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effet du nombre des graphèmes en Anglais - Aix Marseille Université

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240App<strong>en</strong>dice Iteractive processes operating betwe<strong>en</strong> orthographic and phonological repres<strong>en</strong>tations, and that the pres<strong>en</strong>tMROM-P provi<strong>des</strong> a viable "model-system" within which such effects can be understood at suffici<strong>en</strong>t levelsof clarity/transpar<strong>en</strong>cy and formality/precision.Feedback consi st<strong>en</strong>tFeedback i nconsi st<strong>en</strong>t1M R OM1M R OM - P0. 80. 80. 50. 50. 20. 21 1 a( ms) ( ms) (ms)000 10 20 30 400 10 20 30 40Cy cl esCy cl esStone et al . ( 1 9 9 7 )950925900875850F B conF B i nc28M R OM28M R OM - P2727262625251 1 b24F B conF B i nc24F B conF B i ncFigure 11 : Simulation of Stone et al.'s nonword data.MODEL EVALUATIONIn this section, we follow the t<strong>en</strong>tative criteria for model comparison and evaluation proposed in Jacobsand Grainger (1994), in particular : i) pot<strong>en</strong>tial and actual <strong>des</strong>criptive accuracy, ii) horizontal and verticalg<strong>en</strong>erality, and iii) simplicity and falsifiability.POTENTIAL AND ACTUAL DESCRIPTIVE ACCURACY. The first aspect of this accuracy criterion ispot<strong>en</strong>tial <strong>des</strong>criptive accuracy . The question here is : Does the model allow predictions at the level of scale atwhich the dep<strong>en</strong>d<strong>en</strong>t variables of interest are actually measured. For example, if the dep<strong>en</strong>d<strong>en</strong>t variable thatreflects the effect is interval-scaled (e.g., a frequ<strong>en</strong>cy effect measured in ms), th<strong>en</strong> a model has pot<strong>en</strong>tial <strong>des</strong>criptiveaccuracy if it allows predictions on the scale of ms. Any curr<strong>en</strong>t psychological A-type model canonly achieve this in an indirect way, for example, by transforming cycle times into RTs via regressionanalyses.Despite complex considerations concerning measurem<strong>en</strong>t problems, we think that A-type modelersshould take this issue seriously and provide a means by which model users can formally compare the valuesof the dep<strong>en</strong>d<strong>en</strong>t variable(s) they want to study with those of the model's output. This is necessary to developstandards for evaluating the relative goodness-of-fit for competing models. Why should "eye balling"or "hand waving" be accepted as alternatives to model-to-data fitting wh<strong>en</strong> using complex A-type models,while they are not accepted for any other formal model format? Massaro and Friedman (1990) provide an <strong>en</strong>couragingexample for evaluating the <strong>des</strong>criptive accuracy of a set of comparable M- and A-type models,

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