Causal modeling & alternative medicine

Many problems of health promotion or prevention call for an
understanding of relations among variables embedded in complex
causal webs that may include psychosocial, cultural, or
environmental factors as well as biological dysfunction.
Experimental investigation of these kinds of research problems
is frequently impossible or not feasible. Causal modeling,
particularly latent variable structural modeling, can provide
a useful alternative to manipulative experimentation when one
is trying to build and test explanatory models in a rigorous
and systematic fashion. A hypothetical model of fibromyalgia
is presented to illustrate how latent variable models can
prove useful when the malady under investigation is of
relatively complex multifactorial origin. Topics discussed
include the fundamental notion underlying causal models, how
such models solve problems due to measurement error, and why
both cross-sectional and longitudinal models deserve
consideration. A number of applications in medical research
are described. [References: 72]

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