Statistics for Categorical Data: Odds Ratios and Chi-Square

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.

 

Note: You do not need to use the Minitab 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.

 

Submission Details:

 

Name your worksheet SU_PHE5020_W3_A2a_LastName_FirstInitial.xls.

 

Name your document SU_PHE5020_W3_A2b_LastName_FirstInitial.doc.

 

Submit your document to the Submissions Area by the due date assigned.

 

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. 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.

 

The data are presented as follows:

 

Table 2: Association between Postmenopausal Hormone Use and Risk of Nonfatal MI

 

 

 

Cases

 

Controls

 

Total

 

Currently use

 

32

 

825

 

857

 

Never use

 

56

 

1,048

 

1,104

 

Total

 

88

 

1,873

 

1,961

 

 

 

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 the Minitab procedure, enter the data, perform appropriate procedures, and provide calculations from the table.

 

In addition, in a Microsoft Word document, provide a written interpretation of your results in APA format.

 

Submission Details:

 

Name your Minitab output file SU_PHE5020_W3_A2c_LastName_FirstInitial.mtw.

 

Name your document SU_PHE5020_W3_A2d_LastName_FirstInitial.doc.

 

Submit your document to the Submissions Area by the due date assigned.

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