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SERIAL DEPENDENCY IN THE METHOD OF LIMITS
Author(s) -
Speight L. R.
Publication year - 1970
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1111/j.2044-8317.1970.tb00437.x
Subject(s) - mathematics , dependency (uml) , probit model , statistics , psychophysics , markov chain , computer science , artificial intelligence , neuroscience , perception , biology
Empirical investigations suggest that dependency between successive responses in psychophysical experiments may not be uncommon. This paper puts forward a simple Markov model of response dependency. The constant method is briefly reviewed in the light of this model, and is shown to result in unbiased estimates of the psychophysical function. The method of limits is examined in more detail. Estimates of psychophysical function parameters obtained by this method, whether by averaging stopping‐point values or by conducting a probit analysis on the derived data, are shown to be a function of the inter‐stimulus interval chosen, the stopping criterion selected, and the degree of response dependency. However, bias is very small when stopping‐point averages are employed, provided that the inter‐stimulus interval is fairly large compared with the slope of the psychophysical function, and that use is made of a simple correction formula.