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:

Table 1: Chili Pepper Consumption and Gastric Cancer Risk
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.

In a Microsoft Excel worksheet, calculate the odds of having gastric cancer.
In addition, provide a written interpretation of your results in APA format.

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:

SPSS Dataset Variables
Name Label of Variable Values
Group Association Group 1. Control
Use Hormone use 2. Case

Currently Use
Never 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.

Using SPSS, download the data, perform appropriate procedures, and provide calculations.