Chi-Square Analysis Application
Week 3 Project – Chi-Square
This assignment focuses on categorical data, and two of the statistics most often used to test hypotheses about categorical data are odds ratios (ORs) and the chi-square. A chi-square is calculated first to identify if two categorical variables are associated with each other, and if they are then an odds ratio is often calculated. 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.
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Chi-Square Analysis Application
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. The SPSS data are provided in the link below. The SPSS dataset consists of two variables:
Click here to access the SPSS data.
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.
Refer to following video on how perform a Chi-square analysis. https://www.youtube.com/watch?v=ysn-YL9bLdo
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.
