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 …
[PDF][PDF] Multiple imputation by chained equations in praxis: guidelines and review
JN Wulff, LE Jeppesen - Electronic Journal of Business Research …, 2017 - vbn.aau.dk
Multiple imputation by chained equations (MICE) is an effective tool to handle missing data-
an almost unavoidable problem in quantitative data analysis. However, despite the empirical …
an almost unavoidable problem in quantitative data analysis. However, despite the empirical …
Missing data: Five practical guidelines
DA Newman - Organizational research methods, 2014 - journals.sagepub.com
Missing data (a) reside at three missing data levels of analysis (item-, construct-, and person-
level),(b) arise from three missing data mechanisms (missing completely at random, missing …
level),(b) arise from three missing data mechanisms (missing completely at random, missing …
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 model-based imputation procedure for multilevel regression models with random coefficients, interaction effects, and nonlinear terms.
Despite the broad appeal of missing data handling approaches that assume a missing at
random (MAR) mechanism (eg, multiple imputation and maximum likelihood estimation) …
random (MAR) mechanism (eg, multiple imputation and maximum likelihood estimation) …
Full information maximum likelihood estimation for latent variable interactions with incomplete indicators
H Cham, E Reshetnyak, B Rosenfeld… - Multivariate behavioral …, 2017 - Taylor & Francis
Researchers have developed missing data handling techniques for estimating interaction
effects in multiple regression. Extending to latent variable interactions, we investigated full …
effects in multiple regression. Extending to latent variable interactions, we investigated full …
Life satisfaction and academic performance in early adolescents: Evidence for reciprocal association
Student subjective well-being remains a relatively neglected topic despite its intimate link to
positive school outcomes. As academic achievement is a widely used yardstick of student …
positive school outcomes. As academic achievement is a widely used yardstick of student …
Not too tired to be proactive: Daily empowering leadership spurs next-morning employee proactivity as moderated by nightly sleep quality
Building on the Model of Proactive Motivation, we hypothesize that a leader's daily
empowering leadership behaviors function as a motivator for employees to display a greater …
empowering leadership behaviors function as a motivator for employees to display a greater …
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 …
Animal welfare and cow-calf contact-farmers' attitudes, experiences and adoption barriers
BG Hansen, E Langseth, C Berge - Journal of Rural Studies, 2023 - Elsevier
While separating the calf from the dairy cow shortly after birth is common practice around the
world, stakeholders have conflicting perspectives on whether this practice is harmful or …
world, stakeholders have conflicting perspectives on whether this practice is harmful or …