Technometrics: Book Reviews

By Jeffrey E. Jarrett. 2013

1,813 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/ab989fe79c21dc9b22e6989ddb050ad8c07edc64

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Citations in the corpus

Multiple imputation as a flexible tool for missing data handling in clinical research. (2017, methodology): “…Equation (8) to include random slope residuals reflects the current implementation of multilevel FCS (Enders et al., 2016; Grund et al., 2016; van Buuren, 2011, 2012; van Buuren et al., 2014), although new approaches to this problem are flexible tool for missing data handling in clinical…”
The Role of Personality in COVID-19-Related Perceptions, Evaluations, and Behaviors: Findings Across Five Samples, Nine Traits, and 17 Criteria (2021, methodology): “We assumed missing-at-random and consequently conducted (partly passive; Van Buuren, 2018) multiple imputation analyses with 20 imputations using predictive mean matching for continuous and logistic regression for categorical outcomes with the MICE package (Van Buuren & Groothuis-Oudshoorn, 2011), i”
Multiple Imputation of Missing Data: A Simulation Study on a Binary Response (2013, positive): “However, it has been criticised by van Buuren [30] because the interaction terms are no longer the product of the underlying main effects, but receive additional random error due to the multiple imputation.”
Living well by “flowing’ well: The indirect effect of autotelic personality on well-being through flow experience (2020, background): “%) to avoid biasing the results (Graham, 2012; van Buuren, 2018).”
Prevention of Cyberbullying and Cyber Victimization: Evaluation of the ViSC Social Competence Program (2015, methodology): “Each variable was imputed with the predictive mean matching algorithm (van Buuren, 2012) using Tukey’s tricube weighting function (Harrell, 2006).”
Handbook of International Large-Scale Assessment : Background, Technical Issues, and Methods of Data Analysis (2013, methodology): “Fully conditionally specified models implemented in SAS (versions 9.3) were used to impute missing school and student level variables (Van Buuren, 2011, 2012).”
missMDA: A Package for Handling Missing Values in Multivariate Data Analysis (2016, methodology): “The main packages that implement multiple imputation methods are Amelia (Honaker, King, and Blackwell 2011), mice (Van Buuren and Groothuis-Oudshoorn 2011) and mi (Su, Gelman, Hill, and Yajima 2011).”
Predictive mean matching imputation of semicontinuous variables (2014, background): “The normal distribution, however, may not accurately describe the data, potentially leading to unsatisfactory solutions (Van Buuren, 2012), which stresses the need for a method without distributional assumptions.”
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets (2019, background): “Yoon et al. (2018) considered a way to do so by building on the generative adversarial networks (GANs) of Goodfellow et al.”
Regression imputation in the functional linear model with missing values in the response (2019, background): “Then, to impute a missing value, say Y` (where ` is a given integer between 1 and n), a simple way is to consider complete case analysis (see for instance [19, 7, 29, 22, 28]).”
Handling missing values in trait data (2020, background): “Complete−case Rphylopars Mice: regression + phylogeny Mice: mean matching + phylogeny Mice: random forest + phylogeny BHPMF + phylogeny Sl op e er ro r ± 9 5% c on fid en ce in te rv al s | 59JOHNSON et al. approach (Van Buuren, 2012).”
MICE: Multivariate Imputation by Chained Equations in R (2011, background): “Theory and applications of multiple imputation have been developed in Rubin (1987) and Rubin (1996). van Buuren (2012) introduces multiple imputation from an applied perspective.”