Description Usage Arguments Details Value Note References Examples
Perform a metaanalysis with RMSTD using individual patient data. Methods include:
"mvma"
a multivariate metaanalysis borrowing strength across timepoints with withintrial covariance matrix derived analytically
"mvma_boot"
a multivariate metaanalysis borrowing strength across timepoints with withintrial covariance matrix derived by bootstrap
"uni"
a univariate metaanalysis for combined effect at each timepoint using only available data
"uni_flex"
a univariate metaanalysis for combined effect at each timepoint using estimates based on flexible parametric models as described by Wei et al (Stat Med 2015).
1  metaRMSTD(trialdata, time_horizons, MA_method, nboot = 500)

trialdata 
IPD trial data, see details for specifications 
time_horizons 
specified vector of time horizons for the metaanalysis 
MA_method 
the desired metaanalysis method; options are: "mvma", "mvma_boot", "uni", "uni_flex" 
nboot 
the number of bootstrap iterations, if using the MVMA with bootstrap covariance matrix; default=500 
Specify the time horizons at which to calculate the metaanalytic results.
The trialdata
must be formatted as a dataframe containing the IPD for each single trial.
Variable names must include Trial ID ("trialID"), Time ("Time"), Event status ("Event"), and randomization group ("Arm").
The metaRMSTD
function returns a list object containing the randomeffects model results,
the RMSTD and SE values for each trial at each available time horizon, and the estimated withintrial covariance matrix for each RCT.
RMSTD is estimable if time horizon > minimum of last observed times across the two groups. We implement the methodofmoments estimator for MVMA (Chen et al. Biometrics 2012, Jackson et al. Biometrical Journ 2013) and Dersimonian and Laird for univariate MA.
Wei, Y, Royston, P, Tierney, JF and Parmar, MKB. (2015). Metaanalysis of timetoevent outcomes from randomized trials using restricted mean survival time: application to individual participant data. Stat Med 34(21), 28812898.
Chen, Han, Alisa K. Manning, and Josée Dupuis. "A method of moments estimator for random effect multivariate metaanalysis." Biometrics 68.4 (2012): 12781284.
Jackson, Dan, Ian R. White, and Richard D. Riley. "A matrixbased method of moments for fitting the multivariate random effects model for metaanalysis and metaregression." Biometrical Journal 55.2 (2013): 231245.
1 2 3 4 5 6 7 8 9 10  # read in builtin dataset
data(AorticStenosisTrials)
# metaanalysis to obtain combined effect by multivariate model (method="mvma")
result < metaRMSTD(AorticStenosisTrials, time_horizons=c(12,24,36), MA_method="mvma")
# generate figure:
obj < RMSTcurves(AorticStenosisTrials, time_horizons=c(12,24,36), tmax=40, nboot=500)
RMSTplot(obj, xlim=c(0,40), ylim=c(0.25,2.75), yby=0.5, ylab="RMSTD (mos)", xlab="Time (mos)")

Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.