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Integrative data analysis: The simultaneous analysis of multiple data sets
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There are both quantitative and methodological techniques that foster the development and maintenance of a cumulative knowledge base within the psychological sciences. Most noteworthy of these techniques is meta-analysis, which allows for the synthesis of summary statistics drawn from multiple studies when the original data are not available. However, when the original data can be obtained from multiple studies, many advantages stem from the statistical analysis of the pooled data. The authors define integrative data analysis (IDA) as the analysis of multiple data sets that have been pooled into one. Although variants of IDA have been incorporated into other scientific disciplines, the use of these techniques is much less evident in psychology. In this article the authors present an overview of IDA as it may be applied within the psychological sciences, discuss the relative advantages and disadvantages of IDA, describe analytic strategies for analyzing pooled individual data, and offer recommendations for the use of IDA in practice.
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“First, IPD metaanalyses provide substantially more statistical power. This increased power is particularly important for subgroups that are numerically small in any single study; our data on underrepresented students are notable in this regard (73, 74).”
From Active learning narrows achievement gaps for underrepresented students in undergraduate science, technology, engineering, and math (2020) · cites this paper as [73]
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“For multigroup analysis, scores of the two samples were equated, using methods described by [42].”
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Metadata
- Authors
- Curran, P. J., & Hussong, A. M.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Venue
- Psychological Methods
- Published
- 2009
- Volume
- 14
- Issue
- 2
- Pages
- 81-100
- ISSN
- 1082-989X (ISSN-L)
- 1939-1463
- PMC
- PMC2777640
- OpenAlex
- W2072327382
- Cited by
- 867
- References
- 112
- Citations by year
- 2026: 61 · 2025: 51 · 2024: 95 · 2023: 73 · 2022: 95 · 2021: 94 · 2020: 80 · 2019: 61 · 2018: 51 · 2017: 35 · 2016: 45 · 2015: 43 · 2014: 23 · 2013: 17 · 2012: 21
- FWCI
- 17.24
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Psychological Methods (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- UNC Libraries
- Funders
- National Institute on Drug Abuse (DA013148, DA15398)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Keywords
- integrative data analysis, pooled analysis, multiple data sets, meta-analysis, analytical strategies, evidence synthesis
- MeSH terms
- Data Collection, Data Interpretation, Statistical, Humans, Research, Research Design, Meta-Analysis as Topic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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