## What does significant greenhouse-Geisser mean?

# What does significant greenhouse-Geisser mean?

## What does significant greenhouse-Geisser mean?

The Greenhouse-Geisser is used to assess the change in a continuous outcome with three or more observations across time or within-subjects. When the assumption of sphericity is violated with repeated-measures ANOVA, then the Greenhouse-Geisser correction is used.

## Should I use greenhouse-Geisser and Huynh Feldt?

When ε ≤ 0.75 (or you don’t know what the value for the statistic is), use the Greenhouse-Geisser correction. This is a conservative correction that increases the risk of Type II error. When ε > 0.75, use the Huynh-Feldt correction.

**What is sphericity assumption in ANOVA?**

Sphericity is an important assumption of a repeated-measures ANOVA. It is the condition where the variances of the differences between all possible pairs of within-subject conditions (i.e., levels of the independent variable) are equal.

**When might you use the greenhouse Geisser correction?**

As a general rule of thumb, the Greenhouse–Geisser correction is the preferred correction method when the epsilon estimate is below 0.75. Otherwise, the Huynh–Feldt correction is preferred.

### How do you know if a Mauchly’s test is significant?

→ If Mauchly’s test statistic is significant (i.e. has a probability value less than . 05) we conclude that there are significant differences between the variance of differences: the condition of sphericity has not been met.

### What does Mauchly’s test of sphericity tell you?

Mauchly’s Test of Sphericity indicated that the assumption of sphericity had not been violated, χ2(2) = 3.343, p = . If your data does not violate the assumption of sphericity, you do not need to modify your degrees of freedom. [If you are using SPSS, your results will be presented in the “sphericity assumed” row(s).]

**What is Bartlett’s test of sphericity?**

Bartlett’s test of sphericity tests the hypothesis that your correlation matrix is an identity matrix, which would indicate that your variables are unrelated and therefore unsuitable for structure detection.

**What does it mean if sphericity is not violated?**

[If you are using SPSS, your results will be presented in the “sphericity assumed” row(s).] Not violating this assumption means that the F-statistic that you have calculated is valid and can be used to determine statistical significance.

## How does the greenhouse Geisser correction work?

The correction functions as both an estimate of epsilon (sphericity) and a correction for lack of sphericity. To correct for this inflation, multiply the Greenhouse–Geisser estimate of epsilon to the degrees of freedom used to calculate the F critical value.