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Set advanced parameters for analysis of data from stepped wedge trials

Source: R/params.R
params.Rd

This should be used in conjunction with analyze to set parameters controlling analysis; see examples.

Usage

params(
  offset = NULL,
  n_knots_exp = 4,
  n_knots_cal = 4,
  var_est = "model",
  var_est_type = "classic",
  return_ncs = F
)

Arguments

offset

A linear predictor offset term; see docs for `lme4::lmer`.

n_knots_exp

An integer; only relevant when exp_time="NCS". Specifies the number of knots to use for exposure time, including boundary knots. The spline basis includes an intercept, and the degree of the basis is equal to the number of knots.

n_knots_cal

An integer; only relevant when cal_time="NCS". Specifies the number of knots to use for calendar time, including boundary knots. The spline basis includes an intercept, and the degree of the basis is equal to the number of knots.

var_est

A character string; either "model", for model-based variance, or "robust", to use the robust variance estimator.

var_est_type

A character string; one of c("classic","DF","KC","MD","FG"); only relevant when var_est="robust".

return_ncs

Logical; only relevant when exp_time="NCS". Specifies whether the full covariance matrix for the calendar time parameters and the transformed treatment effect parameters are returned.

Value

A list of options

Examples

dat <- load_data(time = "period", cluster_id = "cluster", individual_id = NULL,
treatment = "trt", outcome = "outcome_bin", data = sw_data_example)

analyze(dat = dat, method = "mixed", estimand_type = "TATE",  exp_time = "NCS",
family = binomial)