Zum Vergleich ausgewählter Missing Data Techniken nutzt dieses Papier eine Befragung, in der u. a. die Zustimmung zum Record Linkage der Befragungs- mit administrativen Prozessdaten abgefragt wurde. Bei nicht zustimmenden Befragten, werden ihre gegebenen Antworten auf 'fehlend' gesetzt, um so...

Abstract The problem of missingness in observational data is ubiquitous. When the confounders are missing at random, multiple imputation is commonly used; however, the method requires congeniality conditions for valid inferences, which may not be satisfied when estimating average causal treatment...

Previous studies that analyzed multiple imputation using survey data did not take into account the survey sampling design. The objective of the current study is to analyze the impact of survey sampling design missing data imputation, using multivariate multiple imputation method. The results of...

Missing data is a problem that occurs frequently in survey data. Missing data results in biased estimates and reduced efficiency for regression estimates. The objective of the current study is to analyze the impact of missing-data imputation, using multiple-imputation methods, on regression...

This paper investigates secular changes in the distribution of personal expen-diture in Italy over the period 1881-1961. To do so, the authors constructed a new dataset, the Italian Household Budgets Database (IHBD), consisting of 4,370 family-level budgets. Methodologically, this paper improves...

Many studies delete incomplete data prior to model estimation, resulting in less efficient and potentially biased parameter estimates. Multiple imputation provides a model-based method of simultaneously estimating missing values for several variables, conditioned on the observed values. The...

Economists are giving more attention to the issue of subjective well-being. A recent study of households in West Virginia treats subjective well-being in a quality of life context (Bukenya 2003) in rural areas. Wolfers (2003) examines business cycle volatility and subjective well-being, while...

Positive and negative predictive values are important measures of accuracy whenone compares the accuracy of diagnostic tests. When more than one diagnostic tests areavailable, one may has to choose one of the possible diagnostic tests due to cost, time, orethical reason. We consider a pair study...