Indirect adjustment for multiple missing variables applicable to environmental epidemiology

Indirect adjustment for multiple missing variables applicable to environmental epidemiology.

OBJECTIVES Develop statistical methods for survival models to indirectly adjust hazard ratios of environmental exposures for missing risk factors. METHODS A partitioned regression approach for linear models is applied to time to event survival analyses of cohort study data. Information on the correlation between observed and missing risk factors is obtained from ancillary data sources such as...

Kernel Methods for Missing Variables

We present methods for dealing with missing variables in the context of Gaussian Processes and Support Vector Machines. This solves an important problem which has largely been ignored by kernel methods: How to systematically deal with incomplete data? Our method can also be applied to problems with partially observed labels as well as to the transductive setting where we view the labels as miss...

Environmental epidemiology: An introduction

Missing-Values Adjustment for Mixed-Type Data

We propose a new method of single imputation, reconstruction, and estimation of nonreported, incorrect, implausible, or excluded values in more than one field of the record. In particular, we will be concerned with data sets involving a mixture of numeric, ordinal, binary, and categorical variables. Our technique is a variation of the popular nearest neighbor hot deck imputation NNHDI where “ne...

“vitality” a missing link in adjustment to childhood cancer

background: a number of randomized trial studies and longitudinal researches emphasize that despite problems in social adjustment and cognitive damages, children with cancer demonstrate good emotional adjustment. methods: most of the research findings in this area are obtained using objective tools such as questionnaires. “vitality of children”, as a drawing tool, was used as a basis to draw a ...