makeTargetGrids: Makes a dataframe "grid" of estimands to estimate

In BarkleyBG/stabilizedinterference: Stabilized IPW Estimators for Causal Effects with Partial Interference

Description

This function can be called prior to and then passed into estimateEffects informally by specifying target_grids = makeTargetGrids(alphas = c(0.4,0.5)) via the ... argument.

Usage

makeTargetGrids(alphas, treatments = c(0, 1))

Arguments

alphas

the range of allocations or policies from 0 to 1. When model_method == "oracle" then model_options must be a list with named numeric vectors fixefs and var_comp. See prepareOracle. For mixed effect model, note that that random intercept's term in the modeling formula (e.g., ( 1 | cluster_ID ) ) must be omitted from formula. Arguments that can be passed through ... include: integrate_alphas. Not yet supported. verbose. Set to TRUE for more verbose messaging. Default FALSE. contrast_type. Not yet supported. keep_components. Set to TRUE for more verbose output. Default FALSE. target_grids. User can supply target estimands with makeTargetGrids. deriv_control. User can supply the deriv_control argument to m_estimate with setup_deriv_control.

treatments

defaults to 0:1 as in TV2012

Value

a list of pop_means and effects grids

Author(s)

Bradley Saul and Brian G. Barkley

See Also

The effect_grid function in the inferference package

BarkleyBG/stabilizedinterference documentation built on May 23, 2019, 8:37 a.m.