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. Author manuscript; available in PMC: 2015 Sep 20.
Published in final edited form as: Stat Med. 2014 May 7;33(21):3710–3724. doi: 10.1002/sim.6173

Table IV.

Posterior predictive checking results from the medical records and medicare claims, a subsample of CanCORS data.

Medical records Medicare claims

Study
site
Observed
capturing rate
Median from
predictions
ppp Observed
capturing rate
Median
from predictions
ppp
GHC .38 .31 .78 .92 .89 .64
HPHC 1 1 .41 1 1 .16
HFHS .78 .67 .73 .70 .83 .18
KPHI .20 .38 .48 1 1 .20
KPNW .67 .67 .48 .85 .85 .51
NCCC .25 .26 .43 .78 .83 .25
UAB .20 .22 .30 1 .89 .92
UCLA .44 .41 .73 .87 .83 .79
IOWA .73 .71 .66 .90 .88 .72
UNC .22 .23 .46 1 1 .44
Var .08 .07 .21 .01 .01 .54

Note: The subsample consists of 2669 CanCORS patients who died within 15 months of diagnosis and had at least one observed hospice-use record from two sources. The posterior predictive checks are based on 105 replicates. ppp, posterior predictive p-values. For example in the GHC site, the capturing rate is 23/(23 + 38) = .38 for medical records and 23/(23 + 2) = .92 for Medicare claims. The corresponding numerators and denominators can be found in Table AI.