retails sales) while the federal government retrospectively collected others during the 2010 census (e.g. Local governments prospectively collect some variables as events unfolded (e.g. Some data sets, such as county, may contain both rospectively- and retrospectively-collected variables. researchers may review past events in medical records. Retrospective studies collect data after events have taken place, e.g. This prospective study recruits registered nurses and then collects data from them using questionnaires. One example of such a study is The Nurses Health Study, started in 1976 and expanded in 1989. For instance, medical researchers may identify and follow a group of similar individuals over many years to assess the possible influences of behavior on cancer risk. A prospective study identifies individuals and collects information as events unfold. Observational studies come in two forms: prospective and retrospective studies. Additionally, the high density may contribute to increases in property value, making homeownership infeasible for many residents. If a county is very dense, then this may require a larger fraction of residents to live in multi-unit structures. Suggest one or more other variables that might explain the relationship visible in Figure 1.9.Īnswers will vary. However, it is unreasonable to conclude that there is a causal relationship between the two variables. In the same way, the county data set is an observational study with confounding variables, and its data cannot easily be used to make causal conclusions.įigure 1.9 shows a negative association between the homeownership rate and the percentage of multi-unit structures in a county. While one method to justify making causal conclusions from observational studies is to exhaust the search for confounding variables, there is no guarantee that all confounding variables can be examined or measured. Sun exposure is what is called a confounding variable (also called a lurking variable, confounding factor, or a confounder), which is a variable that is correlated with both the explanatory and response variables. Exposure to the sun is unaccounted for in the simple investigation. If someone is out in the sun all day, she is more likely to use sunscreen and more likely to get skin cancer. One important piece of information that is absent is sun exposure. Some previous research tells us that using sunscreen actually reduces skin cancer risk, so maybe there is another variable that can explain this hypothetical association between sunscreen usage and skin cancer. See the paragraph following the exercise for an explanation. Does this mean sunscreen causes skin cancer? Suppose an observational study tracked sunscreen use and skin cancer, and it was found that the more sunscreen someone used, the more likely the person was to have skin cancer.
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