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Such phenomena can be observed in selection contexts (Bagby and Marshall, 2003), and are as problematic as low coherence. Because a statistical model is not human, people are unlikely to have a response coherence of 1, so such cases indicate that participants gave the description of an expected model rather than of themselves. Capel (2009) stated that low values in response coherence could result from a lack of maturity and are likely found in adolescent participants; this is consistent with Soto et al. (2008) results with another approach of test results coherence. Response reliability Another important measure of one's response quality is response reliability. Response reliability is an unusual application of a well-known technique used in test validation, namely the bisection method. Usually, the bisection method is used to calculate the split-half reliability of a test among a sample of subjects' answers; calculating split-half reliability in one only person's responses is of little relevance and is quite unfeasible in CTT. Yet, Drewes (2000) highlighted that reliability of a measurement can be modeled. Thereby, FMT's purpose is to calculate split-half reliability based on one's modeled response. Thus, two vectors of strategy (s��� and s���) can be obtained from two halves of the original questionnaire completed by one individual; the correlation between those two vectors is a first approximation of the person's response reliability. Still, conforming to its classical use, the bisection method underestimates the reliability due to the number of items taken into account by the half tests. A first solution is to calculate the exact split-half reliability. Because Cronbach's alpha is not calculable in FMT (given that every item is related to every factor); another Ramoplanin possibility is to calculate the mean correlation between each parallel form, which is a feasible but far too laborious solution. As a remaining possibility, the reliability can be adjusted using the Spearman-Brown correction formula: Corrected?response?reliability=rSB???????????????????????????????????????????=?2*cor[(S1��S2��S3�䡭Si��),(S1��S2��S3�塭Si��)]1+cor?[(S1��S2��S3�䡭Si��),?(S1��S2��S3�塭Si��)]?? Response reliability is of great importance in interpreting test results. A high response reliability indicates that one completed the questionnaire with care, that one was able to understand the meaning of the items, and that one was stable in the manner s/he responded throughout the test. On the other hand, a low response reliability means that the person had problems in responding, consisting either of a lack of care, a lack of comprehension, or a lack of stability in responding (e.g., due to fatigue). Indeed, one of those three issues is enough to make test results completely unreliable.