Improving the Health and Safety of Transit Workers with Corresponding Impacts on the Bottom Line (2020) / Chapter Skim
Currently Skimming:
Pages 127-136
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
From page 127... ...
C-1 A P P E N D I X C Regression Models for Indianapolis, Indiana; Rochester, New York; and Louisville, Kentucky C.1 Limitations of Regression Analysis The results of the Indianapolis Public Transportation Corporation (IndyGo) , Rochester Regional Transit Service (RTS)
|
From page 128... ...
C-2 Improving the Health and Safety of Transit Workers with Corresponding Impacts on the Bottom Line time, infrequency coupled with a small population would create high variability from year to year and the downward trend might not be detected. It is possible that an agency's wellness program may have been substantially beneficial, but in addition to the benefits not being picked up by the metrics, the effects of the program may have been diffused.
|
From page 129... ...
Regression Models for Indianapolis, Indiana; Rochester, New York; and Louisville, Kentucky C-3 employees who do not opt in for insurance do not receive access to the program and act as the control group. As Bushnell notes, those who obtain insurance through their spouse may work for employers offering less generous health benefits and may have different working conditions and health characteristics than those who have spouses with more generous plans (Bushnell, Li, and Landen 2011)
|
From page 130... ...
C-4 Improving the Health and Safety of Transit Workers with Corresponding Impacts on the Bottom Line 1. The observations that make up the data were at the employee level.
|
From page 131... ...
Regression Models for Indianapolis, Indiana; Rochester, New York; and Louisville, Kentucky C-5 included an additional variable to capture effects of race.) Table C-1 presents the results of the two regressions.
|
From page 132... ...
C-6 Improving the Health and Safety of Transit Workers with Corresponding Impacts on the Bottom Line Table C-2. Effect of health promotion program on absent hours, 2010–2013.
|
From page 133... ...
Regression Models for Indianapolis, Indiana; Rochester, New York; and Louisville, Kentucky C-7 statistic for this coefficient was not significant at the 10% levels of significance, however, so the results were not substantiated. None of the variables in the model were statistically significantly different from zero except for one -- age -- for which the estimated effect was in the wrong theorized direction.
|
From page 134... ...
C-8 Improving the Health and Safety of Transit Workers with Corresponding Impacts on the Bottom Line Figure C-2 compares average annual total absentee hours between frontline employees with a high Humana Go level (blue) and employees with a baseline Humana Go level (red)
|
From page 135... ...
Regression Models for Indianapolis, Indiana; Rochester, New York; and Louisville, Kentucky C-9 The health program was introduced in January 2016. To capture any lagged effects, three time periods were compared in creating the dependent variables for the Humana Go level and boot camp equations.
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.