Table 3.
Estimated Effects of County-Level and Individual-Level Factors on Depression: Cross-Level Interaction between Income Inequality and Number of Illnesses
| Model 3 | ||
|---|---|---|
| Fixed Effect | Coefficients | Standard Error |
| Intercept | 1.8727*** | 0.0854 |
| County-Level Variables | ||
| Gini | 2.6387*** | 0.8143 |
| Mean income | 0.0021 | 0.0030 |
| Individual-Level Variables† | ||
| Age | −0.0023*** | 0.0046 |
| Female | 0.1534 | 0.0534 |
| Married | −0.3556*** | 0.0544 |
| Education | −0.0602*** | 0.0071 |
| Income: Groups -Middle | −0.0747 | 0.0794 |
| -High | −0.0001 | 0.0720 |
| Wealth: Groups -Middle | −0.2100*** | 0.0697 |
| -High | −0.1750*** | 0.0636 |
| Race/ethnicity: Black-non-Hispanic | −0.0992 | 0.0765 |
| Hispanic | 0.2935** | 0.1161 |
| ADL limitations | 0.3351*** | 0.0284 |
| IADL limitations | 0.1949*** | 0.0317 |
| Number of illnesses | 0.2176*** | 0.0169 |
| Cross-Level interaction | ||
| Gini* Number of illnesses | 1.1721*** | 0.4001 |
| Random Effect‡ | Variance component | χ2 (d.f.) |
| Intercept (county mean depression) | 0.0327*** | 285.80 (208) |
| Individual-level effect | 3.1065 | |
p≤0.01
p≤0.05
p≤0.10. (two-tailed tests)
Note: Models 3 is a random intercept models estimated based on the restricted maximum likelihood method, using unweighted data. All the continuous variables were centered to facilitate the interpretation of the intercept. The intercept represents the level of depression when independent variables are constrained at the average value for continuous variables or at the reference category for categorical variables. Depression is measured by an eight-item abbreviated CES-D scale, which ranges from 0 (not depressed at all) to 8 (maximum level of depression). Robust or “Huber-corrected” standard errors are reported.
Reference categories are male (gender), not currently married (marital status), low (income groups), and low (wealth groups).
The variance component of the intercept (county mean depression) represents the county-level residual variance or county effects that are left unexplained by the model. The variance component of individual-level effects represents the individual-level residual variance. Since the individual-level models are virtually the same in Models 1 and 3 except that the latter involves cross-level interaction term, the level-1 variance estimates were almost identical across these models. Proportion reduction in variance statistics at county-level is interpretable only for the same individual-level model. The cross-level interaction term in Models 3 did not allow calculation of those statistics based on Models 1 and 3.