Logistic regression analysis can provide an estimate of the odds ratio (OR), adjusted for a number of confounders. It is known that it is approximately equal to the associated adjusted relative risk (RR) if the incidence of an outcome of interest is rare in a cohort study or a clinical trial study. In this paper, we consider the incidence of an outcome that is relatively common in a study population, and investigate the relationship between the two null hypotheses that an OR and the associated RR are equal to unity. It is shown that the p-values associated with the two null hypotheses are asymptotically equivalent. This complements the existing formula for converting an adjusted estimate of the OR and the associated confidence interval to t...
In randomized controlled trials (RCTs), the odds ratio (OR) can substantially overestimate the risk ...
Background: In case-cohort studies with binary outcomes, ordinary logistic regression analyses have ...
The extensive use of logistic regression models in analytical epidemiology as well as in randomized ...
ObjectiveIn clinical trials, the relative risk or risk ratio (RR) is a mainstay of reporting of the ...
The relative risk or prevalence ratio is a natural and familiar summary of association between a bin...
In medical and epidemiological studies, the odds ratio is a commonly applied measure to approximate ...
Logistic regression and odds ratios (ORs) are powerful tools recently becoming more common in the so...
Both the absolute risk and the relative risk (RR) have a crucial role to play in epidemiology. RR is...
<div><p>Both the absolute risk and the relative risk (RR) have a crucial role to play in epidemiolog...
Background: Binary outcomes are common in prospective studies such as randomized controlled trials a...
Logistic regression yields an adjusted odds ratio that approximates the adjusted relative risk when ...
Objectives: In a recent paper we suggest that the relative risk (RR) be replaced with the odds ratio...
Relative risk and odds ratio are often confused or interchanged. Especially while coefficients in lo...
a logistic regression. When the outcome prevalence is high (>10%), the OR can still be estimated ...
Recent studies have emphasized that there is no justification for using the odds ratio (OR) as an ap...
In randomized controlled trials (RCTs), the odds ratio (OR) can substantially overestimate the risk ...
Background: In case-cohort studies with binary outcomes, ordinary logistic regression analyses have ...
The extensive use of logistic regression models in analytical epidemiology as well as in randomized ...
ObjectiveIn clinical trials, the relative risk or risk ratio (RR) is a mainstay of reporting of the ...
The relative risk or prevalence ratio is a natural and familiar summary of association between a bin...
In medical and epidemiological studies, the odds ratio is a commonly applied measure to approximate ...
Logistic regression and odds ratios (ORs) are powerful tools recently becoming more common in the so...
Both the absolute risk and the relative risk (RR) have a crucial role to play in epidemiology. RR is...
<div><p>Both the absolute risk and the relative risk (RR) have a crucial role to play in epidemiolog...
Background: Binary outcomes are common in prospective studies such as randomized controlled trials a...
Logistic regression yields an adjusted odds ratio that approximates the adjusted relative risk when ...
Objectives: In a recent paper we suggest that the relative risk (RR) be replaced with the odds ratio...
Relative risk and odds ratio are often confused or interchanged. Especially while coefficients in lo...
a logistic regression. When the outcome prevalence is high (>10%), the OR can still be estimated ...
Recent studies have emphasized that there is no justification for using the odds ratio (OR) as an ap...
In randomized controlled trials (RCTs), the odds ratio (OR) can substantially overestimate the risk ...
Background: In case-cohort studies with binary outcomes, ordinary logistic regression analyses have ...
The extensive use of logistic regression models in analytical epidemiology as well as in randomized ...