How to control confounding effects by statistical analysis
Gastroenterology and Hepatology from Bed to Bench. 2012; 5 (2): 79-83
en Inglés
| IMEMR
| ID: emr-116797
ABSTRACT
A Confounder is a variable whose presence affects the variables being studied so that the results do not reflect the actual relationship. There are various ways to exclude or control confounding variables including Randomization, Restriction and Matching. But all these methods are applicable at the time of study design. When experimental designs are premature, impractical, or impossible, researchers must rely on statistical methods to adjust for potentially confounding effects. These Statistical models [especially regression models] are flexible to eliminate the effects of confounders
Buscar en Google
Índice:
IMEMR (Mediterraneo Oriental)
Idioma:
Inglés
Revista:
Gastroenterol. Hepatol. Bed Bench
Año:
2012
Similares
MEDLINE
...
LILACS
LIS