Visual slow brain potentials in children with attention deficit disorder

Using a two-stimulus reaction time paradigm, with two separate reward conditions (contingent and noncontingent), we compared slow wave brain potentials (ERPs) in 144 children with attention deficit disorder (ADD) and 30 normal control children. This article reviews the findings during the 900 msec visual warning stimulus. As we had expected, based on ERP work of Forth and Hare (1989) and Raine, Venables and Williams (1990), and on previous work from our own laboratory, the group differences were found in the negative slow wave portions of the ERP complex during the contingent reward condition but not during the noncontingent condition. Aggressive hyperactive subjects with attention deficit disorder (ADDHA) were discriminated from nonaggressive subjects (including control subjects) during the contingent reward condition in the following ways: (1) greater fronto-central negativity (640–900 msec slow wave) and (2) greater right parietal than left parietal negativity (430–750 msec slow wave). All ADD subgroups, when compared to control (CONTR) subjects, showed greater slow wave negativity (700–900 msec) at the midline occipital electrode site during the contingent reward condition. This could be explained in part as an IQ effect on ERPs reflecting the IQ difference between the ADD subgroups and the controls. These slow wave findings seem to relate to attentional problems of these children. They are discussed in terms of a psychobiological model of inhibition/disinhibition and appetitive activation.     

An investigation of the sampling distributions of item discrimination indices

The sampling properties of four item discrimination indices (biserialr, Cook's indexB, theU–L 27 per cent index, and DeltaP) were investigated in order to ascertain their sampling properties when small samples drawn from actual test data rather than constructed data were employed. The empirical results indicated that the mean index values approximated the population values and that values of the standard deviations computed from large sample formulas were good approximations to the standard deviations of the observed distributions based on samples of size 120 or less. Goodness of fit tests comparing the observed distributions with the corresponding distribution of the product-moment correlation coefficient based upon a bivariate normal population indicated that this correlational model was inappropriate for the data. The lack of adequate mathematical models for the sampling distributions of item discrimination indices suggests that one should avoid indices whose only real reason for existence was the simplification of computational procedures.This research reported herein was performed pursuant to a contract (OE-2-10-071) with the United States Office of Education, Department of Health, Education and Welfare.