Examination 2

Directions:
Respond to each item in a clear and concise paragraph. Do not copy passages from the lectures or book. Rather, express your own understanding of the material. Do not write anything or everything that comes to mind; instead, try to devise a brief answer that captures the most relevant information.

1. How do odds express the nature of a relationship between an independent and dependent variable?

2. Why does taking the inverse of the odds sometimes make it easier to express the relationship between variables. Give an example.

3. If you analyzed the relationship between a binary independent variable and a binary dependent variable with crosstabulation and odds, on the one hand, and with logistic regression, on the other, how would the results compare?

4. Select a binary dependent variable and a binary two binary independent variables from one of our data frames. Calculate crosstabulations with odds in R and compare the results. What can you say sociologically about these two potential causal models? [At the bottom of your answer, paste your R code -- recodes and model commands -- in case I have a question about your answer.]

5. Using the model you computed in class, identify an additional independent variable and compute the log-linear analysis using the step() and loglm() functions. [At the bottom of your answer, paste your R code -- recodes and model commands -- in case I have a question about your answer.]

6. Using the model you computed in class, identify at least one more independent variable and compute the Poisson regression using the step() and glm() functions. [At the bottom of your answer, paste your R code -- recodes and model commands -- in case I have a question about your answer.]

7. Summarize Table 2 in the Shortell (MCS) article. What do the odds ratios suggest about any region effect?

8. What is the research question presented in the Beck article.

9. Summarize the results shown in Table 3 of Beck. Did the authors find what they expected?

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