Statistical Analyses
cancer
REGRESSION, CANCER
Descriptive characteristics are presented as mean and standard deviation (Multiple linear regression was performed to examine the associations of (1) MVPA level at 12-month follow-up and (2) long-term MVPA patterns with each cancer-related health outcome, respectively. For the analyses with long-term MVPA patterns as independent variable, the variable was included in models using dummy-coding (High & Increasing/ High & Decreasing/ Low & Increasing/ Low & Decreasing) and the category “Low & Decreasing” was used as reference in the analyses to test the hypothesis that high and/or increased MVPA after the end of an exercise intervention would be associated with improved health outcomes compared to those remaining less physically active. All cancer-related health outcomes were treated as continuous variables. All models included immediately post-intervention value of the health outcome to increase precision and were adjusted for age, gender, and cancer treatment. The results are presented as unstandardized regression coefficients (β) with 95% Confidence Intervals (95% CI). The unstandardized coefficients can be interpreted as the mean change in the outcome (1) per 30 minutes/day increase in MVPA for the analyses with MVPA level at 12-month follow-up and (2) when comparing the group “High & Increasing,” “High & Decreasing” or “Low & Increasing” with the reference group “Low & Decreasing” for the analyses with long-term MVPA patterns.Missing data were <10% in all cancer-related health outcomes, except for functioning in daily life (13% missing) and cardiorespiratory fitness (24% missing). Multiple imputation was used to handle missing data in the cancer-related health outcomes.