Statistics in medicine
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Statistics in medicine · May 2008
ReviewA critical appraisal of propensity-score matching in the medical literature between 1996 and 2003.
Propensity-score methods are increasingly being used to reduce the impact of treatment-selection bias in the estimation of treatment effects using observational data. Commonly used propensity-score methods include covariate adjustment using the propensity score, stratification on the propensity score, and propensity-score matching. Empirical and theoretical research has demonstrated that matching on the propensity score eliminates a greater proportion of baseline differences between treated and untreated subjects than does stratification on the propensity score. ⋯ Thirteen (28 per cent) of the articles explicitly used statistical methods appropriate for the analysis of matched data when estimating the treatment effect and its statistical significance. Common errors included using the log-rank test to compare Kaplan-Meier survival curves in the matched sample, using Cox regression, logistic regression, chi-squared tests, t-tests, and Wilcoxon rank sum tests in the matched sample, thereby failing to account for the matched nature of the data. We provide guidelines for the analysis and reporting of studies that employ propensity-score matching.
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We consider evaluation and comparison of the diagnostic accuracy of biomarkers with continuous test outcomes, possibly correlated due to repeated measurements. We develop nonparametric group sequential testing procedures to evaluate and compare the area of biomarkers under their receiver operating characteristic curves, with either independent or paired test outcomes. These procedures rely on the construction of a two-dimensional statistic of Whitehead (Statist. Med. 1999; 18:2271-2286) so that design methods based on Brownian motion can be applied.
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Statistics in medicine · May 2008
Adaptive dose finding based on t-statistic for dose-response trials.
The goals of phase II dose-response studies are to prove that the treatment is effective and to choose the dose for further development. Randomized designs with equal allocation to either a high dose and placebo or to each of several doses and placebo are typically used. ⋯ We propose an adaptive design for dose-response trials that concentrates the allocation of subjects in one or more areas of interest, for example, near a minimum clinically important effect level, or near some maximal effect level, and also allows for the possibility to stop the trial early if needed. The proposed adaptive design yields higher power to detect a dose-response relationship, higher power in comparison with placebo, and selects the correct dose more frequently compared with a corresponding randomized design with equal allocation to doses.
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Statistics in medicine · Feb 2008
Sample size calculation for the Wilcoxon-Mann-Whitney test adjusting for ties.
In this paper we study sample size calculation methods for the asymptotic Wilcoxon-Mann-Whitney test for data with or without ties. The existing methods are applicable either to data with ties or to data without ties but not to both cases. ⋯ In addition, the new method can be applied to both data with or without ties. Simulations have demonstrated that the new sample size formula performs very well as the corresponding actual powers are close to the nominal powers.
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Statistics in medicine · Dec 2007
Comparative StudyA competing risks analysis of bloodstream infection after stem-cell transplantation using subdistribution hazards and cause-specific hazards.
After peripheral blood stem-cell transplantation, patients treated for severe haematologic diseases enter a critical phase (neutropenia). Analysis of bloodstream infection during neutropenia has to account for competing risks. ⋯ Proportional subdistribution hazards modelling of the subdistribution of the CIF is establishing itself as an interpretation-friendly alternative. We apply both methods and discuss their relative merits.