Package: nbpInference 1.0.2

nbpInference: Inference on Average Treatment Effects for Continuous Treatments

Conduct inference on the sample average treatment effect for a matched (observational) dataset with a continuous treatment. Equipped with calipered non-bipartite matching, bias-corrected sample average treatment effect estimation, and covariate-adjusted variance estimation. Matching, estimation, and inference methods are described in Frazier, Heng and Zhou (2024) <doi:10.48550/arXiv.2409.11701>.

Authors:Anthony Frazier [aut, cre, cph], Siyu Heng [aut], Wen Zhou [aut]

nbpInference_1.0.2.tar.gz
nbpInference_1.0.2.zip(r-4.7)nbpInference_1.0.2.zip(r-4.6)nbpInference_1.0.2.zip(r-4.5)
nbpInference_1.0.2.tgz(r-4.6-any)nbpInference_1.0.2.tgz(r-4.5-any)
nbpInference_1.0.2.tar.gz(r-4.7-any)nbpInference_1.0.2.tar.gz(r-4.6-any)
nbpInference_1.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
nbpInference/json (API)
NEWS

# Install 'nbpInference' in R:

install.packages('nbpInference', repos = c('https://anthonyfraziercsu.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/anthonyfraziercsu/nbpinference/issues

On CRAN:

2.70 score 141 downloads 7 exports 59 dependencies

Last updated from:f1cb19186a. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	129
source / vignettes	OK	201
linux-release-x86_64	OK	130
macos-release-arm64	OK	271
macos-oldrel-arm64	OK	132
windows-devel	OK	79
windows-release	OK	85
windows-oldrel	OK	78
wasm-release	OK	136

Exports:bias.corrected.neyman classic.neyman covAdj.variance generate.data.dose generate.data.dose2 make.pmatrix nbp.caliper

Dependencies:backports base64enc bslib cachem checkmate cli cluster colorspace cpp11 data.table digest evaluate farver fastmap fontawesome foreign Formula fs ggplot2 glue gridExtra gtable highr Hmisc htmlTable htmltools htmlwidgets isoband jquerylib jsonlite knitr labeling lifecycle magrittr MASS memoise mime nbpMatching nnet R6 rappdirs rbibutils RColorBrewer Rdpack rlang rmarkdown rpart rstudioapi S7 sass scales stringi stringr tinytex vctrs viridisLite withr xfun yaml

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Bias-corrected Neyman Sample Average Treatment Effect Estimator	bias.corrected.neyman
Classic Neyman Sample Average Treatment Effect Estimator	classic.neyman
Covariate-Adjusted Variance Estimation	covAdj.variance
Generate example data with five covariates	generate.data.dose
Generate sample data with six covariates	generate.data.dose2
Make matrix of treatment assignment probabilities	make.pmatrix
non-bipartite matching with treatment assignment caliper	nbp.caliper