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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, anc 0.0017, respectively. For each variable in the model calculate the odds ratio, 95% confidence interval, and interpret the results.

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.

Linear Algebra: A Modern Introduction
Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter7: Distance And Approximation
Section7.3: Least Squares Approximation
Problem 31EQ
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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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