What is a competing risk analysis? Competing risk analysis refers to a special type of survival analysis that aims to correctly estimate marginal probability of an event in the presence of competing events. What is

## What is a competing risk analysis?

Competing risk analysis refers to a special type of survival analysis that aims to correctly estimate marginal probability of an event in the presence of competing events.

### What is a Subdistribution hazard ratio?

The subdistribution hazard function, introduced by Fine and Gray, for a given type of event is defined as the instantaneous rate of occurrence of the given type of event in subjects who have not yet experienced an event of that type.

**What is a fine and Gray regression model?**

As remedy, Fine and Gray [22] proposed CIF based PH model to analyze survival data arising from a competing risk setup. In the competing risks setup, under each cause for the occurrence of an event of interest, a hazard function in the presence of covariates is considered.

**What is Aalen Johansen estimator?**

Abstract. The Aalen-Johansen estimator is the standard nonparametric estimator of the cumulative incidence function in competing risks. Estimating its variance in small samples has attracted some interest recently, together with a critique of the usual martingale-based estimators.

## Is survival analysis a regression?

Analogous to a linear regression analysis, a survival analysis typically examines the relationship of the survival variable (the time until the event) and the predictor variables (the covariates).

### How do you interpret hazard ratios in survival analysis?

Hazard is defined as the slope of the survival curve — a measure of how rapidly subjects are dying. The hazard ratio compares two treatments. If the hazard ratio is 2.0, then the rate of deaths in one treatment group is twice the rate in the other group.

**When to use competing risks regression in Stata?**

ORDER STATA. Competing-risks survival regression provides a useful alternative to Cox regression in the presence of one or more competing risks. For example, say that you are studying the time from initial treatment for cancer to recurrence of cancer in relation to the type of treatment administered and demographic factors.

**When to use Cox regression or competing risks regression?**

Competing-risks regression. Competing-risks survival regression provides a useful alternative to Cox regression in the presence of one or more competing risks. For example, say that you are studying the time from initial treatment for cancer to recurrence of cancer in relation to the type of treatment administered and demographic factors.

## What to look for in a competing risk regression?

In competing-risks regression, you instead focus on the cumulative incidence function, which indicates the probability of the event of interest happening before a given time. Competing-risks regression is semiparametric in that the baseline subhazard of the event of interest is left unspecified,…

### What is the method of a competing risk analysis?

Like many analyses, the competing risk analysis includes a non-parametric method which involves the use of a modified Chi-squared test to compare CIF curves between groups, and a parametric approach which model the CIF based on a subdistribution hazard function. 1. What is “competing event” and “competing risk”?