subsetting: Subsetting methods

In causalGel: Causal Inference using Generalized Empirical Likelihood Methods

Description

Different subsetting methods for S4 class objects of the package. The subset method returns an new object with observations selected by the second argument. See example.

Methods

signature(x = "causalModel", i = "missing", j = "numericORlogical")

Subsets observations.

signature(x = "causalModel", i = "numeric", j = "missing")

Selects balancing covatriates.

signature(x = "causalModel", i = "numeric", j = "numericORlogical")

Selects balancing covariates and observations.

signature(x = "rcausalModel", i = "missing", j = "numericORlogical")

Subsets observations for restricted models.

signature(x = "rcausalModel", i = "numeric", j = "missing")

Selects balancing covatriates for restricted models.

signature(x = "rcausalModel", i = "numeric", j = "numericORlogical")

Selects balancing covariates and observations for restricted models.

signature(x = "causalGelfit", i = "missing", j = "numericORlogical")

Subsets observations and refit the model.

signature(x = "causalGelfit", i = "numeric", j = "missing")

Selects balancing covatriates and refit the model.

signature(x = "causalGelfit", i = "numeric", j = "numericORlogical")

Selects balancing covariates and observations and refit the model.

Examples

data(nsw)

balm <- ~age+ed+black+hisp:married+nodeg+re75+I(re75^2)
g <- re78~treat
         
model <- causalModel(g, balm, nsw)           
model[1:5, 1:500]

fit <-  gelFit(model, gelType="EL")
fit[1:5,1:500]

causalGel documentation built on Feb. 10, 2021, 3:01 a.m.