Data analysis
REGRESSION, SECONDARY
We will use descriptive statistics, t-tests, and Chi-square tests as appropriate to compare patients in each study arm. We will assess group differences between baseline and the week before TKR, 6 weeks after TKR, and 6-, 12-, and 24-months after TKR with parametric and nonparametric analyses including one-sample t-tests, Wilcoxon rank sum, and Chi-square tests or Fisher’s exact test of proportions, as appropriate. All tests will be two-sided (unless otherwise stated) and the overall type I error will be maintained at 5%.We will use linear and generalized linear mixed effects regression models to analyze the repeated measures of all outcomes. Although a significant treatment*time interaction will conclude rejection of the hypothesis, in this pilot study we will focus on obtaining estimates of baseline adjusted treatment effects at the end of treatment as preliminary evidence of effectiveness to power a future trial. We will correct the inflation of the type I error due to multiple primary outcomes using Holm’s stepdown procedure. Due to the exploratory nature of the secondary outcomes, we will not adjust the type I error. Our mixed models provide valid inferences when data are missing at random. However, we will also test the plausibility of this assumption and repeat our analysis using pattern-mixture models [