QR with 2-sided measurement error

Estimates QR parameters in the case with measurement error in the outcome and measurement error in a particular continuous "treatment" variable.

Usage

qr2me(
  y_name,
  t_name,
  x_formula,
  tau,
  data,
  x_data = NULL,
  t_values = NULL,
  me_distribution = "gaussian",
  copula = "gaussian",
  Qyx,
  Qtx,
  return_fytx_list = FALSE,
  n_copula_me_draws = 100L,
  n_copula_draws = 100L,
  verbose = FALSE
)

Arguments

y_name: name of the outcome in the passed in data
t_name: name of the treatment in the passed in data
x_formula: a one-sided formula for additional covariates (assumed not to be measured with error)
tau: a vector containing particular quantiles that have been estimated ??
data: a data.frame containing the data used for estimation
x_data: If you want conditional distributions to be returned, pass in the value of the distribution here; otherwise the default behavior is to return a single distribution that averages over all values of X in the dataset
t_values: a vector of values of the treatment variable at which to compute the conditional distribution of Y given X and T
me_distribution: which type of measurement error distribution to use (default is "gaussian"), "laplace" is also supported
copula: which type of copula to use. Options are "gaussian" (the default), "clayton", "gumbel", or "frank"
Qyx: quantile regression estimates (can be adjusted for measurement error) of Y on X
Qtx: quantile regression estimates (can be adjusted for measurement error) of T on X
return_fytx_list: whether or not to return the conditional distribution for every value of x in x_data (default is FALSE because this can take up a lot of room in memory)
n_copula_me_draws: Number of measurement-error draws used in the second-stage copula likelihood (default 100). Increase this for a less noisy copula likelihood at the cost of speed.
n_copula_draws: Number of copula draws per covariate row used to compute mobility summaries such as transition matrices and rank correlations (default 100).
verbose: Logical or nonnegative integer. If FALSE (default), suppresses progress output. If TRUE or 1, reports major computational stages, EM iteration numbers, and convergence diagnostics. If 2, also reports qrme-native details such as pi, mu, sigma, tolerance, finite-mixture summaries, and the no-measurement-error comparison copula step. If 3 or larger, also reports raw normalmixEM() output, which uses lambda for mixture probabilities.