This chapter focuses on next-generation selection models that allow us to expand on the Heckman model using copula and control function models that allow one to estimate selection models for a large range of other statistical distributions. This chapter also shows how to generate weights that account for nonignorable nonresponse; not only do these weights increase the weight on demographic groups that respond with lower probabilities, they also increase weights on people with opinions that may make them less inclined to respond. This chapter also shows how to modify a Heckman model to allow for estimation of a nonignorable nonresponse selection model when we have a response-related variable that is available only for people in the survey sample.

It is frequently reported that processing speed slows and executive functions (EFs) become less effective in the course of healthy aging. This chapter highlights research supporting these claims in three areas of investigation: cognitive aging research, the neuropsychological perspective, and studies evaluating the association of EF with structural and functional imaging measures. Several themes emerge in this review. For example, diminished processing speed with aging appears to reflect aging-related changes in the anterior cingulate/superior medial frontal cortex, as well as perceptuomotor slowing. The definition of EF varies between different publications and there is a need for more precise operational definitions. There is also a need to decompose EFs into their component processes. Impairments of EF are strongly related to damage in prefrontal regions, but disorders of EF also occur with injury to nonfrontal regions, indicating that complex networks are involved in EF. Additionally, domain-specific changes beyond the changes in EF are important considerations in network analyses. We propose a method to advance future research on EF by using focal frontal lesion studies and neural network principles as frameworks to expand our understanding of aging-related changes in EF and processing speed.