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  2. Mixed-design analysis of variance - Wikipedia

    en.wikipedia.org/wiki/Mixed-design_analysis_of...

    In statistics, a mixed-design analysis of variance model, also known as a split-plot ANOVA, is used to test for differences between two or more independent groups whilst subjecting participants to repeated measures. Thus, in a mixed-design ANOVA model, one factor (a fixed effects factor) is a between-subjects variable and the other (a random ...

  3. Mauchly's sphericity test - Wikipedia

    en.wikipedia.org/wiki/Mauchly's_sphericity_test

    Sphericity can be evaluated when there are three or more levels of a repeated measure factor and, with each additional repeated measures factor, the risk for violating sphericity increases. If sphericity is violated, a decision must be made as to whether a univariate or multivariate analysis is selected. If a univariate method is selected, the ...

  4. Analysis of covariance - Wikipedia

    en.wikipedia.org/wiki/Analysis_of_covariance

    ANCOVA evaluates whether the means of a dependent variable (DV) are equal across levels of one or more categorical independent variables (IV) and across one or more continuous variables. For example, the categorical variable(s) might describe treatment and the continuous variable(s) might be covariates (CV)'s, typically nuisance variables; or ...

  5. Between-group design experiment - Wikipedia

    en.wikipedia.org/wiki/Between-group_design...

    In the design of experiments, a between-group design is an experiment that has two or more groups of subjects each being tested by a different testing factor simultaneously. This design is usually used in place of, or in some cases in conjunction with, the within-subject design , which applies the same variations of conditions to each subject ...

  6. Factorial experiment - Wikipedia

    en.wikipedia.org/wiki/Factorial_experiment

    This experiment is an example of a 2 2 (or 2×2) factorial experiment, so named because it considers two levels (the base) for each of two factors (the power or superscript), or #levels #factors, producing 2 2 =4 factorial points. Cube plot for factorial design . Designs can involve many independent variables.

  7. 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 .

  8. Repeated measures design - Wikipedia

    en.wikipedia.org/wiki/Repeated_measures_design

    The independent variable is the time (Levels: Time 1, Time 2, Time 3, Time 4) that someone took the measure, and the dependent variable is the happiness measure score. Example participant happiness scores are provided for 3 participants for each time or level of the independent variable. Repeated measures analysis of variance (rANOVA) is a ...

  9. Effect size - Wikipedia

    en.wikipedia.org/wiki/Effect_size

    In statistics, an effect size is a value measuring the strength of the relationship between two variables in a population, or a sample-based estimate of that quantity. It can refer to the value of a statistic calculated from a sample of data, the value of one parameter for a hypothetical population, or to the equation that operationalizes how statistics or parameters lead to the effect size ...