Description Usage Arguments Value See Also Examples

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

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`x` |
Object of class "gformula_continuous_eof". |

`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 |

`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 |

`legend` |
Character string specifying the legend position. Valid values are |

`xlab` |
Character string for the x axes of all plots. By default, this argument is set to the |

`ylab_cov` |
Vector of character strings for the y axes of the plots for the covariates. This argument must be the same length as |

`...` |
Other arguments, which are passed to |

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

.

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## Estimating the effect of treatment strategies on the mean of a continuous
## end of follow-up outcome
library('Hmisc')
id <- 'id'
time_name <- 't0'
covnames <- c('L1', 'L2', 'A')
outcome_name <- 'Y'
covtypes <- c('categorical', 'normal', 'binary')
histories <- c(lagged)
histvars <- list(c('A', 'L1', 'L2'))
covparams <- list(covmodels = c(L1 ~ lag1_A + lag1_L1 + L3 + t0 +
rcspline.eval(lag1_L2, knots = c(-1, 0, 1)),
L2 ~ lag1_A + L1 + lag1_L1 + lag1_L2 + L3 + t0,
A ~ lag1_A + L1 + L2 + lag1_L1 + lag1_L2 + L3 + t0))
ymodel <- Y ~ A + L1 + L2 + lag1_A + lag1_L1 + lag1_L2 + L3
intvars <- list('A', 'A')
interventions <- list(list(c(static, rep(0, 7))),
list(c(static, rep(1, 7))))
int_descript <- c('Never treat', 'Always treat')
nsimul <- 10000
gform_cont_eof <- gformula_continuous_eof(obs_data = continuous_eofdata,
id = id,
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_cont_eof)
``` |

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