Alexandru Cernat joined Social Statistics in July 2016. Prior to this he was a Research Associate at the National Centre for Research Methods.
An important part of his research is centred around modelling measurement error in the framework of generalized latent variables (i.e., Structural Equation Modelling, Latent Class and Item Response Theory) with a particular interest in applying these to longitudinal data.
These statistical models are often used in the context of survey methodology to investigate topics such as: measurement error, non-response, mixed mode designs, longitudinal surveys, paradata, interviewer effects, surveying sensitive topics, etc.
Another research area of interest is missing data and ways to correct for this. This work focuses especially on missing biomarkers in surveys and is part of the National Centre for Research Methods grant: Acounting for informative item nonresponse in biomarkers collected in longitudinal surveys (WP3).