plot.gformula_survival: Plot method for objects of class "gformula_survival"

Description Usage Arguments Value See Also Examples

View source: R/s3methods.R

Description

This function generates graphs of the mean simulated vs. observed values at each time point of the time-varying covariates, risk, and survival under the natural course. For categorical covariates, the observed and simulated counts of the levels of the factors are plotted at each time point.

Usage

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
## S3 method for class 'gformula_survival'
plot(
  x,
  covnames = NULL,
  risk = TRUE,
  survival = FALSE,
  ncol = NULL,
  nrow = NULL,
  common.legend = TRUE,
  legend = "bottom",
  xlab = NULL,
  ylab_cov = NULL,
  ylab_risk = "risk",
  ylab_surv = "survival",
  pos_risk = NULL,
  pos_surv = NULL,
  ci_risk = FALSE,
  ...
)

Arguments

x

Object of class "gformula_survival".

covnames

Vector of character strings specifying the names of the time-varying covariates to be plotted. The ordering of covariates given here is used in the plot grid. Time-varying covariates of type "categorical time" cannot be included. To plot none of the time-varying covariates, set this argument to NA. By default, this argument is set equal to the covnames argument used in gformula_survival, where covariates of type 'categorical time' are removed.

risk

Logical scalar indicating whether to include a plot for the risk. The default is TRUE.

survival

Logical scalar indicating whether to include a plot for the survival. The default is FALSE.

ncol

Number of columns in the plot grid. By default, two columns are used when there is at least two plots.

nrow

Number of rows in the plot grid. By default, a maximum of six rows is used and additional plots are included in subsequent pages.

common.legend

Logical scalar indicating whether to include a legend. The default is TRUE.

legend

Character string specifying the legend position. Valid values are "top", "bottom", "left", "right", and "none". The default is "bottom".

xlab

Character string for the x axes of all plots. By default, this argument is set to the time_name argument specified in gformula_survival.

ylab_cov

Vector of character strings for the y axes of the plots for the covariates. This argument must be the same length as covnames. The i-th element of this argument corresponds to the plot for the i-th element of covnames.

ylab_risk

Character string for the y axis of the plot for the risk (if applicable). The default is "risk".

ylab_surv

Character string for the y axis of the plot for the survival (if applicable). The default is "survival".

pos_risk

Integer specifying the position at which to order the risk plot (if applicable). By default, this argument is set to the number of plots in the grid minus one (i.e., orders the risk plot second last).

pos_surv

Integer specifying the position at which to order the survival plot (if applicable). By default, this argument is set to the number of plots in the grid (i.e., orders the survival plot last).

ci_risk

Logical scalar specifying whether to include error bars for the 95% confidence intervals of the estimated risk under the natural course. This argument is only effective if the argument nsamples was set to a positive value in gformula_survival. The default is TRUE.

...

Other arguments, which are passed to ggarrange.

Value

An object of class "ggarrange". See documentation of ggarrange.

See Also

gformula_survival

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
## 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'
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
intvars <- list('A', 'A')
interventions <- list(list(c(static, rep(0, time_points))),
                      list(c(static, rep(1, time_points))))
int_descript <- c('Never treat', 'Always treat')
nsimul <- 10000

gform_basic <- gformula_survival(obs_data = basicdata_nocomp, id = id,
                                 time_points = time_points,
                                 time_name = time_name, covnames = covnames,
                                 outcome_name = outcome_name,
                                 covtypes = covtypes,
                                 covparams = covparams, ymodel = ymodel,
                                 intvars = intvars,
                                 interventions = interventions,
                                 int_descript = int_descript,
                                 histories = histories, histvars = histvars,
                                 basecovs = c('L3'), nsimul = nsimul,
                                 seed = 1234)
plot(gform_basic)

gfoRmula documentation built on July 13, 2021, 9:07 a.m.