Optimal crossover designs for the comparison of two treatments in the presence of carryover effects and autocorrelated errors
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Publication:3759751
DOI10.1093/biomet/74.2.311zbMath0622.62077OpenAlexW2081179957MaRDI QIDQ3759751
Publication date: 1987
Published in: Biometrika (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1093/biomet/74.2.311
tablesinformation matrixlinear modelautoregressive processautocorrelated errorsdependent errorscomparison of two treatmentscarryover effectsEfficienciesdirect and first-order carryover treatment effectsfixed subject effectsoptimal crossover designs
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Modelling and optimality in the design of crossover studies for medical applications ⋮ Optimal crossover designs when carryover effects are proportional to direct effects ⋮ Optimal repeated measurements designs: The linear optimality equations ⋮ Crossover designs based on type I orthogonal arrays for a self and simple mixed carryover effects model with correlated errors ⋮ Extension and necessity of Cheng and Wu conditions ⋮ Optimal change-over designs for correlated observations ⋮ Optimal two treatment repeated measurement designs for three periods ⋮ Robust assessment of two-treatment higher-order cross-over designs against missing values ⋮ Computer-Generated Change-Over Designs for Correlated Observations ⋮ Trend-resistant and cost-efficient cross-over designs for mixed models ⋮ On optimal two-period repeated measurements designs ⋮ CONSTRUCTION OF CROSSOVER DESIGNS WITH CORRELATED ERRORS ⋮ Adaptive two‐treatment two‐period crossover design for binary treatment responses ⋮ The construction of nearly balanced and nearly strongly balanced uniform cross-over designs ⋮ Repeated measurements designs - a review ⋮ Min-max crossover designs for two treatments binary and Poisson crossover trials ⋮ Crossover designs for two-treatment clinical trials ⋮ Estimating treatment effects in clinical crossover trials ⋮ Crossover designs with correlated observations ⋮ Allocation rules for adaptive repeated measurements designs
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