Psychology as an academic subject started in Germany and England, and two lasting quantitative traditions emerged from those beginnings. The German approach emphasized formal theory about aspects of cognition possessed in common by most humans. This approach led eventually to the fields of Mathematical Psychology and Cognitive Modeling in the 1950s, spearheaded by such scholars as William Estes, Duncan Luce, and George Miller. The English approach emphasized statistical models for measuring how humans differ in aspects of cognition. This approach led almost immediately to the field of Psychometrics, and such scholars as Louis Thurstone, Frederick Lord, and Georg Rasch contributed to its further development. The basic tools of cognitive modeling and psychometrics are computational statistics, mathematics, and probability, yet at least until recently, there has been relatively little joint work between researchers in these two quantitative traditions. This is particularly surprising because the basic data structure for most research in both approaches is identical, namely it is a matrix of participant by item or trial random variables. Cognitive Psychometrics is my name for an approach to quantitative psychology that attempts to fuse the best from both of these quantitative traditions. I will describe two examples from my Cognitive Psychometrics Lab. One uses a simple Multinomial Processing Tree (MPT) model of memory categorization to separately measure the storage capacity and retrieval capacity of brain damaged alcoholics, and the second example uses a Cultural Consensus Theory (CCT) model to measure different clusters of shared beliefs about healthy living.