Due to the proliferation of biomedical imaging modalities, such as Photoacoustic
Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, etc …

For researchers and practitioners interested in social relationships, the question remains as
to how large social networks typically are, and how their size and composition change …

Latin American populations may present patterns of sociodemographic, ethnic and cultural
diversity that can defy current universal models of healthy aging. The potential combination …

Objectives Researchers are concerned whether multiple imputation (MI) or complete case
analysis should be used when a large proportion of data are missing. We aimed to provide …

Feature selection (FS) is an important research topic in machine learning. Usually, FS is
modelled as a bi-objective optimization problem whose objectives are: 1) classification …

Background Nearest neighbor (NN) imputation algorithms are efficient methods to fill in
missing data where each missing value on some records is replaced by a value obtained …

The contribution of medical mistrust to healthcare utilization delays has gained increased
public health attention. However, few studies examine these associations among African …

Multiple imputation by chained equations is a flexible and practical approach to handling
missing data. We describe the principles of the method and show how to impute categorical …

The most user-friendly and authoritative resource on missing data has been completely
revised to make room for the latest developments that make handling missing data more …

Das vorliegende Studienskript ist die komplett überarbeitete und um viele zusätzliche
Inhalte und Kapitel ergänzte Neuauflage des Studienskipts „Regressionstheorie und …