Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
3396352 | Clinical Epidemiology and Global Health | 2013 | 5 Pages |
Abstract
Statistical modeling techniques have become important analytical tools and are contributing immensely to the field of epidemiology. However, many users do not understand their effective use and applications. Underlying epidemiologic concepts, and not the statistics, should govern or justify the proper use and application of any modeling exercise. Main utility of the statistical model lies in its ability to provide a general but practical conceptual framework for causal problems, explaining and evaluating role of biases, confounders and effect modifiers. Successful modeling of a complex data is part science, part statistics, part experience, but major part is logic or common sense.
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Authors
Suresh Ughade,