In the full workers' data set, a new variable was created indicating whether the employee missed two or more days from work in the past 4 weeks because of illness. Another variable was created which grouped self-rated job performance as high (9 or 10) vs. low (0 – 8). Using logistic regression to assess the association between absence and self-job performance rating, the following estimated model was obtained. a. The standard error for the estimated slope coefficient was 0.0379. Calculate the odds ratio, its 95% confidence interval, and interpret the results. b. Now assume we want to adjust for the potential confounding influence of gender and age. Adding these two variables to the model gives the following: The standard errors for the estimated slope coefficients are 0.0383, 0.0408, anc 0.0017, respectively. For each variable in the model calculate the odds ratio, 95% confidence interval, and interpret the results.

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ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:James Stewart, Lothar Redlin, Saleem Watson
Chapter1: Equations And Graphs
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In the full workers' data set, a new variable was created indicating whether the
employee missed two or more days from work in the past 4 weeks because of
illness. Another variable was created which grouped self-rated job performance
as high (9 or 10) vs. low (0 - 8). Using logistic regression to assess the
association between absence and self-job performance rating, the following
estimated model was obtained.
a. The standard error for the estimated slope coefficient was 0.0379. Calculate
the odds ratio, its 95% confidence interval, and interpret the results.
b. Now assume we want to adjust for the potential confounding influence of
gender and age. Adding these two variables to the model gives the following:
The standard errors for the estimated slope coefficients are 0.0383, 0.0408, and
0.0017, respectively. For each variable in the model calculate the odds ratio,
95% confidence interval, and interpret the results.
Transcribed Image Text:In the full workers' data set, a new variable was created indicating whether the employee missed two or more days from work in the past 4 weeks because of illness. Another variable was created which grouped self-rated job performance as high (9 or 10) vs. low (0 - 8). Using logistic regression to assess the association between absence and self-job performance rating, the following estimated model was obtained. a. The standard error for the estimated slope coefficient was 0.0379. Calculate the odds ratio, its 95% confidence interval, and interpret the results. b. Now assume we want to adjust for the potential confounding influence of gender and age. Adding these two variables to the model gives the following: The standard errors for the estimated slope coefficients are 0.0383, 0.0408, and 0.0017, respectively. For each variable in the model calculate the odds ratio, 95% confidence interval, and interpret the results.
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