Investigating the Validity of the Australian Early Development Index

Abstract

This article aims to contribute to the ongoing evaluation of the Australian Early Development Index (AEDI) by investigating its construct and concurrent validity with a subsample of 642 children aged 4 to 5 years drawn from the Longitudinal Study of Australian Children (LSAC). Construct validity was examined by considering the theoretical consistency of the network of correlations between the AEDI subconstructs and the independently reported multimethod measures of early learning skills and development collected contemporaneously by the LSAC. Concurrent validity was examined by assessing the extent to which children who were “developmentally vulnerable” on the AEDI domains corresponded with the LSAC outcome indices classification of children as “developmentally at risk.” Moderate to large correlations were observed between each of the AEDI domains and subconstructs when compared to analogous teacher-rated LSAC measures, with lower levels of association observed for parent-rated LSAC measures. Concurrent validity was explored; however, with no criterion measure with which to assess the AEDI, findings are inconclusive prior to predictive validity assessment. Future waves of the LSAC will collect information on the children's abilities at school and developmental outcomes, enabling further interpretation of these concurrent and construct validity findings by triangulation and predictive validity analyses.

Notes

¹Correlation coefficients of .9 to 1.00 are very large, .7 to .89 large, .5 to .69 moderate, .3 to .49 small, and 0 to .29 little or none

²The teacher ratings on the fine and the gross motor skills scales ranged from 1 to 4, with 1 representing more competent than others and 4 representing much less competent than others, whereas the AEDI was scored in the opposite direction, thus accounting for the direction of the correlation.

*p < .05, one-tailed.

**p < .01, one-tailed.

*p < .05, one-tailed.

**p < .01, one-tailed.

*p < .05, one-tailed.

**p < .01, one-tailed.

³ Sensitivity = True Positive / (True Positive + False Negative), specificity = True Negative / (True Negative + False Positive), positive predictive value = True Positive / (True Positive + False Positive), and negative predictive value = True Negative / (True Negative +False Negative).

* p < .05, one-tailed.

**p < .01, one-tailed.

** p < .01, one-tailed.

**p< .000.