Handling Missing Values in Relational Event History Data using Multiple Imputation: A Framework in Social Network Research

Abstract

Background - Missing data is a problem that is common. It affects the accuracy and introduces biases in social network analysis, which can have a significant effect on the interpretation of findings. Relational event history (REH) data, a type of social network data, is becoming increasingly available due to new technological developments and can enhance the understanding of dynamic social networks. However, research on handling missing values in social network data is limited and statistical tools for incomplete REH data are underdeveloped. This paper focuses on using multiple imputation to handle missing values within REH data. Methods – Relational event history model analysis is first performed on the fully observed dataset to produce true estimates. Next, a simulation study is conducted to introduce missingness to this fully observed dataset, assuming missing completely at random (MCAR) and right-tailed missing at random (MAR). After multiple imputation, the relational event model is applied on the simulations and the results are compared to the analysis of the fully observed dataset. Results – The results of the relational event model of the simulations and the true estimates show inconsistency in the significance of the results. The simulations generally have a low bias, good coverage rate an low average width. A higher proportion of missingness resulted in a decrease in the performance. Multiple imputation thus produces unbiased inferences under the MCAR and MAR mechanism, however unexpected significant results are found. Conclusion – This study provides insights into the use of multiple imputation for producing valid inferences when applied on REH data. It shows that under the assumption of MCAR and MAR, multiple imputation can be a valid method for missing data in REH data when the percentage of missingness is not too high. Further research is needed confirm an expand upon the results obtained in this study.