We investigate estimation in Poisson regression model when the count response is right-censored and censoring indicators are missing at random. propose several estimators based on calibration, multiple imputation augmented inverse probability weighting methods. Under appropriate regularity conditions, we prove consistency of our derive their asymptotic distributions. Simulation experiments carr...

background policy makers need models to be able to detect groups at high risk of hiv infection. incomplete records and dirty data are frequently seen in national data sets. presence of missing data challenges the practice of model development. several studies suggested that performance of imputation methods is acceptable when missing rate is moderate. one of the issues which was of less concern...

Microarray experiments generate data sets with information on the expression levels of thousands of genes in a set of biological samples. Unfortunately, such experiments often produce multiple missing expression values, normally due to various experimental problems. As many algorithms for gene expression analysis require a complete data matrix as input, the missing values have to be estimated i...

Under-reporting occurs in survey data when there is a reason to systematically misreport the response to a question. For example, in studies dealing with low birth weight infants, the smoking habits of the mother are very likely to be misreported. This creates problems for calculating effect sizes, such as bias, but these problems are commonly ignored due to lack of generally accepted solutions...