The Greenhouse-Geisser correction is a statistical method used to adjust the degrees of freedom in repeated measures ANOVA tests when the assumption of sphericity is violated. This correction helps to reduce the Type I error rate, making the test results more reliable when the data does not meet the sphericity assumption.

Greenhouse-Geisser Correction

Greenhouse-Geisser correction

Statistical methods are a collection of mathematical techniques used to analyze and interpret data, helping to make informed decisions based on empirical evidence. They encompass a range of procedures, including data collection, analysis, interpretation, and presentation, enabling researchers to draw valid conclusions and predictions from data samples.

statistical method

Degrees of freedom refer to the number of independent values or quantities that can be assigned to a statistical distribution or model without violating any constraints. They are crucial in determining the validity of statistical tests and models, influencing the shape of distributions and the accuracy of parameter estimates.

degrees of freedom

Repeated measures ANOVA is a statistical technique used to analyze data where the same subjects are measured multiple times under different conditions. It accounts for the correlation between repeated measures, providing more accurate results than a traditional ANOVA when dealing with within-subject factors.

repeated measures ANOVA

Sphericity refers to the condition where the variances of the differences between all combinations of related groups are equal. It is a crucial assumption in repeated measures ANOVA, and violations of sphericity can lead to incorrect conclusions unless adjustments like the Greenhouse-Geisser correction are applied.

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