Table 4. Regression results and diagnostics. Coefficients with standard errors in parantheses. Bold estimates have 95% confidence or greater. Max variance inflation factors (VIF) is the largest variance inflation factor for any predictor in the given model. A VIF of 10 or greater is considered an indication of multicolinearity (Fox and Monette 1992). †A random-effects poisson was over-dispersed (dev/df = 2.17; Lindsey 1999), while a negative binomial model without village was not (dev/df = 1.29). Village-level variance were calculated with a mixed effects poisson. ‡The diversity predictor variable used for workdays was number of castes with 10 or more households.
| |
| |
|
|
Workdays |
Adequacy |
Fairness |
| |
|
Family |
negative
binomial† |
binomial |
binomial |
|
Intercept |
-1.58 (0.83) |
-3.43
(1.03) |
-2.45 (1.31) |
|
Village-level |
|
LNPOP |
0.77
(0.15) |
-0.25 (0.13) |
0.57
(0.19) |
|
DISTANCE |
-0.01
(0.01) |
0.00 (0.01) |
0.02
(0.01) |
|
CASTES‡ |
-0.26
(0.08) |
0.16
(0.06) |
-0.11 (0.09) |
|
WEALTHGINI |
-0.03
(0.01) |
0.05
(0.02) |
-0.11
(0.02) |
|
Household-level |
|
|
|
|
AGE |
0.00 (0.00) |
0.00 (0.00) |
0.00 (0.01) |
|
EDUC |
-0.01 (0.02) |
-0.01 (0.02) |
-0.02 (0.02) |
|
HHSIZE |
0.06 (0.04) |
0.06 (0.05) |
0.15
(0.06) |
|
LNWEALTH |
-0.01 (0.04) |
-0.01 (0.04) |
0.22
(0.06) |
|
FRAC |
1.14
(0.44) |
0.27 (0.44) |
2.56
(0.64) |
|
DALIT |
-0.03 (0.23) |
-0.15 (0.25) |
-1.24
(0.58) |
|
CHANNEL |
0.38
(0.17) |
0.96
(0.18) |
3.36
(0.28) |
|
DALIT*CHANNEL |
0.12 (0.31) |
0.36 (0.33) |
1.95
(0.67) |
|
Village
variance |
|
|
|
|
Full Model |
0 |
0.001 |
0
|
|
Model Fit &
Diagnostics |
|
|
|
|
ML
pseudo-R² |
0.22 |
0.28 |
0.94 |
|
DF |
241 |
243 |
243 |
|
Deviance |
310 |
143 |
473 |
|
Max VIF |
7.9 |
7.2 |
7.2 |
|
| |
|