摘要:

AbstractComposite measurement scales (CMS) are increasingly used in medicine to measure complex phenomena or concepts such as disease risk and severity, physical and psychological functioning and quality of life. To investigate the methodology currently used in the construction of CMS, we examined 46 studies recently published in six major medical and epidemiological journals. Important measurement properties such as measurement level, content and construct validity and reliability are often neglected. Statistical methods, particularly multivariate methods are frequently misused; verifications of model relevance and assumptions, and cross‐validations to avoid overfitting are seldom performed. We propose recommendations for the construction and the presentation of CMS, to help authors and investigators to report and choose, respectively, measurement instruments for a complex phenomeno

ISSN:0277-6715    

DOI:10.1002/sim.4780140402

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

年代:1995

数据来源: WILEY

摘要:

AbstractWe present a general approach based on chi‐square goodness‐of‐fit tests for performing tests of significance about the kappa statistic. We make recommendations for the particular goodness‐of fit test to use under different situations. We also compare the test statistics in terms of the generated confidence intervals about the kappa st

ISSN:0277-6715    

DOI:10.1002/sim.4780140403

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

年代:1995

数据来源: WILEY

摘要:

AbstractWe present a Bayesian approach for monitoring multiple outcomes in single‐arm clinical trials. Each patient's response may include both adverse events and efficacy outcomes, possibly occurring at different study times. We use a Dirichlet‐multinomial model to accommodate general discrete multivariate responses. We present Bayesian decision criteria and monitoring boundaries for early termination of studies with unacceptably high rates of adverse outcomes or with low rates of desirable outcomes. Each stopping rule is constructed either to maintain equivalence or to achieve a specified level of improvement of a particular event rate for the experimental treatment, compared with that of standard therapy. We avoid explicit specification of costs and a loss function. We evaluate the joint behaviour of the multiple decision rules using frequentist criteria. One chooses a design by considering several parameterizations under relevant fixed values of the multiple outcome probability vector. Applications include trials where response is the cross‐product of multiple simultaneous binary outcomes, and hierarchical structures that reflect successive stages of treatment response, disease progression and survival. We illustrate the approach with a variety of single‐arm cancer trials, including bio‐chemotherapy acute leukaemia trials, bone marrow transplantation trials, and an anti‐infection trial. The number of elementary patient outcomes in each of these trials varies from three to seven, with as many as four monitoring boundaries running simultaneously. We provide general guidelines for eliciting and parameterizing Dirichlet priors and for specifying design

ISSN:0277-6715    

DOI:10.1002/sim.4780140404

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

年代:1995

数据来源: WILEY

摘要:

AbstractGroup sequential designs for randomized clinical trials allow analyses of accruing data. Most group sequential designs in the literature concern the comparison of two treatments and maintain an overall prespecified type I error. As the number of treatments increases, however, so does the probability of falsely rejecting the null hypothesis. Bayesian statisticians concern themselves with the observed data and abide by the likelihood principle. As long as previous analyses do not change the likelihood, these analyses do not change Bayesian inference. In this paper, we discuss a group sequential design for a proposed randomized clinical trial comparing four treatment regimens. Bayesian ideas underlie the design and posterior probability calculations determine the criteria for stopping accrual to one or more of the treatments. We use computer simulation to estimate the frequentist properties of the design, information of interest to many of our collaborators. We show that relatively simple posterior probability calculations, along with simulations to calculate power under alternative hypotheses, can produce appealing designs for randomized clinical trials.

ISSN:0277-6715    

DOI:10.1002/sim.4780140405

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

年代:1995

数据来源: WILEY

摘要:

AbstractMany meta‐analyses use a random‐effects model to account for heterogeneity among study results, beyond the variation associated with fixed effects. A random‐effects regression approach for the synthesis of 2 × 2 tables allows the inclusion of covariates that may explain heterogeneity. A simulation study found that the random‐effects regression method performs well in the context of a meta‐analysis of the efficacy of a vaccine for the prevention of tuberculosis, where certain factors are thought to modify vaccine efficacy. A smoothed estimator of the within‐study variances produced less bias in the estimated regression coefficients. The method provided very good power for detecting a non‐zero intercept term (representing overall treatment efficacy) but low power for detecting a weak covariate in a meta‐analysis of 10 studies. We illustrate the model by exploring the relationship between vaccine efficacy and one factor thought to modify efficacy. The model also applies to the meta‐analysis of continuous outcomes when cova

ISSN:0277-6715    

DOI:10.1002/sim.4780140406

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

年代:1995

数据来源: WILEY

摘要:

AbstractWe investigate population‐averaged (PA) and cluster‐specific (CS) associations for clustered binary logistic regression in the context of a longitudinal clinical trial that investigated the association between tooth‐specific visual elastase kit results and periodontal disease progression within 26 weeks of follow‐up. We address estimation of population‐averaged logistic regression models with generalized estimating equations (GEE), and conditional likelihood (CL) and mixed effects (ME) estimation of CS logistic regression models. Of particular interest is the impact of clusters that do not provide information for conditional likelihood methods (non‐informative clusters) on inferences based upon the various methodologies. The empirical and analytical results indicate that CL methods yield smaller test statistics than ME methods when non‐informative clusters exist, and that CL estimates are less efficient than ME estimates under certain conditions. Moreover, previously reported relationships between population‐averaged and cluster‐specific parameters appear to hold for the corresponding estimates in the presence

ISSN:0277-6715    

DOI:10.1002/sim.4780140407

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

年代:1995

数据来源: WILEY

摘要:

AbstractThis paper evaluates the performance of four variable selection methods suitable for case‐control studies. Two of the methods are logistic regression and the rank transformed version of it which uses the ranks of the explanatory variables in place of the original observations. The third method is based on Kendall's τbcorrelations. I propose a fourth method, a sign score regression model to select variables. To evaluate these four methods, I generate many data sets for a case group and a control group with the use of several different distributions and covariance matrices. I evaluate the methods on their ability to select correctly the variables related to case‐control status while not selecting the unrelated variables. Using this criterion, the sign score regression method and the τbmethod are more effective than the other two methods with uncorrelated or weakly correlated variables. The sign score regression method is more effective than the τbmethod for all simulations that use normal variables and for some that use log‐normal variables. Overall, the sign score regression method is the most effective variable selection method for data sets that have low or moderate correlations between v

ISSN:0277-6715    

DOI:10.1002/sim.4780140408

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

年代:1995

数据来源: WILEY

ISSN:0277-6715    

DOI:10.1002/sim.4780140409

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

年代:1995

数据来源: WILEY

ISSN:0277-6715    

DOI:10.1002/sim.4780140401

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

年代:1995

数据来源: WILEY