Faculty Collaboration Database

Statistical methods in SUPPORT. J Clin Epidemiol 1990;43 Suppl:89S-98S

Date

01/01/1990

Pubmed ID

2254801

DOI

10.1016/0895-4356(90)90227-g

Scopus ID

2-s2.0-0025696009 (requires institutional sign-in at Scopus site)   8 Citations

Abstract

The analysis and interpretation of the data collected in SUPPORT provide great potential for understanding the relationships among treatment choices, patient and physician values and preferences, perceptions about the risks and benefits of treatments, institutional characteristics, and outcomes (as measured by quality of life, survival, and satisfaction). The complicated analyses required to elucidate these relationships will pose many technical challenges in dealing with longitudinal observational data collected from seriously ill patients at multiple sites. Major challenges include the handling of incomplete data, proper parameterization of treatment effects, strategies to avoid various potential biases, validating predictive models, and constructing endpoints that combine survival with quality of life. Within the structure of the SUPPORT study, mechanisms have been established to guide the analyses and to ensure their quality and validity.

Author List

Harrell FE Jr, Marcus SE, Layde PM, Broste SK, Cook EF, Wagner DP, Muhlbaier LH, Peck SL

Author

Peter M. Layde MS, MD Emeritus Professor in the Emergency Medicine department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Data Interpretation, Statistical
Health Services Research
Humans
Models, Statistical
Probability
Quality Control
Reproducibility of Results
United States