The analysis most commonly used in case-control studies is an odds ratio, which is the chance (odds) of the outcomes occurring in the case group versus the control group. attribution bias may occur when patients with unfavourable outcomes are less likely to attend follow-ups.selection bias can happen when participants are assigned without randomisation.This is especially important in designs that are non-randomised. Confounding variables and biasesĬonfounding variables (variables other than the one you are interested in that may influence the results) and biases (errors that influence the sample selected and results observed) are important to consider when conducting any research. However, think about other characteristics and attributes that might influence the use of your product, and the subsequent outcomes. You should pick characteristics that have an effect on the usage of digital devices and services. In a matched case-control design, controls are selected case-by-case based on specified characteristics. There are 2 main types of case-control design: matched and unmatched.Įssentially, in an unmatched case-control design, a shared control group is selected for all cases at random given certain attributes. Ideally, they will only differ in whether they received your digital product (cases) or not (controls). This means the participants will be similar to each other in terms of factors that may influence the outcomes you’re looking at. The comparison group should be as similar as possible to the source population that produced the cases. Selecting an appropriate control is an important part of a case-control study. Some researchers use the term prospective case-control study when, for example, a prospective group exposed to an intervention is compared to a retrospective control.
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