maicT2Test function

Hotelling's T-square test to check whether maic is needed

maicT2Test(ipd, ad, n.ad = Inf)

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 column. The matching variables should be in the same order as that in ipd. The function does not check this.
• n.ad: default is Inf assuming ad is a fixed (known) quantity with infinit accuracy. In most MAIC applications ad is the sample statistics and n.ad is known.

Returns

• T.sq.f: the value of the T^2 test statistic

• p.val: the p-value corresponding to the test statistic. When the p-value is small, matching is necessary.

Details

When n.ad is not Inf, the covariance matrix is adjusted by the factor n.ad/(n.ipd + n.ad)), where n.ipd is nrow(ipd), the sample size of ipd.

Examples

## eAD[1,] is the scenario A in the reference paper,
## i.e. when AD is perfectly within IPD
maicT2Test(eIPD, eAD[1,2:3])

References

Glimm & Yau (2021). "Geometric approaches to assessing the numerical feasibility for conducting matching-adjusted indirect comparisons", Pharmaceutical Statistics, 21(5):974-987. doi:10.1002/pst.2210.