Applauded for its clarity, this accessible introduction helps readers apply multilevel
techniques to their research. The book also includes advanced extensions, making it useful …

Multiple imputation (MI) is one of the principled methods for dealing with missing data. In
addition, multilevel models have become a standard tool for analyzing the nested data …

Multiple imputation is a widely recommended means of addressing the problem of missing
data in psychological research. An often-neglected requirement of this approach is that the …

Girls have much lower mathematics self-efficacy than boys, a likely contributor to the
underrepresentation of women in STEM. To help explain this gender confidence gap, we …

Belonging uncertainty, defined as the general concern about the quality of one's social
relationships in an academic setting, has been found to be an important determinant of …

The legal socialization framework emphasizes the importance of adolescents' encounters
with police. We examine how different types of police contact and neighborhood …

Nascent entrepreneurs (NEs) take action in the startup process by initiating startup activities
in hopes of manifesting a new firm, though some NEs experience a quit outcome. Other NEs …

With the fast-growing sector of information technology in digitizing societies, the attraction
and education of qualified recruits in computer science becomes a key task of tertiary …

Objectives We provide guidelines for handling the most common missing data problems in
repeated measurements in observational studies and deal with practicalities in producing …

Multiple imputation (MI) can be used to address missing data at Level 2 in multilevel
research. In this article, we compare joint modeling (JM) and the fully conditional …