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In a study9 on the effects of AZT in slowing the development of AIDS symptoms, 338 veterans whose immune systems were beginning to falter after infection with the AIDS virus were randomly assigned either to receive AZT immediately or to wait until their T cells showed severe immune weakness. Output follows of modeling the 2 × 2 × 2 cross-classification of race, whether AZT was given immediately, and whether AIDS symptoms developed during the three-year study. What null hypothesis is tested by the difference between the null deviance and the residual deviance? Interpret. Explain how to set up indicator variables for azt and race to obtain the estimates shown.

In a study9 on the effects of AZT in slowing the development of AIDS symptoms, 338 veterans whose immune systems were beginning to falter after infection with the AIDS virus were randomly assigned either to receive AZT immediately or to wait until their T cells showed severe immune weakness. Output follows of modeling the 2 × 2 × 2 cross-classification of race, whether AZT was given immediately, and whether AIDS symptoms developed during the three-year study. What null hypothesis is tested by the difference between the null deviance and the residual deviance? Interpret. Explain how to set up indicator variables for azt and race to obtain the estimates shown.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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In a study9 on the effects of AZT in slowing the development of AIDS symptoms, 338 veterans whose immune systems were beginning to falter after infection with the AIDS virus were randomly assigned either to receive AZT immediately or to wait until their T cells showed severe immune weakness. Output follows of modeling the 2 × 2 × 2 cross-classification of race, whether AZT was given immediately, and whether AIDS symptoms developed during the three-year study.

  1. What null hypothesis is tested by the difference between the null deviance and the residual deviance? Interpret. Explain how to set up indicator variables for azt and race to obtain the estimates shown.

**AIDS Research Data Analysis** This dataset is focused on analyzing categories of AIDS symptoms responses based on race and the usage of the drug AZT. The data is structured as follows: - **Variables:** - `race`: Racial category of the participant (white or black). - `azt`: Whether the participant received AZT treatment (`yes` or `no`). - `yes`: The number of individuals showing AIDS symptoms. - `no`: The number of individuals not showing AIDS symptoms. **Dataset Details:** 1. **White participants receiving AZT:** - Show symptoms: 14 - No symptoms: 93 2. **White participants not receiving AZT:** - Show symptoms: 32 - No symptoms: 81 3. **Black participants receiving AZT:** - Show symptoms: 11 - No symptoms: 52 4. **Black participants not receiving AZT:** - Show symptoms: 12 - No symptoms: 43 **Statistical Analysis:** A logistic regression model (`glm`) is used to examine the relationship between symptom response (yes or no) with predictors `azt` and `race`. The analysis uses a binomial family with specific weights. **Model Summary:** - **Intercept:** - Estimate: -1.07357 - Std. Error: 0.26294 - z value: -4.083 - Pr(>|z|): 4.45e-05 - **AZT (aztyes):** - Estimate: -0.71946 - Std. Error: 0.27898 - z value: -2.579 - Pr(>|z|): 0.00991 - **Race White (racewhite):** - Estimate: 0.05548 - Std. Error: 0.28861 - z value: 0.192 - Pr(>|z|): 0.84755 **Deviance Information:** - Null deviance: 8.3499 on 3 degrees of freedom - Residual deviance: 1.3835 on 1 degree of freedom This analysis provides insights into the effect of race and AZT treatment on AIDS symptom manifestation. The statistical significance of
Transcribed Image Text:**AIDS Research Data Analysis** This dataset is focused on analyzing categories of AIDS symptoms responses based on race and the usage of the drug AZT. The data is structured as follows: - **Variables:** - `race`: Racial category of the participant (white or black). - `azt`: Whether the participant received AZT treatment (`yes` or `no`). - `yes`: The number of individuals showing AIDS symptoms. - `no`: The number of individuals not showing AIDS symptoms. **Dataset Details:** 1. **White participants receiving AZT:** - Show symptoms: 14 - No symptoms: 93 2. **White participants not receiving AZT:** - Show symptoms: 32 - No symptoms: 81 3. **Black participants receiving AZT:** - Show symptoms: 11 - No symptoms: 52 4. **Black participants not receiving AZT:** - Show symptoms: 12 - No symptoms: 43 **Statistical Analysis:** A logistic regression model (`glm`) is used to examine the relationship between symptom response (yes or no) with predictors `azt` and `race`. The analysis uses a binomial family with specific weights. **Model Summary:** - **Intercept:** - Estimate: -1.07357 - Std. Error: 0.26294 - z value: -4.083 - Pr(>|z|): 4.45e-05 - **AZT (aztyes):** - Estimate: -0.71946 - Std. Error: 0.27898 - z value: -2.579 - Pr(>|z|): 0.00991 - **Race White (racewhite):** - Estimate: 0.05548 - Std. Error: 0.28861 - z value: 0.192 - Pr(>|z|): 0.84755 **Deviance Information:** - Null deviance: 8.3499 on 3 degrees of freedom - Residual deviance: 1.3835 on 1 degree of freedom This analysis provides insights into the effect of race and AZT treatment on AIDS symptom manifestation. The statistical significance of
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