Our work uses experimental methods to test children's judgment/decision-making (JDM). Experimental work often focuses on task and process analyses at the group level, with individual differences treated as error variability. Here, we describe how to assess/interpret individual differences within experiments using single-subject design. Traditionally, single-subject design appears in single case studies, with issues of generalizability arising. Our approach, in contrast, involves groups of standard size, analyzed at group and individual subject level. We then group individuals with similar patterns, for conclusions about the existence and contributions of systematic individual differences to development. Our examples here use Information Integration Theory (IIT). Our general perspective, however, could be useful for other experimental paradigms as well.IIT is a well-known approach to studying multi-dimensional judgment/problem-solving in adults and children (Anderson, 1981(Anderson, , 1982(Anderson, , 1991(Anderson, , 1996. It diagnoses how multiple informers combine into a unitary judgment, describing the process through algebraic models. These abound in JDM, but are rarely tested directly. IIT has made important basic contributions to JDM, providing, for instance, tests of how the structure of human judgment corresponds to classic models for probability (Lopes, 1976), expected value (Shanteau, 1974), and sequential decision-making (Shanteau, 1970).Recently, similar tests were done with children (Schlottmann & Wilkening, 2011). The examples in this chapter concern the Expected Value (EV) model, under which outcome value (v) and probability (p) combine multiplicatively, while component EVs combine additively, illustrated for two-outcome events below:Children from pre-school age make such structurally appropriate EV judgments. They know that EV depends on probabilities and values, combining them multiplicatively, although there are doubts, for adults and children, about component additivity. Children also know determinants of probability, for instance, that this increases with number of targets, but decreases with number of non-targets.A key feature of IIT is that it empirically separates how individuals evaluate probabilities and values from their strategies for integrating informers. Individuals typically do not quantify informers in an objective, precise way, but estimate subjective values and probabilities intuitively. Children's subjective values differ from adults' and may, occasionally, seem odd. While this may produce deviations from normativity, such subjective evaluation is qualitatively different, in our view, from structurally incorrect judgment. If children come closer to the mathematical standard with age, or if some children are better at this, it could reflect either or both. IIT studies, which often focus on the structural components of judgment, have established conclusively that these are operational from young ages. But individual children still differ in their judgments. How can we deal with th...