1989
DOI: 10.4324/9780203009277
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Design and Analysis of Cross-Over Trials

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Cited by 649 publications
(453 citation statements)
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“…The response to treatment was analysed as a standard two-phase crossover trial with binary data. Estimates of true treatment success rates were derived using a log-linear model [23]. The exact p-value was calculated from Prescott's test.…”
Section: Discussionmentioning
confidence: 99%
“…The response to treatment was analysed as a standard two-phase crossover trial with binary data. Estimates of true treatment success rates were derived using a log-linear model [23]. The exact p-value was calculated from Prescott's test.…”
Section: Discussionmentioning
confidence: 99%
“…When applicable, regression models benefitted from the robust standard error approach [29], so that the participant's series of repeated measurements were considered as individual clusters. Absence of a carryover effect was checked before treatment-effect analysis, following a method described elsewhere [30]. Statistical comparisons were two-tailed, and all testing was conducted at a ¼ 0.05, on per protocol data.…”
Section: Methodsmentioning
confidence: 99%
“…Jones and Keward [14] suggest the use of the ordinary least squares (OLS) covariance estimate is in keeping with the spirit of this approach. However, for data which are unbalanced or have missing values, so that the OLS and restricted maximum likelihood (REML) estimates do not coincide, it may be more practical to simply adopt the unstructured REML estimate, which is widely implemented in existing software.…”
Section: Box's Correctionmentioning
confidence: 98%