vcov.gformula | R Documentation |
This function extracts the variance-covariance matrices of the parameters of the fitted models for the time-varying covariates, outcome, and competing event (if applicable).
## S3 method for class 'gformula'
vcov(object, ...)
object |
Object of class "gformula". |
... |
Other arguments. |
If bootdiag
was set to FALSE
in gformula
,
this function returns a list of the variance-covariance matrices of the
parameters of the fitted models to the observed data set. If bootstrapping
was used and bootdiag
was set to TRUE
in
gformula
, this function returns a list described as follows.
The first element (named 'Original sample') is a list of the
variance-covariance matrices of the parameters of the fitted models to the
observed data set. The kth element (named 'Bootstrap sample k-1') is a list
of the variance-covariance matrices of the parameters of the fitted models
corresponding to the k-1th bootstrap sample.
gformula
## Estimating the effect of static treatment strategies on risk of a
## failure event
id <- 'id'
time_points <- 7
time_name <- 't0'
covnames <- c('L1', 'L2', 'A')
outcome_name <- 'Y'
outcome_type <- 'survival'
covtypes <- c('binary', 'bounded normal', 'binary')
histories <- c(lagged, lagavg)
histvars <- list(c('A', 'L1', 'L2'), c('L1', 'L2'))
covparams <- list(covmodels = c(L1 ~ lag1_A + lag_cumavg1_L1 + lag_cumavg1_L2 +
L3 + t0,
L2 ~ lag1_A + L1 + lag_cumavg1_L1 +
lag_cumavg1_L2 + L3 + t0,
A ~ lag1_A + L1 + L2 + lag_cumavg1_L1 +
lag_cumavg1_L2 + L3 + t0))
ymodel <- Y ~ A + L1 + L2 + L3 + lag1_A + lag1_L1 + lag1_L2 + t0
intervention1.A <- list(static, rep(0, time_points))
intervention2.A <- list(static, rep(1, time_points))
int_descript <- c('Never treat', 'Always treat')
nsimul <- 10000
gform_basic <- gformula(obs_data = basicdata_nocomp, id = id,
time_points = time_points,
time_name = time_name, covnames = covnames,
outcome_name = outcome_name,
outcome_type = outcome_type, covtypes = covtypes,
covparams = covparams, ymodel = ymodel,
intervention1.A = intervention1.A,
intervention2.A = intervention2.A,
int_descript = int_descript,
histories = histories, histvars = histvars,
basecovs = c('L3'), nsimul = nsimul,
seed = 1234)
vcov(gform_basic)
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