Description Usage Arguments Value See Also Examples
Considers MITT data collected through an interim timepoint and generates independent time-to-event data-sets, ignoring treatment assignments, to assess the distribution of the number of treatment arm-pooled endpoints at the end of the follow-up period. A Bayesian model for the treatment arm-pooled endpoint rate, offering the option to specify a robust mixture prior distribution, is used for generating future data (see the vignette).
1 2 3 4 5 6 7 | completeTrial.pooledArms(interimData, nTrials, N, enrollRate = NULL,
enrollRatePeriod = NULL, eventPriorWeight, eventPriorRate = NULL,
fixedDropOutRate = NULL, ppAnalysis = FALSE, missVaccProb = NULL,
ppAtRiskTimePoint = NULL, fuTime, mixture = FALSE,
mix.weights = NULL, eventPriorWeightRobust = NULL, visitSchedule,
visitSchedule2 = NULL, saveFile = NULL, saveDir = NULL,
randomSeed = NULL)
|
interimData |
a data frame capturing observed MITT data at an interim timepoint that contains one row per enrolled participant in the MITT cohort and the following variables: |
nTrials |
the number of trials to be simulated |
N |
the total target number of enrolled participants |
enrollRate |
a treatment arm-pooled weekly enrollment rate used for completing enrollment if fewer than |
enrollRatePeriod |
the length (in weeks) of the time period preceding the time of the last enrolled participant in |
eventPriorWeight |
a numeric value in [0,1] representing a weight assigned to the prior gamma distribution of the treatment arm-pooled event rate at the time when 50% of the estimated total person-time at risk has been accumulated (see the vignette) |
eventPriorRate |
a numeric value of a treatment arm-pooled prior mean incidence rate for the endpoint, expressed as the number of events per person-year at risk. If |
fixedDropOutRate |
the pre-trial assumed annual dropout rate. If |
ppAnalysis |
a logical value ( |
missVaccProb |
a probability that a participant misses at least one vaccination. If |
ppAtRiskTimePoint |
a minimal follow-up time (in weeks) for a participant to qualify for inclusion in the per-protocol cohort ( |
fuTime |
a follow-up time (in weeks) of each participant |
mixture |
a logical value indicating whether to use the robust mixture approach (see the vignette). If equal to |
mix.weights |
a numeric vector of length 2 representing prior weights (values in [0,1]) of the informative and the weakly informative component, respectively, of the prior gamma-mixture distribution of the treatment arm-pooled event rate. The two weights must sum up to 1. If |
eventPriorWeightRobust |
a numeric value representing the weight w used to calculate the β parameter of the weakly informative gamma distribution in the mixture prior. If |
visitSchedule |
a numeric vector of visit weeks at which testing for the endpoint is conducted |
visitSchedule2 |
a numeric vector of visit weeks at which testing for the endpoint is conducted in a subset of participants (e.g., those who discontinue administration of the study product but remain in follow-up). If |
saveFile |
a character string specifying an |
saveDir |
a character string specifying a path for the output directory. If supplied, the output is saved as an |
randomSeed |
seed of the random number generator for simulation reproducibility |
If saveDir
is specified, the output list (named trialObj
) is saved as an .RData
file; otherwise it is returned. The output object is a list with the following components:
trialData
: a list with nTrials
components each of which is a data.frame
with the variables arm
, entry
, exit
, event
, and dropout
storing the treatment assignments, enrollment times, study exit times, event indicators, and dropout indicators respectively. The observed follow-up times can be recovered as exit
- entry
. If ppAnalysis=TRUE
, then the indicators of belonging to the per-protocol cohort (named pp
) are included.
nTrials
: the number of simulated trials
N
: the total number of enrolled trial participants
rates
: a list with three components:
enrollRate
: the treatment arm-pooled weekly enrollment rate
dropRate
: fixedDropOutRate
, or, if NULL
, the annual treatment arm-pooled dropout rate in interimData
eventPostRate
: a numeric vector of length nTrials
of the treatment arm-pooled annual event rates sampled from the posterior distribution
BetaOverBetaPlusTk
: the weight placed on the prior mean event rate
TkOverTstar
: the ratio of the observed person-time at risk to the estimated total person-time at risk, with the event rate set equal to eventPriorRate
in the estimator for the total person-time at risk
randomSeed
: seed of the random number generator for simulation reproducibility
w.post
: the weights, summing up to 1, of the gamma components of the posterior mixture distribution of the treatment arm-pooled event rate. If mixture=FALSE
, then w.post=NA
.
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 | arm <- rep(c("C3","T1","T2"), each=250)
schedule <- rbinom(length(arm), 1, 0.01)
entry <- rpois(length(arm), lambda=60)
entry <- entry - min(entry)
last_visit_dt <- entry + runif(length(arm), min=0, max=80)
event <- rbinom(length(arm), 1, 0.01)
dropout <- rbinom(length(arm), 1, 0.02)
dropout[event==1] <- 0
exit <- rep(NA, length(arm))
exit[event==1] <- last_visit_dt[event==1] + 5
exit[dropout==1] <- last_visit_dt[dropout==1] + 5
followup <- ifelse(event==1 | dropout==1, 0, 1)
interimData <- data.frame(arm=arm, schedule2=schedule, entry=entry, exit=exit,
last_visit_dt=last_visit_dt, event=event, dropout=dropout, complete=0,
followup=followup)
completeData <- completeTrial.pooledArms(interimData=interimData, nTrials=5, N=1500,
enrollRatePeriod=24, eventPriorWeight=0.5, eventPriorRate=0.001, fuTime=80,
visitSchedule=seq(0, 80, by=4),
visitSchedule2=c(0,seq(from=8,to=80,by=12)), randomSeed=9)
### alternatively, to save the .RData output file (no '<-' needed):
completeTrial.pooledArms(interimData=interimData, nTrials=5, N=1500,
enrollRatePeriod=24, eventPriorWeight=0.5, eventPriorRate=0.001, fuTime=80,
visitSchedule=seq(0, 80, by=4),
visitSchedule2=c(0,seq(from=8,to=80,by=12)), saveDir="./", randomSeed=9)
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