standardize_treatment_kernel: Re-weight groups to target population means

In ebenmichael/balancer: Matrix constraints for covariate balance

Re-weight groups to target population means

Description

Re-weight groups to target population means

Usage

standardize_treatment_kernel(
  X0,
  Xtau,
  Xtarget,
  S,
  Z,
  pscores,
  kernel0 = kernlab::vanilladot(),
  kerneltau = kernlab::vanilladot(),
  lambda = 0,
  lowlim = 0,
  uplim = nrow(X0),
  scale_sample_size = F,
  data_in = NULL,
  verbose = TRUE,
  return_program = TRUE,
  init_uniform = F,
  eps_abs = 1e-05,
  eps_rel = 1e-05,
  gc = TRUE,
  ...
)

Arguments

X0	n x d0 matrix of untransformed covariates defining the mean control response function
Xtau	n x dtau matrix of untransformed covariates defining the mean treatment effect function
Xtarget	ntarget x dtau matrix of untransformed covariates constituting the target population
S	Numeric vector of site indicators with J levels
Z	Numeric vector of treatment indicators with 2 levels
pscores	Numeric vector of propensity scores
kernel0	Kernel for control outcome covariates, default is the inner product
kerneltau	Kernel for treatment effect covariates, default is the inner product
lambda	Regularization hyper parameter, default 0
lowlim	Lower limit on weights, default 0
uplim	Upper limit on weights, default nrow(X0)
scale_sample_size	Whether to scale the dispersion penalty by the sample size of each group, default F
data_in	Optional list containing pre-computed objective matrix/vector and constraints (without regularization term)
verbose	Whether to show messages, default T
return_program	Whether to return the objective matrix and vector and constraints, default T
init_uniform	Wheter to initialize solver with uniform weights, default F
eps_abs	Absolute error tolerance for solver
eps_rel	Relative error tolerance for solver
gc	boolean indicating whether to garbage collect between operations
...	Extra arguments for osqp solver

Value

• weights Estimated primal weights as an n x J matrix

• imbalance_0 Imbalance in covariates defining mean control response function as a d0 x J matrix

• imbalance_tau Imbalance in covariates defining mean treatment effect function as a dtau x J matrix

• data_out List containing elements of QP min 0.5 x'Px + q'x st l <= Ax <= u

  • P, q

  • constraints A, l , u

ebenmichael/balancer documentation built on Jan. 17, 2024, 2:56 p.m.