In the prerequisite course, Quantitative Reasoning and Analysis
In the prerequisite course, Quantitative Reasoning and Analysis, you constructed basic contingency (crosstab) tables. You might be surprised to learn that you can estimate a simple logistic regression model, with a categorical predictor, using the descriptive values presented in the crosstab table.
In this assignment, you use Microsoft Excel to construct a specialized tool that creates basic logistic regression models given a crosstab/contingency table. As if that were not useful enough, this Excel tool is not specialized—you can use it given any crosstab/contingency tables you encounter in research. In the field of statistical research, this is just about as exciting as you can get!
To prepare
- Review the sections in the Osborne text that present a template for constructing an Excel worksheet.
- Review the video in the Learning Resources, in which Dr. Matt Jones explains how to harness the power of Excel using contingency tables.
- Think about the types of variables that are useful for cross tab tables.
Using one of the datasets provided, select two variables that allow you to construct a 2×2 contingency table. Use SPSS to run the initial crosstab table, using any two variables that you think are appropriate. Then, use Excel to construct a table in which you report:
- Conditional probabilities
- Conditional odds
- Logits
- Odds ratios
- Relative risk
- Slope
Be sure to apply the template from the Osborne text. Note that page 42 has a completed example that should help you determine these values. Be sure to use formulas and cell references in Excel so that the spreadsheet you create can be used as a tool for calculating similar values for other datasets.
Once you have created the tool, write a 1- to 2-paragraph summary in APA format interpreting your results. Submit both your Excel file and your summary to complete this assignment.
https://class.waldenu.edu/bbcswebdav/institution/USW1/201850_27/XX_RSCH/RSCH_8260_WC/artifacts/USW1_RSCH_8260_statsAnxietyAdvQuant.sav
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