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What population does the sample represent? The answer to this question is of crucial importance when estimating a survivor function in duration studies. As is well-known, in a stationary population, survival data obtained from a c...
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What population does the sample represent? The answer to this question is of crucial importance when estimating a survivor function in duration studies. As is well-known, in a stationary population, survival data obtained from a cross-sectional sample taken from the population at time t_0 represents not the target density f(t) but its length-biased version proportional to tf(t). for t >0. The problem of estimating survivor function from such length-biased samples becomes more complex, and interesting, in presence of competing risks and censoring. This paper lays out a sampling scheme related to a mixed Poisson process and develops nonparametric estimators of the survivor function of the target population assuming that the two independent competing risks have proportional hazards. Two cases are considered: with and without independent censoring before length biased sampling. In each case, the weak convergence of the process generated by the proposed estimator is proved. A well-known study of the duration in power for political leaders is used to illustrate our results. Finally, a simulation study is carried out in order to assess the finite sample behaviour of our estimators.
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We consider a data set on nosocomial infections of patients hospitalized in a French intensive care facility. Patients may suffer from recurrent infections of different types and they also have a high risk of death. To deal with s...
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We consider a data set on nosocomial infections of patients hospitalized in a French intensive care facility. Patients may suffer from recurrent infections of different types and they also have a high risk of death. To deal with such situations, a model of recurrent events with competing risks and a terminal event is introduced. Our aim was to compare the occurrence rates of two types of events. For this purpose, we propose two tests: one to detect if the occurrence rate of a given type of event increases with time; a second to detect if the instantaneous probability of experiencing an event of a given type is always greater than the one of another type. The asymptotic properties of the test statistics are derived and Monte Carlo methods are used to study the power of the tests. Finally, the procedures developed are applied to the French nosocomial infections data set.
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Let X be a nonnegative random variable with cumulative distribution function F. In this article, we introduce a concept of deviation from exponentiality for F, based on the Mean Residual Life function. Our. aim is to estimate this...
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Let X be a nonnegative random variable with cumulative distribution function F. In this article, we introduce a concept of deviation from exponentiality for F, based on the Mean Residual Life function. Our. aim is to estimate this deviation under the random censorship model. For this purpose, we propose two slightly different estimators. For each one, we determine the limit distribution of an appropriately normalized version. Then, this work leads to the construction of a test of H_0 : F is exponential vs. H_1: F is not exponential. It is applied to the Koziol and Green data set (Koziol, S. A., Green, S. B. (1976). A cramer-von mises statistic for randomly censored data. Biometrika 23:465-474).
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The simultaneous modeling of ageing and maintenance efficiency of repairable systems is a major issue in reliability. Many imperfect maintenance models have been proposed. To analyze a dataset, it is necessary to check whether the...
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The simultaneous modeling of ageing and maintenance efficiency of repairable systems is a major issue in reliability. Many imperfect maintenance models have been proposed. To analyze a dataset, it is necessary to check whether these models are adapted or not. In this paper, we propose a general methodology for testing the goodness of fit of any kind of imperfect maintenance model. Two families of tests are presented, based respectively on martingale residuals and probability integral transforms. The quantiles of the test statistics distributions under the null hypothesis are computed with parametric bootstrap methods. An extensive simulation study is provided, from which we recommend the use of two tests in practice, one from each family. Finally, the tests are applied to several real datasets.
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In many practical situations, such as cross-sectional sampling, the observed random sample suffers from selection bias in the sense that it does not represent the target population. This paper considers the problem of estimating t...
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In many practical situations, such as cross-sectional sampling, the observed random sample suffers from selection bias in the sense that it does not represent the target population. This paper considers the problem of estimating the target survivor function when the data for two independent competing risks having proportional hazards is observed under such a selection bias. The large sample behavior of the proposed estimator is studied through martingale representation and stochastic integrals.
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ImportanceCompared with standard cytotoxic therapies, randomized immune checkpoint inhibitor (ICI) phase 3 trials reveal delayed benefits in terms of patient survival and/or long-term response. Such outcomes generally violate the ...
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ImportanceCompared with standard cytotoxic therapies, randomized immune checkpoint inhibitor (ICI) phase 3 trials reveal delayed benefits in terms of patient survival and/or long-term response. Such outcomes generally violate the assumption of proportional hazards, and the classical Cox proportional hazards regression model is therefore unsuitable for these types of analyses.ObjectiveTo evaluate the ability of the flexible parametric cure model (FPCM) to estimate treatment effects and long-term responder fractions (LRFs) independently of prespecified time points.Evidence ReviewThis systematic review used reconstructed individual patient data from ICI advanced or metastatic melanoma and lung cancer phase 3 trials extracted from the literature. Trials published between January 1, 2010, and October 1, 2019, with long-term follow-up periods (maximum follow-up, ≥36 months in first line and ≥30 months otherwise) were selected to identify LRFs. Individual patient data for progression-free survival were reconstructed from the published randomized ICI phase 3 trial results. The FPCM was applied to estimate treatment effects on the overall population and on the following components of the population: LRF and progression-free survival in non–long-term responders. Results obtained were compared with treatment effects estimated using the Cox proportional hazards regression model.FindingsIn this systematic review, among the 23 comparisons studied using the FPCM, a statistically significant association between the time-to-event component and experimental treatment was observed in the main analyses and confirmed in the sensitivity analyses of 18 comparisons. Results were discordant for 4 comparisons that were not significant by the Cox proportional hazards regression model. The LRFs varied from 1.5% to 12.7% for the control arms and from 4.6% to 38.8% for the experimental arms. Differences in LRFs varied from 2% to 29% and were significantly increased in the experimental compared with the control arms, except for 4 comparisons.Conclusions and RelevanceThis systematic review of reconstructed individual patient data found that the FPCM was a complementary approach that provided a comprehensive and pertinent evaluation of benefit and risk by assessing whether ICI treatment was associated with an increased probability of patients being long-term responders or with an improved progression-free survival in patients who were not long-term responders.
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To study the nuclear export of preribosomes, ribosomal RNAs were detected by in situ hybridization using fluorescence and EM, in the yeast Saccharomyces cerevisiae . In wild-type cells, semiquantitative analysis shows that the dis...
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To study the nuclear export of preribosomes, ribosomal RNAs were detected by in situ hybridization using fluorescence and EM, in the yeast Saccharomyces cerevisiae . In wild-type cells, semiquantitative analysis shows that the distributions of pre-40S and pre-60S particles in the nucleolus and the nucleoplasm are distinct, indicating uncoordinated transport of the two subunits within the nucleus. In cells defective for the activity of the GTPase Gsp1p/Ran, ribosomal precursors accumulate in the whole nucleus. This phenotype is reproduced with pre-60S particles in cells defective in pre-rRNA processing, whereas pre-40S particles only accumulate in the nucleolus, suggesting a tight control of the exit of the small subunit from the nucleolus. Examination of nucleoporin mutants reveals that preribosome nuclear export requires the Nup82p–Nup159p–Nsp1p complex. In contrast, mutations in the nucleoporins forming the Nup84p complex yield very mild or no nuclear accumulation of preribosome. Interestingly, domains of Nup159p required for mRNP trafficking are not necessary for preribosome export. Furthermore, the RNA helicase Dbp5p and the protein Gle1p, which interact with Nup159p and are involved in mRNP trafficking, are dispensable for ribosomal transport. Thus, the Nup82p–Nup159p–Nsp1p nucleoporin complex is part of the nuclear export pathways of preribosomes and mRNPs, but with distinct functions in these two processes.
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We investigate the parametric maximum likelihood estimator for truncated data when the truncation value is different according to the observed individual or item. We extend Lehmann’s proof (1983) of the asymptotic properties of t...
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We investigate the parametric maximum likelihood estimator for truncated data when the truncation value is different according to the observed individual or item. We extend Lehmann’s proof (1983) of the asymptotic properties of the parametric maximum likelihood estimator in the case of independent nonidentically distributed observations. Two cases are considered: either the number of distinct probability distribution functions that can be observed in the population from which the sample comes from is finite or this number is infinite. Sufficient conditions for consistency and asymptotic normality are provided for both cases.
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The aim of this paper is to introduce and study a new model of Imperfect Maintenance in Reliability. A model of arithmetic reduction of intensity is assumed on the interarrival times of failures on a system subject to recurrent fa...
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The aim of this paper is to introduce and study a new model of Imperfect Maintenance in Reliability. A model of arithmetic reduction of intensity is assumed on the interarrival times of failures on a system subject to recurrent failures. Based on the observation of the recurrent failures of a single repairable system and assuming that a perfect repair is operated after
$N$
failures, we introduce estimators of the parameters (Euclidean and functional) of this semiparametric model and we prove their asymptotic normality. Statistical inference is also carried out using this model. Finally, a simulation study is performed to learn the behavior of these estimators on samples of small or moderate size. We end this work with an application on a real dataset.
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In this paper, we propose a Bayesian method for modelling count data by Poisson, binomial or negative binomial distributions. These three distributions have in common that the variance is, at most, a quadratic function of the mean...
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In this paper, we propose a Bayesian method for modelling count data by Poisson, binomial or negative binomial distributions. These three distributions have in common that the variance is, at most, a quadratic function of the mean. We use prior distributions on the variance function coefficients to consider simultaneously the three possible models and decide which one fits the data better. This approach sheds new light on the analysis of the Sibship data (Sokal and Rohlf, 1987). The Jeffreys-Lindley paradox is discussed through some illustrations.
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