Eight hundred nineteen school students were selected in the present study in an age range between 9 and 16 years (M = 12.14; SD = 1.78 years). All of them were healthy and proficient in English. Participants were excluded from the study if they indicated that they had a history of neurological or psychiatric disturbance, and were using medication with central nervous system problems, or had a history of any learning disability. After completely describing the study to the participants, written informed consent was obtained.

The six letter cancellation task consisted of a test worksheet which specified the six target letters to be cancelled and had a ‘working section’ which consisted of letters of the alphabet arranged randomly in 22 rows and 14 columns. The participants were asked to cancel as many of the six target letters as possible in the specified time, i.e., 1 min, 30 sec. They were told to choose from two possible strategies, i.e., (i) doing all six letters at a time or (ii) to selective any one target letter out of the six. They were also told that they could follow a horizontal, vertical, or a random path, according to their choice.[10] The total number of cancellations and wrong cancellations were scored and the net scores were calculated by deducting wrong cancellations from the total cancellations attempted. Tests were administered by five trained assistants in the neuropsychological test laboratory.

The normative procedure for net six letter cancellation scores (NSLCT) involved the fitting of multiple linear regression models adjusted for age (in years) and
sex. The core assumptions of regression analysis (homoscedasticity, normal distribution of the residuals, absence of multicollinearity, and the absence of ‘influential cases’) were tested for each model. Homoscedasticity was evaluated by visual inspection of the scatter plots of the residuals on the predicted values. The normal distribution of the residuals was investigated by visual inspection of the histograms and the normal probability plots. The occurrence of multicollinearity was checked by calculating the Variance Inflation Factors (VIFs), which should not exceed 10.[20] Cook’s distances were computed
to identify any possible influential cases. Normative data can then be obtained by calculating the residuals for the NSLCT scores (ei = observed score – predicted score). The residuals are then standardized (Zi = ei / SD [residual]). All analyses were performed by using the SPSS 10.0 version software package.