TY - JOUR

T1 - Change-point diagnostics in competing risks models

T2 - Two posterior predictive p-value approaches

AU - Wang, Chen Pin

AU - Ghosh, Malay

PY - 2007/5/1

Y1 - 2007/5/1

N2 - This paper presents a Bayesian diagnostic procedure for examining change-point assumption in the competing risks model framework. It considers the family of distributions arising from the cause-specific model as reported by Chiang (Introduction to stochastic processes in biostatistics. Wiley, New York, 1968) upon which change-points are added to accommodate possible distributional heterogeneity. Model departure, due to misspecification of change-points associated with either the overall survival distribution or cause-specific probabilities, is quantified in terms of a sequence of cumulative-sum statistics between each pair of adjacent change-points assumed. When assessing the asymptotic behavior of each sequence of cumulative-sum statistics using its posterior predictive p-values, see Rubin (Ann Stat 12:1151-1172, 1984) and partial posterior predictive p-values as reported by Bayarri and Berger (J Am Stat Assoc 95:1127-1142, 2000), we show that both types of p-values attain their greatest departure from 0.5 at the change-point that is missed in the assumed model, from which a diagnostic procedure is formalized. Statistical power of these two types of p-values is discussed.

AB - This paper presents a Bayesian diagnostic procedure for examining change-point assumption in the competing risks model framework. It considers the family of distributions arising from the cause-specific model as reported by Chiang (Introduction to stochastic processes in biostatistics. Wiley, New York, 1968) upon which change-points are added to accommodate possible distributional heterogeneity. Model departure, due to misspecification of change-points associated with either the overall survival distribution or cause-specific probabilities, is quantified in terms of a sequence of cumulative-sum statistics between each pair of adjacent change-points assumed. When assessing the asymptotic behavior of each sequence of cumulative-sum statistics using its posterior predictive p-values, see Rubin (Ann Stat 12:1151-1172, 1984) and partial posterior predictive p-values as reported by Bayarri and Berger (J Am Stat Assoc 95:1127-1142, 2000), we show that both types of p-values attain their greatest departure from 0.5 at the change-point that is missed in the assumed model, from which a diagnostic procedure is formalized. Statistical power of these two types of p-values is discussed.

KW - Change-point

KW - Competing risks

KW - Posterior predictive p-values

UR - http://www.scopus.com/inward/record.url?scp=70349578777&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=70349578777&partnerID=8YFLogxK

U2 - 10.1007/s11749-006-0006-x

DO - 10.1007/s11749-006-0006-x

M3 - Article

AN - SCOPUS:70349578777

VL - 16

SP - 145

EP - 171

JO - Trabajos de Estadistica Y de Investigacion Operativa

JF - Trabajos de Estadistica Y de Investigacion Operativa

SN - 0041-0241

IS - 1

ER -