UPShclus                package:USPS                R Documentation

_H_i_e_r_a_r_c_h_i_c_a_l _C_l_u_s_t_e_r_i_n_g _o_f _P_a_t_i_e_n_t_s _o_n _X-_c_o_v_a_r_i_a_t_e_s _f_o_r _U_n_s_u_p_e_r_v_i_s_e_d _P_r_o_p_e_n_s_i_y _S_c_o_r_i_n_g

_D_e_s_c_r_i_p_t_i_o_n:

     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.

_U_s_a_g_e:

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

_A_r_g_u_m_e_n_t_s:

  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".

_D_e_t_a_i_l_s:

     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.

_V_a_l_u_e:

     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.

_A_u_t_h_o_r(_s):

     Bob Obenchain <sunsetstats@earthlink.net>

_R_e_f_e_r_e_n_c_e_s:

     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. (2005) *USPSinR.pdf*  ../R_HOME/library/USPS  40
     pages.

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

_S_e_e _A_l_s_o:

     'UPSaccum', 'UPSnnltd' and 'UPSgraph'.

_E_x_a_m_p_l_e_s:

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

