ISSN:0277-6715    

DOI:10.1002/sim.4780122402

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1993

数据来源: WILEY

ISSN:0277-6715    

DOI:10.1002/sim.4780122403

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1993

数据来源: WILEY

摘要:

AbstractMany clinical trials yield data on an ordered categorical scale such asvery good, good, moderate, poor. Under the assumption of proportional odds, such data can be analysed using techniques of logistic regression. In simple comparisons of two treatments this approach becomes equivalent to the Mann–Whitney test. In this paper sample size formulae consistent with an eventual logistic regression analysis are derived. The influence on efficiency of the number and breadth of categories will be examined. Effects of misclassification and of stratification are discussed, and examples of the calculations are give

ISSN:0277-6715    

DOI:10.1002/sim.4780122404

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1993

数据来源: WILEY

摘要:

AbstractThe usual meta‐analysis of a sequence of randomized clinical trials only considers the difference between two treatments and produces a point estimate and a confidence interval for a parameter that measures this difference. The usual parameter is the log)odds ratio( linked to Mantel–Haenszel methodology. Inference is made either under the assumption of homogeneity or in a random effects model that takes account of heterogeneity between trials. This paper has two goals. The first is to present a likelihood based method for the estimation of the parameters in the random effects model, which avoids the use of approximating Normal distributions. The second goal is to extend this method to a bivariate random effects model, in which the effects in both groups are supposed random. In this way inference can be made about the relationship between improvement and baseline effect. The method is demonstrated by a meta‐analysis dataset of Collins and La

ISSN:0277-6715    

DOI:10.1002/sim.4780122405

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1993

数据来源: WILEY

摘要:

AbstractWe consider a relative risk and a risk difference model for binomial data, and a rate difference model for Poisson )person year( data. It is assumed that the data are stratified in a large number of small strata. If each stratum has its own parameter in the model, then, due to the large number of parameters, straightforward maximum likelihood leads to inconsistent estimates of the relevant parameters. By contrast to the logistic model, conditioning on the number of events per stratum does not help in eliminating the stratum nuisance parameters. We propose a pseudo likelihood method to overcome these consistency problems. The resulting pseudo maximum likelihood estimates can easily be computed with standard statistical software. Our approach gives a more general framework for the Mantel–Haenszel type estimators proposed in the literature. In the special case of a series of 2 × 2 tables, for the risk and rate difference models, our approach yields exactly thesead hocMantel–Haenszel estimators, while for the relative risk model it gives a close approximation of the Mantel–Haenszel relative risk estimator. For the regression models corresponding to the association measures relative risk, risk difference and rate difference, our method provides analogues of conditional logistic regression, which were not previously ava

ISSN:0277-6715    

DOI:10.1002/sim.4780122406

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1993

数据来源: WILEY

摘要:

AbstractThe predictive value of a statistical model is conceptually different from the explained variation. In this paper we construct a measure of the predictive value of the Cox proportional hazards model, computed from the leave‐one‐out regression coefficients. These coefficients can also be used to calculate a shrinkage factor which can be applied to improve the predictions and that can be used inR2‐type measures of the proportion of explained variation. Our methods are illustrated by a study of chemotherapy for advanced ovarian c

ISSN:0277-6715    

DOI:10.1002/sim.4780122407

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1993

数据来源: WILEY

摘要:

AbstractMultistate survival analysis usually involves a series of detailed regression analyses describing transitions between various states. There is an often neglected need for the many estimates resulting from such an analysis to be re‐synthesized into summary statements, such as prediction of various outcomes from specified patient histories. Arjas and Eerola recently proposed a framework for dynamic probabilistic causality which has calculation of such prediction statements as a central tool. We illustrate these procedures on data from a multicentre bone marrow transplantation study, with death while in remission and relapse as terminal events and recovery of the patients's platelets to a normal level and the onset of acute graft‐versus‐host disease as intermediate events, using Cox regression models throughout. Among the features illustrated by the resulting plots is a strong effect on death while in remission if the platelets do not recover within the first three m

ISSN:0277-6715    

DOI:10.1002/sim.4780122408

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1993

数据来源: WILEY

摘要:

AbstractThe case‐crossover design provides a means to study the effects of transient exposures on the risk of acute illness, for example, the effects of drinking alcohol on the immediate risk of a heart attack. Only cases are required by the design, since each case is effectively its own control; what a case was doing at the time of an acute event is compared with what the case would have been doing usually. Maclure has described an approach based on the Mantel–Haenszel method of analysis. It is shown here how the analysis of case‐crossover designs can be achieved by a method of maximum likelihood. The method is quite general and, in principle, can be used to analyse the joint effects of many transient exposures. For binary exposures the Mantel–Haenszel approach is an approximate solution to the likelihood equations.In practice, case‐crossover designs are limited by the information available on each case's ‘usual’ behaviour. Extracting such information requires in‐depth questioning, but, in principle, it can be obtained. To do so requires careful questionnaire design. The approach is illustrated by analysis of 24 hour alcohol consumption and the risk of myocardial infarction. The problem with this analysis is how to estimate the probability of what a case would ‘usually’ have been doing from information on

ISSN:0277-6715    

DOI:10.1002/sim.4780122409

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1993

数据来源: WILEY

摘要:

AbstractCommon methods of treatment allocation for multi‐centre and/or stratified randomized clinical trials can result in substantial differences between the number of patients allocated to each treatment arm. This can occur in the overall trial for a permuted block design or within individual institutions/strata when using a minimization scheme. This may lead to a bias in the result. Also, these procedures can be predictable, with the possibility of an investigator‐introduced selection bias. An easily implemented method of randomization is proposed which attempts to overcome these problems by balancing treatment allocations both within strata and across the trial as a whole. The method keeps a running tally on total treatment allocation numbers at all stratification levels. When a patient accrues a hierarchical decision rule is applied, and the allocation is deterministic if certain pre‐defined limits are exceeded, and random otherwise. The method is an extension of the big stick design of Soares and Wu, and is related to both Zelen's key number randomization methods and the schemes of Nordle and Brantmark. Simulation studies are used to demonstrate that major imbalances possible with other schemes do not occur using this method, and that the potential for selection bias is much re

ISSN:0277-6715    

DOI:10.1002/sim.4780122410

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1993

数据来源: WILEY

摘要:

AbstractIn a clinical trial comparing different treatments the patients may be rather heterogeneous with regard to their natural prognosis. Simple overall comparison of the treatment groups may lead to a biased estimate of the treatment effect even in a well‐balanced randomized study, at least when survival time is the outcome. An adequate analysis of the treatment effect is only feasible in a multivariate framework where the important prognostic factors are accounted for and, additionally, treatment‐covariate interactions may be evaluated. Analyses using the Cox model are compared with alternative approaches based on the Classification and Regression Tree )CART( technique. Basic differences between these approaches are outlined and discussed in the context of a randomized clinical trial of chemotherapy in patients with brain tumo

ISSN:0277-6715    

DOI:10.1002/sim.4780122411

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1993

数据来源: WILEY