The DOI matches its Crossref record; 50 of the 51 references it cites were found in a registry or an index.
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.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“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]
Citations
Cites
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
A Coefficient of Agreement for Nominal Scales
Cohen, J. (1960) · Educational and Psychological Measurement · doi:10.1177/001316446002000104 · Cited by 42,398
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1994) · doi:10.1201/9780429246593 · Cited by 40,500
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1993) · doi:10.1007/978-1-4899-4541-9 · Cited by 21,230
Bootstrap methods: another look at the jackknife
Efron, B. (1979) · The Annals of Statistics · doi:10.1214/aos/1176344552 · Cited by 17,602
Hao (2015) · doi:10.1002/14651858 · Cited by 11,321
Statistical Methods for Psychology.
Gudgeon, A. C., & Howell, D. C. (1994) · Journal of the Royal Statistical Society Series D (The Statistician) · doi:10.2307/2348956 · Cited by 8,277
Bootstrap Methods and their Application
Davison, A. C., & Hinkley, D. V. (1997) · doi:10.1017/cbo9780511802843 · Cited by 7,350
Agresti, A. (2002) · Wiley Series in Probability and Statistics · doi:10.1002/0471249688 · Cited by 6,746
Bootstrap Methods and Their Application
Loughin, T. M., Davison, A. C., & HINKLEY, D. V. (1999) · Journal of the American Statistical Association · doi:10.2307/2669707 · Cited by 5,478
Research works printed but not linked: 2
- Binks C. A., 2006, Cochrane Database of Systematic Reviews
- Field A. P., Discovering statistics using R: and sex and drugs and rock ‘n’ roll.
Cited by
Sorted by citations
The psychological impact of COVID-19 and restrictive measures in the world
Passavanti, M., Argentieri, A., Barbieri, D. M., Lou, B., Wijayaratna, K. P., Mirhosseini, A. F., Wang, F., Naseri, S., Qamhia, I. I. A., Tangerås, M., et al. (2021) · Journal of Affective Disorders · doi:10.1016/j.jad.2021.01.020 · Cited by 211
Predicting student success using fine grain clicker data
Porter, L., Zingaro, D., & Lister, R. (2014) · ACM Conference on International Computing Education Research (ICER) · doi:10.1145/2632320.2632354 · Cited by 110
Choi, H.-Y. (2022) · Sustainability · doi:10.3390/su14063629 · Cited by 85
Characterizing cardiac autonomic dynamics of fear learning in humans
Battaglia, S., Orsolini, S., Borgomaneri, S., Barbieri, R., Diciotti, S., & di Pellegrino, G. (2022) · Psychophysiology · doi:10.1111/psyp.14122 · Cited by 83
Sexual abuse predicts functional somatic symptoms: An adolescent population study
Bonvanie, I. J., van Gils, A., Janssens, K. A. M., & Rosmalen, J. G. M. (2015) · Child Abuse & Neglect · doi:10.1016/j.chiabu.2015.06.001 · Cited by 68
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
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 ›
Are you an author, or do you see a problem with this page? Request a review
