Methodological guidance paper: High-quality meta-analysis in a systematic review
TD Pigott, JR Polanin - Review of Educational Research, 2020 - journals.sagepub.com
This methodological guidance article discusses the elements of a high-quality meta-analysis
that is conducted within the context of a systematic review. Meta-analysis, a set of statistical …
that is conducted within the context of a systematic review. Meta-analysis, a set of statistical …
Missing data: An update on the state of the art.
CK Enders - Psychological Methods, 2023 - psycnet.apa.org
The year 2022 is the 20th anniversary of Joseph Schafer and John Graham's paper titled
“Missing data: Our view of the state of the art,” currently the most highly cited paper in the …
“Missing data: Our view of the state of the art,” currently the most highly cited paper in the …
[图书][B] Flexible imputation of missing data
S Van Buuren - 2018 - books.google.com
Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or
mean imputation, only work under highly restrictive conditions, which are often not met in …
mean imputation, only work under highly restrictive conditions, which are often not met in …
Multiple imputation as a flexible tool for missing data handling in clinical research
CK Enders - Behaviour research and therapy, 2017 - Elsevier
The last 20 years has seen an uptick in research on missing data problems, and most
software applications now implement one or more sophisticated missing data handling …
software applications now implement one or more sophisticated missing data handling …
A comparison of multiple imputation methods for missing data in longitudinal studies
Background Multiple imputation (MI) is now widely used to handle missing data in
longitudinal studies. Several MI techniques have been proposed to impute incomplete …
longitudinal studies. Several MI techniques have been proposed to impute incomplete …
[图书][B] An introduction to multilevel modeling techniques: MLM and SEM approaches
Multilevel modelling is a data analysis method that is frequently used to investigate
hierarchal data structures in educational, behavioural, health, and social sciences …
hierarchal data structures in educational, behavioural, health, and social sciences …
Multiple imputation of missing data for multilevel models: Simulations and recommendations
S Grund, O Lüdtke, A Robitzsch - Organizational Research …, 2018 - journals.sagepub.com
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 …
addition, multilevel models have become a standard tool for analyzing the nested data …
The rise and fall of depressive symptoms and academic stress in two samples of university students
Self-reported depressive experiences are common among university students. However,
most studies assessing depression in university students are cross-sectional, limiting our …
most studies assessing depression in university students are cross-sectional, limiting our …
A fully conditional specification approach to multilevel imputation of categorical and continuous variables.
Specialized imputation routines for multilevel data are widely available in software
packages, but these methods are generally not equipped to handle a wide range of …
packages, but these methods are generally not equipped to handle a wide range of …
Perceived mastery climate, felt trust, and knowledge sharing
Interpersonal trust is associated with a range of adaptive outcomes, including knowledge
sharing. However, to date, our knowledge of antecedents and consequences of employees …
sharing. However, to date, our knowledge of antecedents and consequences of employees …