Description Usage Arguments Value

View source: R/simdat2randlevels.R

Internal function to simulate joint data with random effect at the both
individual level and the study level. Used inside
`simjointmeta`

.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ```
simdat2randlevels(
k,
n,
rand_ind,
rand_stud,
sepassoc,
ntms,
longmeasuretimes,
beta1,
beta2,
gamma,
sigb_ind,
sigb_stud,
vare,
theta0,
theta1,
censoring,
censlam,
truncation,
trunctime,
q,
r
)
``` |

`k` |
the number of studies to be simulated |

`n` |
a vector of length equal to k denoting the number of individuals to simulate per study |

`rand_ind` |
a character string specifying the individual level random
effects structure. If |

`rand_stud` |
a character string specifying the study level random effects
structure. If this is set to |

`sepassoc` |
a logical taking value |

`ntms` |
the maximum possible number of longitudinal measurements - should
equal the length of the supplied |

`longmeasuretimes` |
a vector giving the exact times of the longitudinal
measurement times. If this is not specified in the function call then the
measurement times of the longitudinal outcome are set to start at 0 then
take integer values up to and including |

`beta1` |
a vector of the fixed effects for the longitudinal sub-model. Here the first element gives the coefficient for a fixed or population intercept, the second gives the coefficient for the binary treatment assignment covariate and the third element gives the covariate for the time (slope) covariate |

`beta2` |
the coefficient for the binary treatment assignment covariate |

`gamma` |
are the association parameters. If different association
parameters are supplied for each study in the dataset, this is a list of
vectors each of length equal to the total number of random effects. If the
same association parameters are supplied for each study in the dataset then
this is a vector of length equal to the number of random effects. If
separate association parameters are defined for different random effects
(i.e. if |

`sigb_ind` |
the covariance matrix for the individual level random effects. This should have number of rows and columns equal to the number of individual level random effects. |

`sigb_stud` |
the covariance matrix for the study level random effects.
This should have number of rows and columns equal to the number of study
level random effects. This should only be specified if |

`vare` |
the variance of the measurement error term |

`theta0` |
parameter defining the distribution of the survival times. A
separate parameter can be defined per study or a common parameter across
all studies. See Bender et al 2005 for advice on approximating appropriate
values for |

`theta1` |
parameter defining the distribution of the survival times. A
separate parameter can be defined per study or a common parameter across
all studies. See Bender et al 2005 for advice on approximating appropriate
values for |

`censoring` |
a logical indicating whether the simulated survival times should be censored or not |

`censlam` |
the lambda parameter controlling the simulated exponentially distributed censoring times. This can either be supplied as one value for all studies simulated, or a vector of length equal to the number of studies in the dataset. |

`truncation` |
a logical value to specify whether the simulated survival times should be truncated at a specified time or not. |

`trunctime` |
if |

`q` |
the number of individual level random effects |

`r` |
the number of study level random effects |

This function returns a list with three named elements. The first
element is named `'longdat'`

, the second `'survdat'`

, the third
`'percentevent'`

. Each of these elements is a list of length equal to
the number of studies specified to simulate in the function call.

The element `'longdat'`

is a list of the simulated longitudinal data
sets. Each longitudinal dataset contains the following variables:

`id`

a numeric id variable

`Y`

the continuous longitudinal outcome

`time`

the numeric longitudinal time variable

`study`

a study membership variable

`intercept`

an intercept term

`treat`

a treatment assignment variable to one of two treatment groups

`ltime`

a duplicate of the longitudinal time variable

The element `'survdat'`

is a list of the simulated survival data sets.
Each survival dataset contains the following variables:

`id`

a numeric id variable

`survtime`

the numeric survival times

`cens`

the censoring indicator

`study`

a study membership variable

`treat`

a treatment assignment variable to one of two treatment groups

The element `'percentevent'`

is a list of the percentage of events
over censorings seen in the simulated survival data.

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