UPShclus {USPS}R Documentation

Hierarchical Clustering of Patients on X-covariates for Unsupervised Propensiy Scoring

Description

Derive a full, hierarchical clustering tree (dendrogram) for all patients (regardless of treatment received) using Mahalonobis between-patient distances computed from specified baseline X-covariate characteristics.

Usage

  hclobj <- UPShclus(dframe, xvars, method="diana")

Arguments

dframe Name of data.frame containing baseline X covariates.
xvars List of names of X variable(s).
method Hierarchical Clustering Method: "diana", "agnes" or "hclus".

Details

The first step in an Unsupervised Propensity Scoring alalysis is always to hierarchically cluster patients in baseline X-covariate space. UPShclus uses a Mahalabobis metric and clustering methods from the R "cluster" library for this key initial step.

Value

An output list object of class UPShclus:

dframe Name of data.frame containing baseline X covariates.
xvars List of names of X variable(s).
method Hierarchical Clustering Method: "diana", "agnes" or "hclus".
upshcl Hierarchical clustering object created by choice between three possible methods.

Author(s)

Bob Obenchain <wizbob@att.net>

References

Kaufman L, Rousseeuw PJ. (1990) Finding Groups in Data. An Introduction to Cluster Analysis. New York: John Wiley and Sons.

Kereiakes DJ, Obenchain RL, Barber BL, et al. (2000) Abciximab provides cost effective survival advantage in high volume interventional practice. Am Heart J 140: 603-610.

Obenchain RL. (2004) Unsupervised Propensity Scoring: NN and IV Plots. Proceedings of the American Statistical Association (on CD) 8 pages.

Obenchain RL. (2009) USPSinR.pdf ../R_HOME/library/USPS 40 pages.

Rubin DB. (1980) Bias reduction using Mahalanobis metric matching. Biometrics 36: 293-298.

See Also

UPSaccum, UPSnnltd and UPSgraph.

Examples

  data(lindner)
  UPSxvars <- c("stent", "height", "female", "diabetic", "acutemi", "ejecfrac", "ves1proc")
  UPSharch <- UPShclus(lindner, UPSxvars)
  plot(UPSharch)

[Package USPS version 1.2-0 Index]