Hypothesized and confounded explanations in theory tests: a Bayesian analysis

Article Abstract:

Traditional views of research methodology hold that little, if any, useful information can be obtained from one or more confounded studies, unless the results from one study rule out or falsify an alternative explanation from a previous study. We present a Bayesian analysis of hypothesis testing to model knowledge accumulation from a series of confounded or unconfounded experiments. By applying this Bayesian analysis, we find that a hypothesis can receive support from a study with known flaws. Our analysis also implies that the status of an explanation is independent of whether it was proposed a priori or post hoc. (Reprinted by permission of the publisher.)

Methods, Testing, Bayesian statistical decision theory, Bayesian analysis, Statistical hypothesis testing, Theory (Philosophy)

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Task, expectancy, and information assessment effects in information utilization processes

Article Abstract:

Consumers are awash in objective information. A pair of researchers has developed a model to help explain how consumers integrate that information into their purchasing decisions. The model is based upon the application of a small list of information attributes, and can help explain why people change their minds about products while using them.

Psychological aspects, Research, Marketing research, Market research, Consumers, Human information processing

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