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  1. Stanley A. Mulaik (2001). The Curve-Fitting Problem: An Objectivist View. Philosophy of Science 68 (2):218-241.
    Model simplicity in curve fitting is the fewness of parameters estimated. I use a vector model of least squares estimation to show that degrees of freedom, the difference between the number of observed parameters fit by the model and the number of explanatory parameters estimated, are the number of potential dimensions in which data are free to differ from a model and indicate the disconfirmability of the model. Though often thought to control for parameter estimation, the AIC and similar indices (...)
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  2. Stanley A. Mulaik (1995). The Metaphoric Origins of Objectivity, Subjectivity, and Consciousness in the Direct Perception of Reality. Philosophy of Science 62 (2):283-303.
    This paper utilizes the theories of metaphor of George Lakoff, Mark Johnson and Julian Jaynes to extend Jaynes' metaphor theory of consciousness by treating consciousness as an operator that works with 'covert behavior' so that humans can integrate temporally discontinuous percepts with concepts based on metaphoric extensions of the embodied schemas of direct and immediate perception and thereby transcend the limitations of direct perception. A theory of first-person expressions and covert behavior to account for self-conscious awareness as language-based is advanced. (...)
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  3. Stanley A. Mulaik (1991). Factor Analysis, Information-Transforming Instruments, and Objectivity: A Reply and Discussion. British Journal for the Philosophy of Science 42 (1):87-100.
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  4. Stanley A. Mulaik (1986). Toward a Synthesis of Deterministic and Probabilistic Formulations of Causal Relations by the Functional Relation Concept. Philosophy of Science 53 (3):313-332.
    There have been two principal paradigms for the formulation of the causal relation--logical implication and functional relationship. In this paper, I present a case for preferring the functional relationship formulation and then discuss how the functional relationship formulation may be implemented in the probabilistic case in a manner analogous to the way others have implemented the logical implication formulation in the probabilistic case. I show how the "local independence" assumption found in many models used in the behavioral and social sciences (...)
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  5. Stanley A. Mulaik (1985). Exploratory Statistics and Empiricism. Philosophy of Science 52 (3):410-430.
    Exploratory statistics represents the transformation of a realist theory of statistics held by early nineteenth-century astronomers into an empiricist theory of statistics held by biometricians at the turn of the twentieth century. This paper discusses four key ideas in empiricist thought that influenced the form exploratory statistics took: (1) Baconianism, (2) associationism, (3) the search for cognitive calculi, and (4) phenomenalism. Some limitations of and alternatives to exploratory statistics as a hypothesis-generating methodology are discussed.
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