Journal of biopharmaceutical statistics
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Recent progress in biosimilars development is overviewed, with attention to the history of issues and processes leading to current regulations, and to scientific considerations, including progress on design and operational implementation issues that arise and are peculiar to biosimilars trial design and implementation.
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This article proposes a general comparison model for assessing individual agreement of k ≥ 2 raters evaluating n subjects with m ≥ 2 replicated readings. Users can explore total-rater agreement relative to intrarater agreement where any subset of the k raters can be selected in the numerator and denominator. Users are also allowed to compare intrarater agreement among selected raters. ⋯ The method used by the Food and Drug Administration (FDA) for evaluating individual bioequivalence under relative scale becomes the special case of our approach. The IIR is a classical assessment such that the precision of selected raters can be better than; equal to; or worse than that of other raters. The estimation and statistical inference of TIR and IIR are obtained through GEE methodology.
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This article reviews nonparametric alternatives to the mixed model normal theory analysis for the analyses of multicenter clinical trials. Under a mixed model, the traditional analysis is based on maximum likelihood theory under normal errors. This analysis, though, is not robust to outliers. ⋯ These rank-based analyses offer a complete analysis, including estimation of fixed effects and their standard errors, and tests of linear hypotheses. Both rank-based estimates of contrasts and individual treatment effects are reviewed. We illustrate the analyses using real data from a clinical trial.
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Comparative Study
A profile analysis approach using MMRM in acute schizophrenia: a comparison to some traditional approaches.
The analysis of schizophrenia studies is plagued by inefficiency and bias due to much missing data. Mixed-effect models for repeated measures designs help address these problems, but to gain even more efficiency it is desirable to judiciously use additional longitudinal data in such designs by comparing treatment groups over multiple time points. Simulations were conducted to compare a profile analysis approach to other commonly used analysis methods in the presence of data missing at random. One gains efficiency by using a composite contrast over multiple time points when the treatment effect over the time points is not substantially different.