Structural equation models are highly suited for evaluating ecosystem-level hypotheses, but to be effective, structural equation models need to be able to accommodate spatial and temporal data. Here, ...

Structural equation modeling (SEM) encompasses such diverse statistical techniques as path analysis, confirmatory factor analysis, causal modeling with latent variables, and even analysis of variance ...

The assessment of change in patient-reported outcomes is hindered by the fact that there are different types of change. Besides 'true' change, different types of response shift, such as recalibration, ...

Abstract: We present a robust method to infer network topology in the presence of outliers from given observations at nodes under the structural equation model. We introduce auxiliary matrices ...

Abstract: Public attitudes towards energy sources and climate change are increasingly complex. This paper explores Americans’ perceptions of energy sources including renewables, Electric Vehicles (EVs ...