What is the basic unit of analysis often used in meta-analyses for assessing the effectiveness of addiction treatments?

The basic unit of analysis commonly used in meta-analyses to assess the effectiveness of addiction treatments is the effect size. Effect size provides a quantitative measure of the magnitude of the treatment effect, enabling researchers to compare results across different studies that may use various scales and measurement tools.

In the context of addiction treatment research, effect size allows for the integration of findings from multiple studies, facilitating a more comprehensive understanding of how effective a particular treatment is compared to control conditions or other treatments. Different types of effect sizes can be calculated, such as Cohen's d, odds ratios, or correlation coefficients, which offer flexibility in representing the impact of interventions.

While variance, standard deviation, and mean difference are important statistical concepts, they serve different functions. Variance measures the spread of data, standard deviation indicates how much individual scores deviate from the mean, and mean difference specifically compares the averages of two groups. However, none of these options serve as a standardized measure to aggregate treatment effects across studies like effect size does.