Add to ORKGFitting parametric survival models with interval-censored data is a common task in survival analysis and implemented in many statistical software packages. Here, we present a novel approach to fit such models if the values on the scale of interest are measured with error. Random effects ANOVA models are used to account for the measurement errors and the likelihood function of the parametric survival model is maximized with numerical methods. An illustration is provided with a real data set on the rejection of yogurt as a function of its acid tastePeer Reviewe
We propose a method for calculating power and sample size for studies involving interval-censored fa...
In survival or reliability data analysis, it is often useful to estimate the quantiles of the lifeti...
Shelf life is defined as the length of time a pharmaceutical product is expected to remain within ap...
Fitting parametric survival models with interval-censored data is a common task in survival analysis...
In the present work we applied interval-censored survival analysis techniques to estimate sensory cu...
Data from sensory shelf-life studies can be analyzed using survival statistical methods. The objecti...
Survival analysis statistics have been used to estimate shelf life of foods based on consumers’ acce...
Simultaneous discrimination among various parametric lifetime models is an important step in the par...
Often in survival analysis, response that is measured over time is not a continuous measure but is t...
Although semi- and non-parametric approaches are frequently used to analyse survival data, there are...
This work concerns some problems in the area of survival analysis that arise in real clinical or epi...
Survival analysis is a popular area of statistics dealing with time-to-event data. A special charact...
By interval-censored failure time data, we mean that the failure time of interest is observed to bel...
The properties of Palm Oil (PO) and Coconut Oil (CO) offer the potential for transformers Interval-c...
Quantile regression models the conditional quantile as a function of independent variables providing...
We propose a method for calculating power and sample size for studies involving interval-censored fa...
In survival or reliability data analysis, it is often useful to estimate the quantiles of the lifeti...
Shelf life is defined as the length of time a pharmaceutical product is expected to remain within ap...
Fitting parametric survival models with interval-censored data is a common task in survival analysis...
In the present work we applied interval-censored survival analysis techniques to estimate sensory cu...
Data from sensory shelf-life studies can be analyzed using survival statistical methods. The objecti...
Survival analysis statistics have been used to estimate shelf life of foods based on consumers’ acce...
Simultaneous discrimination among various parametric lifetime models is an important step in the par...
Often in survival analysis, response that is measured over time is not a continuous measure but is t...
Although semi- and non-parametric approaches are frequently used to analyse survival data, there are...
This work concerns some problems in the area of survival analysis that arise in real clinical or epi...
Survival analysis is a popular area of statistics dealing with time-to-event data. A special charact...
By interval-censored failure time data, we mean that the failure time of interest is observed to bel...
The properties of Palm Oil (PO) and Coconut Oil (CO) offer the potential for transformers Interval-c...
Quantile regression models the conditional quantile as a function of independent variables providing...
We propose a method for calculating power and sample size for studies involving interval-censored fa...
In survival or reliability data analysis, it is often useful to estimate the quantiles of the lifeti...
Shelf life is defined as the length of time a pharmaceutical product is expected to remain within ap...