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. 2021 Jul 14;42(5):729–745. doi: 10.1111/pops.12773

Table 4.

Hierarchical Linear Regression Models

Total Number of COVID‐19 Cases COVID‐19 Cases per 1000 People
Effect SE Effect SE
Fixed Effects (Level 1)
Intercept (Outcome variable) γ 00 .09 .06 .05 .06
Negative peace γ 10 −.57*** .02 .03 .02
Neighborhood desegregation γ 20 −.08*** .02 −.10*** .02
Income equality γ 30 −.05* .02 .01 .02
Employment γ 40 .05 .02 −.04 .03
High‐school Graduation γ 50 −.01 .02 −.04 .02
Percentage of people over 50 γ 60 .07** .02 −.03 .02
Percentage of BIPOC γ 70 .20*** .03 .44*** .03
Republican/Democrat ratio γ 80 .11*** .01 .05*** .01
Population density γ 90 .01* .01 .01 .01
Residual Variances
VarianceCounty .72*** .02 .85*** .02
VarianceState .17*** .04 .17*** .04
Intraclass correlation (ρ) .13 .16
Model Fit Comparisons
2 Log Likelihood (df) 1619.20 (3)*** 1004.48 (3)***

All model fit comparisons are relative to the unconditional model. All predictors were group mean centered.

*

p < .05;

**

p < .01;

***

p < .005.