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Assignment 3 Exercise 1: Often media’s coverage of health and health care related research can be characterized as erroneous, misleading, or even deceptive. TV, newspapers, and magazines sometimes use sensational language at the expense of accuracy, in order to provoke lots of public excitement or interest. As a result, they can spread incorrect or incomplete reports of scientific findings. Other times, they may fail to detect or acknowledge limitations of research studies that make wrongful claims of causal findings. This is especially the case if the evidence is based solely on observational studies. Now imagine that you read news stories with these headlines: 1A. “Excessive alcohol use can lead to depression.” 1B. “Men are much more likely to die from COVID-19 than women.” Each of these headlines imply strong correlation between pairs of variables. However, observation of a correlation does not necessarily mean a causal relationship. Pick either 1A or 1B above and answer all of the following questions in a few sentences: 1) Identify the dependent and independent variables implied by the headline. ii) What is the direction of relationship between the two variables, i.e. does the headline imply a positive or negative correlation between the two Briefly explain. iii) Is there a plausible mechanism through which we could explain why the independent variable has a causal impact on the outcome? Briefly explain. iv) Now try to think of reasons why this could be a spurious relationship instead. This means that you need to construct alternative explanations. For this, either try to come up with a potentially confounding (third) variable that may be responsible for the reported associations; or a plausible explanation for reverse causation. In either case, briefly explain how these can provide an alternative explanation for observed associations. Example: “Married people are healthier.” i-ill) The headline suggests a positive effect of marriage on health. Thus, the implied independent variable is marriage and the implied dependent variable is health. Note that this could possibly be true because married people provide emotional and financial support for each other, which would improve their health. iv) However, this observed positive correlation could also be due to a potentially confounding factor, such as income. Both of the following two arguments are needed to form a complete reasoning: On average, people with higher income are more likely to get married. In addition, people with higher income tend to be healthier. Hence, income as a confounding factor makes it look as if marriage causes better health. Alternatively, we could argue reverse causation: healthier people are more likely to find partners and to get married. Therefore, not only being married affects health, but also health status affects being married or single. Exercise 2: In order to expand testing to larger number of people, a new and cheaper rapid test kit for COVID-19 is being developed at FAU that can easily be used by patients themselves in a home setting. While the idea is rather appealing, we need to be vigilant about the accuracy of such tests since incorrect diagnoses would lead to fear, confusion, unnecessary use of health care, as well as disruption of daily lives. False negatives can lead to a false sense of security and contribute to further spread of the virus. On the other hand, false positives can unnecessarily keep people out of work, school, etc. The new FAU rapid test kit was assessed for a sample of individuals whose COVID-19 status have already been confirmed as absent or present based on a standard testing done in a clinical setting. The findings reveal the following data: COVID-19 absent COVID-19 present Negative test 1,978 53 Positive test 408 280 Based on this information, answer the following questions about the new FAU test kit and make sure to show all your work: a. What is the proportion of false positives with the new test? b. What is the proportion of false negatives with the new test? c. What is the sensitivity of the new test? d. What is the specificity of the new test? For the next two parts, we will make a simplifying assumption that everyone sick with COVID-19 recovers by the next day and will be at risk to catch the disease again. Pick either e or f: e. If this test kit were to be utilized daily across the entire US, with a total population of 330 million and 0.1% of the population infected every day, about how many people would be incorrectly diagnosed with COVID-19? f. If this test kit were to be utilized daily across the entire US, with a total population of 330 million and 0.1% of the population infected every day, about how many people would be incorrectly diagnosed as being COVID-19-free?
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