This paper shows how heaping of duration data eg caused by rounding due to memory eects can be analyzed If the data are heaped Coxs partial likelihood approach which is often used in survival analysis is no longer appropriate We show how this problem can be overcome by considering the problem as a missing data problem A variant of Coxs Proportional Hazard Model is constructed that takes heaping into account and is estimated by maximum likelihood using the EM algorithm with many nuisance parameters simultaneously for all parameters Ingredients of our method are application of the EM algorithm Cox regression and nonparametric maximumlikelihood calculation with predicted data in each M step An example from practice where jackknife is used to e...
Interval censored data are often observed in studies where event processes are monitored only at cer...
This report presents basic statistical methods for analyzing data obtained by observing random time ...
This dissertation includes three papers on missing data problems where methods other than parametric...
This paper shows how heaping of duration data, e.g. caused by rounding due to memory effects, can be...
This paper shows how heaping of duration data, e.g. caused by rounding due to memory effects, can be...
This paper examined the use of multiple imputation to analyze heaped data. When people are asked to ...
Kauermann G, Xu R, Vaida F. Stacked Laplace-EM algorithm for duration models with time-varying and r...
In 2005, the Indian Government launched a conditional cash-incentive program to encourage institutio...
Heaping is a common type of measurement error emerging when data are collected with various degrees ...
The Cox proportional hazards regression model has been widely used in the analysis of survival/durat...
SUMMARY. Some failure time data come from a population that consists of some subjects who are suscep...
This paper studies the Cox model with time-varying coefficients for cause-specific hazard functions ...
Data with missing value are common in clinical studies. This study investigated to assess the effect...
In 2005, the Indian Government launched a conditional cash-incentive program to en- courage institut...
The Cox proportional hazards model is the most commonly used method when analyzing the impact of cov...
Interval censored data are often observed in studies where event processes are monitored only at cer...
This report presents basic statistical methods for analyzing data obtained by observing random time ...
This dissertation includes three papers on missing data problems where methods other than parametric...
This paper shows how heaping of duration data, e.g. caused by rounding due to memory effects, can be...
This paper shows how heaping of duration data, e.g. caused by rounding due to memory effects, can be...
This paper examined the use of multiple imputation to analyze heaped data. When people are asked to ...
Kauermann G, Xu R, Vaida F. Stacked Laplace-EM algorithm for duration models with time-varying and r...
In 2005, the Indian Government launched a conditional cash-incentive program to encourage institutio...
Heaping is a common type of measurement error emerging when data are collected with various degrees ...
The Cox proportional hazards regression model has been widely used in the analysis of survival/durat...
SUMMARY. Some failure time data come from a population that consists of some subjects who are suscep...
This paper studies the Cox model with time-varying coefficients for cause-specific hazard functions ...
Data with missing value are common in clinical studies. This study investigated to assess the effect...
In 2005, the Indian Government launched a conditional cash-incentive program to en- courage institut...
The Cox proportional hazards model is the most commonly used method when analyzing the impact of cov...
Interval censored data are often observed in studies where event processes are monitored only at cer...
This report presents basic statistical methods for analyzing data obtained by observing random time ...
This dissertation includes three papers on missing data problems where methods other than parametric...