Hello All
I am trying to work on gender differentials and urban-rural differentials.
I have used mvdcmp for the decomposition analysis as my outcome variable is binary.
I am having problem with the interpretation of the results.
Can anyone please help me out with the same?
Glimpse of my output is :
From the paper on the same topic in the STATA journal I could understand that the differences in the effects accounts for 64.71% of the observed rural-urban differentials in the prevalence of diabetes. I have used same wording from the mvdcmp paper in the STATA journal because I don' understand it properly.
And how do I interpret E and R here? How can I interpret the coefficients in the tables below?
Looking forward for your help.
Thanks in Advance.
I am trying to work on gender differentials and urban-rural differentials.
I have used mvdcmp for the decomposition analysis as my outcome variable is binary.
I am having problem with the interpretation of the results.
Can anyone please help me out with the same?
Glimpse of my output is :
| Coeff (95% CI) | Percentage | |
| E | 0.042***(0.0379, 0.047) | 35.2810 |
| C | 0.078***(0.071, 0.0848) | 64.7190 |
| R | 0.12***(0.1143, 0.1264) | |
| Due to Difference in Characteristics | ||
| Body Mass Index | 0.021***(0.0185, 0.0236) | 17.4960 |
| Age | -0.003***(-0.0033, -0.0027) | -2.4857 |
| Education | 0.011***(0.0069, 0.0144) | 8.8424 |
| Due to Difference in Coefficients | ||
| Body Mass Index | -0.005***(-0.0072, -0.0032) | -4.3464 |
| Age | 0.007 (-0.0045, 0.0189) | 5.9450 |
| Education | -0.013***(-0.0163, -0.0089) | -10.4600 |
From the paper on the same topic in the STATA journal I could understand that the differences in the effects accounts for 64.71% of the observed rural-urban differentials in the prevalence of diabetes. I have used same wording from the mvdcmp paper in the STATA journal because I don' understand it properly.
And how do I interpret E and R here? How can I interpret the coefficients in the tables below?
Looking forward for your help.
Thanks in Advance.
