IVEware: Imputation and Variance Estimation Software User Guide

By T. Raghunathan, John Van Hoewyk. 2002

498 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/1a1ff4280f88d626b58ebf43269cfdd07c67313c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

ON THE STATIONARY DISTRIBUTION OF ITERATIVE IMPUTATIONS (2010, methodology): “Even if, as we would prefer, the fitting of each imputation model and the imputations themselves are performed using conditional Bayesian inference, the stationary distribution of the algorithm (if it exists) does not in general correspond to Bayesian inference on any specified multivariate…”
Missing data: our view of the state of the art. (2002, methodology): “MI, proposed by Rubin (1987), has emerged as a flexible alternative to likelihood methods for a wide variety of missing-data problems. MI retains much of the attractiveness of single imputation from a conditional distribution but solves the problem of understating uncertainty. In MI, each missing va”
Relationships Between Self-Determination and Postschool Outcomes for Youth With Disabilities (2015, unknown): “To address this missingness, we used IVEware version 0.1 (Raghunathan, Solenberger, & Van Hoewyk, 2000).”
synthpop: Bespoke Creation of Synthetic Data in R (2016, unknown): “2013) and its stand-alone version SRCware (Raghunathan et al. 2002; Survey Methodology Program 2011), originally developed for multiple imputation, include SYNTHESIZE module that allows to produce synthetic data.”
HOW TO IMPUTE INTERACTIONS, SQUARES, AND OTHER TRANSFORMED VARIABLES (2009, methodology): “The passive imputation method was carried out using IVEware for SAS (Raghunathan et al. 2002), while the other imputation methods used the MI procedure in SAS software, version 9.”
Should a Normal Imputation Model be Modified to Impute Skewed Variables (2013, methodology): “We could have maintained a truncation point of 0 if SAS truncated imputed values by sampling importance resampling, which is used by IVEware (Raghunathan et al. 2001, 2002).”
Regression with missing Ys: An improved strategy for analyzing multiply imputed data (2007, methodology): “Although there does exist software for imputing multicategory variables (e.g., Raghunathan et al. 2002; Royston 2004), initially it was more convenient to use imputation software that assumed normality (the MI procedure in SAS version 9).”
Predictive mean matching imputation of semicontinuous variables (2014, methodology): “The iterative robust model-based imputation (irmi) algorithm from the package VIM mimics the functionality of IVEware (Raghunathan et al., 2002) but claims several improvements with respect to the robustness of the imputed values and the stability of the initialized values (Templ et al., 2011).”
Multiple Imputation by Chained Equations: What is it and how does it work? (2011, methodology): “Generally, 10 cycles are performed (Raghunathan et al., 2002); however, research is needed to identify the optimal number of cycles when imputing data under different conditions.”