A nested-factorial design was employed with four fixed independent variables of gender, subject (nested within gender), span (2, 4, 6, and 8 cm) and wrist posture (neutral, maximal extension and maximal flexion).
In this paper, we present distribution-free tests to evaluate the effect of multiple treatments when there are a large number of repeated measurements from each subject nested in a treatment.
Subject nested within gender was included as a random factor variable to account for interindividual variation.
For these models a mixed random effect was considered with the subject nested into sequence.
The ANCOVA model included sequence, treatment, and period as fixed effects, and subject nested within sequence as a random effect.
Considering the cross-over design, the primary analysis was performed by analysis of variance (ANOVA) with fixed factors for treatment, period, sequence and subject nested within sequence.
This was performed with the use of hierarchical linear models that included subject (nested by supplement group), time (2, 13, or 52 wk), supplement group (calcium or placebo) plus a time-by-group interaction time-by-group interaction
This was achieved through the use of hierarchical linear models that included supplement trial group (calcium and placebo), subject (nested by supplement group), and time point (L52, NPNL, and F52).
The log-transformed values of UAER were analyzed by a PROC MIXED model with sequence, treatment, and period as fixed factors and subject (nested in sequence) as a random factor.
In part 2, an analysis of variance (anova) was performed on the log-transformed AUC 0,∞), AUC 0, tlast) and Cmax fitting sequence and fed/fasting status as fixed effects and subject nested within sequence as a random effect.
The effect of the intervention on outcomes measured on a continuous scale will be estimated and tested using mixed model analysis of variance in which time and treatment group will be fixed effects and GP practice and subject nested within practice will be random effects.
