# What is I2 heterogeneity?

## What is I2 heterogeneity?

Heterogeneity in meta-analysis refers to the variation in study outcomes between studies. The I² statistic describes the percentage of variation across studies that is due to heterogeneity rather than chance (Higgins and Thompson, 2002; Higgins et al., 2003).

**What is high heterogeneity I2?**

In case of I2, we usually define what means high, moderate or low. For example, if you define that I2 > 75% is considered as substantial heterogeneity and I2 of your meta-analysis is more than 75%, that means considerable heterogeneity is present.

### What does it mean if heterogeneity is high?

When heterogeneity is very high and between-study variation dominates, random-effects meta-analyses weight studies nearly equally, regardless of sample sizes, yielding a meta-analytic summary close to the more easily calculated arithmetic mean of the individual study results.

**Is heterogeneity bad in a study?**

Heterogeneity and its opposite, homogeneity, refer to how consistent or stable a particular data set or variable relationship are. Having statistical heterogeneity is not a good or bad thing in and of itself for the analysis; however, it’s useful to know to design, choose and interpret statistical analyses.

#### How is the I 2 index used to measure heterogeneity?

the I 2 index is able to quantify the degree of heterogeneity in a meta-analysis and to measure the extent of true heterogeneity by dividing the difference between Q (chi-squared statistic) and its degrees of freedom (k – 1) by Q, and multiplying by 100.

**Is there any thumb rule for I²-heterogeneity?**

Hi, in a multilevel metaanalysis I had a total heterogeneity of 63% but after eliminating one article with a size effect considerably larger than the rest it went down to 0.000004. Is that possible? I am worried I may be doing something wrong.

## Which is a rough guide to interpreting heterogeneity?

A rough guide to interpretation is as follows: 75% to 100%: considerable heterogeneity*. *The importance of the observed value of I2 depends on (i) magnitude and direction of effects and (ii) strength of evidence for heterogeneity (e.g. P value from the chi-squared test, or a confidence interval for I2).

**Which is the correct statistic for heterogeneity across studies?**

The I² statistic describes the percentage of variation across studies that is due to heterogeneity rather than chance ( Higgins and Thompson, 2002; Higgins et al., 2003 ). I² = 100% x (Q-df)/Q. I² is an intuitive and simple expression of the inconsistency of studies’ results.