Editing and Imputation for Quantitative Survey Data
From MaRDI portal
Publication:3747468
DOI10.2307/2289125zbMath0608.62003OpenAlexW4238364034MaRDI QIDQ3747468
Philip J. Smith, Roderick J. A. Little
Publication date: 1987
Full work available at URL: https://doi.org/10.2307/2289125
EM algorithmmaximum likelihoodimputationsurvey datarobust estimationmultivariate normalMahalanobis distancedistance measuresgraphical proceduresdetection of outlying casesmissing and outlying values
Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).
Related Items (13)
Analysis of incomplete data under non-random mechanisms: bayesian inference ⋮ Robust methods for generalized linear models with nonignorable missing covariates ⋮ Design-based estimation for geometric quantiles with application to outlier detection ⋮ A unified approach to exploratory factor analysis with missing data, nonnormal data, and in the presence of outliers ⋮ Simultaneous edit-imputation and disclosure limitation for business establishment data ⋮ Principal component regression for data containing outliers and missing elements ⋮ Improvements over the duplicate performance method for outlier detection in categorical multivariate surveys ⋮ Using a Mixture Model for Multiple Imputation in the Presence of Outliers: The ‘Healthy for Life’ Project ⋮ M-estimation with incomplete and dependent multivariate data ⋮ Unnamed Item ⋮ Automatic Editing for Business Surveys: An Assessment of Selected Algorithms ⋮ Discussion of: ``The power of monitoring: how to make the most of a contaminated multivariate sample ⋮ Expectation-robust algorithm and estimating equations for means and dispersion matrix with missing data
This page was built for publication: Editing and Imputation for Quantitative Survey Data
