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New and Emerging Methods for Imputation and Editing in Data Analysis

This discussion focuses on new and emerging methods for imputation and editing in data analysis. Topics include partial imputation with adjustments, a forward search algorithm for compositional data, automatic editing with soft edits, imputation of binary variables in registers, imputation and editing of income from the administrative file, and an R package for selective editing based on a latent class model.

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New and Emerging Methods for Imputation and Editing in Data Analysis

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  1. Discussants: Rudi Seljak / SORS Daniel Kilchmann / SFSO Topic (vii): New and emerging methodsDiscussion UNECE Work session on SDE Topic (vii) New and emerging methods

  2. UNECE Work session on SDE Topic (vii) New and emerging methods Summary of papers (1) • WP.40: Partial (donor) imputation with adjustments (Netherlands, Norway) Discussion of different distance metrics to perform minimal adjustments to imputed data in order to guarantee consistency. • WP.41: A forward search algorithm for compositional data (Italy) Discussion of a procedure for detecting outliers in compositional data.

  3. UNECE Work session on SDE Topic (vii) New and emerging methods Summary of papers (2) • WP.42: Automatic editing with soft edits (Netherlands) New formulation of the error localisation problem including hard and soft edits and its solution with a branch-and-bound algorithm. • WP.43: On imputation of binary variables in registers (Sweden) Discussion of random imputation versus deterministic imputation in the case of imputing binary variables with respect to accuracy leading to a recommendation which method to use.

  4. UNECE Work session on SDE Topic (vii) New and emerging methods Summary of papers (3) • WP.44: Imputation and editing of income from the administrative file in the Census (Israel) Procedure adopted to overcome the deficiencies of Census and administrative data in the case of imputing income. • WP.45: An R package for selective editing based on a latent class model (Italy) Discussion of the use of the R package SeleMix where a method taking explicitly the probability of being in error and the error impact into account is implemented.

  5. UNECE Work session on SDE Topic (vii) New and emerging methods Paper-Specific Questions

  6. UNECE Work session on SDE Topic (vii) New and emerging methods Paper-Specific Questions WP.40: Partial (donor) imputation with adjustments (Netherlands) • What happens if the only reported value is 0? • Is it possible to include domains (e.g. salary boundaries per education level)? WP.41: A forward search algorithm for compositional data (Italy) • Efficiency of the method (true, false) x (detected, undetected)? • Does the method work if there are lots of zeros in the data?

  7. UNECE Work session on SDE Topic (vii) New and emerging methods Paper-Specific Questions WP.42: Automatic editing with soft edits (Netherlands) • Is there already a strategy or idea how to define the cost of failed soft edit rules? • Advances in the implementation? WP.43: On imputation of binary variables in registers (Sweden) • Why not use multiple imputation instead of repeated random imputation? • The risk of bias and the loss of variance for deterministic imputation and the loss of efficiency for random imputation increases for small sub-populations. Limitation for imputation in general?

  8. UNECE Work session on SDE Topic (vii) New and emerging methods Paper-Specific Questions WP.44: Imputation and editing of income from the administrative file in the Census (Israel) • Is it possible to validate the strategy adopted by the insurance salary data base 2009? WP.45: An R package for selective editing based on a latent class model (Italy) • When will the R package be available on the Cran library?

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