Reporting of multivariable methods in the medical literature

Journal of Investigative Medicine

Volumn 56, Issue 7, 2008, Pages 954-957

  Tetrault, Jeanette M ^a,b   Sauler, Maor ^a,b   Wells, Carolyn K ^a,b   Concato, John ^a,b  

^a VA CONNECTICUT HEALTHCARE SYSTEM   (United States)

^b YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Multivariable analysis; Regression analysis; Statistical models

Indexed keywords

ANALYTIC METHOD; ARTICLE; CODING; HAZARD ASSESSMENT; INTERNAL MEDICINE; LOGISTIC REGRESSION ANALYSIS; MEDICAL LITERATURE; MEDICAL PRACTICE; MEDICAL SOCIETY; METHODOLOGY; POISSON DISTRIBUTION; PREVALENCE; PROPORTIONAL HAZARDS MODEL; TRAINING; UNITED STATES; BIOMETRY; MULTIVARIATE ANALYSIS; PUBLISHING; STATISTICAL ANALYSIS; STATISTICAL MODEL;

BIOMETRY; DATA INTERPRETATION, STATISTICAL; LOGISTIC MODELS; MULTIVARIATE ANALYSIS; PROPORTIONAL HAZARDS MODELS; PUBLISHING;

EID: 58149144668     PISSN: 17088267     EISSN: None     Source Type: Journal    
DOI: 10.2310/JIM.0b013e31818914ff     Document Type: Article

References (20)

1. Concato J, Feinstein AR, Holford TR. The risk of determining risk with multivariable models. Ann Intern Med. 1993;118:201-210.
2. Katz MH. Multivariable analysis: a primer for readers of medical research. Ann Intern Med. 2003;138:644-650.
3. Harrell FE Jr, Lee KL, Pollock BG. Regression models in clinical studies: determining relationships between predictors and response. J Natl Cancer Inst. 1988;80: 1198-1202.
4. Berwick DM, Fineberg HV, Weinstein MC. When doctors meet numbers. Am J Med. 1981;71:991-998.
5. Windish DM, Diener-West M. A clinician-educator's roadmap to choosing and interpreting statistical tests. J Gen Intern Med. 2006;21:656-660.
6. Peduzzi P, Concato J, Kemper E, et al. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol. 1996;49:1373-1379.
7. Concato J, Peduzzi P, Holford TR, et al. Importance of events per independent variable in proportional hazards analysis. I. Background, goals, and general strategy. J Clin Epidemiol. 1995;48:1495-1501.
8. Peduzzi P, Concato J, Feinstein AR, et al. Importance of events per independent variable in proportional hazards regression analysis. II. Accuracy and precision of regression estimates. J Clin Epidemiol. 1995;48:1503-1510.
9. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33: 159-174.
10. O'Quigley J, Flandre P. Predictive capability of proportional hazards regression. Proc Natl Acad Sci U S A. 1994; 91:2310-2314.
11. Wei LJ. The accelerated failure time model: a useful alternative to the Cox regression model in survival analysis. Stat Med. 1992;11:1871-1879.
12. Walker S, Mallick BK. A Bayesian semiparametric accelerated failure time model. Biometrics. 1999;55: 477-483.
13. Harrell FE Jr, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996;15:361-387.
14. Hosmer DW, Lemeshow S. Applied Logistic Regression. New York, NY: Wiley; 1989.
15. Grambsch RM, Therneau TM. Proportional hazards tests and diagnostics based on weighted residuals. Biometrika. 1994;81:515-526.
16. Moss M, Wellman DA, Cotsonis GA. An appraisal of multivariable logistic models in the pulmonary and critical care literature. Chest. 2003;123:923-928.
17. Khan KS, Chien PF, Dwarakanath LS. Logistic regression models in obstetrics and gynecology literature. Obstet Gynecol. 1999;93:1014-1020.
18. Goodman SN, Berlin J, Fletcher SW, et al. Manuscript quality before and after peer review and editing at Annals of Internal Medicine. Ann Intern Med. 1994;121:11-21.
19. Goodman SN, Altman DG, George SL. Statistical reviewing policies of medical journals: caveat lector? J Gen Intern Med. 1998;13:753-756.
20. Altman DG, Goodman SN, Schroter S. How statistical expertise is used in medical research. JAMA. 2002;287: 2817-2820.