Function called by cov.sel if type="np". Not meant to be used on its own.
cov.sel.np(T, Y, X, alg, scope, thru, thro, thrc, dat, data.0,
data.1, covar, ...)Function returns subsets, methods and removed covariates. See cov.sel for details.
A vector, containing 0 and 1, indicating the binary treatment variable.
A vector of observed outcomes.
A matrix or data frame containing columns of covariates. The covariates may be a mix of continuous, unordered discrete
(to be specified in the data frame using factor), and ordered discrete (to be specified in the data frame using ordered).
Specifying which algorithm to be use. 1
indicates Algorithm A, 2 indicates Algorithm B and
3 runs them both. See Details. alg = 3 is default.
A character string giving the name of one (or several) covariate(s) that must not be removed.
Bandwidth threshold for unordered discrete covariates. Values in \([0,1]\) are valid. thru=0 removes all unordered discrete covariates and thru=1 removes none of them. Default is thru=0.5.
Bandwidth threshold for ordered discrete covariates. Values in \([0,1]\) are valid. thro=0 removes all unordered discrete covariates and thro=1 removes none of them. Default is thro=0.25.
Bandwidth threshold for continuous covariates. Non-negative values are valid. Default is thr=100.
Passed on from cov.sel
Passed on from cov.sel
Passed on from cov.sel
Passed on from cov.sel
Additional arguments passed on to npregbw. regtype can be set to "lc" or "ll", the first being default and bwtype can be set to "fixed", "generalized_nn" or "adaptive_nn", defaults to "fixed".
Jenny Häggström, <jenny.haggstrom@umu.se>
See cov.sel for details.
de Luna, X., I. Waernbaum, and T. S. Richardson (2011). Covariate selection for the nonparametric estimation of an average treatment effect. Biometrika 98. 861-875
Häggström, J., E. Persson, I. Waernbaum and X. de Luna (2015). An R Package for Covariate Selection When Estimating Average Causal Effects. Journal of Statistical Software 68. 1-20
Hall, P., Q. Li and J.S. Racine (2007). Nonparametric estimation of regression functions in the presence of irrelevant regressors. The Review of Economics and Statistics, 89. 784-789
np