Some principles pertaining to multilevel analysis have been articulated by Cacioppo and Berntson (1992; see also Cacioppo, Berntson, et al., 2000), which serve to frame issues and organize research perspectives. They are enumerated following.
The principle of multiple determinism stipulates that a target event at one level of organization, especially at more molar levels, will have multiple antecedents within and across levels of analysis. Parenting, for example, has both social and genetic determinants (Meaney, 2001). Because of the multiple antecedents across even proximal levels, the mappings across more divergent levels of analysis become increasingly complex. This is captured by an important corollary to the principle of multiple determinism. Although the ultimate goal of multilevel analysis is to bridge distal levels, the corollary of proximity suggests that this effort may be more straightforward for more proximal levels. As bridges are built among adjacent levels, those integrations will facilitate the superordinate mappings across progressively more disparate levels. This is not to say that bridging across broader levels of analysis is not possible or desirable. There are examples of programmatic research efforts that span multiple levels, such as the collaborative effort of Michael Meaney to map from the gene to maternal behavior and back again (Meaney, 2001). This was accomplished, however, through a systematic series of interdisciplinary collaborative efforts, which individually cut across a more limited span of levels.
'Originally petitio principu from Aristotle (350 B.C.) Posterior Analytics, translated by G. R. G. Mure, MIT Internet Classics Archive: http://classics.mit.edu/Aristotle/posterior.mb.txt.
The principle of reciprocal determinism asserts that there may be mutual, reciprocal influences among levels of organization—that is, the direction of causation is not one way. To continue with our example of gene-maternal interaction, there is a clear genetic bias in the pattern of maternal behavior in rats, but the pattern of maternal behavior has also been shown to impact specific gene expression in the offspring (Meaney, 2001). Moreover, this experience-dependent influence on gene regulation can extend beyond the subsequent generation, through nongenomic inheritance (Meaney, 2001). The principle of reciprocal determinism also has a guiding research corollary. Because causal influences among levels can be bi-directional, the corollary of interdependence states that a single level of analysis cannot yield a comprehensive account of multilevel phenomena, and that no single, preferred level of analysis applies uniformly. This is not to say that researchers should not do single-level research, as important phenomena for multilevel analyses derive from research and theory within a single level of analysis. Moreover, the selection of the most optimal level of analysis for single-level research depends on the experimental question and the theoretical interest (e.g., genetic vs. maternal determinants). The corollary indicates, however, that a comprehensive understanding of multilevel phenomena will require multilevel analysis.
Finally, the principle of nonadditive determinism reflects the fact that the properties of the whole cannot always be predicted by knowledge of properties of the parts. The sources of variance from higher level processes are often broader than those for lower levels of organization, so higher level systems tend to be more complex. Following the preceding example, the mere knowledge of a genotype may be uninformative as to phenotype, which in critical ways depends on multiple interactions with the social/maternal context (Meaney, 2001). Consequently, understanding genetics would not be complete if the study were restricted to the cellular domain. This principle reflects the increase in relational complexity with higher levels of organization and introduces the final corollary. The corollary of asymmetry states that the definition of a phenomena of interest should include observations at the highest level of organization at which it manifests, as it may not be understood by appeal exclusively to lower levels of analysis. That is, higher level analyses can identify and characterize phenomena that may be explicated in part by lower level organizations, but these phenomena may never be known from analyses limited to the lower level processes. This corollary would not preclude strictly lower level (e.g., molecular) analyses, but would apply at the point those molecular analyses were invoked to account for higher level phenomena (e.g., behavior).
The principles and corollaries just outlined are conceptual guidelines rather than prescriptions. Moreover, we wish to emphasize that merely mapping concepts from one level to another, although informative, does not in itself constitute an explanation of those relations. The latter will require well-developed theories that can foster predictions, allow experimental control, and permit hypothesis testing and theoretical refinements.
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