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  2. Confounding - Wikipedia

    en.wikipedia.org/wiki/Confounding

    A reduction in the potential for the occurrence and effect of confounding factors can be obtained by increasing the types and numbers of comparisons performed in an analysis. If measures or manipulations of core constructs are confounded (i.e. operational or procedural confounds exist), subgroup analysis may not reveal problems in the analysis.

  3. Controlling for a variable - Wikipedia

    en.wikipedia.org/wiki/Controlling_for_a_variable

    Instead, they must control for variables using statistics. 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 ...

  4. Blocking (statistics) - Wikipedia

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

    They are considered potential sources of variability that, if not controlled or accounted for, may confound the interpretation between the independent and dependent variables. To address nuisance variables, researchers can employ different methods such as blocking or randomization.

  5. 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

  6. Dependent and independent variables - Wikipedia

    en.wikipedia.org/wiki/Dependent_and_independent...

    In mathematics, a function is a rule for taking an input (in the simplest case, a number or set of numbers) [5] and providing an output (which may also be a number). [5] A symbol that stands for an arbitrary input is called an independent variable, while a symbol that stands for an arbitrary output is called a dependent variable. [6]

  7. Lord's paradox - Wikipedia

    en.wikipedia.org/wiki/Lord's_paradox

    In statistics, Lord's paradox raises the issue of when it is appropriate to control for baseline status. In three papers, Frederic M. Lord gave examples when statisticians could reach different conclusions depending on whether they adjust for pre-existing differences.

  8. The new college student sex trend and why it's so dangerous

    www.aol.com/college-student-sex-trend-why...

    A new sex trend among college students is getting attention on TikTok − and it has doctors worried.. That trend is using honey packets, a controversial supplement marketed for sexual enhancement ...

  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 ...