The Fleming-Harrington class for right-censored data was first introduced by Harrington and Fleming (1982). This class is widely used in survival analysis studies and it is a subset of the so-called weighted logrank test statistics. Recently, Oller and Gómez (2012) proposed an extension of this class for interval-censored data. This paper introduces the R package FHtest, which implements the Fleming-Harrington class for right-censored and interval-censored survival data. It provides an integrated approach for performing two-sample, k-sample and trend tests based on either counting process theory, likelihood theory, or permutation distributions. In this paper, we summarize the main aspects of the theory framework and present several examples...
Abstract: The problem of two-sample survival comparisons has been investigated by several authors. P...
Correlated survival outcomes occur quite frequently in the biomedical research. Available software i...
This book provides a groundbreaking introduction to the likelihood inference for correlated survival...
The Fleming-Harrington class for right-censored data was first introduced by Harrington and Fleming ...
The Fleming-Harrington class for right-censored data was first introduced by Harrington and Fleming ...
The class Gρ,λ of weighted log-rank tests proposed by Fleming & Harrington [Fleming & Harrington (1...
Background and objective: In survival analysis, estimating the survival probability of a population ...
The main objective of this master s degree thesis is to build a R package for the goodness-of-fit te...
The nonparametric tests are introduced and provides a new method to compare survival functions among...
Although many theoretical developments have appeared in the last fifty years, interval censoring is ...
In clinical trials, information about certain time points may be of interest in making decisions abo...
This paper is a version of Fay and Shaw (2010) published in the Journal of Statistical Software, and...
Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of...
We propose logrank-type tests for comparing several survival functions from interval-censored data. ...
Survival analysis includes a wide variety of methods for analyzing time-to-event data. One basic but...
Abstract: The problem of two-sample survival comparisons has been investigated by several authors. P...
Correlated survival outcomes occur quite frequently in the biomedical research. Available software i...
This book provides a groundbreaking introduction to the likelihood inference for correlated survival...
The Fleming-Harrington class for right-censored data was first introduced by Harrington and Fleming ...
The Fleming-Harrington class for right-censored data was first introduced by Harrington and Fleming ...
The class Gρ,λ of weighted log-rank tests proposed by Fleming & Harrington [Fleming & Harrington (1...
Background and objective: In survival analysis, estimating the survival probability of a population ...
The main objective of this master s degree thesis is to build a R package for the goodness-of-fit te...
The nonparametric tests are introduced and provides a new method to compare survival functions among...
Although many theoretical developments have appeared in the last fifty years, interval censoring is ...
In clinical trials, information about certain time points may be of interest in making decisions abo...
This paper is a version of Fay and Shaw (2010) published in the Journal of Statistical Software, and...
Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of...
We propose logrank-type tests for comparing several survival functions from interval-censored data. ...
Survival analysis includes a wide variety of methods for analyzing time-to-event data. One basic but...
Abstract: The problem of two-sample survival comparisons has been investigated by several authors. P...
Correlated survival outcomes occur quite frequently in the biomedical research. Available software i...
This book provides a groundbreaking introduction to the likelihood inference for correlated survival...