Abstract
Errors relating to the use of the correlation coefficient and bivariate linear regression are often to be found in medical publications. This paper reports a literature search to define the problems. All the papers and letters published in the British Medical Journal, The Lancet and the New England Journal of Medicine during 1997 were screened for examples. Fifteen categories of errors were identified of which eight were important or common. These included: failure to define clearly the relevant sample number; the display of potentially misleading scatterplots; attachment of unwarranted importance to significance levels; and the omission of confidence intervals for correlation coefficients and around regression lines.
Keywords
MeSH Terms
Related Publications
On the misuse of residuals in ecology: regression of residuals vs. multiple regression
1 Residuals from linear regressions are used frequently in statistical analysis, often for the purpose of controlling for unwanted effects in multivariable datasets. This paper ...
Introduction to Econometrics
Foreword. Preface to the Second Edition. Preface to the Third Edition. Obituary. INTRODUCTION AND THE LINEAR REGRESSION MODEL. What is Econometrics? Statistical Background and M...
Statistical Problems in the Reporting of Clinical Trials
Reports of clinical trials often contain a wealth of data comparing treatments. This can lead to problems in interpretation, particularly when significance testing is used exten...
Underestimation of Risk Associations Due to Regression Dilution in Long-term Follow-up of Prospective Studies
In prospective studies, disease rates during follow-up are typically analyzed with respect to the values of factors measured during an initial baseline survey. However, because ...
Publication Info
- Year
- 1999
- Type
- review
- Volume
- 92
- Issue
- 3
- Pages
- 123-128
- Citations
- 63
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.1177/014107689909200306
- PMID
- 10396255
- PMCID
- PMC1297101