Statistics in medicine
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Statistics in medicine · Aug 2002
Comparative StudyA solution to the problem of separation in logistic regression.
The phenomenon of separation or monotone likelihood is observed in the fitting process of a logistic model if the likelihood converges while at least one parameter estimate diverges to +/- infinity. Separation primarily occurs in small samples with several unbalanced and highly predictive risk factors. ⋯ Corresponding Wald tests and confidence intervals are available but it is shown that penalized likelihood ratio tests and profile penalized likelihood confidence intervals are often preferable. The clear advantage of the procedure over previous options of analysis is impressively demonstrated by the statistical analysis of two cancer studies.
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Statistics in medicine · Jun 2002
Simultaneous estimation of intrarater and interrater agreement for multiple raters under order restrictions for a binary trait.
It is valuable in many studies to assess both intrarater and interrater agreement. Most measures of intrarater agreement do not adjust for unequal estimates of prevalence between the separate rating occasions for a given rater and measures of interrater agreement typically ignore data from the second set of assessments when raters make duplicate assessments. In the event when both measures are assessed there are instances where interrater agreement is larger than at least one of the corresponding intrarater agreements. ⋯ In the situation of multiple raters making duplicate assessments on all subjects, the authors propose properties for an agreement measure based on the odds ratio for a dichotomous trait: (i) estimate a single prevalence across two reading occasions for each rater; (ii) estimate pairwise interrater agreement from all available data; (iii) bound the pairwise interrater agreement above by the corresponding intrarater agreements. Estimation of odds ratios under these properties is done by maximizing the multinomial likelihood with constraints using generalized log-linear models in combination with a generalization of the Lemke-Dykstra iterative-incremental algorithm. An example from a mammography examination reliability study is used to demonstrate the new method.
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Statistics in medicine · Jun 2002
Comparative StudyStatistical methods for assessing the influence of study characteristics on treatment effects in 'meta-epidemiological' research.
Biases in systematic reviews and meta-analyses may be examined in 'meta-epidemiological' studies, in which the influence of trial characteristics such as measures of study quality on treatment effect estimates is explored. Published studies to date have analysed data from collections of meta-analyses with binary outcomes, using logistic regression models that assume that there is no between- or within-meta-analysis heterogeneity. ⋯ We also consider how to allow for the confounding effects of different trial characteristics. We show that both within- and between meta-analysis heterogeneity may be of importance in the analysis of meta-epidemiological studies, and that confounding exists between the effects of publication status and trial quality.
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Statistics in medicine · Jun 2002
Exploring sources of heterogeneity in systematic reviews of diagnostic tests.
It is indispensable for any meta-analysis that potential sources of heterogeneity are examined, before one considers pooling the results of primary studies into summary estimates with enhanced precision. In reviews of studies on the diagnostic accuracy of tests, variability beyond chance can be attributed to between-study differences in the selected cutpoint for positivity, in patient selection and clinical setting, in the type of test used, in the type of reference standard, or any combination of these factors. In addition, heterogeneity in study results can also be caused by flaws in study design. ⋯ Application of regression techniques in meta-analysis of diagnostic tests can provide relevant additional information. Results of such analyses will help understand problems with the transferability of diagnostic tests and to point out flaws in primary studies. As such, they can guide the design of future studies.