Package: causaldrf 0.4.2

Douglas Galagate

causaldrf: Estimating Causal Dose Response Functions

Functions and data to estimate causal dose response functions given continuous, ordinal, or binary treatments. A description of the methods is given in Galagate (2016) <https://drum.lib.umd.edu/handle/1903/18170>.

Authors:Douglas Galagate [cre], Joseph Schafer [aut]

causaldrf_0.4.2.tar.gz
causaldrf_0.4.2.tar.gz(r-4.5-noble)causaldrf_0.4.2.tar.gz(r-4.4-noble)
causaldrf_0.4.2.tgz(r-4.4-emscripten)causaldrf_0.4.2.tgz(r-4.3-emscripten)
causaldrf.pdf |causaldrf.html✨
causaldrf/json (API)

# Install 'causaldrf' in R:

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

Datasets:

hi_sim_data - Simulated data from Hirano and Imbens
nmes_data - Data set containing data from the National Medical Expenditure Survey
sim_data - Simulated data from Schafer and Galagate

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.16 score 4 stars 36 scripts 240 downloads 16 exports 12 dependencies

Last updated 2 years agofrom:cb67aca60b. Checks:OK: 2. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 01 2024
R-4.5-linux	OK	Nov 01 2024

Exports:add_spl_est aipwee_est bart_est gam_est get_ci hi_est iptw_est ismw_est iw_est nw_est overlap_fun prop_spline_est reg_est scalar_wts t_mod wtrg_est

Dependencies:DBI lattice Matrix mgcv minqa mitools nlme numDeriv Rcpp RcppArmadillo survey survival

Using causaldrf

Rendered fromUsing_causaldrf.Rnwusingknitr::knitron Nov 01 2024.

Last update: 2022-09-29
Started: 2015-11-30

Citation

Readme and manuals

Help Manual

Help page	Topics
The additive spline estimator	add_spl_est
Prediction with a residual bias correction estimator	aipwee_est
The BART estimator	bart_est
The GAM estimator	gam_est
This calculates an upper and lower bound from bootstrap matrix	get_ci
The Hirano and Imbens estimator	hi_est
Simulated data from Hirano and Imbens (2004)	hi_sim_data
The inverse probability of treatment weighting (iptw) estimator	iptw_est
The inverse second moment weighting (ismw) estimator	ismw_est
The inverse weighting estimator (nonparametric method)	iw_est
Data set containing data from the National Medical Expenditure Survey (NMES)	nmes_data
The Nadaraya-Watson modified estimator	nw_est
This function creates an overlapping dataset	overlap_fun
The propensity-spline prediction estimator	prop_spline_est
The regression prediction estimator	reg_est
This function calculates scalar weights for use in other models	scalar_wts
Simulated data from Schafer and Galagate (2015)	sim_data
A function to estimate conditional expected values and higher order moments	t_mod
The weighted regression estimator	wtrg_est