Mean field theories of ion distributions, such as the Gouy-Chapman theory that describes the distribution near a charged planar surface, ignore the molecular-scale structure in the liquid solution. The predictions of the Gouy-Chapman theory vary substantially from our x-ray reflectivity measurements of the interface between two electrolyte solutions. Molecular dynamics simulations, which include the liquid structure, were used to calculate the potential of mean force on a single ion. We used this potential of mean force in a generalized Poisson-Boltzmann equation to predict the full ion distributions. These distributions agree with our measurements without any adjustable parameters.

Meehl's taxometric method was developed to distinguish categorical and continuous constructs. However, taxometric output can be difficult to interpret because expected results for realistic data conditions and differing procedural implementations have not been derived analytically or studied through rigorous simulations. By applying bootstrap methodology, one can generate empirical sampling distributions of taxometric results using data-based estimates of relevant population parameters. We present iterative algorithms for creating bootstrap samples of taxonic and dimensional comparison data that reproduce important features of the research data with good precision and negligible bias. In a series of studies, we demonstrate the utility of these comparison data as an interpretive aid in taxometric research. Strengths and limitations of the approach are discussed along with directions for future research.