A quantitative analysis method which aggregates a number of (similar) individual studies into a large data set from which to compute an over all “effect size” (based on similar study procedures and treatments) is commonly known as
probably statistics
The quantitative analysis method you are referring to is called meta-analysis.
Meta-analysis involves systematically reviewing and collecting data from multiple individual studies on a particular research question or topic. These individual studies, often referred to as primary studies, usually investigate similar research questions and have comparable research designs and treatments.
To perform a meta-analysis, the following steps are typically followed:
1. Formulating the research question or objective: Determine the specific research question or objective that the meta-analysis aims to address. This step helps to define the scope and focus of the analysis.
2. Literature search and study selection: Conduct a comprehensive search of the existing literature to identify all relevant studies. This involves searching databases, journals, conference proceedings, and other sources to collect as much information as possible. Then, based on predefined inclusion and exclusion criteria, select the studies that meet the criteria for inclusion in the meta-analysis.
3. Data extraction: Once the relevant studies are identified, the next step is to extract relevant data from each study. This may include study characteristics (e.g., sample size, study design, treatment protocols) and outcome measures (e.g., effect sizes, p-values).
4. Effect size computation: Compute effect sizes for each included study. Effect sizes quantify the magnitude of the treatment effect or the relationship between variables of interest. Commonly used effect size measures include standardized mean difference (Cohen's d), correlation coefficient (r), or odds ratio (OR).
5. Statistical analysis: Analyze the collected data using appropriate statistical methods. This may involve using statistical software to calculate weighted average effect sizes and to estimate the overall effect size. Additionally, statistical techniques like subgroup analysis and sensitivity analysis can be used to explore potential sources of heterogeneity across studies.
6. Interpretation and reporting: Interpret the results of the meta-analysis and report the findings. This includes discussing the overall effect size, its statistical significance, and potential implications for the research question under investigation. It is important to report any limitations or biases that may have influenced the results.
Meta-analysis is a powerful technique that allows researchers to synthesize and summarize the evidence from multiple studies, providing more robust and reliable conclusions than individual studies alone.