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

Variable approach	Description	Examples
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]