You are not currently logged in.
Access your personal account or get JSTOR access through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
A Nonparametric Model for Multiple Recurrences
Journal of the Royal Statistical Society. Series C (Applied Statistics)
Vol. 37, No. 2 (1988), pp. 157-168
Stable URL: http://www.jstor.org/stable/2347335
Page Count: 12
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
In this paper we present a new statistical model which permits the analysis of clinical trials where each patient is regularly examined for multiple recurrences of a disease. This model, based on logistic regression, allows the estimation of the probability of recurrence adjusted for various concomitant variables, including treatment and patient characteristics. In the absence of missing data, our model turns out to be of the generalised linear type, and the computations can be performed by means of standard programmes. The EM algorithm is adapted here to deal with missing observations. We derive the parameter covariance matrix as well as a χ2 goodness-of-fit measure. The method is illustrated using data from a clinical trial on the treatment of superficial (Ta, T1) bladder cancer by local chemotherapy.
Journal of the Royal Statistical Society. Series C (Applied Statistics) © 1988 Royal Statistical Society