The CanMarg index had the

The CanMarg index had the second highest adjusted R2 in two out of the four provinces examined. At the same time, its adjusted R2 values tended to be similar to, or below, those of the SEFI and CanDep indices in all EDI domains other than the Communication Skills and General Knowledge domain. In this domain, the ECMap and CanMarg both have relatively high associations. Relative to their other components, the effect sizes of the components representing immigration/language in a neighbourhood was the largest for both of these indices. This suggests that the relationship between these components and the Communication Skills and General Knowledge domain is driving a large proportion of its explanatory power on overall vulnerability. This makes intuitive sense because the Communication Skills and General Knowledge domain primarily represents children\'s proficiency in communicating in the schools’ language of instruction, which would be a challenge for the newly immigrated JWH 073 in a neighbourhood coming from language backgrounds other than English or French. The fact that the CanMarg index has 18 variables representing a diverse range of constructs poses a limitation/challenge in terms of interpretability. Also, when combined into an aggregated index, the CanMarg index has the lowest adjusted R2 value among all of the other indices. The SEFI\'s biggest advantage, in our view, was its interpretability. With only four variables and one component, it was arguably the most easily interpretable index we examined. Its adjusted R2 values were of a comparable magnitude to CanDep and CanMarg across most provinces and domains. However, while the advantage of the SEFI was the simplicity of its single component structure, it was also its disadvantage. The single component did not allow for the SEFI to be used in the discussion of differential effects sizes between different aspects of SES, and excluded language/immigration factors altogether. This said, the results indicate that a relatively simple index, such as the SEFI, may be as useful as the more complex indices in terms of explanatory power for ECD outcomes if highly relevant variables are used. The CanDep index\'s advantage is that it performed moderately well on all of our criteria, making it a well-rounded index. In terms of explanatory power, the CanDep index performed similarly to the SEFI and the CanMarg index. When aggregated, the CanDep index had one of the highest adjusted R2 values. In terms of interpretability, the CanDep index had only six variables and two components, meaning that it competed with the SEFI for the simplest index structure. Also, the CanDep index has both a material and social component, enabling matter to be used in regressions distinguishing between the effects of these two aspects of SES. One limitation of the CanDep index is that it does not include a language/immigration component, or another component that relates to ‘cultural diversity’ or other cultural aspects of neighborhoods. In sum, similar to the SEFI, the CanDep index is another simple index which explains a relatively large amount of variation, however it goes further than the SEFI by making use of a two-component structure.
Conclusion While this paper focused primarily on discerning the aspects of a neighbourhood SES index which make it relevant to the analysis of ECD outcomes, there are many more analytical questions which could be asked using such an index. While answering specific research questions was beyond the scope of this paper, one insight which can be inferred from our analysis is that the geographical area and specific ECD outcome of interest should be thought out carefully since the scope of analysis (both in terms of geography and outcomes) may impact the findings. For instance, if a research question in one jurisdiction was whether children tended to score worse on the Physical Health and Well-Being domain in neighbourhoods with high material deprivation, the highest level of precision would be achieved by narrowing the geographical scope (and therefore reference group) to include only that specific jurisdiction and narrowing the outcome of interest specifically to this domain. This also implies that findings regarding a gradient in Canada may not apply directly to other countries. Analyses in other countries would have to use the neighbourhood SES indices most relevant to their experience and analyze their relationship to ECD outcomes specific to that country, which has already been done, for example, in Australia and Scotland (Brinkman et al., 2012; Woolfson, Geddes, McNicol, Booth, & Frank, 2013). Even though the distribution of scores may be specific to Canada, the methodology used in this paper for finding the most relevant indices could inform similar studies in other countries. The findings that certain index components showed relatively larger associations with certain domains of ECD could also be tested in other countries to put results in context. Based on the analyses in this paper, we believe that indices relevant to children\'s developmental outcomes anywhere need to include, at a minimum, material, social and cultural components.