What is the DerSimonian and Laird method?

What is the DerSimonian and Laird method?

A variation on the inverse-variance method is to incorporate an assumption that the different studies are estimating different, yet related, intervention effects. This produces a random-effects meta-analysis, and the simplest version is known as the DerSimonian and Laird method (DerSimonian 1986).

What is tau2?

Tau-squared, the between-study variance, is derived from this Q and subsequently used to conduct random effects analysis. Under an inverse-variance model, there is no need to switch to a fixed effect model in the absence of heterogeneity, as the two results will be exactly identical.

What is heterogeneity in meta-analysis?

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).

How do you read I2?

Researchers often use the I2 index to quantify the dispersion of effect sizes in a meta-analysis. Some suggest that I2 values of 25%, 50%, and 75%, correspond to small, moderate, and large amounts of heterogeneity. In fact though, I2 is a not a measure of absolute heterogeneity.

What is heterogeneity in data?

Heterogeneity in statistics means that your populations, samples or results are different. It is the opposite of homogeneity, which means that the population/data/results are the same. For example, if everyone in your group varied between 4’3″ and 7’6″ tall, they would be heterogeneous for height.

How is I2 calculated?

I2 can be calculated from Cochran’s Q (the most commonly used heterogeneity statistic) according to the formula: I2 = 100% X (Cochran’s Q – degrees of freedom). Any negative values of I2 are considered equal to 0, so that the range of I2 values is between 0-100%.

How is I2 heterogeneity calculated?

I2 can be readily calculated from basic results obtained from a typical meta-analysis as I2 = 100%×(Q – df)/Q, where Q is Cochran’s heterogeneity statistic and df the degrees of freedom. Negative values of I2 are put equal to zero so that I2 lies between 0% and 100%.

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