Estimates the MAIC weights for each individual in the IPD. Should only be used after it is ascertained that AD is indeed within the convex hull of IPD.
Usage
maicWt(ipd, ad, max.it = 25)
Value
The main code are taken from Philippo (2016). It returns the following:
optim.out
results of optim()
maic.wt
MAIC un-scaled weights for each subject in the IPD set
maic.wt.rs
re-scaled weights which add up to the original total sample size, i.e. nrow(ipd)
ipd.ess
effective sample size
ipd.wtsumm
weighted summary statistics of the matching variables after matching. they should be identical to the input AD when AD is within the IPD convex hull.
Arguments
ipd
a dataframe with n row and p column, where n is number of subjects and p is the number of variables used in matching.
ad
a dataframe with 1 row and p coln. The matching variables should be in the same order as that in ipd. The function does not check this.
max.it
maximum iteration passed to optim(). if ad is within ipd convex hull, then the default 25 iterations of optim() should be enough.
References
Phillippo DM, Ades AE, Dias S, et al. (2016). Methods for population-adjusted indirect comparisons in submissions to NICE. NICE Decision Support Unit Technical Support Document 18.