We develop an approach, based on multiple imputation, that estimates the marginal survival distribution in survival analysis using auxiliary variables to recover information for censored observations. To conduct the imputation, we use two working proportional hazards models to define an imputing...

Standard statistical analyses of observational data often exclude valuable information from individuals with incomplete measurements. This may lead to biased estimates of the treatment effect and loss of precision. The issue of missing data for inverse probability of treatment weighted...

Clustered data arise in many settings, particularly within the social and biomedical sciences. For example, multiple-source reports are commonly collected in child and adolescent psychiatric epidemiologic studies where researchers use various informants (for instance, parents and adolescents) to...

We present an update of mim, a program for managing multiply im- puted datasets and performing inference (estimating parameters) using Rubin’s rules for combining estimates from imputed datasets. The new features of particular importance are an option for estimating the Monte Carlo error (due...

Following the seminal publications of Rubin about thirty years ago, statisticians have become increasingly aware of the inadequacy of "complete-case" analysis of datasets with missing observations. In medicine, for example, observations may be missing in a sporadic way for different covariates,...

Our new command midiagplots makes diagnostic plots for multiple imputations created by mi impute. The plots compare the distribution of the imputed values with that of the observed values so that problems with the imputation model can be corrected before the imputed data are analyzed. We include...

This article describes a substantial update to mvis, which brings it more closely in line with the feature set of S. van Buuren and C. G. M. Oudshoorn’s implementation of the MICE system in R and S-PLUS (for details, see http://www.multiple-imputation.com). To make a clear distinction from...

In the first part of the dissertation, we derive two methods for responders analysis in longitudinal data with random missing data. Often a binary variable is generated by dichotomizing an underlying continuous variable measured at a specific point in time according to a prespecified threshold...

We use imputation techniques and combine official data sources to address the various shortcomings affecting the analysis of value-added data at the level of production units in Switzerland. The new ad hoc databases that emerge include consistent information on value added and employment at the...

This paper considers the problem of record linkage between a household-level survey and an establishment-level frame in the absence of unique identifiers. Linkage between frames in this setting is challenging because the distribution of employment across establishments is highly skewed. To...