causal

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causal

Philosophy (of a theory) explaining a phenomenon or analysing a concept in terms of some causal relation
References in periodicals archive ?
Causal modeling seeks to estimate the ratio of the expected value of outcome in the population of subjects i under the exposure they received versus what it would have been had they received the alternative exposure: E([Y.
Instead, he offers causal modeling as a tool to be used to simplify and understand existing research, compare and integrate theories, and allow for productive generation of hypotheses about autism, dyslexia, hyperactivity, and conduct disorders.
Fortunately, there is technology new to the commercial marketplace which solves the risk management "reasoning" problem very effectively, This technology is explicit causal modeling.
For significant contributions to the theory and applications of Bayesian reasoning and causal modeling, and the promotion of artificial intelligence within medicine.
Both simple comparison and causal modeling indicate that adolescent runaway is more likely with lower parent monitoring and better friend relationship.
Miller and Thoresen (2003) recently published an article highlighting the following areas that should be of concern to those interested in furthering the field: (a) basic assumptions contributing to the sparsity of research dealing with spirituality; (b) overview of the emergence of research dealing with religion and health; (c) definitions of spirituality, religion, and religiousness; (d) a levels-of-evidence approach to reviewing studies; (e) the unique variance and causal modeling approaches to statistical control; and (f) criticisms and concerns about religion and health.
Analysis of Moment Structures (AMOS) is a technique and related software application similar to LISREL for conducting structural equation modeling, analysis of covariance structures, or causal modeling (Arbuckle, 1997).
Judea Pearl has been at the forefront of research in the burgeoning field of causal modeling, and Causality is the culmination of his work over the last dozen or so years.
Using causal modeling techniques, it identified latent variables of civic awareness (including exposure to media on public affairs and political knowledge), electoral participation, and mobilization by politicians and estimated their relationships.
Modeling and analysis of complicated data structures, including techniques for correlated, spatial, clustered, longitudinal, survey, environmental, and genetic data; repeated measures; empirical Bayes methods; medical errors; and hierarchical and causal modeling.
Results of causal modeling demonstrate the significant contribution of studying on the student's life satisfaction and studying as a result of attention to public affairs, past achievement, study time, and majoring in social science.