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  2. Confounding - Wikipedia

    en.wikipedia.org/wiki/Confounding

    Depending on the type of study design in place, there are various ways to modify that design to actively exclude or control confounding variables: [26] Case-control studies assign confounders to both groups, cases and controls, equally. For example, if somebody wanted to study the cause of myocardial infarct and thinks that the age is a ...

  3. Controlling for a variable - Wikipedia

    en.wikipedia.org/wiki/Controlling_for_a_variable

    Observational studies are used when controlled experiments may be unethical or impractical. For instance, if a researcher wished to study the effect of unemployment ( the independent variable ) on health ( the dependent variable ), it would be considered unethical by institutional review boards to randomly assign some participants to have jobs ...

  4. Blocking (statistics) - Wikipedia

    en.wikipedia.org/wiki/Blocking_(statistics)

    In the examples listed above, a nuisance variable is a variable that is not the primary focus of the study but can affect the outcomes of the experiment. [3] They are considered potential sources of variability that, if not controlled or accounted for, may confound the interpretation between the independent and dependent variables.

  5. Control variable - Wikipedia

    en.wikipedia.org/wiki/Control_variable

    A variable in an experiment which is held constant in order to assess the relationship between multiple variables [a], is a control variable. [2] [3] A control variable is an element that is not changed throughout an experiment because its unchanging state allows better understanding of the relationship between the other variables being tested.

  6. Randomized controlled trial - Wikipedia

    en.wikipedia.org/wiki/Randomized_controlled_trial

    They concluded that most of the studies were of low quality and advocated the use of randomized controlled trials wherever possible in future transport research. Dr. Steve Melia [ 114 ] took issue with these conclusions, arguing that claims about the advantages of RCTs, in establishing causality and avoiding bias, have been exaggerated.

  7. Propensity score matching - Wikipedia

    en.wikipedia.org/wiki/Propensity_score_matching

    Choose appropriate confounders (variables hypothesized to be associated with both treatment and outcome) Obtain an estimation for the propensity score: predicted probability p or the log odds, log[p/(1 − p)]. 2. Match each participant to one or more nonparticipants on propensity score, using one of these methods: Nearest neighbor matching

  8. 10 Reasons Why Every American Woman Should Vote In November

    testkitchen.huffingtonpost.com/our-vote-counts

    History tells us that matters like marriage equality, voting rights, abortion access and campaign finance are often adjudicated through the court system.

  9. Spurious relationship - Wikipedia

    en.wikipedia.org/wiki/Spurious_relationship

    Graphical model: Whereas a mediator is a factor in the causal chain (top), a confounder is a spurious factor incorrectly implying causation (bottom). In statistics, a spurious relationship or spurious correlation [1] [2] is a mathematical relationship in which two or more events or variables are associated but not causally related, due to either coincidence or the presence of a certain third ...