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...

Abstract Doubly robust (DR) estimators are an important class of statistics derived from a theory of semiparametric efficiency. They have become a popular tool in causal inference, including applications to dynamic treatment regimes. The doubly robust estimators for the mean response to a...

Policy analysts involved in quantitative research have many options for handling missing data. The method chosen will often greatly influence the substantive policy conclusions that will be drawn from the data. The most frequent methods for handling missing data assume that the data are missing...

In this thesis, we address issues of model estimation for longitudinal categorical data and of model selection for these data with missing covariates. Longitudinal survey data capture the responses of each subject repeatedly through time, allowing for the separation of variation in the measured...

In dieser Arbeit werden die Auswirkungen einer Ersetzung von fehlenden Werten auf das Ergebnis einer Regressionsanalyse untersucht. Grundlage ist eine Untersuchung von Klasen (2000) über die Unterschiede im Zusammenhang zwischen Unterernährung und Kindersterblichkeit in Afrika und Südasien....

We develop a method for directly modeling cointegrated multivariate time series that are observed in mixed frequencies. We regard lower-frequency data as regularly (or irregularly) missing and treat them with higher-frequency data by adopting a state-space model. This utilizes the structure of...

In zahlreichen großen Datensätzen von wissenschaftlichem Interesse sind einige Variablen, wie z. B. die Lohnhöhe, top-coded oder rechtszensiert. Zur Analyse von Löhnen auf der Grundlage der IAB-Beschäftigtenstichprobe muss zunächst das Problem der, an der Beitragsbemessungsgrenze der...

Traditional instrumental variable estimators do not generally estimate effects for the treated population but for the unobserved population of compliers. They do identify effects for the treated when there is one-sided perfect non-compliance. However, this property is lost when covariates are...

A common approach to dealing with missing data is to estimate the model on the common subset of data, by necessity throwing away potentially useful data. We derive a new probit type estimator for models with missing covariate data where the dependent variable is binary. For the benchmark case of...

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...