Sufficient cause interactions concern cases in which there is a particular causal mechanism for some outcome that requires the presence of 2 or more specific causes to operate. Empirical conditions have been derived to test for sufficient cause interactions. However, when regression outcome models are used to control for confounding variables in tests for sufficient cause interactions, the outc...

This paper presents simple analytical approaches for evaluating progressive collapse potential of lowand mid-rise buildings that could be used in routine design by design professionals. Although nonlinear time history analysis would be more realistic in representing progressive collapse phenomenon, high fidelity structural models to represent nonlinear structural behavior are required to produc...

This paper describes a freely available software suite that allows the modelling of large conformational changes of high-resolution three-dimensional protein structures under the constraint of a low-resolution electron-density map. Typical applications are the interpretation of electron-microscopy data using atomic scale X-ray structural models. The software package provided should enable the i...

Research interest often lies in comparing structural model specifications implying different relationships among latent factors. In this context parceling is commonly accepted, assuming the item-level measurement structure is well known and, conservatively, assuming items are unidimensional in the population. Under these assumptions, researchers compare competing structural models, each specifi...

Most cognitive processes are supported by large networks of brain regions. To describe the operation of these networks, it is critical to understand how individual areas are functionally connected. Here, we establish a statistical framework for studying effective and functional brain connectivity, using data obtained with a relatively new neuroimaging method, the event-related optical signal (E...

The continuously increasing amount of RNA sequence and experimentally determined 3D structure data drives the development of computational methods supporting exploration of these data. Contemporary functional analysis of RNA molecules, such as ribozymes or riboswitches, covers various issues, among which tertiary structure modeling becomes more and more important. A growing number of tools to m...

BACKGROUND Observational studies have consistently demonstrated the survival benefits of a greater dialysis dose in maintenance hemodialysis (MHD) patients, whereas randomized controlled trials have shown conflicting results. The possible causal impact of dialysis dose on mortality needs to be investigated using rich cohort data analyzed with novel statistical methods such as marginal structura...

Recognizing the structural similarity without significant sequence identity (called fold recognition) is the key for bridging the gap between the number of known protein sequences and the number of structures solved. Previously, we developed a fold-recognition method called SP(3) which combines sequence-derived sequence profiles, secondary-structure profiles and residue-depth dependent, structu...

In this article, we show the general relation between standardization methods and marginal structural models. Standardization has been recognized as a method to control confounding and to estimate causal parameters of interest. Because standardization requires stratification by confounders, the sparse-data problem will occur when stratified by many confounders and one then might have an unstabl...