Construct Measurement Error in Social Network Relationships: An Item Response Theory-Based Latent Space Model

Abstract

Social network relationships are often not directly observable or easily measured. Reliance on a single survey item to capture such relationships is likely to introduce construct measurement error. Although latent constructs and latent variable measurement models are widely used in the social sciences, they are rarely applied to the measurement of social network ties and, to our knowledge, have not been used to account for construct measurement error in network selection models. To address this gap, we propose an item response theory-based latent space model (IRT-LSM) that employs a multi-item scale measurement model to more accurately measure social relationships, which are then predicted using a latent space model. In addition to introducing the model, we present a simulation study demonstrating its capabilities and improvements over existing approaches. Finally, an empirical data analysis illustrates how substantive conclusions may vary depending on the modeling approach used.