Risky Predictions and Damn Strange Coincidences in Theory Appraisal
An Examination of a Multivariate Corroboration Index for Path Analytic Models
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The elucidation and empirical testing of theories arevital components of research in any field. However,the extent to which theories are supported orcontradicted by the results of empirical researchremains ill defined. Commonly, support orcontradiction is based solely on the reject or fail to reject decisions that result from nullhypothesis tests derived from aspects of theory. Decisions and recommendations based on this forcedand often artificial dichotomy have been scrutinizedin the past. This overly simplified approach totheory testing has been challenged on logical grounds(Meehl, 1997, 199...
The elucidation and empirical testing of theories are
vital components of research in any field. However,
the extent to which theories are supported or
contradicted by the results of empirical research
remains ill defined. Commonly, support or
contradiction is based solely on the reject or fail to reject decisions that result from null
hypothesis tests derived from aspects of theory.
Decisions and recommendations based on this forced
and often artificial dichotomy have been scrutinized
in the past. This overly simplified approach to
theory testing has been challenged on logical grounds
(Meehl, 1997, 1990, 1978; Serlin & Lapsley, 1985).
Theories differ in the extent to which they provide
precise predictions about observations and the
precision derived from theories is proportional to
the strength of support that may be provided by
empirical evidence congruent with the prediction.
The notion of linking precision to strength of
support is surprisingly absent from many discussions
in this realm. Using Monte Carlo methods, this study
examined the performance of a multivariate extension
of Meehl s Corroboration Index. Implications for
theory and practice are discussed.
vital components of research in any field. However,
the extent to which theories are supported or
contradicted by the results of empirical research
remains ill defined. Commonly, support or
contradiction is based solely on the reject or fail to reject decisions that result from null
hypothesis tests derived from aspects of theory.
Decisions and recommendations based on this forced
and often artificial dichotomy have been scrutinized
in the past. This overly simplified approach to
theory testing has been challenged on logical grounds
(Meehl, 1997, 1990, 1978; Serlin & Lapsley, 1985).
Theories differ in the extent to which they provide
precise predictions about observations and the
precision derived from theories is proportional to
the strength of support that may be provided by
empirical evidence congruent with the prediction.
The notion of linking precision to strength of
support is surprisingly absent from many discussions
in this realm. Using Monte Carlo methods, this study
examined the performance of a multivariate extension
of Meehl s Corroboration Index. Implications for
theory and practice are discussed.
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