Table 2List of Matching Algorithms

MethodTypeDistanceCaliper, Y/NClusteringMatching ratio to control
VMVMLinear GPSYk-means1:1:1…1
VM2VMLinear GPSYk-means1:2:2…2
VMncVMLinear GPSNk-means1:1:1…1
VMnrVM without replacementLinear GPSYk-means1:1:1…1
VMFVMLinear GPSYFuzzy1:1:1…1
KMVM logit(r^(t,X), r^(t,X)) Yk-means1:1:1…1
KMncVM logit(r^(t,X), r^(t,X)) Nk-means1:1:1…1
FMVM logit(r^(t,X), r^(t,X)) YFuzzy1:1:1…1
FMncVM logit(r^(t,X), r^(t,X)) NFuzzy1:1:1…1
GPSBasicMahalanobis GPSYNone1:1:1…1
GPSncBasicMahalanobis GPSNNone1:1:1…1
COVncBasicMahalanobis covariatesNNone1:1:1…1

Abbreviations: COVnc, covariate matching, no caliper; FM, fuzzy clustering matching; FMnc, fuzzy clustering matching, no caliper; GPS, Mahalanobis on the generalized propensity score; GPSnc, Mahalanobis on the generalized propensity score, no caliper; KM, k-means matching; KMnc, k-means matching, no caliper; N, no; VM, vector matching; VM2, vector matching to 2 units in other groups; VMF, vector matching, fuzzy clustering; VMnc, vector matching, no caliper; VMnr, vector matching, no replacement; Y, yes.

From: Creating and Testing Methods to Estimate Treatment Effect in Observational Studies with Three or More Treatments

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Creating and Testing Methods to Estimate Treatment Effect in Observational Studies with Three or More Treatments [Internet].
Gutman R, Scotina A, Smith RJ, et al.
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