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The result of this analysis shows that the matching at the level of the geographical place (village or city) has the most discriminant power (coefficient of discrimination of 0.39), followed by the matching at the geographical administration subunit level (coefficient 0.12), then matching at the geographical administration unit level (coefficient 0.05).
Tjur's coefficient of discrimination (D) was used to evaluate and compare the different models, since it is closely related to linear measures of fit and is not based on the likelihood function (Tjur 2009).
This could be compared with the number of differences actually observed and expressed as a ratio: the coefficient of discrimination.
Predictive value was studied using various measures such as the McFadden R and the Tjur's coefficient of discrimination (14).
It is possible, however, to incorporate these elements into the computation of a coefficient of discrimination if required.
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Table 4 AIC and coefficients of discrimination (D) values of the different forms of the model fitted to the dataset using logistic regression AIC D Adaptation Belief 484.86 0.01 Adaptation Belief + Experience 482.12 0.03 Full model 196.29 0.65 The value in bold is the most parsimonious model as selected by AIC comparison (ΔAIC > 2).
Coefficients of difficulty, discrimination and impact on the test's overall reliability are computed at question and case levels.
Item-rest = coefficient of item-rest discrimination according to factorial solution.
Recently Hankins (re- introduced Fere- introducedicient δ as an index oFergusonmination, to be distinguished from the well-known measurement properties validity and reliability [ 1, 2].
In (4) s is an exogenous separation rate, and Wi(c) the wage earned by a type i worker at a job with a discrimination coefficient of c. Equations (5) and (6) give the value to the employer of a vacancy and a filled job as functions of the job's discrimination coefficient, c. rV c = - k + φy c [ E J i c – V c (5) rJ i c = x – W i c – c i + s rV c – J i c, i = A, B (6).
It is hoped that researchers will now report and seek to maximise both coefficients of reliability and discrimination when evaluating and designing questionnaire measures.
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