Robert Krause

Robert Krause
Freie Universität Berlin | FUB · Education and Psychology

PhD
Postdoc at Free University Berlin

About

14
Publications
55,751
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Introduction
I am working statistical models for network structure and network evolution. My work focuses primarily on missing data handling in the context of network data. Specifically I am working with SAOMs for longitudinal network dynamics and ERGMs for cross-sectional network structure, both Bayesian and non-Bayesian estimation. And because this is not complex enough, I am also working on multiplex models for SAOMs and Bayesian ERGMs.
Additional affiliations
November 2020 - October 2024
Freie Universität Berlin
Position
  • PostDoc Position

Publications

Publications (14)
Article
Full-text available
Gossip is a pervasive phenomenon in organizations causing many individuals to have second-hand information about their colleagues. However, whether it is used to inform friendship choices (i.e., friendship creation, friendship maintenance, friendship discontinuation) is not that evident. This paper articulates and empirically tests a complex contag...
Conference Paper
Complex contagion theory is used to develop novel hypotheses on the effects of workplace gossip on expressive relations. It is argued that hearing gossip from multiple senders or about multiple targets impacts receivers’ friendships with gossip targets. Hypotheses are tested in a two-wave sociometric panel study among 148 employees of three units i...
Preprint
Full-text available
Recent advances in computational methods for intractable models have made network data increasingly amenable to statistical analysis. Exponential random graph models (ERGMs) emerged as one of the main families of models capable of capturing the complex dependence structure of network data in a wide range of applied contexts. The Bergm package for R...
Article
Full-text available
The social-ecological effects of agricultural intensification are complex. We explore farmers’ perceptions about the impacts of their land management and the impact of social information flows on their management through a case study in a farming community in Navarra, Spain, that is undergoing agricultural intensification due to adoption of large s...
Article
Full-text available
This paper compares several missing data treatment methods for missing network data on a diverse set of simulated networks under several missing data mechanisms. We focus the comparison on three different outcomes: descriptive statistics, link reconstruction, and model parameters. The results indicate that the often used methods (analysis of availa...
Article
Full-text available
Centrality indices are a popular tool to analyze structural aspects of psychological networks. As centrality indices were originally developed in the context of social networks, it is unclear to what extent these indices are suitable in a psychological network context. In this article we critically examine several issues with the use of the most po...
Chapter
In this paper we present an estimation algorithm for Bayesian exponential random multi-graphs (BERmGMs) under missing network data. Social actors are often connected with more than one type of relation, thus forming a multiplex network. It is important to consider these multiplex structures simultaneously when analyzing a multiplex network. The imp...
Preprint
Full-text available
Centrality indices are a popular tool to analyze structural aspects of psychological networks. As centrality indices were originally developed in the context of social networks, it is unclear to what extent these indices are suitable in a psychological network context. In this paper we critically examine several issues with the use of the most popu...
Preprint
Full-text available
In this paper we present an estimation algorithm for Bayesian multiplex exponential random graphs (BmERGMs) under missing network data. Social actors are often connected with more than one type of relation, thus forming a multiplex network. It is important to consider these multiplex structures simultaneously when analyzing a multiplex network. The...
Conference Paper
Full-text available
This paper compares several imputation methods for missing data in network analysis on a diverse set of simulated networks under several missing data mechanisms. Previous work has highlighted the biases in descriptive statistics of networks introduced by missing data. The results of the current study indicate that the default methods (analysis of a...
Article
Full-text available
Missing data on network ties are a fundamental problem for network analysis. The biases induced by missing edge data are widely acknowledged. In this paper, we present a new method with two variants to handle missing data due to actor non-response in the framework of stochastic actor-oriented models (SAOMs). The proposed method imputes missing tie...
Article
Full-text available
Reproducibility is a defining feature of science, but the extent to which it characterizes current research is unknown. We conducted replications of 100 experimental and correlational studies published in three psychology journals using high-powered designs and original materials when available. Replication effects were half the magnitude of origin...

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Projects

Projects (2)
Project
Investigation of imputation methods for missing network data (ties, attributes, behavioral data), for cross-sectional and longitudinal analysis.