enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Confounding - Wikipedia

    en.wikipedia.org/wiki/Confounding

    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 probable confounding variable, each 67-year-old infarct patient will be matched with a healthy 67-year-old "control" person.

  3. 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.

  4. Recall bias - Wikipedia

    en.wikipedia.org/wiki/Recall_bias

    Recall bias is a type of measurement bias, and can be a methodological issue in research involving interviews or questionnaires. In this case, it could lead to misclassification of various types of exposure . [ 2 ]

  5. Controlling for a variable - Wikipedia

    en.wikipedia.org/wiki/Controlling_for_a_variable

    For example, if an outdoor experiment were to be conducted to compare how different wing designs of a paper airplane (the independent variable) affect how far it can fly (the dependent variable), one would want to ensure that the experiment is conducted at times when the weather is the same, because one would not want weather to affect the ...

  6. 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

  7. Simpson's paradox - Wikipedia

    en.wikipedia.org/wiki/Simpson's_paradox

    The phenomenon may disappear or even reverse if the data is stratified differently or if different confounding variables are considered. Simpson's example actually highlighted a phenomenon called noncollapsibility, [32] which occurs when subgroups with high proportions do not make simple averages when combined. This suggests that the paradox ...

  8. What You Didn't Learn In Sex Ed

    projects.huffingtonpost.com/cliteracy/education?...

    Wallace eventually decided that shining the spotlight on the clitoris was more important than any potential repercussions she might face. Once she decided to take on the work, she didn’t look back. Soon, she’d created Cliteracy, an art project that fuses street art, textiles and typography with the goal of educating a largely “ilcliterate ...

  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 ...