Practical Statistics for Medical Research
Abstract
Practical Statistics for Medical Research is a problem-based text for medical researchers, medical students, and others in the medical arena who need to use statistics but have no specialized mathematics background. The author draws on twenty years of experience as a consulting medical statistician to provide clear explanations to key statistical concepts, with a firm emphasis on practical aspects of designing and analyzing medical research. Using real data and including dozens of interesting data sets, this bestselling text gives special attention to the presentation and interpretation of results and the many real problems that arise in medical research.
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The interpretation of Cohen kappa was based on Altman's categories.
“The interpretation of the Cohen kappa coefficient was based on the categories developed by Douglas Altman: 0.00-0.20 (poor), 0.21-0.40 (fair), 0.41-0.60 (moderate), 0.61-0.80 (good), and 0.81-1.00 (very good) [56,57].”
From Voice-Based Conversational Agents for the Prevention and Management of Chronic and Mental Health Conditions: Systematic Literature Review (2021) · cites this paper as [57]
Interrater reliabilities (AC1) ranged from low for anxiety disorders (−0.09 to 0.15) to moderate-to-good for somatoform and associated disorders (0.65 to 0.76).
“Interrater reliabilities (AC1) ranged from low strengths of agreement for anxiety disorders (−0.09 to 0.15) to moderate-to-good strengths of agreement for somatoform and associated disorders (0.65 to 0.76) according to proposed benchmarking thresholds [54].”
From Diagnostic Performance of an App-Based Symptom Checker in Mental Disorders: Comparative Study in Psychotherapy Outpatients (2022) · cites this paper as [54]
The classification of strategy types had good inter-rater reliability in each n-back task.
“An unweighted Cohen’s kappa inter-rater reliability for the two independent raters showed an overall good level of agreement in each n-back task (trained digit n-back, κ = 0.708, 95% CI [0.594, 0.822]; letter n-back, κ = 0.656, 95% CI [0.538, 0.775]; color n-back, κ = 0.693, 95% CI [0.577, 0.810])19.”
From The early effects of external and internal strategies on working memory updating training (2018) · cites this paper as [19]
The scoring procedure for level of detail in self-reported strategies had very good inter-rater reliability.
“Inter-rater reliability analysis (two raters; a linearly weighted kappa analysis, κw)18 applied to our ordinal scale data revealed a very good reliability for the scoring procedure, κw = 0.844, 95% CI [0.774, 0.914]19.”
From The early effects of external and internal strategies on working memory updating training (2018) · cites this paper as [19]
Interrater reliability for study selection was good (Cohen's kappa = 0.71).
“They performed an interrater reliability check where Cohen’s kappa was 0.71, which is considered ‘good’ [36].”
From Can We Increase Psychological Well-Being? The Effects of Interventions on Psychological Well-Being: A Meta-Analysis of Randomized Controlled Trials (2016) · cites this paper as [36]
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- Authors
- Altman, D. G.
- Corresponding author
- Altman, Douglas G.
- ORCID
- Altman, Douglas G.
- Venue
- Chapman & Hall/CRC eBooks
- Publisher
- Chapman and Hall/CRC
- Published
- 1990-11-22
- OpenAlex
- W2118202495
- Cited by
- 10,668
- References
- 0
- Citations by year
- 2026: 196 · 2025: 270 · 2024: 301 · 2023: 223 · 2022: 298 · 2021: 301 · 2020: 297 · 2019: 285 · 2018: 237 · 2017: 248 · 2016: 304 · 2015: 395 · 2014: 448 · 2013: 415 · 2012: 451
- FWCI
- 18.66
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Chapman & Hall/CRC eBooks (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Probabilistic Statistics in Medicine
- Physical Sciences › Mathematics › Statistics and Probability › Statistics Education and Methodologies
- Keywords
- medical statistics, statistical interpretation, medical research methodology, statistical consulting
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.
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