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appropriate units of analysis, level-specific contextual effects, and nested random influences in estimating the influences of competing factors on various transitional events.

Data from Cameroon are used to illustrate the features of this methodology and to test several assumptions of the theoretical framework of the NRC’s Panel on Transitions to Adulthood in Developing Countries. Cameroon has special appeal because it is generally considered a microcosmic representation of tropical Africa due to its diversity. We use a multilevel modeling framework because individuals are bound by family, neighborhood, community, regional, national, and international factors that influence their individual or collective behaviors, so that treating these individuals as independent observations within a study may be quite misleading. Indeed, there is potentially some correlation among individuals interacting and behaving like others within their various contexts of life, which may remain even after all measured variables are taken into account in analyses. This study posits that this correlation is a consequence of developmental, normative or behavioral, structural or contextual factors that are related to various transitions to adulthood and are common to groups of individuals but that are unmeasured or unmeasurable. Correlated observations violate a standard assumption of independence in statistical analyses, resulting in understated standard errors and a greater likelihood of committing Type I errors and, in the case of nonlinear models such as survival models, estimated parameters that are both biased and inconsistent (Kuate-Defo, 2001).

The next section of this chapter considers the meaning of successful and healthy transitions to adulthood in the context of a developing country. The following section presents the logic and assumptions of multilevel modeling as well as data requirements. The data set, main relations considered and statistical methods are then described. The two final sections present the main empirical findings and discuss their implications.


Half of the population worldwide is now under age 25, with the largest ever generation of adolescents—1.2 billion people between the ages of 10 and 19—representing one fifth of the world’s population (UNFPA, 2003a). Such growth puts untimely pressure on the limited and/or scarce resources that can prepare these young people for a better future. This is because more than 87 percent of them live in a developing world with changing and diverse socioeconomic, cultural, and epidemiological circumstances often made harsh by poverty. The impact of these circumstances on the options of adolescents and youth is apparent as they move through the lifecycle and are expected to assume adult roles. On the other hand, this large number of

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