Descriptive analysis of the test of everyday attention for children in a Spanish normative sample

Introduction. Test of Everyday Attention for Children (TEA-Ch) has been validated in different countries demonstrating that it is an instrument with a correct balance between reliability and duration. Given the shortage of trustworthy instruments of evaluation in our language for infantile population we decide to explore the Spanish version of the TEA-Ch. Methods. We administered TEA-Ch (version A) to a sample control of 133 Spanish children from 6 to 11 years enrolled in school in the Community of Madrid. Four children were selected at random by course of Primary Education, distributing the sex of equivalent form. Descriptive analysis and comparison by ages and sex in each of the TEA-Ch's subtests were conducted to establish a profile of the sample. In order to analyze the effect of the age, subjects were grouped in six sub-samples: 6, 7, 8, 9, 10 and 11 years-old. Results. This first descriptive analysis demonstrates age exerted a significant effect on each measure, due to an important "jump" in children's performance between 6 and 7 years-old. The effect of sex was significant only in two visual attention measures (Sky Search & Map) and interaction age and sex exerted a significant effect only in the dual task (Score DT). Conclusions. The results suggest that the Spanish version of the TEA-Ch (A) might be a useful instrument to evaluate attentional processes in Spanish child population.

Influence analysis of robust Wald-type tests

We consider a robust version of the classical Wald test statistics for testing simple and composite null hypotheses for general parametric models. These test statistics are based on the minimum density power divergence estimators instead of the maximum likelihood estimators. An extensive study of their robustness properties is given though the influence functions as well as the chi-square inflation factors. It is theoretically established that the level and power of these robust tests are stable against outliers, whereas the classical Wald test breaks down. Some numerical examples confirm the validity of the theoretical results.