Missing Data

Encyclopedia of Social Network Analysis and Mining. 2nd Ed., 2018

456 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/f418d78070e577a951058bb89e18e8b7b68a4289

Citations in the corpus

• Is the future still open? The mediating role of occupational future time perspective in the effects of career adaptability and aging experience on late career planning (2019, unknown): “…likelihood estimator (Wang et al., 2017) as the results of the dropout analysis indicated that data are missing at random (Goodman & Blum, 1996; Newman, 2014).3 Further, we used bootstrapping (with 10,000 draws) to account for deviations from normality for testing the indirect effects…”
• Hypocritical organizations: Implications for employee social responsibility (2020, methodology): “After filtering out unusable returns with a person-level response rate below 30% (Newman, 2014), including people who were not employed at the time of the study, we were left with 457 completed questionnaires for analysis at time 1.”
• Best Practices in Data Collection and Preparation: Recommendations for Reviewers, Editors, and Authors (2019, background): “Directly related to the aforementioned discussion regarding sampling procedures, it is likely that the resulting data set includes missing data (Newman, 2014; Schafer & Graham, 2002).”
• Why Ordinal Variables Can (Almost) Always Be Treated as Continuous Variables: Clarifying Assumptions of Robust Continuous and Ordinal Factor Analysis Estimation Methods (2020, background): “However, it could be argued that there are typically only mild deviations of the MCAR assumption in empirical datasets (Newman, 2014).”
• Enhancing Rigor in Quantitative Entrepreneurship Research (2019, methodology): “, multiple imputation [MI] or full information maximum likelihood [FIML]) are needed (Newman, 2014).”