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What is a cause-specific hazard?

What is a cause-specific hazard?

The cause-specific hazard function denotes the instantaneous rate of occurrence of the kth event in subjects who are currently event free (ie, in subjects who have not yet experienced any of the different types of events).

What is cause-specific hazard ratio?

Therefore, the cause‐specific hazard ratio denotes the relative change in the instantaneous rate of the occurrence of the primary event in subjects who are currently event‐free. The rate of the occurrence of the event denotes the intensity with which events occur.

How do I analyze multiple failure time data using Stata?

The steps for analyzing multiple failure data in Stata are (1) decide whether the failure events are ordered or unordered, (2) select the proper statistical model for the data, (3) organize the data according to the model selected, and (4) use the proper commands and command options to stset the data and fit the model.

What is 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 Cox regression used for?

Cox regression (or proportional hazards regression) is method for investigating the effect of several variables upon the time a specified event takes to happen. In the context of an outcome such as death this is known as Cox regression for survival analysis.

What is Gray’s test?

Gray’s test is used to evaluate hypotheses of equality of cause-specific cumulative incidence functions between two groups, but as in the case of comparing survival curves, the test actually compares an underlying function of the cumulative incidence function, namely the subdistribution hazard.

What is Aalen Johansen estimator?

The Aalen–Johansen estimator is a matrix version of the Kaplan–Meier estimator, and it can be used to estimate the transition probability matrix of a Markov process with a finite number of states. The estimator is first presented for the competing risks model and the Markov illness-death model for a chronic disease.

What is cumulative hazard?

We can say that the cumulative hazard function: measures the total amount of risk that has been accumulated up to a certain point of time t. provides the number of times we would mathematically expect the occurrence of the event of interest over a certain period if only the events were repeatable.

What does a Kaplan-Meier curve show?

The Kaplan-Meier estimator is used to estimate the survival function. The visual representation of this function is usually called the Kaplan-Meier curve, and it shows what the probability of an event (for example, survival) is at a certain time interval.

What is fine and gray Subdistribution hazard model?

The Fine-Gray subdistribution hazard model has become the default method to estimate the incidence of outcomes over time in the presence of competing risks. This model is attractive because it directly relates covariates to the cumulative incidence function (CIF) of the event of interest.

What is the difference between Kaplan Meier and Cox regression?

Cox Regression. KM Survival Analysis cannot use multiple predictors, whereas Cox Regression can. KM Survival Analysis can run only on a single binary predictor, whereas Cox Regression can use both continuous and binary predictors. KM is a non-parametric procedure, whereas Cox Regression is a semi-parametric procedure.

How do you interpret the hazard ratio in Cox regression?

If the hazard ratio is less than 1, then the predictor is protective (i.e., associated with improved survival) and if the hazard ratio is greater than 1, then the predictor is associated with increased risk (or decreased survival).