Finally, we will conduct incremental cost-benefit regression analysis to identify subgroups where the intervention is particularly cost-effective.
To obtain the incremental QALY multiple regression analysis was applied to control for the differences in baseline utility.
An incremental net benefit regression analysis will be performed to ascertain which sub-groups benefit more from the intervention in terms of superior cost-effectiveness.
Ancillary analyses (i.e., incremental net-benefit regression analysis) will identify subgroups of workers (e.g., participants with and without impaired work functioning or mental health) who derive particular benefit from the intervention.
The same set of predictor variables will also be used in an incremental net benefit regression analysis to addresses the research question in what groups the intervention is likely to be particularly cost-effective.
Even though we can examine incremental validity, similar to a hierarchical multiple regression analysis, model fit cannot be computed.
Incremental net-benefits are analysed using a regression analysis approach [ 67] and helps to identify sub-groups for which the intervention is particularly cost-effective.
Furthermore, the regression analysis shows that IdentifiedTM adds incremental variance over IntrinsicTM to the explanation of PTI.
With QOL scores (PCS and MCS) as dependent variables, Hierarchical Multiple Regression analysis was performed to test the incremental variance by any given set of independent variables.
With demographic and work characteristics and organizational behavior factors as independent variables, Hierarchical Multiple Regression analysis was conducted to test the incremental variance by independent variables (i.e. PCS and MCS scores).
The per minute ventilation/carbon dioxide output slope was calculated using a linear regression analysis based on all points of the incremental exercise [ 20].
