I will greatly appreciate your advice.
I will like to control for family income in my analysis of trends in self-rated health between year 2000 and 2018. The NHIS data from IPUMS that I'm using has five imputed family income variables. The imputed variables are measured in intervals, rather than point estimates. For years 2000-2007, some of the intervals are $5,000 apart while others are $10,000 apart. The last category for years 2000-2007 is $75,000 and above (please see below). For the latter years, the intervals are mostly $5,000 apart and the categories extend beyond $75,000 and above, to around $115,000 and above. This means that whereas the income variables for the first several years have 11 categories, the latter years have up to 24 categories. My question is, which of the two approaches below would you recommend that I use?
I am not sure if it is okay to simply control for family income in categories in a trend analysis. Even if it is okay to control for family income in ordinal categories as in 2 above, I wonder if I will then be controlling for differences in income among respondents rather than changes in income over the years. Please help me. I am open to other suggestions.
Categories of imputed income variables for 2000-2007
Categories of imputed income variables for 2007-2018
I will like to control for family income in my analysis of trends in self-rated health between year 2000 and 2018. The NHIS data from IPUMS that I'm using has five imputed family income variables. The imputed variables are measured in intervals, rather than point estimates. For years 2000-2007, some of the intervals are $5,000 apart while others are $10,000 apart. The last category for years 2000-2007 is $75,000 and above (please see below). For the latter years, the intervals are mostly $5,000 apart and the categories extend beyond $75,000 and above, to around $115,000 and above. This means that whereas the income variables for the first several years have 11 categories, the latter years have up to 24 categories. My question is, which of the two approaches below would you recommend that I use?
- Convert the midpoint of each interval of the imputed income variables to 2018 dollars and treat the new variable as a continuous variable (of course analyzing all five datasets with the imputed five variables using mi estimate in stata)
- Measure income in few categories (e.g. <$25,000, $25,000-$44,999, $45,000-64,999, $65,000-$74,999 and $75,000 and above) that will be consistent across years (also analyzing all five datasets with the imputed variables using mi estimate in stata)
I am not sure if it is okay to simply control for family income in categories in a trend analysis. Even if it is okay to control for family income in ordinal categories as in 2 above, I wonder if I will then be controlling for differences in income among respondents rather than changes in income over the years. Please help me. I am open to other suggestions.
Categories of imputed income variables for 2000-2007
| imputed total | |||
| combined family | |||
| income (1997+ | |||
| grouping) | Freq. | Percent | Cum. |
| $0-$4,999 | 495 | 5.11 | 5.11 |
| $5,000-$9,999 | 1,013 | 10.46 | 15.58 |
| $10,000-$14,999 | 943 | 9.74 | 25.32 |
| $15,000-$19,999 | 901 | 9.31 | 34.62 |
| $20,000-$24,999 | 814 | 8.41 | 43.03 |
| $25,000-$34,999 | 1,331 | 13.75 | 56.78 |
| $35,000-$44,999 | 1,070 | 11.05 | 67.83 |
| $45,000-$54,999 | 870 | 8.99 | 76.81 |
| $55,000-$64,999 | 660 | 6.82 | 83.63 |
| $65,000-$74,999 | 489 | 5.05 | 88.68 |
| $75,000 and over | 1,096 | 11.32 | 100.00 |
| imputed total | |||
| combined family | |||
| income (1997+ | |||
| grouping) | Freq. | Percent | Cum. |
| $0-$4,999 | 184 | 1.92 | 1.92 |
| $5,000-$9,999 | 273 | 2.86 | 4.78 |
| $10,000-$14,999 | 450 | 4.71 | 9.49 |
| $15,000-$19,999 | 431 | 4.51 | 14.00 |
| $20,000-$24,999 | 553 | 5.78 | 19.78 |
| $25,000-$29,999 | 560 | 5.86 | 25.64 |
| $30,000-$34,999 | 638 | 6.67 | 32.31 |
| $35,000-$39,999 | 491 | 5.14 | 37.45 |
| $40,000-$44,999 | 567 | 5.93 | 43.38 |
| $45,000-$49,999 | 477 | 4.99 | 48.37 |
| $50,000-$54,999 | 459 | 4.80 | 53.17 |
| $55,000-$59,999 | 362 | 3.79 | 56.96 |
| $60,000-$64,999 | 445 | 4.65 | 61.61 |
| $65,000-$69,999 | 206 | 2.15 | 63.77 |
| $70,000-$74,999 | 337 | 3.53 | 67.29 |
| $75,000-$79,999 | 330 | 3.45 | 70.74 |
| $80,000-$84,999 | 304 | 3.18 | 73.92 |
| $85,000-$89,999 | 147 | 1.54 | 75.46 |
| $90,000-$94,999 | 191 | 2.00 | 77.46 |
| $95,000-$99,999 | 131 | 1.37 | 78.83 |
| $100,000-$104,999 | 314 | 3.28 | 82.11 |
| $105,000-$109,999 | 91 | 0.95 | 83.06 |
| $110,000-$114,999 | 106 | 1.11 | 84.17 |
| $115,000 and over | 1,513 | 15.83 | 100.00 |
