERROR204
windows-oldrelERROR210
wasm-releaseOK98

Exports:add_bound_to_contouradjusted_ciadjusted_critical_valueadjusted_estimateadjusted_partial_r2adjusted_seadjusted_tbiasextreme_robustness_valuegroup_partial_r2model_helperovb_boundsovb_contour_plotovb_extreme_plotovb_minimal_reportingovb_partial_r2_boundpartial_fpartial_f2partial_r2rel_biasrelative_biasresid_makerrobustness_valuervsensemakrsensitivity_statsxrv

Dependencies:

The Risks of Informal Benchmarking
Introduction | Background | Simulating the data | Fitting the model | Informal benchmarks | Formal bounds | References
Rendered frominformal_benchmarking.Rmdusingknitr::rmarkdown

Last update: 2021-07-26
Started: 2020-02-09

An introduction to sensitivity analysis using sensemakr
Introduction | Violence in Darfur | The data and research question | The threat of unobserved confounders | Sensitivity Analysis | Minimal sensitivity reporting | Sensitivity contour plots of point estimates and t-values | Sensitivity plots of extreme scenarios | A disciplined discussion about confounding | Going further | References
Rendered fromsensemakr.Rmdusingknitr::rmarkdown

Last update: 2020-04-28
Started: 2017-08-23

Readme and manuals

Help Manual

Help pageTopics
Sensemakr: extending omitted variable biassensemakr-package
Add bounds to contour plot of omitted variable biasadd_bound_to_contour add_bound_to_contour.fixest add_bound_to_contour.lm add_bound_to_contour.numeric
Bias-adjusted critical valuesadjusted_critical_value
Bias-adjusted estimates, standard-errors, t-values and confidence intervalsadjusted_ci adjusted_ci.fixest adjusted_ci.lm adjusted_ci.numeric adjusted_estimate adjusted_estimate.fixest adjusted_estimate.lm adjusted_estimate.numeric adjusted_partial_r2 adjusted_partial_r2.fixest adjusted_partial_r2.lm adjusted_partial_r2.numeric adjusted_se adjusted_se.fixest adjusted_se.lm adjusted_se.numeric adjusted_t adjusted_t.fixest adjusted_t.lm adjusted_t.numeric bias bias.fixest bias.lm bias.numeric relative_bias relative_bias.fixest relative_bias.lm relative_bias.numeric rel_bias
Data from the 2016 referendum for peace with the FARC in Colombia.colombia
Data from survey of Darfurian refugees in eastern Chad.darfur
Partial R2 of groups of covariates in a linear regression modelgroup_partial_r2 group_partial_r2.fixest group_partial_r2.lm group_partial_r2.numeric
Bounds on the strength of unobserved confounders using observed covariatesovb_bounds ovb_bounds.fixest ovb_bounds.lm ovb_partial_r2_bound ovb_partial_r2_bound.fixest ovb_partial_r2_bound.lm ovb_partial_r2_bound.numeric
Contour plots of omitted variable biasovb_contour_plot ovb_contour_plot.fixest ovb_contour_plot.formula ovb_contour_plot.lm ovb_contour_plot.numeric
Extreme scenarios plots of omitted variable biasovb_extreme_plot ovb_extreme_plot.fixest ovb_extreme_plot.formula ovb_extreme_plot.lm ovb_extreme_plot.numeric
Computes the partial R2 and partial (Cohen's) f2partial_f partial_f.fixest partial_f.lm partial_f.numeric partial_f2 partial_f2.fixest partial_f2.lm partial_f2.numeric partial_r2 partial_r2.default partial_r2.fixest partial_r2.lm partial_r2.numeric
Sensitivity analysis plots for 'sensemakr'plot.sensemakr
Sensitivity analysis print and summary methods for 'sensemakr'ovb_minimal_reporting print.sensemakr summary.sensemakr
Computes the (extreme) robustness valueextreme_robustness_value extreme_robustness_value.default extreme_robustness_value.fixest extreme_robustness_value.lm extreme_robustness_value.numeric robustness_value robustness_value.default robustness_value.fixest robustness_value.lm robustness_value.numeric rv xrv
Sensitivity analysis to unobserved confounderssensemakr sensemakr.fixest sensemakr.formula sensemakr.lm sensemakr.numeric
Sensitivity statistics for regression coefficientssensitivity_stats sensitivity_stats.fixest sensitivity_stats.lm sensitivity_stats.numeric