Comparison of Some Statistical Methods for Counting Process Observations

Author(s):  
Giorgio Koch
Author(s):  
Jimmy T. Efird ◽  
Charulata Jindal

Censoring occurs when complete follow-up time information is unavailable for patients enrolled in a clinical study. The process is considered to be informative (nonignorable) if the likelihood function for the censoring model cannot be partitioned into a set of response parameters that are independent of the censoring parameters. In such cases, estimated survival time probabilities may be biased, prompting the need for special statistical methods to remedy the situation. The problem is especially salient when censoring is skewed toward the early phase of a study. In this paper, we describe a method to impute censored follow-up times using a counting process method.


1978 ◽  
Vol 48 ◽  
pp. 7-29
Author(s):  
T. E. Lutz

This review paper deals with the use of statistical methods to evaluate systematic and random errors associated with trigonometric parallaxes. First, systematic errors which arise when using trigonometric parallaxes to calibrate luminosity systems are discussed. Next, determination of the external errors of parallax measurement are reviewed. Observatory corrections are discussed. Schilt’s point, that as the causes of these systematic differences between observatories are not known the computed corrections can not be applied appropriately, is emphasized. However, modern parallax work is sufficiently accurate that it is necessary to determine observatory corrections if full use is to be made of the potential precision of the data. To this end, it is suggested that a prior experimental design is required. Past experience has shown that accidental overlap of observing programs will not suffice to determine observatory corrections which are meaningful.


1973 ◽  
Vol 18 (11) ◽  
pp. 562-562
Author(s):  
B. J. WINER
Keyword(s):  

1996 ◽  
Vol 41 (12) ◽  
pp. 1224-1224
Author(s):  
Terri Gullickson
Keyword(s):  

1979 ◽  
Vol 24 (6) ◽  
pp. 536-536
Author(s):  
JOHN W. COTTON
Keyword(s):  

2020 ◽  
Author(s):  
J. M. Schauer ◽  
L. V. Hedges
Keyword(s):  

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