All analyses were conducted according to intention to treat (ie, comparing participants in the groups to which they were originally randomly assigned). Analyses were performed using SAS statistical software (version 9.2; SAS Institute Inc). All P values are 2 sided and Wald based, with statistical significance at the P = .05 level. hat factors did the authors consider when accepting or rejecting a candidate from the study? Are there any comments on their methods?
Statistical Analysis
We calculated summary statistics (frequencies, means, and standard deviations) for baseline study participant characteristics by treatment group to identify any important baseline differences across groups. Following the a priori primary analysis plan, differences across treatment groups in the primary outcomes, a clinically meaningful improvement in neck-related dysfunction (≥5 points on NDI)24 or in pain (≥30% reduction on neck pain intensity scale)25 measured at 5 weeks after randomization, were evaluated using modified Poisson regression fitting a Poisson log-link regression model with generalized estimating equations (GEE) and robust standard errors.26 To avoid the pitfall of multiple comparisons related to having 6 treatment groups, we used the Fisher protected least-significant difference approach.27 This approach makes pairwise comparisons among the 6 treatment groups only if the overall omnibus Wald test statistic is significant. Prespecified secondary analyses using linear regression models with GEE and robust standard errors were used to estimate differences in mean changes from baseline across treatment groups for the 5-week NDI and neck pain intensity outcomes. All adjusted models included baseline NDI and neck pain intensity, age, sex, neck pain longer than 5 years in duration, use of medications for neck pain, and race (white non-Hispanic vs other). All adjusted variables were prespecified except for race, which was shown at baseline to have larger than expected differences across groups and met the adjustment criteria of not being related to any other prespecified adjustment variable and may be predictive of outcome response, drop-out, or both.
We used similar adjusted models to analyze the secondary outcomes. For the binary outcomes—more than 7 days in the past week that normal activities were cut by at least one-half due to neck pain, at least 1 day in the past 4 weeks that neck pain kept you in bed or lying down for most of the day, and at least 1 day in the past 4 weeks neck pain kept you out of work or school—we adjusted for only baseline NDI and neck pain intensity because of model-fitting issues for these uncommon outcomes. Further, for the secondary continuous outcome, perceived stress scale, we also adjusted for baseline perceived stress scale response.
All analyses were conducted according to intention to treat (ie, comparing participants in the groups to which they were originally randomly assigned). Analyses were performed using SAS statistical software (version 9.2; SAS Institute Inc). All P values are 2 sided and Wald based, with statistical significance at the P = .05 level.
hat factors did the authors consider when accepting or rejecting a candidate from the study? Are there any comments on their methods?
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