Exponential Survivals with Censoring and Explanatory Variables

Prentice, R. L.

doi:10.2307/2334539

Cited by 59 publications

(82 citation statements)

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“…Wherever possible, the following informa- Cox (1972) while the Weibull form used here has been used by Prentice (1973) and Williams (1978), amongst others. This particular parametric form was initially chosen because the data sets at several sites w%rere quite small and, as pointed out by Williams (1978), it is not clear that efficiency losses in using the non-parametric form (Cox, 1972) are negligible in such small samples.…”

Section: Methodsmentioning

confidence: 99%

Prognostic significance of modal DNA value and other factors in malignant tumours, based on 1465 cases

Atkin¹,

Kay²

1979

Br J Cancer

275

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Summary. The modal DNA values of 1465 tumours, together with other factors of possible prognostic importance, were related to the survival of the patients, using regression models (Kay, 1977). For most tumour sites except the testis, the distributions of modal DNA values were bimodal, with peaks at the diploid level and in the triploid-tetraploid range. For all tumour sites except the cervix uteri, patients in the low (near-diploid) range showed better survival; the reverse was true for squamouscell carcinoma of the cervix uteri. Other variables showed the following effects: for all sites except the testis, younger patients showed a better survival; for the cervix and corpus uteri, breast and ovary, increasing clinical stage was associated with poorer survival. Where evaluated, histological grade appeared to be associated with survival rate, the less well differentiated tumours having a worse prognosis, except for the breast, where the reverse correlation was noted. For carcinoma of the bladder, females had a poorer survival rate than males.

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Section: Methodsmentioning

confidence: 99%

Prognostic significance of modal DNA value and other factors in malignant tumours, based on 1465 cases

Atkin¹,

Kay²

1979

Br J Cancer

275

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“…Following Reich, et al (2009), the distribution of b could be obtained if a is given and f Y (y) is known. Thus,…”

Section: The Modelmentioning

confidence: 99%

“…The A ~ U(0,16) and Y is assumed to follow the log logistic distribution (special case, γ = 1) with parameter λ. The value of −4.3 was chosen as the true parameter value of λ to simulate the survival times that mimic those seen in lung cancer data (Prentice, 1973).…”

Section: Simulation Studymentioning

confidence: 99%

“…The proposed model was later adapted by Darby, et al (1990) and fitted to data on the development of AIDS in hemophiliacs in the United Kingdom who are seropositive for HIV. Reich, et al (2009) studied two procedures for estimating the incubation time distribution. The first procedure defined the likelihood function with DIC data scheme and obtained the MLEs parametrically.…”

Section: Introductionmentioning

confidence: 99%

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Inferential Procedures for Log Logistic Distribution with Doubly Interval Censored Data

Loh

Arasan

Midi

et al. 2017

J. Mod. App. Stat. Meth.

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“…The second justi cation is that the partial likelihood (11) actually becomes a full likelihood if a part of the data is discarded, namely the times at which deaths occur. It is a full likelihood for the part of the data consisting of the order in which individuals die and the risk sets, R i , corresponding to each death (Savage 1957 Kalb eisch andPrentice 1973).…”

Section: The Cox Proportional Hazards Modelmentioning

confidence: 99%

Bayesian Information Criterion for Censored Survival Models

2000

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We i n vestigate the Bayesian Information Criterion (BIC) for variable selection in models for censored survival data. Kass and Wasserman (1995) showed that BIC provides a close approximation to the Bayes factor when a unit-information prior on the parameter space is used. We propose a revision of the penalty term in BIC so that it is de ned in terms of the number of uncensored events instead of the number of observations. For the simplest censored data model, that of exponential distributions of survival times (i.e. a constant hazard rate), this revision results in a better approximation to the exact Bayes factor based on a conjugate unit-information prior. In the Cox proportional hazards regression model, we propose de ning BIC in terms of the maximized partial likelihood. Using the number of deaths rather than the number of individuals in the BIC penalty term corresponds to a more realistic prior on the parameter space, and is shown to improve predictive performance for assessing stroke risk in the Cardiovascular Health Study.

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Exponential Survivals with Censoring and Explanatory Variables

Cited by 59 publications

References 0 publications

Prognostic significance of modal DNA value and other factors in malignant tumours, based on 1465 cases

Prognostic significance of modal DNA value and other factors in malignant tumours, based on 1465 cases

Inferential Procedures for Log Logistic Distribution with Doubly Interval Censored Data

Bayesian Information Criterion for Censored Survival Models

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