RECPAM: a computer program for recursive partition and amalgamation for censored survival data and other situations frequently occurring in biostatistics. I. Methods and program features.

The methodology of recursive partition and amalgamation in biostatistics is presented and a FORTRAN program for its implementation, RECPAM, is described. RECPAM can be used to obtain classifications of patients according to several criteria commonly occurring in clinical biostatistics: an example is prognostic classification based on survival data. Classes are defined by simple statements, expressed in clinical terms, about predictor variables (e.g. prognostic factors). Special features of RECPAM are: the possibility of implementing a variety of classification criteria, the integration of recursive partition and amalgamation, and the availability of several strategies for constructing classification trees. A simple example to illustrate input and output features is given. The scope and flexibility of RECPAM will be illustrated in greater detail in a subsequent paper.

[1]  D. Rubin,et al.  Reducing Bias in Observational Studies Using Subclassification on the Propensity Score , 1984 .

[2]  A Morabito,et al.  Prognostic factors and risk groups: some results given by using an algorithm suitable for censored survival data. , 1983, Statistics in medicine.

[3]  John A. Hartigan,et al.  Clustering Algorithms , 1975 .

[4]  M. Stone,et al.  Cross‐Validatory Choice and Assessment of Statistical Predictions , 1976 .

[5]  David R. Cox,et al.  Regression models and life tables (with discussion , 1972 .

[6]  H. Akaike A new look at the statistical model identification , 1974 .

[7]  James N. Morgan,et al.  Searching for structure;: An approach to analysis of substantial bodies of micro-data and documentation for a computer program , 1973 .

[8]  David P. Harrington,et al.  Modified Kolmogorov-Smirnov Test Procedures with Application to Arbitrarily Right-Censored Data , 1980 .

[9]  A Ciampi,et al.  An approach to classifying prognostic factors related to survival experience for non‐Hodgkin's lymphoma patients: Based on a series of 982 patients: 1967–1975 , 1981, Cancer.

[10]  Antonio Ciampi,et al.  Recursive Partition: A Versatile Method for Exploratory-Data Analysis in Biostatistics , 1987 .

[11]  C. J. Stone,et al.  Consistent Nonparametric Regression , 1977 .

[12]  Jerald F. Lawless,et al.  Statistical Models and Methods for Lifetime Data , 1983 .

[13]  J. Kalbfleisch,et al.  The Statistical Analysis of Failure Time Data , 1980 .