Standardierojen

Standardierojen, in statistics, refer to standardized differences between groups. They are a type of effect size used to express how far two groups differ on a continuous outcome on a common, unitless scale. This makes it possible to compare results across studies or measures that use different scales.

The most common form is the standardized mean difference. It is calculated by taking the mean difference between two groups and dividing it by a pooled standard deviation. Formula in plain terms: SMD = (mean of group 1 minus mean of group 2) divided by the pooled standard deviation. The pooled standard deviation combines the variability of both groups and is computed from their variances and sample sizes. In practice, two related measures are frequently used: Cohen’s d, which is the unadjusted version, and Hedges’ g, which adds a small-sample correction to reduce bias.

Interpretation of standardized differences is scale-independent but requires context. Conventional benchmarks from Cohen suggest small around 0.2, medium around 0.5, and large around 0.8, though these guidelines are rough and depend on the field and outcome. Standardierojen are widely used in meta-analyses to synthesize continuous outcomes measured differently across studies, enabling a common comparison metric. They can be converted back to more interpretable units if a representative standard deviation from a relevant population is known.

Limitations and considerations include sensitivity to the chosen standard deviation, potential loss of intuitive meaning when scales differ markedly, and possible bias in small samples. Assumptions of normality and similar variability between groups can affect the reliability of the estimate. When reporting, authors typically specify whether they use Cohen’s d or Hedges’ g and describe the context for interpretation.