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Step 1: Understanding Meta-Analysis

Because meta-analyses summarize (all) the existing literature of a particular field in a quantitative manner, each individual study, in a sense, becomes a participant from which you must collect your data. Data collection occurs through a process called coding (See Step 4 and Step 5). Once you have coded all the articles, you will need to select the meta-analytic model that best fits the type of data you have collected (Step 6). You will then begin the analysis process using SPSS.

Before you begin this adventure, it is important to understand that doing a meta-analysis is an iterative process. Thus, you may have to repeat steps multiple times before your meta is complete.

STRENGTHS OF META-ANALYSIS:

  1. Takes into account multiple factors (moderators) outside the variable of interest that may influence the dependent variable.

  2. Indicates areas for improvement in existing techniques and suggests future research possibilities.

  3. Combines multiple methods of measuring the same variable into a single model.

LIMITATIONS:

  1. Too few or too many relevant articles on a particular subject.

  2. Can only prove correlation, not causation.

  3. Dependent on the information that others have reported.

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Step 2: Establishing a Question

The question will determine not only the search terms you use to collect studies, but also the inclusion criteria and the moderators.

Video Tutorials
AcqKnowledge Tutorial - Part 2
06:48
AcqKnowledge Tutorial - Part 1
02:11
Meta-analysis in R - Plotting Data
07:47
Meta-analysis in R - Data Culmination
01:18
Meta-analysis in R - Filtering Data
01:04
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