Analysis of the residual correlation matrix revealed little redun

Analysis of the residual correlation matrix revealed little redundancy in the test items, meaning that most items targeted

a unique level of cognitive ability. The component analysis of the residuals suggested only minor extradimensionality of the test (9% of the residual variance; eigenvalue >2.03), which was associated with items requiring abstract reasoning. The internal consistency of the test was only 0.52, probably because the variation in cognitive ability of this sample was limited. The bar graph in Fig. 2a shows the distribution of persons (upper bars) and items (lower bars). Many of the test items were too easy for the ability level of this patient sample. Three people could not be measured accurately because they obtained perfect scores. The ability of the remaining patients ranged from +0.422 to +3.456. E7080 manufacturer The information function (plotted as a line over the person distribution) shows that measurement precision is greatest around

the mid-range of difficulty (0 logits), which is below the range of cognitive ability in this patient sample. In the iterative process of Rasch analysis, two test scores were removed because they showed a poor fit to the model (reversal learning score and flanker test) and one (FAS) because selleck screening library it yielded no additional information beyond that provided by the fluency item on the MoCA. Three items were rescored because the thresholds defining the ability to move from one level to the next were disordered or because of too few observations in a particular response category (digit spans and spatial working memory). The resulting set of items showed good fit to a unidimensional Rasch model, including absence of an item–trait interaction (χ2=67.062; P=0.509). As seen in the lower bars of Fig. 2b, the distribution of items spans the range of difficulty from –3.120 logits (easiest) for tapping to the letter A to +3.321 logits for performance faster than 500 ms on the ‘go’ RT of

the stop-signal test. In other words, the items are well spread out along the continuum of cognitive ability check details assessed by the items and span a greater range than the MoCA alone. Minimal extradimensionality was observed, with one additional component associated with orientation to time that accounted for just 7.6% of the residual variance. The additional test items improved the internal consistency to 0.75. They also led to improved targeting of the range of ability in the patient sample (−0.027 to +4.608; Fig. 2b), and allowed for estimation of cognitive ability in the patients who scored at ceiling on the MoCA alone. The information function (Fig. 2b) shows that measurement precision was greatest in the range from +1 to +2 logits on the scale of cognitive ability. A university-level education was associated with higher estimates of cognitive ability for the MoCA items alone but did not reach significance for the combined data set (see Table 2).

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