Interval Censored Observations in Clinical Trials

1994 ◽  
pp. 451-467
Author(s):  
Armin Koch
Keyword(s):  
Clinical Trials ◽  
Interval Censored ◽  
Censored Observations

Urn sampling, interval censoring and proportional hazard models

2009 ◽  
Vol 9 (4) ◽  
pp. 361-379
Author(s):  
Lu Zheng ◽  
Marvin Zelen
Keyword(s):  
Survival Data ◽  
Interval Censoring ◽  
Interval Length ◽  
Hazard Models ◽  
Proportional Hazard ◽  
Survival Times ◽  
Proportional Hazard Models ◽  
Interval Censored ◽  
The Mean ◽  
Censored Observations

This paper proposes a new distribution-free statistical method for testing hypotheses about covariates for survival data having simultaneously right-, left- and interval-censored survival times. The new test is motivated by the analogue between urn sampling and the Cox’s proportional hazard models. Investigations of the significance levels and power as a function of the proportion of interval-censored observations and interval length show that the test performs well for most censoring situations encountered in practice. Simulation results also suggest that there is negligible loss of power in the practical situation in which the mean interval length for interval-censored observations is less than the mean survival time. This holds even with heavy interval censoring. Comparison with the widely used Mantel’s method for comparing two groups shows that the power of the new method appears to be superior. Furthermore, the test is relatively simple to carry out and generalizes to comparing k populations as well as the testing of general linear hypothesis for arbitrary covariates.

scholarly journals A Two-Sample Parametric Test for Partly Interva-Censored Data with Nonproportional Hazard

2014 ◽  
Vol 2014 ◽  
pp. 1-10
Author(s):  
Azzah Mohammad Alharpy ◽  
Noor Akma Ibrahim
Keyword(s):  
Failure Time ◽  
Score Test ◽  
Reliability Function ◽  
Failure Time Data ◽  
Ratio Test ◽  
Time Data ◽  
Interval Censored ◽  
Piecewise Exponential Distribution ◽  
Piecewise Exponential ◽  
Censored Observations

In clinical trials and engineering studies that are followed by periodic follow-ups, it is predominantly to have partly interval-censored failure time data. Partly interval-censored failure time data is composed of exact observations and interval-censored observations. This paper discusses two-sample parametric comparison of reliability function in the existence of partly interval-censored failure time data. We have constructed a score test and likelihood ratio test for this kind of failure time data under piecewise exponential distribution by using multiple imputation technique. Simulation study is established to assess the proposed test, which indicates that the presented procedure works well. Finally, an example is given for illustration purposes.

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