Statistics for Categorical Data: Odds Ratios and Chi-Square
This assignment focuses on categorical data. Two of the statistics most often used to test hypotheses about categorical data are odds ratios (ORs) and the chi-square. The disease-OR refers to the odds in favor of disease in the exposed group divided by the odds in favor of the unexposed group. Chi-square statistics measure the difference between the observed counts and the corresponding expected counts. The expected counts are hypothetical counts that would occur if the null hypothesis were true.
Part 1: ORs
A study conducted by López-Carnllo, Avila, and Dubrow (1994) investigated health hazards associated with the consumption of food local to a particular geographic area, in this case chili peppers particular to Mexico. It was a population-based case-control study in Mexico City on the relationship between chili pepper consumption and gastric cancer risk. Subjects for the study consisted of 213 incident cases and 697 controls randomly selected from the general population. Interviews produced the following information regarding chili consumption:
| Chili pepper consumption | Case of gastric cancer | Controls |
|---|---|---|
| Yes | A = 204 | B = 552 |
| No | C = 9 | D = 145 |
Reference:
López-Carnllo, L., Avila, M. H., & Dubrow, R. (1994). Chili pepper consumption and gastric cancer in Mexico: A case-control study. American Journal of Epidemiology, 139(3), 263–271.
Note: You do not need to use the SPSS software to complete this assignment.
In a Microsoft Excel worksheet, calculate the odds of having gastric cancer. In addition, provide a written interpretation of your results in APA format.
Refer to the Assignment Resources: Odds Ratio to view an example of odds ratio. The same resource is also available under lecture Testing Hypotheses.
Part 2: Chi-Square
Bain, Willett, Hennekens, Rosner, Belanger, and Speizer (1981) conducted a study of the association between current postmenopausal hormone use and risk of nonfatal myocardial infarction (MI), in which 88 women reporting a diagnosis of MI and 1,873 healthy control subjects were identified from a large population of married female registered nurses aged thirty to fifty-five years. There were 32 women who currently used hormones and had a diagnosis of MI and 56 women reporting a MI and never used hormones. Of the women controls (women who did not report a MI) 825 currently use hormones and 1,048 never used hormones. To test the hypothesis that there is no association between use of postmenopausal hormones and risk of MI, chi-square statistics need to be calculated in SPSS using a 0.05 level of significance. The SPSS data are provided in the link below. The SPSS dataset consists of two variables:
Click here to access the SPSS data.
| Name | Label of Variable | Values |
| Group Association | Group |
|
| Use | Hormone Use |
|
Reference: Bain, C., Willett, W., Hennekens, C. H., Rosner, B., Belanger, C., & Speizer, F. E. (1981). Use of postmenopausal hormones and risk of myocardial infarction. Circulation, 64(1), 42–46.
First, refer to following video on how perform a Chi-square analysis.
Using SPSS, download the data, perform appropriate procedures, and provide calculations.
In addition, in a Microsoft Word document, provide a written conclusion and interpretation of your results in APA format.