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Predictors of FCR, distress and QoL at baseline will be explored using multiple linear regression.
Factors associated with missing data (such as demographics and values of primary and important secondary outcome variables at baseline) will be explored.
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Baseline data will be explored by descriptive statistics.
In addition to these outcome analyses, comparative cost analysis of the two programs, potential mediators of intervention success, and baseline moderators of intervention effects will be explored to better determine which subgroups do best with which type of intervention.
Any baseline imbalances (p < 0.05) will be explored as a possible factor to adjust for when the outcome measures are analyzed.
The influence of baseline patient characteristics on this outcome will be explored using logistical regression procedures.
Baseline differences between the treatment groups will be explored with independent t tests and chi square tests.
The predictive validity of participants' baseline characteristics on treatment retention and outcomes will be explored.
Any evidence of selection bias in rate of uptake to the research and in baseline descriptive statistics between the control and intervention practices will be explored.
Analyses of treatment group differences in change from baseline in fasting plasma glucose, weight, waist circumference, triglycerides, lipid profile, and blood pressure will be explored.
Sound will be explored in many guises.
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CEO of Professional Science Editing for Scientists @ prosciediting.com