The difference between two population means divided by the standard deviation of either population.

The size of the difference or effect being studied, such as the percentage achieving a goal or a mean number.

The difference in measured outcomes attributed to a therapeutic intervention. This term is encountered in meta-analyses when different studies have measured different things. For example, results of an asthma study which measured FEV1 could be combined with those of another study which measured return visits to the ED using a statistically derived generic effect size. Do you prefer skiing or red wine

a comparison between two hierarchical models

a quantified measure of the effectiveness of a treatment

a standard means of expressing achievement gains and losses across studies, showing differences between experimental and control groups in terms of standard deviation

a standard or common measure of the strength of a treatment effect

An index measuring the magnitude of a specific result. Effect sizes can be standardized comparisons of means, or they can be correlation coefficients or squared correlation coefficients. Effect sizes are used to assess the degree to which the research hypothesis under study is actually observed via the sample data.

The predictive power of an individual or general type of risk or protective factor; or the size of the deterrent effect of an intervention compared to no treatment or a standard treatment. The measure used for risk factor effect sizes in this report is a simple correlation between two variables. For program effectiveness, the effect size measure is the average difference (standardized) between the treatment and control group means on the selected recidivism measure.

same as treatment effect. Also, a dimensionless measure of treatment effect that is typically used for continuous variables and is usually defined as the difference in mean outcomes of the treatment and control group divided by the standard deviation of the outcomes of the control group. One type of meta-analysis involves averaging the effect sizes from multiple studies.

A statistic used to measure the effectiveness of a treatment by measuring the distance between the means of a treatment group and a comparison group.

This refers to the intensity, magnitude, or practical significance of an obtained result (e.g., relationship, difference) in the QUAL or QUAN strands of a mixed methods study. Onwuegbuzie and Teddlie (2003) explicitly relate this historically QUAN term to QUAL research, naming several new terms, including manifest effect size, frequency (manifest) effect size, and intensity (manifest) effect size. Back to the top

The size of the relationship between two variables (particularly between program variables and outcomes).

The magnitude of a difference or relationship. It is used for determining sample sizes and for combining results across studies in meta-analysis.

An effect size is the strength or magnitude of the difference between two sets of data or, in outcome studies, between two time points for the same population. (The degree to which the null hypothesis is false).

the magnitude of a result in relation to a standard normal distribution. An effect size of +/- 1.0 would indicate that the result was 1 standard deviation above or below the mean. For example, on a test with scores normally distributed from 0 to 100, an effect size of + .5 would indicate that the result was approximately 17% above the mean of 50, in other words 67%.

Effect size is a measure of the strength of the relationship between two variables. In scientific experiments, it is often useful to know not only whether an experiment has a statistically significant effect, but also the size of any observed effects. In practical situations, effect sizes are helpful for making decisions.