Table 1 Approaches used to construct variables to model the effects of collective efficacy or related social-environmental variables, such as income inequality or social capital

Derived variable

Derived variables are created by summarizing the characteristics of individuals within a group, using means, medians, proportions, or measures of dispersion (e.g., variances) or other aggregation approaches

 Based on group-level mean

Use average individual responses to items on a given scale; these means are then subsequently averaged across individuals living in the same context (e.g., neighborhood) to arrive at a contextual-level measure.

[10,14,16,17]

 Based on group-level variance

Use average individual responses to items on a given scale; the variance (or standard deviation) in these means are then examined among individuals living in the same context (e.g., neighborhood) to arrive at a contextual-level measure.

[19]

Factor Analysis

Capture the shared variance among an observed set of variables in terms of a potentially smaller number of unobserved constructs or latent factors.

 Single-level factor analysis

Latent factors are estimated at only one level (i.e., the individual or contextual level).

[18]

 Multilevel factor analysis (MLFA)

Latent factors are estimated at two-levels of analysis. Latent factors structures can differ at each level of analysis.

[24-28]

Hierarchical Latent Variable Model

A special case of the 2-level MLFA that imposes stricter parameter constraints than the most general MLFA wherein latent factors are estimated at only the individual level with the factor variances decomposed into within- and between-group components.

[9,51]