(2014-Oct-10, 02:11:07)Chuck Wrote: What were the gaps for each age group in the first and last survey year?

Cohort or survey year ? I thought you would need cohort as well ?

I don't know how you want me to calculate the age gap. By way of correlation ?

The numbers are displayed below, for survey year categories. I also display the SD of wordsum and age for black and white groups separately, you see that the SD of the two variables declines over time. This means that the increase in age gap by survey year is under-estimated. Still, I think the increase in the age gap is clearly big. (the correlations are computed for the entire group, I did not separate blacks and whites)

correlate wordsum age [aweight = weight] if year4==1

r=0.0684

sd of wordsum

2.01 (for blacks) 2.12 (for whites)

sd of age

14.62 (for blacks) 14.61 (for whites)

correlate wordsum age [aweight = weight] if year4==2

r=0.0934

sd of wordsum

1.95 (for blacks) 2.09 (for whites)

sd of age

14.51 (for blacks) 14.12 (for whites)

correlate wordsum age [aweight = weight] if year4==3

r=0.1174

sd of wordsum

1.86 (for blacks) 2.02 (for whites)

sd of age

12.81 (for blacks) 13.29 (for whites)

correlate wordsum age [aweight = weight] if year4==4

r=0.1541

sd of wordsum

1.87 (for blacks) 1.84 (for whites)

sd of age

13.52 (for blacks) 13.80 (for whites)

The numbers below are the correlations for blacks, and whites separately.

correlate wordsum age [aweight = weight] if year4==1 & bw1==0

correlate wordsum age [aweight = weight] if year4==2 & bw1==0

correlate wordsum age [aweight = weight] if year4==3 & bw1==0

correlate wordsum age [aweight = weight] if year4==4 & bw1==0

-0.0480

0.0298

-0.0592

0.0059

correlate wordsum age [aweight = weight] if year4==1 & bw1==1

correlate wordsum age [aweight = weight] if year4==2 & bw1==1

correlate wordsum age [aweight = weight] if year4==3 & bw1==1

correlate wordsum age [aweight = weight] if year4==4 & bw1==1

0.0706

0.0897

0.1318

0.1258

No increase in age gap among blacks but a large one for whites.

Now, if you want the results by way of regression, the unstandardized coefficients are shown below, again for each category of survey year. For blacks first, and for whites next.

tobit wordsum age if year4==1 & bw1==0 [pweight = weight], ll ul

tobit wordsum age if year4==2 & bw1==0 [pweight = weight], ll ul

tobit wordsum age if year4==3 & bw1==0 [pweight = weight], ll ul

tobit wordsum age if year4==4 & bw1==0 [pweight = weight], ll ul

-.0070517

.0041364

-.0091082

.0007717

tobit wordsum age if year4==1 & bw1==1 [pweight = weight], ll ul

tobit wordsum age if year4==2 & bw1==1 [pweight = weight], ll ul

tobit wordsum age if year4==3 & bw1==1 [pweight = weight], ll ul

tobit wordsum age if year4==4 & bw1==1 [pweight = weight], ll ul

.0113877

.0145335

.0220242

.0179635

There is no tendency for age gap to increase in blacks. But the tendency is visible for whites. Remember that the unstandardized coeff is the effect of one-unit change in age var on the wordsum. To obtain a gap between, say, 18 and 68-yrs-old, you must do 0.0179*50=0.895, i.e., a difference of almost one word correct. The age gap for the first category of survey year is 0.01138*50=0.569. The difference is 0.33 word correct, which is more or less the same amount of the gap narrowing in black-white when you look at survey year which is about 0.30.

So, what do you think ?

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By the way, I have detected a silly mistake in my syntax. All analyses are weighted, indeed. Except my correlation of wordsum with age. Initially, I reported it to be 0.1005. But the weighted correlation is 0.1085. So, I made this modification (in the appendix and in the text) in my latest version.

This mistake is due to the fact I'm not very used to Stata, even though I know the commands well. In SPSS, when you use option weight, all of your subsequent analyses are weighted, unless you decide to unable weight option. In Stata however, each analysis must be weighted individually (or not). So that's a big difference.