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Week 3 Project

The project focuses on analyzing categorical data using chi-square statistics and odds ratios to evaluate the association between postmenopausal hormone use and the risk of nonfatal myocardial infarction (MI). A study by Bain et al. (1981) provides data for this analysis, requiring the calculation of chi-square statistics in SPSS at a 0.05 significance level. Students must submit their SPSS output and a written conclusion in APA format.

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5 views2 pages

Week 3 Project

The project focuses on analyzing categorical data using chi-square statistics and odds ratios to evaluate the association between postmenopausal hormone use and the risk of nonfatal myocardial infarction (MI). A study by Bain et al. (1981) provides data for this analysis, requiring the calculation of chi-square statistics in SPSS at a 0.05 significance level. Students must submit their SPSS output and a written conclusion in APA format.

Uploaded by

timber9655
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Download as DOCX, PDF, TXT or read online on Scribd
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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.

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.

SPSS Dataset Variables

Name Label of Variable Values

1. Control
Group Association Group
2. Case

1. Currently Use
Use Hormone Use
2. 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.

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.

Submission Details:

 Name your SPSS output


file SU_PHE5020_W3_A2c_LastName_FirstInitial.mtw.

 Name your
document SU_PHE5020_W3_A2d_LastName_FirstInitial.doc.

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