question archive A researcher decides to conduct a study to observe the association between smoking cessation among long-term smokers and obesity since it has been previously well documented in the literature that smokers tend to gain weight when they stop smoking
A researcher decides to conduct a study to observe the association between smoking cessation among long-term smokers and obesity since it has been previously well documented in the literature that smokers tend to gain weight when they stop smoking
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A researcher decides to conduct a study to observe the association between smoking cessation among long-term smokers and obesity since it has been previously well documented in the literature that smokers tend to gain weight when they stop smoking. The researcher notes that among the individuals who gain weight, many of them have developed heart problems or other medical problems that typically prevent them from exercising as much as their counterparts. In this case the individuals who developed these health problems had specific genetic markers putting them at higher risk of developing their health problems while they were smoking than their counterparts. This is an example of which of the following?
(1) Confounding.
(2) Statistical interaction.
(3) Misclassification bias.
(4) Recall bias.
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The given example is an example of statistical interaction.
In this example, smoking cessation is an independent variable and gaining weight or becoming obese is a dependent variable. When people stop smoking, they tend to gain weight according to the research. Then considering the factor of gaining weight, many of those people develop heart problems that is yet another factor caused due to weight gain. So we have the factor of gaining weight as an independent variable and the development of heart problems as a dependent variable.
So here we have independent variable(s) in this case whose overall effect will be higher than the individual effect of the variables on the dependent variable and hence it is a case of statistical interaction.
Since we take into consideration the effect of all the variables into account and forms a valid relation rather than just a casual concept of affecting the relationship between the dependent and independent variables, it cannot be considered as an example of confounding.
Coming to the misclassification bias and recall bias, the former is related to the categorization of data into an incorrect category whereas the latter term deals with the inaccuracy or incomplete information retrieval leading to the systematic error of biasedness in classifying.
