摘要:

AbstractReference ranges which take time (such as age) into account are often required in medicine, but simple, systematic and efficient statistical methods for constructing them are lacking. A method is described which is based on low order polynomial curves (linear, quadratic or occasionally cubic), together with guidelines for when and how to apply a logarithmic transformation to the variable analysed, testing for departures from normality, and assessment of the adequacy of the reference range which is constructed from the regression line plus or minus a multiple of the standard deviation. Standard statistical packages may be used to carry out the calculations. The question of comparing two or more groups of patients is addressed. Three examples are discussed in detail.

ISSN:0277-6715    

DOI:10.1002/sim.4780100502

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

年代:1991

数据来源: WILEY

摘要:

AbstractReference ranges are very widely used in medicine, and are typically computed as mean plus or minus two standard deviations. However, their precise statistical basis is rarely discussed, and is open to different interpretations. They are sometimes calculated using the Studenttdistribution and satisfy the condition that the expected coverage of the reference population is some nominal value such as 95 per cent or 99 per cent. A case is made for using reference ranges which are based on estimating symmetric centiles of the underlying normal distribution, and appropriate formulae are given. The simplest such estimator, the sample mean plus or minus the normal‐based number of sample standard deviations, is shown to have both theoretical and practical advantage

ISSN:0277-6715    

DOI:10.1002/sim.4780100503

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

年代:1991

数据来源: WILEY

摘要:

AbstractNon‐linear relationships between two variables are often detected as a result of a preliminary statistical test for linearity. Common approaches to dealing with non‐linearity are to (a) make a linearizing transformation in the independent variable or (b) fit a relationship that is non‐linear in the independent variable, such as including a quadratic term. With either approach, the resulting test for association between the two variables can have an inflated type I error. We consider testing the significance of the quadratic term in a quadratic model as a preliminary test for non‐linearity. Using simulation experiments and asymptotic arguments, we quantify the type I error inflation and suggest simple modifications of standard practice to protect the size of the type I error. In the case of quadratic regression, the type I error will be increased by roughly 50 per cent. The simple strategy of appropriately correcting the α‐level is shown to have minimal loss of power if the relationship is truly linear. In the case of a linearizing transformation, the impact on the type I error will depend on the values of the independent variable and on the set of potential linearizing transformations considered. Simulation results suggest that a procedure which adjusts the test statistic according to the results of the preliminary test may offer adequate

ISSN:0277-6715    

DOI:10.1002/sim.4780100504

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

年代:1991

数据来源: WILEY

摘要:

AbstractA common mode of regression analysis is a stepwise regression. One of the problems associated with the stepwise algorithm is that the data analyst may wrongly identify the selected variables astheimportant variables. We propose a simple table as an aid in examining and reporting stepwise regression analyses. The key to our proposal is recognition of ‘close alternatives’, that is, those variables excluded from selection by the inclusion of another variable. This presentation should encourage the analyst and reader to think in terms of sets of variables that, together, represent factors associated with the outc

ISSN:0277-6715    

DOI:10.1002/sim.4780100505

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

年代:1991

数据来源: WILEY

摘要:

AbstractOne encounters in the literature estimates of some rates of genetic and congenital disorders based on log‐linear methods to model possible interactions among sources. Often the analyst chooses the simplest model consistent with the data for estimation of the size of a closed population and calculates confidence intervals on the assumption that this simple model is correct. However, despite an apparent excellent fit of the data to such a model, we note here that the resulting confidence intervals may well be misleading in that they can fail to provide an adequate coverage probability. We illustrate this with a simulation for a hypothetical population based on data reported in the literature from three sources. The simulated nominal 95 per cent confidence intervals contained the modelled population size only 30 per cent of the time. Only if external considerations justify the assumption of plausible interactions of sources would use of the simpler model's interval be justifie

ISSN:0277-6715    

DOI:10.1002/sim.4780100506

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

年代:1991

数据来源: WILEY

摘要:

AbstractIn order to examine the bias of the estimate of the log odds ratio in a 2 × 2 contingency table, Walter computed the entire distribution of the estimated log odds ratio using various small sample sizes. This is equivalent to computing the distribution of the estimated parameterb1in a logistic regression with one independent binary variable. In this paper, the distributions of the estimated parametersb1andb2for two independent binary variables are computed for some small sample logistic regressions using six different estimation methods based on maximum likelihood. These estimates are then compared to the true parameter values. The best estimation method depends on the frequency of the outcome of interest and on whether the bias or mean square error is considered more important

ISSN:0277-6715    

DOI:10.1002/sim.4780100507

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

年代:1991

数据来源: WILEY

摘要:

AbstractBased on historical regression analyses of survival one may calculate expected survival curves for patients in a study group, based on their observed covariates. This note discusses this calculation and illustrates it on a comparison of the survival of a certain group of liver transplant patients to their prognosis under conservative treatment.

ISSN:0277-6715    

DOI:10.1002/sim.4780100508

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

年代:1991

数据来源: WILEY

摘要:

AbstractNested case‐control studies, or case‐control studies within a cohort, combine the advantages of cohort studies with the efficiency of case‐control studies. Case‐control studies can often be viewed as having two stages; the first stage consists of vital status, disease, and basic covariate ascertainment, and the second stage consists of detailed covariate and exposure ascertainment. Breslow and Cain (1988) and Breslow and Zhao (1988) recently showed that conventional analyses of such two‐stage studies may ignore some of the available information. In this paper, we show how one can adapt the pseudo‐likelihood analyses developed by Kalbfleisch and Lawless (1988) to the analysis of data from two‐stage case‐

ISSN:0277-6715    

DOI:10.1002/sim.4780100509

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

年代:1991

数据来源: WILEY

摘要:

AbstractTwo hazard ratio estimators based on the logrank test are investigated using a simulation study. The Pike estimator (ratio of relative death rates) was shown to be consistently less biased than the Peto (1‐step) estimator. The latter has recently been advocated as the method of choice for point and interval estimation.8Both estimators exhibited bias with increasing hazard ratios, although the bias was minimal for effects less than 3. The confidence intervals also did not achieve the nominal coverage with increasing hazard ratios, but again the Pike estimator was superior. The coverage could be improved by recalculation of the variance incorporating the point estimate. For a hazard ratio of less than 3 we recommend the use of the Pike estimator, otherwise it is necessary to use a more complex method of estimatio

ISSN:0277-6715    

DOI:10.1002/sim.4780100510

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

年代:1991

数据来源: WILEY

摘要:

AbstractMethods of multiple group discriminant analysis have not been fully studied with respect to classification into more than two populations when the covariate distributions are normal or non‐normal. The present study examines the classification performance of several multiple discrimination methods under a variety of simulated continuous normal and non‐normal covariate distributions. The methods include polychotomous logistic regression, multiple group linear discriminant analysis, kernel density estimation, and rank transformations of the data as input into the linear function. The parameters of interest were distance among populations, configuration of population mean vectors (collinear or forming the vertices of a regular simplex), skewness, kurtosis and bimodality. Simulation of the last three parameters was by log‐normal, sinh−1normal and a two‐component mixture of normal distributions, respectively. Results with three trivariate populations show that for all distributions, logistic discrimination classifies close to the optimal under Neyman‐Pearson allocation. These results suggest that logistic discrimination is preferable to other widely‐used methods for multiple group classification with non‐normal data, and is comparable to classification by multiple linear discrimination w

ISSN:0277-6715    

DOI:10.1002/sim.4780100511

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

年代:1991

数据来源: WILEY