摘要:

AbstractMINQUE (Minimum Norm Quadratic Unbiased Estimators) theory is applied to the problem of estimation of variance components in family data (siblings) with variable family size. Using this approach, the traditional iterative maximum likelihood estimators are shown to be asymptotically normal, even though the data come from non‐identical parent distributions. Asymptotic expressions are also obtained for the variance of the MINQUE estimators which hold even if the data are decidedly non‐normal (e.g. a mixture of normals). In the case of normal data, exact small‐sample variance estimates are derived. Simulations demonstrate the fast rate of convergence to asymptotic properties as the number of families increases. These desirable qualities suggest that the easy to compute MINQUE class of estimators may provide a useful alternative method for modelling familial aggreg

ISSN:0323-3847    

DOI:10.1002/bimj.4710350802

出版商:WILEY‐VCH Verlag    

年代:1993

数据来源: WILEY

ISSN:0323-3847    

DOI:10.1002/bimj.4710350803

出版商:WILEY‐VCH Verlag    

年代:1993

数据来源: WILEY

摘要:

AbstractIn this paper a generalization of the Poisson regression model indexed by a shape parameter is proposed for the analysis of life table and follow‐up data with concomitant variables. The model is suitable for analysis of extra‐Poisson variation data. The model is used to fit the survival data given in Holford (1980). The model parameters, the hazard and survival functions are estimated by the method of maximum likelihood. The results obtained from this study seem to be comparable to those obtained by Chen (1988). Approximate tests of the dispersion and goodness‐of‐fit of the data to the model are also di

ISSN:0323-3847    

DOI:10.1002/bimj.4710350804

出版商:WILEY‐VCH Verlag    

年代:1993

数据来源: WILEY

ISSN:0323-3847    

DOI:10.1002/bimj.4710350805

出版商:WILEY‐VCH Verlag    

年代:1993

数据来源: WILEY

摘要:

AbstractIn analysis of variance the assumption of non‐additivity has more serious consequences on the interpretation of results than the assumptions of non‐normality or non‐homogeneity of variances. Tukey (1949, 1955) suggested a procedure for separating out a single degree of freedom for non‐additivity for two factor and multi‐factor experiments, respectively. In multifactor experiments Tukey's procedure does not indicate which combinations of the factors contribute to non‐additivity. In this paper a procedure is proposed which separates out a sum of squares with a single degree of freedom from each of the 2P−P−1 interactions in aP‐

ISSN:0323-3847    

DOI:10.1002/bimj.4710350806

出版商:WILEY‐VCH Verlag    

年代:1993

数据来源: WILEY

摘要:

AbstractFirst it is shown that an estimate of the variance of the sample‐mean in systematic sampling from a non‐autocorrelated population with linear trend, which is published in textbooks, isn't a suitable estimate: It is biased and not dependent on the essential parameter, the slope of the linear trend.In section 2 an unbiased estimate of the variance is given. As estimate of the sample‐mean we take the same as usually used in literature.In section 3 a centric estimate of the sample‐mean is introduced, which takes into consideration the slope of the trendline. It is shown that this estimate is unbiased; an unbiased estimate of its variance i

ISSN:0323-3847    

DOI:10.1002/bimj.4710350807

出版商:WILEY‐VCH Verlag    

年代:1993

数据来源: WILEY

ISSN:0323-3847    

DOI:10.1002/bimj.4710350808

出版商:WILEY‐VCH Verlag    

年代:1993

数据来源: WILEY

摘要:

AbstractThe Cochran‐Armitage test has commonly been used for a trend test in binomial proportions. The quasi‐likelihood method provides a simple approach to model extra‐binomial proportions. Two versions of the score and Wald tests using different parameterizations for the extra‐binomial variance were investigated: one in terms of intercluster correlation, and another in terms of variance. The Monte Carlo simulation was used to evaluate the performance of the each version of the score test and the Wald test, and the Cochran‐Armitage test.The simulation shows that the Cochran‐Armitage test has the proper size only for the binomial sample data, and the test is no longer valid when applied to the extra‐binomial data. The Wald test is more likely to exceed the nominal level than the score test under either intercluster correlation model or variance model. Both score tests performed very well even with the binomial data; the tests control the type I error and in the meantime maintain the power of detecting the dose effects. Based on the design considered in this paper, the two scores test are comparable. The score test based on the intercluster correlations model seems better controlling the Type I error but appears less powerful than that based on the variance model. An example from a developmental toxicity experi

ISSN:0323-3847    

DOI:10.1002/bimj.4710350809

出版商:WILEY‐VCH Verlag    

年代:1993

数据来源: WILEY

摘要:

AbstractPerformance of biological entities are defined, in general bykinter‐dependent traits whose error variances are heterogeneous. A method of arriving at “Performance Scores” for the entities along with a multivariate test of significance ofk‐trait differences is described. They are used to compute, for each entity, a “Performance Index” on which a ranking of the relative performance is obtained. The improvement in the present method over an earlier one is illustrated with a numeri

ISSN:0323-3847    

DOI:10.1002/bimj.4710350810

出版商:WILEY‐VCH Verlag    

年代:1993

数据来源: WILEY

摘要:

AbstractA fundamental research goal in clinical studies of progressive, multi‐stage disease is to understand its natural history and its relationship with prognostic factors. Our current understanding of this topic is based on the use of two‐stage methods for event‐time analysis which neglect intermediate transition information. In contrast, a multi‐stage model utilizes all available data and provides more accurate insight into disease progression. We specify a forward‐flowing multi‐stage Markov model based on the discrete clinical stages of disease. By assuming the process to be Markovian, we avoid unnecessary complications to our numerical estimation procedure. Due to noncontinuous patient monitoring and the chronic nature of progressive disease, heavy right‐ and interval‐censoring exists in the transition data. We develop a modified ECM algorithm to numerically carry out the otherwise complicated parameter estimation for this process. We also identify significant prognostic factors relevant to each transition, along with the relative importance of each prognostic factor. The numerical estimation is stable, and the parameter estimates are maximum likelihood estimates (Meng, 1990). In general our forward‐flowing multi‐stage models provide a flexible framework for the study of the effects of prognostic factors on progression among several stages. We apply our Markov model to a dataset of malignant melanoma patients, and present an inferential discussion. Results from our multi‐stage Markov model provide an improved understanding of

ISSN:0323-3847    

DOI:10.1002/bimj.4710350811

出版商:WILEY‐VCH Verlag    

年代:1993

数据来源: WILEY