Collecting together as many as possible MRV participants with any examination data yields N = 2888.
Roughly equal numbers of participants have less than HS, HS, or greater than HS educational attainment:
Educ3
<HS HS >HS
952 942 919
There is a strong association between poverty status and educational attainment:
Cell Contents
|-------------------------|
| N |
| Chi-square contribution |
| N / Row Total |
| N / Col Total |
| N / Table Total |
|-------------------------|
Total Observations in Table: 2813
| PovStat
Educ3 | Above | Below | Row Total |
-------------|-----------|-----------|-----------|
<HS | 418 | 534 | 952 |
| 30.522 | 41.266 | |
| 0.439 | 0.561 | 0.338 |
| 0.259 | 0.446 | |
| 0.149 | 0.190 | |
-------------|-----------|-----------|-----------|
HS | 541 | 401 | 942 |
| 0.000 | 0.001 | |
| 0.574 | 0.426 | 0.335 |
| 0.335 | 0.335 | |
| 0.192 | 0.143 | |
-------------|-----------|-----------|-----------|
>HS | 658 | 261 | 919 |
| 31.859 | 43.073 | |
| 0.716 | 0.284 | 0.327 |
| 0.407 | 0.218 | |
| 0.234 | 0.093 | |
-------------|-----------|-----------|-----------|
Column Total | 1617 | 1196 | 2813 |
| 0.575 | 0.425 | |
-------------|-----------|-----------|-----------|
Statistics for All Table Factors
Pearson's Chi-squared test
------------------------------------------------------------
Chi^2 = 146.7203302 d.f. = 2 p = 1.380654781e-32
There is also a strong relationship between literacy and educational attainment and literacy and poverty status:
Cell Contents
|-------------------------|
| N |
| Chi-square contribution |
| N / Row Total |
| N / Col Total |
| N / Table Total |
|-------------------------|
Total Observations in Table: 2538
| WRAT3
Educ3 | <9th grade | 9-12 grade | >HS | Row Total |
-------------|------------|------------|------------|------------|
<HS | 503 | 211 | 121 | 835 |
| 101.140 | 0.490 | 99.449 | |
| 0.602 | 0.253 | 0.145 | 0.329 |
| 0.513 | 0.314 | 0.137 | |
| 0.198 | 0.083 | 0.048 | |
-------------|------------|------------|------------|------------|
HS | 326 | 239 | 280 | 845 |
| 0.000 | 0.995 | 0.729 | |
| 0.386 | 0.283 | 0.331 | 0.333 |
| 0.333 | 0.355 | 0.316 | |
| 0.128 | 0.094 | 0.110 | |
-------------|------------|------------|------------|------------|
>HS | 151 | 223 | 484 | 858 |
| 98.123 | 0.090 | 114.166 | |
| 0.176 | 0.260 | 0.564 | 0.338 |
| 0.154 | 0.331 | 0.547 | |
| 0.059 | 0.088 | 0.191 | |
-------------|------------|------------|------------|------------|
Column Total | 980 | 673 | 885 | 2538 |
| 0.386 | 0.265 | 0.349 | |
-------------|------------|------------|------------|------------|
Statistics for All Table Factors
Pearson's Chi-squared test
------------------------------------------------------------
Chi^2 = 415.1813069 d.f. = 4 p = 1.458208298e-88
Cell Contents
|-------------------------|
| N |
| Chi-square contribution |
| N / Row Total |
| N / Col Total |
| N / Table Total |
|-------------------------|
Total Observations in Table: 2607
| WRAT3
PovStat | <9th grade | 9-12 grade | >HS | Row Total |
-------------|------------|------------|------------|------------|
Above | 472 | 411 | 654 | 1537 |
| 23.233 | 0.088 | 22.695 | |
| 0.307 | 0.267 | 0.426 | 0.590 |
| 0.472 | 0.598 | 0.710 | |
| 0.181 | 0.158 | 0.251 | |
-------------|------------|------------|------------|------------|
Below | 527 | 276 | 267 | 1070 |
| 33.373 | 0.126 | 32.600 | |
| 0.493 | 0.258 | 0.250 | 0.410 |
| 0.528 | 0.402 | 0.290 | |
| 0.202 | 0.106 | 0.102 | |
-------------|------------|------------|------------|------------|
Column Total | 999 | 687 | 921 | 2607 |
| 0.383 | 0.264 | 0.353 | |
-------------|------------|------------|------------|------------|
Statistics for All Table Factors
Pearson's Chi-squared test
------------------------------------------------------------
Chi^2 = 112.1144931 d.f. = 2 p = 4.514889733e-25
Educational attainment and literacy are also associated with race. The association of race with education is weaker than the association of poverty status with education, but there is a strong relationship between race and literacy status:
Cell Contents
|-------------------------|
| N |
| Chi-square contribution |
| N / Row Total |
| N / Col Total |
| N / Table Total |
|-------------------------|
Total Observations in Table: 2813
| Educ3
Race | <HS | HS | >HS | Row Total |
-------------|-----------|-----------|-----------|-----------|
White | 371 | 336 | 400 | 1107 |
| 0.035 | 3.249 | 4.066 | |
| 0.335 | 0.304 | 0.361 | 0.394 |
| 0.390 | 0.357 | 0.435 | |
| 0.132 | 0.119 | 0.142 | |
-------------|-----------|-----------|-----------|-----------|
AfrAm | 581 | 606 | 519 | 1706 |
| 0.023 | 2.108 | 2.638 | |
| 0.341 | 0.355 | 0.304 | 0.606 |
| 0.610 | 0.643 | 0.565 | |
| 0.207 | 0.215 | 0.185 | |
-------------|-----------|-----------|-----------|-----------|
Column Total | 952 | 942 | 919 | 2813 |
| 0.338 | 0.335 | 0.327 | |
-------------|-----------|-----------|-----------|-----------|
Statistics for All Table Factors
Pearson's Chi-squared test
------------------------------------------------------------
Chi^2 = 12.1197421 d.f. = 2 p = 0.002334701929
Cell Contents
|-------------------------|
| N |
| Chi-square contribution |
| N / Row Total |
| N / Col Total |
| N / Table Total |
|-------------------------|
Total Observations in Table: 2607
| WRAT3
Race | <9th grade | 9-12 grade | >HS | Row Total |
-------------|------------|------------|------------|------------|
White | 286 | 243 | 573 | 1102 |
| 43.984 | 7.737 | 86.666 | |
| 0.260 | 0.221 | 0.520 | 0.423 |
| 0.286 | 0.354 | 0.622 | |
| 0.110 | 0.093 | 0.220 | |
-------------|------------|------------|------------|------------|
AfrAm | 713 | 444 | 348 | 1505 |
| 32.206 | 5.665 | 63.459 | |
| 0.474 | 0.295 | 0.231 | 0.577 |
| 0.714 | 0.646 | 0.378 | |
| 0.273 | 0.170 | 0.133 | |
-------------|------------|------------|------------|------------|
Column Total | 999 | 687 | 921 | 2607 |
| 0.383 | 0.264 | 0.353 | |
-------------|------------|------------|------------|------------|
Statistics for All Table Factors
Pearson's Chi-squared test
------------------------------------------------------------
Chi^2 = 239.717857 d.f. = 2 p = 8.829350117e-53
There are sex differences in educational attainment, but no sex differences in the distribution of literacy status.
Cell Contents
|-------------------------|
| N |
| Chi-square contribution |
| N / Row Total |
| N / Col Total |
| N / Table Total |
|-------------------------|
Total Observations in Table: 2813
| Educ3
Sex | <HS | HS | >HS | Row Total |
-------------|-----------|-----------|-----------|-----------|
Women | 509 | 522 | 544 | 1575 |
| 1.083 | 0.056 | 1.686 | |
| 0.323 | 0.331 | 0.345 | 0.560 |
| 0.535 | 0.554 | 0.592 | |
| 0.181 | 0.186 | 0.193 | |
-------------|-----------|-----------|-----------|-----------|
Men | 443 | 420 | 375 | 1238 |
| 1.378 | 0.071 | 2.145 | |
| 0.358 | 0.339 | 0.303 | 0.440 |
| 0.465 | 0.446 | 0.408 | |
| 0.157 | 0.149 | 0.133 | |
-------------|-----------|-----------|-----------|-----------|
Column Total | 952 | 942 | 919 | 2813 |
| 0.338 | 0.335 | 0.327 | |
-------------|-----------|-----------|-----------|-----------|
Statistics for All Table Factors
Pearson's Chi-squared test
------------------------------------------------------------
Chi^2 = 6.417760157 d.f. = 2 p = 0.04040183483
Cell Contents
|-------------------------|
| N |
| Chi-square contribution |
| N / Row Total |
| N / Col Total |
| N / Table Total |
|-------------------------|
Total Observations in Table: 2607
| WRAT3
Sex | <9th grade | 9-12 grade | >HS | Row Total |
-------------|------------|------------|------------|------------|
Women | 556 | 414 | 505 | 1475 |
| 0.150 | 1.648 | 0.497 | |
| 0.377 | 0.281 | 0.342 | 0.566 |
| 0.557 | 0.603 | 0.548 | |
| 0.213 | 0.159 | 0.194 | |
-------------|------------|------------|------------|------------|
Men | 443 | 273 | 416 | 1132 |
| 0.196 | 2.147 | 0.647 | |
| 0.391 | 0.241 | 0.367 | 0.434 |
| 0.443 | 0.397 | 0.452 | |
| 0.170 | 0.105 | 0.160 | |
-------------|------------|------------|------------|------------|
Column Total | 999 | 687 | 921 | 2607 |
| 0.383 | 0.264 | 0.353 | |
-------------|------------|------------|------------|------------|
Statistics for All Table Factors
Pearson's Chi-squared test
------------------------------------------------------------
Chi^2 = 5.284439682 d.f. = 2 p = 0.07120303459
It's clear that poverty status, race, educational attainment, literacy status, and sex are associated. Using poverty status as our usual measure of socioeconomic status, we can ask the extent to which race, educational attainment, literacy status, and sex (and their interactions) are associated with poverty status. Fortunately, none of the higher order interactions were significant so we need examine only main effects. For the sake of greater complexity, I added age (median split) in a second analysis (in which there was one [likely] spurious 3-way interaction that I ignored).
| Coeff | SE | z | p | OR | CIlo | CIup | ||
|---|---|---|---|---|---|---|---|---|
| (Intercept) | 0.17 | 0.11 | 1.56 | 0.12 | 1.18 | 0.96 | 1.45 | |
| RaceAfrAm | 0.58 | 0.09 | 6.33 | 0.00 | 1.78 | 1.49 | 2.13 | *** |
| Educ3HS | -0.54 | 0.10 | -5.26 | 0.00 | 0.58 | 0.48 | 0.71 | *** |
| Educ3>HS | -1.07 | 0.11 | -9.41 | 0.00 | 0.34 | 0.27 | 0.43 | *** |
| WRAT39-12 grade | -0.29 | 0.11 | -2.74 | 0.01 | 0.75 | 0.61 | 0.92 | ** |
| WRAT3>HS | -0.44 | 0.11 | -3.96 | 0.00 | 0.64 | 0.52 | 0.80 | *** |
| SexMen | -0.28 | 0.09 | -3.26 | 0.00 | 0.76 | 0.64 | 0.89 | ** |
| Coeff | SE | z | p | OR | CIlo | CIup | ||
|---|---|---|---|---|---|---|---|---|
| (Intercept) | 0.30 | 0.12 | 2.58 | 0.01 | 1.35 | 1.07 | 1.69 | * |
| RaceAfrAm | 0.57 | 0.09 | 6.23 | 0.00 | 1.77 | 1.48 | 2.11 | *** |
| Educ3HS | -0.55 | 0.10 | -5.34 | 0.00 | 0.58 | 0.47 | 0.70 | *** |
| Educ3>HS | -1.06 | 0.11 | -9.31 | 0.00 | 0.34 | 0.28 | 0.43 | *** |
| WRAT39-12 grade | -0.29 | 0.11 | -2.74 | 0.01 | 0.75 | 0.61 | 0.92 | ** |
| WRAT3>HS | -0.46 | 0.11 | -4.10 | 0.00 | 0.63 | 0.51 | 0.79 | *** |
| SexMen | -0.27 | 0.09 | -3.18 | 0.00 | 0.76 | 0.64 | 0.90 | ** |
| Age0medAbove | -0.25 | 0.08 | -2.89 | 0.00 | 0.78 | 0.66 | 0.92 | ** |
So what to make of all of this (and analyses to be done including household income)?
It's apparent that the demographic and literacy indicators are associated with poverty status. It also appears that the distribution of participants in these demographic categories will always include the influence of some hidden measure(s). For example, poverty status and education are both associated with race. This means that a composite of the two may act (at least partially) as a proxy for race differences. It also means that the composite may act as a composite for literacy status.