Displaying similar documents to “Study of Bootstrap Estimates in Cox Regression Model with Delayed Entry”

Regression and time series: Discussion.

P. J. Harrison, Arnold Zellner (1980)

Trabajos de Estadística e Investigación Operativa

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Discussion on the papers by Brown, Philip J., Aspects of multivariate regression and by Dempster, Arthur P., Bayesian inference in applied statistics, both of them part of a round table on Regression and time series held in the First International Congress on Bayesian Methods (Valencia, Spain, 28 May - 2 June 1979).

Some inferential questions in regard to analysing two-way Layouts and associated linear model theory and practice

Brenton R. Clarke, Antony G. Monaco (2004)

Discussiones Mathematicae Probability and Statistics

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In analysing a well known data set from the literature which can be thought of as a two-way layout it transpires that a robust adaptive regression approach for identifying outliers fails to be sensitive enough to detect the possible interchange of two observations. On the other hand if one takes the classical approach of diagnostic checking one may also stop too early and be satisfied with a model that falls short of a more detailed analysis that takes account of heteroscedasticity in...

Aspects of analysis of multivariate failure time data.

Ross L. Prentice, John D. Kalbfleisch (2003)

SORT

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Multivariate failure time data arise in various forms including recurrent event data when individuals are followed to observe the sequence of occurrences of a certain type of event; correlated failure time when an individual is followed for the occurrence of two or more types of events for which the individual is simultaneously at risk, or when distinct individuals have depending event times; or more complicated multistate processes where individuals may move among a number of discrete...

Indirect inference for survival data.

Bruce W. Turnbull, Wenxin Jiang (2003)

SORT

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In this paper we describe the so-called indirect method of inference, originally developed from the econometric literature, and apply it to survival analyses of two data sets with repeated events. This method is often more convenient computationally than maximum likelihood estimation when handling such model complexities as random effects and measurement error, for example; and it can also serve as a basis for robust inference with less stringent assumptions on the data generating mechanism....

A comparison of parametric models for mortality graduation. Application to mortality data for the Valencia Region (Spain).

Ana Debón, Francisco Montes, Ramón Sala (2005)

SORT

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The parametric graduation of mortality data has as its objective the satisfactory estimation of the death rates based on mortality data but using an age-dependent function whose parameters are adjusted from the crude rates obtainable directly from the data. This paper proposes a revision of the most commonly used parametric models and compares the result obtained with each of them when they are applied to the mortality data for the Valencia Region. As a result of the comparison, we conclude...

Small-area estimation using adjustment by covariantes.

Nicholas T. Longford (1996)

Qüestiió

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Linear regression models with random effects are applied to estimating the population means of indirectly measured variables in small areas. The proposed method, a hybrid with design- and model-based elements, takes account of the area-level variation and of the uncertainty about the fitted regression model and the area-level population means of the covariates. The method is illustrated on data from the U.S. Department of Labor Literacy Surveys and is informally validated on two states,...

On inconsistency of Hellwig's variable choice method in regression models

Tadeusz Bednarski, Filip Borowicz (2009)

Discussiones Mathematicae Probability and Statistics

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It is shown that a popular variable choice method of Hellwig, which is recommended in the Polish econometric textbooks does not enjoy a very basic consistency property. It means in particular that the method may lead to rejection of significant variables in econometric modeling. A simulation study and a real data analysis case are given to support theoretical results.

Selection in parametric models via some stepdown procedures

Konrad Furmańczyk (2014)

Applicationes Mathematicae

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The paper considers the problem of consistent variable selection in parametic models with the use of stepdown multiple hypothesis procedures. Our approach completes the results of Bunea et al. [J. Statist. Plann. Inference 136 (2006)]. A simulation study supports the results obtained.