Odds Ratio Relative Risk and ANOVA Case

Odds Ratio Relative Risk and ANOVA Case

Instructions/Descriptions

Odds Ratio Relative Risk and ANOVA Case

Module 3 – Case

Odds Ratio, Relative Risk, and ANOVA

Case Assignment

Using the materials in the module homepage and in the background section, please address the following:

1. Define and describe each of the measures of association: OR, RR, ANOVA, and Correlations. (1 page)
2. Provide an example of a study that uses each of the six types of analyses (OR, RR, ANOVA, correlations, chi-square, t-tests). (1- to 2-pages)
3. How are OR and RR different? What types of studies use OR versus RR? (1 page)

Assignment Expectations

Length: Case Assignment should be at least 3 pages (750 words) in length.

References: At least two references from academic sources must be included (e.g., peer-reviewed journal articles). You may use any required readings from this module for your two references. Quoted material should not exceed 10% of the total paper (since the focus of these assignments is critical thinking). Use your own words and build on the ideas of others. When material is copied verbatim from external sources, it MUST be enclosed in quotes. The references should be cited within the text and listed at the end of the assignment in the References section (APA formatting recommended).

Organization: Subheadings should be used to organize your paper according to each question.

Format: APA formatting is recommended for this assignment. See Syllabus page for more information on APA formatting.

Grammar and Spelling: While no points are deducted for minor errors, assignments are expected to adhere to standards guidelines of grammar, spelling, punctuation, and syntax. Points may be deducted if grammar and spelling impact clarity.

Your assignment will not be graded until you have submitted an Originality Report with a Similarity Index (SI) score <20% (excluding direct quotes, quoted assignment instructions, and references). Papers not meeting this requirement by the end of the session will receive a score of 0 (grade of F). Do keep in mind that papers with a lower SI score may be returned for revisions. For example, if one paragraph accounting for only 10% of a paper is cut and pasted, the paper could be returned for revision, despite the low SI score. Please use the report and your SI score as a guide to improve the originality of your work.

The following items will be assessed in particular:

• Achievement of learning outcomes for Case Assignment.
• Relevance: all content is connected to the question.
• Precision: specific question is addressed; statements, facts, and statistics are specific and accurate.
• Depth of discussion: points that lead to deeper issues are presented and integrated.
• Breadth: multiple perspectives, references, and issues/factors considered.
• Evidence: points are well supported with facts, statistics, and references.
• Logic: presented discussion makes sense; conclusions are logically supported by premises, statements, or factual information.
• Clarity: writing is concise, understandable, and contains sufficient detail or examples.
• Objectivity: use of first person and subjective bias are avoided.

Module 3 – Home

Odds Ratio, Relative Risk, and ANOVA

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Modular Learning Outcomes

Upon successful completion of this module, the student will be able to satisfy the following outcomes:

• Case
• Discuss the difference between OR, RR, ANOVA, and correlations; note which measures should be used for which type of study.
• SLP
• Analyze the OR and RR and interpret each accurately.
• Discussion
• Discuss the implications of alpha and beta for a study.

Module Overview

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In order to select the correct statistical tests, the first step is to analyze the exposure (risk factor) and outcome (disease) of interest. If there is just one exposure of interest, then the appropriate analytical method is chi-square, t-test, or one-way ANOVA. For variables with two or more categories, a chi-square test is used (e.g., comparing the number of people with diabetes among men versus among women). For continuous variables (e.g., blood pressure, BMI, fasting glucose, etc.), the statistical test is either the t-test for comparing two categories (e.g., men versus women) or one-way ANOVA for comparing more than two categories (e.g., among different racial groups).

For examining the relationship between an exposure or outcome variable, the most commonly used statistics are correlations, logistical regression, and linear regression. Correlations are used for more than one risk factor or exposure variable. Logistical regression analyzes a binary outcome (or disease status), whereas linear regression analyzes a continuous outcome (e.g., bone mineral density, fast glucose level, etc.).

Module readings will cover correlations, ANOVA, relative risk, and the odds ratio

Odds Ratio Relative Risk and ANOVA Case

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