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Adjusting the weights of the respondents in the sample

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Reference no: EM131715037

Question: Investigators selected an SRS of 200 high school seniors from a population of 2000 for a survey of TV-viewing habits, with an overall response rate of 75%. By checking school records, they were able to find the grade point average (GPA) for the non-respondents and classify the sample accordingly

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a. What is the estimate for the average number of hours of TV watched per week if only respondents are analyzed? What is the standard error of the estimate?

b. Perform a X2 test for the null hypothesis that the three GPA groups have the same response rates. What do you conclude? What do your results say about the type of missing data: Do you think the data are MCAR? MAR? Nonignorable?

c. Perform a one-way ANOVA to test the null hypothesis that the three GPA groups have the same mean level of TV viewing. What do you conclude? Does your ANOVA indicate that GPA would be a good variable for constructing weighting cells? Why, or why not?

d. Use the GPA classification to adjust the weights of the respondents in the sample. What is the weighting-class estimate of the average viewing time?

e. The population counts are 700 students with a GPA between 3 and 4; 800 students with a GPA between 2 and 3; and 500 students with a GPA less than 2. Use these population counts to construct a poststratified estimate of the mean viewing time.

f. What other methods might you use to adjust for the nonresponse?

g. What other variables might be collected that could be used in nonresponse models?

Reference no: EM131715037

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