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Table 3 also shows the RR or OR estimates from start models with adjustment for only gender, age, work unit, and effects of other absence spells or days at risk (see section on statistical analyses and footnotes to Table 3), and the mean percentage change of these estimates from the start model to the final model.
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We suggest that the proposed cold start model could aid in the development of optimal cold start strategies.
Did you start modeling immediately?
We need to start modeling what TO do.
Then start up Rhino and start modeling your different pieces in curve form.
The variables were simultaneously entered in the model (start model).
1) Start model adjusted for age, gender, work-place unit.
Final model as start model and for violence and general health.
These parameters indicated that the start model did not fit well (SRMR = 0.067; modification indices > 3.84).
2) Start model adjusted for age, gender, work-place unit, any medium absence, any long absence.
5) Start model adjusted for age, gender, work-place unit, days at risk.
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