Statistics in medicine
-
Statistics in medicine · Apr 1998
ReviewKappa-like indices of observer agreement viewed from a latent class perspective.
It is common practice to assess consistency of diagnostic ratings in terms of 'agreement beyond chance'. To explore the interpretation of such a term we consider relevant statistical techniques such as Cohen's kappa and log-linear models for agreement on nominal ratings. ⋯ As a result it is shown that Cohen's kappa may be an inadequate and biased index of chance-corrected agreement in studies of intra-observer as well as inter-observer consistency. We suggest a more critical use and interpretation of measures gauging observer reliability by the amount of agreement beyond chance.
-
Statistics in medicine · Dec 1997
Incorporation of sequential trials into a fixed effects meta-analysis.
The technique of meta-analysis provides a systematic and quantitative approach to the summary of results from a collection of similar randomized studies. Comprehensive methodology exists for analysis when all trials are of a fixed sample size design, but this is based on assumptions which are no longer valid when incorporating sequentially designed studies. ⋯ The aim is to quantify the extent to which bias is introduced. It was found that when incorporating two alternative sequential designs, the triangular test and the O'Brien and Fleming procedure, the results of a conventional meta-analysis remain accurate.
-
Statistics in medicine · Nov 1997
ReviewMethods of correcting for multiple testing: operating characteristics.
We examine the operating characteristics of 17 methods for correcting p-values for multiple testing on synthetic data with known statistical properties. These methods are derived p-values only and not the raw data. With the test cases, we systematically varied the number of p-values, the proportion of false null hypotheses, the probability that a false null hypothesis would result in a p-value less than 5 per cent and the degree of correlation between p-values. ⋯ Unfortunately, however, a uniformly best method of those examined does not exist. A suggested strategy for examining corrections uses a succession of methods that are increasingly lax in family-wise error. A computer program for these corrections is available.
-
Statistics in medicine · Oct 1997
ReviewUsing the general linear mixed model to analyse unbalanced repeated measures and longitudinal data.
The general linear mixed model provides a useful approach for analysing a wide variety of data structures which practising statisticians often encounter. Two such data structures which can be problematic to analyse are unbalanced repeated measures data and longitudinal data. Owing to recent advances in methods and software, the mixed model analysis is now readily available to data analysts. ⋯ The extra complexity involved is compensated for by the additional flexibility it provides in model fitting. The purpose of this tutorial is to provide readers with a sufficient introduction to the theory to understand the method and a more extensive discussion of model fitting and checking in order to provide guidelines for its use. We provide two detailed case studies, one a clinical trial with repeated measures and dropouts, and one an epidemiological survey with longitudinal follow-up.
-
Statistics in medicine · Sep 1997
Ten-year follow-up of ARIMA forecasts of attendances at accident and emergency departments in the Trent region.
Forecasting models for first, return and total attendances at accident and emergency (A&E) departments and yearly forecasts were developed ten years ago for all the health districts in the Trent region in England. The one-yearly forecasts had been checked against the 1986 actual figures and found accurate for first attendances but less accurate for return attendances. The forecasts for 1993 and 1994 were much further from the actual figures than the 1986 forecasts, with an increasing bias towards overestimation, particularly for reattendances. ⋯ The ten-year strategic plan for Trent Regional Health Authority overestimated the increase in the number of first attendances at A&E departments in the Trent region. The forecasting methodology on which it was based could be improved by incorporating the ARIMA method into planning at the health district level. New forecasts or updated ones need to be calculated yearly.