Conducting a Meta-Analysis with SPSS Version 28

30/01/2025

Introduction

Scientific research is a cumulative process in which each individual study contributes to advancing a field. However, when looking at multiple studies on a specific topic, it can be challenging to draw clear conclusions, especially when the results vary. A well-known example of this is the debate over the effectiveness of psychotherapy, sparked in the 1950s by Hans Eysenck, who argued that psychotherapy had no positive effects. But in 1976, Gene V. Glass performed a meta-analysis of 375 studies and demonstrated that psychotherapy was indeed effective for patients. Meta-analysis is now an accepted method for statistically combining the results of multiple studies to draw overall conclusions. SPSS Version 28 provides powerful tools to perform meta-analyses, and in this article, we will show you how to use this software effectively.

What is Meta-Analysis?

A meta-analysis is a quantitative method used to combine the results from multiple studies to obtain a summary answer to a research question. It is commonly used in the social and health sciences to understand the effectiveness of various interventions. The foundation of a meta-analysis is the effect size, a standardized measure of the difference or relationship between the variables being studied. SPSS Version 28 allows researchers to conduct these analyses easily by inputting either raw data or pre-calculated effect sizes. The program offers both fixed-effect and random-effects models, depending on whether it is assumed that the parameters are the same across all studies or vary randomly.

Steps to Conduct a Meta-Analysis with SPSS Version 28

Step 1: Prepare Your Data Before you begin your meta-analysis, you need to ensure you have the required data. The key variables include:

  • Effect Size (e.g., Cohen's d, Hedges' g, or Log Odds Ratio)
  • Variance or Standard Error of the effect size
  • Study ID for identifying individual studies

SPSS allows you to input both raw data (e.g., means, standard deviations) and pre-calculated effect sizes.

Step 2: Import Data into SPSS To use your data in SPSS, you can import it from Excel or other formats. To do this, go to "File > Import Data > Excel" to open the file.

Step 3: Open the Meta-Analysis Menu In SPSS 28, you can find the Meta-Analysis menu under "Analyze > Meta-Analysis." Select the appropriate options for your data: raw data or pre-calculated effect sizes, continuous or binary outcomes.

Step 4: Calculate the Effect Size For continuous data, select "Meta-Analysis > Continuous Outcomes > Raw Data." Enter the means, standard deviations, and sample sizes for both the treatment and control groups. Then, choose the effect size type (e.g., Cohen's d) and the model (fixed-effect or random-effects).

Step 5: Check for Heterogeneity One of the key analyses in a meta-analysis is checking for heterogeneity, which refers to the variability of results between studies. In SPSS, you can do this using Q-statistics and I-squared values. Go to "Analyze > Meta-Analysis > Raw Data > Print" and select "Test of Homogeneity" to check for heterogeneity.

Step 6: Create Plots To visually assess heterogeneity, you can create various plots, such as a Forest Plot or a Funnel Plot. Go to the Plot menu and select the desired graphic.

Step 7: Assess Publication Bias Publication bias, which is the tendency for statistically significant results to be published more frequently, can affect a meta-analysis. In SPSS, you can check for this using methods such as the Trim-and-Fill procedure or Egger's Regression Test.

Step 8: Subgroup Analysis and Meta-Regression To examine the influence of moderators (e.g., study region, participant age), you can conduct a subgroup analysis or a meta-regression. In SPSS, you can enter moderator variables into the appropriate fields to perform these analyses.

Conclusion

SPSS Version 28 offers a user-friendly and comprehensive solution for conducting meta-analyses. With the new features in SPSS 28 for meta-analysis, researchers and students can perform effective analyses without extensive programming knowledge. From calculating effect sizes to checking for heterogeneity and publication bias, SPSS provides a suite of tools that make the meta-analysis process significantly easier. By following the steps outlined in this article, you can gain valuable insights by combining the results of multiple studies, laying a solid statistical foundation for your research.

Frequently Asked Questions (FAQ)

  1. What is a meta-analysis? A meta-analysis is a statistical method that combines the results of multiple studies to provide a summary answer to a research question.

  2. How do I conduct a meta-analysis with SPSS Version 28? You need to prepare your data, open the meta-analysis menu in SPSS, select the effect size type and model, check for heterogeneity, and perform bias assessments and subgroup analyses.

  3. What effect sizes can I use in SPSS for a meta-analysis? You can use Cohen's d, Hedges' g, Glass' delta, Log Odds Ratio, and Risk Ratios, among others.

  4. What is heterogeneity in a meta-analysis? Heterogeneity refers to the variability of results between different studies. It helps determine whether the studies are measuring a common effect or if there are differences between them.

  5. How can I detect publication bias in a meta-analysis? You can detect publication bias using tests such as the Trim-and-Fill procedure or Egger's Regression Test in SPSS.