trajmsm (version 0.1.3)

trajmsm_gform: Parametric g-formula

Description

Estimate parameters of LCGA-MSM using g-formula and bootstrap to get standard errors.

Usage

trajmsm_gform(
  formula = formula,
  rep = 50,
  identifier,
  baseline,
  covariates,
  treatment,
  outcome,
  total_followup,
  time = time,
  time_values,
  var_cov,
  trajmodel,
  ref,
  obsdata
)

Value

Provides a matrix of estimates for LCGA-MSM, obtained using the g-formula method.

Arguments

formula

Specification of the model for the outcome to be fitted.

rep

Number of repetitions for the bootstrap.

identifier

Name of the column of the unique identifier.

baseline

Vector of names of the baseline covariates.

covariates

List of names of the time-varying covariates.

treatment

Vector of names of the time-varying treatment.

outcome

Name of the outcome of interest.

total_followup

Total length of follow-up.

time

Name of the time variable.

time_values

Measuring times.

var_cov

Names of the time-varying covariates.

trajmodel

Trajectory model built with the observed treatment.

ref

The reference trajectory group.

obsdata

Observed data in wide format.

Author

Awa Diop Denis Talbot

Examples

# \donttest{
obsdata_long = gendata(n = 1000, format = "long", total_followup = 6, seed = 845)
years <- 2011:2016
baseline_var <- c("age","sex")
variables <- c("hyper", "bmi")
var_cov <- c("statins","hyper", "bmi")
covariates <- lapply(years, function(year) {
paste0(variables, year)})
treatment_var <- paste0("statins", 2011:2016)
formula_treatment = as.formula(cbind(statins, 1 - statins) ~ time)
restraj = build_traj(obsdata = obsdata_long, number_traj = 3,
formula = formula_treatment, identifier = "id")
datapost = restraj$data_post
trajmsm_long <- merge(obsdata_long, datapost, by = "id")
    AggFormula <- as.formula(paste("statins", "~", "time", "+", "class"))
    AggTrajData <- aggregate(AggFormula, data = trajmsm_long, FUN = mean)
    AggTrajData
obsdata = reshape(data = trajmsm_long, direction = "wide", idvar = "id",
v.names = c("statins","bmi","hyper"), timevar = "time", sep ="")
formula = paste0("y ~", paste0(treatment_var,collapse = "+"), "+",
                paste0(unlist(covariates), collapse = "+"),"+",
                paste0(baseline_var, collapse = "+"))
resmsm_gform <- trajmsm_gform(formula = formula, identifier = "id",rep = 5,
baseline = baseline_var, covariates = covariates, var_cov = var_cov,
treatment = treatment_var, outcome = "y", total_followup = 6,time = "time",
time_values = years, trajmodel = restraj$traj_model,ref = "1", obsdata =   obsdata )
resmsm_gform
# }