Factor analysis of a simulated data matrix involving aqueous complex equilibria

factor analyses were performed on databases consisting of simulated samples from aqueous equilbria. The program COMPLEX was used to generate equilibrium species in a system of three reactant metals and five reactant bases. Reactant concentrations and pH were drawn from random–normal distributions so that sample data vectors comprised a multivariate log–normal distribution of equilibrium concentrations. In addition, sample groups were created containing different distributions for pH and reactant concentrations. Equilibrium species were shown to contain variance contributed by change in pH among samples as well as change in reactant concentrations. Factor modelling revealed the qualitative relationships among the species and how the relationships change with pH. Factors also revealed those reactants containing variance in the data matrix. In some cases, reactant variance obscured relationships between pH and the equilibrium species. Since factor modelling of a simulated data matrix revealed the expected chemical equilibrium interactions, a potentially powerful tool exists for investigating the effects of outliers and error.