This thesis addresses three major issues in data mining regarding feature subset selection in large dimensionality domains, plausible reconstruction of incomplete data in cross-sectional applications, and forecasting univariate time series. For the automated selection of an optimal subset of...

Like other data quality dimensions, the concept of accuracy is often adopted to characterise a particular data set. However, its common specification basically refers to statistical properties of estimators, which can hardly be proved by means of a single survey at hand. This ambiguity can be...

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...

The results of a national fear of crime survey are compared with results following the use of different nonresponse correction procedures. We compared naive estimates, weighted estimates, estimates after a thorough nonresponse follow-up and estimates after multiple imputation. A strong...

In much of applied statistics variables of interest are measured with error. In particular, regression with covariates that are subject to measurement error requires adjustment to avoid biased estimates and invalid inference. We consider two aspects of this problem. Detection Limits (DL) arise...

This thesis is comprised of three chapters. The first chapter develops a statistical model that enriches the role that firms playin wage determination, allowing firms to influence both average wages as well as the returns to observable worker characteristics. I exploit the hierarchical nature of...

The definition and operationalization of wealth information in population surveys and the corresponding microdata requires a wide range of more or less normative assumptions. However, the decisions made in both the pre- and post-data-collection stage may interfere considerably with the...

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...

A new database called the World Resource Table (WRT) is constructed in this study. Missing values are known to produce complications when constructing global databases. This study provides a solution for applying multiple imputation techniques and estimates the global environmental Kuznets curve...