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Using Bootstrap Estimation and the Plug-in Principle for Clinical Psychology Data
Abstract
Psychologists estimate the precision of their statistics both to conduct hypothesis tests and to construct confidence intervals. The methods traditionally used for this are available only for a small set of statistics (e.g., the mean and transformations of it) and often make unrealistic assumptions about the variables' distributions. These assumptions are often particularly unrealistic in data derived from clinical samples, or when looking at groups responding at the extreme end of clinical constructs. Bootstrap estimation is a computer intensive procedure that offers a flexible and automatic alternative. The computer takes thousands of bootstrap samples from the observed data and from these bootstrap samples estimates the precision of the statistic. High-speed personal computers make the bootstrap a viable and appealing technique throughout the sciences. This article offers a tutorial on the theory and practice of applying bootstrap estimation to data from clinical samples and measures relevant to experimental psychopathology.
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“The data analysis will use Paired Sample T-Test with bootstrap technique to compare the measures at pre-test and post-test. The bootstrapped statistical significance is used, instead of the usual normal curve statistical significance. The use of bootstrap has been recommended for experimental clinical psychology research, as the normal distribution assumption is rarely met[44]. Furthermore, boot”
From Preliminary Study on the Effectiveness of Short Group Cognitive Behavioral Therapy (GCBT) on Indonesian Older Adults (2013) · cites this paper as [44]
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Metadata
- Authors
- Wright, D. B., London, K., & Field, A. P.
- Affiliations
- Florida International University (US)
- University of Toledo (US)
- University of Sussex (GB)
- Corresponding author
- Wright, Daniel B.
- Venue
- Journal of Experimental Psychopathology
- Publisher
- SAGE Publications
- Published
- 2011-05
- Volume
- 2
- Issue
- 2
- Pages
- 252-270
- ISSN
- 2043-8087 (ISSN-L)
- OpenAlex
- W2036617704
- Cited by
- 187
- References
- 51
- Citations by year
- 2026: 14 · 2025: 13 · 2024: 16 · 2023: 10 · 2022: 25 · 2021: 24 · 2020: 19 · 2019: 18 · 2018: 12 · 2017: 13 · 2016: 7 · 2015: 5 · 2014: 8 · 2013: 3
- FWCI
- 3.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Experimental Psychopathology (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Keywords
- bootstrap estimation, confidence intervals, hypothesis testing, statistical precision, clinical samples
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