Rich
Thanks for the suggestion. Tried that on the cumulative file:
RANK variables = rearn /ntiles (4) into xrearnq .
CRO year by newrearnq.
Year of Interview * Percentile Group of REarn Crosstabulation | ||||||
% within Year of Interview | ||||||
Percentile Group of REarn | Total | |||||
1 | 2 | 3 | 4 | |||
Year of Interview | 1983 | 55.9% | 31.1% | 13.0% | 100.0% | |
1984 | 52.0% | 30.7% | 17.3% | 100.0% | ||
1985 | 47.8% | 30.9% | 21.3% | 100.0% | ||
1986 | 43.8% | 28.5% | 21.9% | 5.8% | 100.0% | |
1987 | 39.1% | 28.9% | 25.5% | 6.5% | 100.0% | |
1989 | 30.0% | 26.9% | 30.6% | 12.5% | 100.0% | |
1990 | 25.8% | 24.4% | 34.0% | 15.8% | 100.0% | |
1991 | 24.9% | 22.4% | 34.2% | 18.5% | 100.0% | |
1993 | 19.7% | 21.2% | 37.1% | 21.9% | 100.0% | |
1994 | 18.0% | 18.9% | 35.7% | 27.4% | 100.0% | |
1995 | 16.4% | 18.4% | 36.2% | 29.0% | 100.0% | |
1996 | 16.2% | 17.8% | 34.1% | 32.0% | 100.0% | |
1997 | 17.7% | 15.2% | 34.1% | 32.9% | 100.0% | |
1998 | 18.1% | 16.6% | 31.1% | 34.3% | 100.0% | |
1999 | 14.0% | 16.3% | 33.0% | 36.7% | 100.0% | |
2000 | 14.6% | 12.6% | 32.2% | 40.6% | 100.0% | |
2001 | 11.6% | 12.2% | 30.2% | 45.9% | 100.0% | |
2002 | 28.9% | 26.7% | 22.0% | 22.3% | 100.0% | |
2003 | 28.9% | 27.8% | 21.7% | 21.5% | 100.0% | |
2004 | 28.1% | 25.9% | 21.6% | 24.4% | 100.0% | |
2005 | 27.0% | 28.1% | 20.8% | 24.2% | 100.0% | |
2006 | 23.3% | 25.1% | 23.4% | 28.2% | 100.0% | |
2007 | 25.1% | 24.7% | 22.0% | 28.2% | 100.0% | |
2008 | 22.6% | 23.2% | 22.9% | 31.3% | 100.0% | |
2009 | 23.4% | 24.5% | 22.6% | 29.5% | 100.0% | |
2010 | 24.4% | 17.4% | 17.6% | 40.6% | 100.0% | |
2015 | 20.5% | 13.7% | 16.0% | 49.8% | 100.0% | |
Total | 25.3% | 22.4% | 26.1% | 26.2% | 100.0% | |
It's done the same for all years. Got round that with:
SPLIT FILE by year.
RANK variables = rearn /ntiles (4) into newrearnq .
SPLIT FILE off.
CRO year by newrearnq /cel row.
Year of Interview * Percentile Group of REarn Crosstabulation | ||||||
% within Year of Interview | ||||||
Percentile Group of REarn | Total | |||||
1 | 2 | 3 | 4 | |||
Year of Interview | 1983 | 21.1% | 34.7% | 20.1% | 24.1% | 100.0% |
1984 | 26.1% | 25.9% | 19.8% | 28.2% | 100.0% | |
1985 | 26.8% | 21.0% | 30.9% | 21.3% | 100.0% | |
1986 | 24.4% | 27.5% | 20.3% | 27.8% | 100.0% | |
1987 | 29.3% | 20.1% | 29.3% | 21.3% | 100.0% | |
1989 | 22.6% | 22.6% | 35.1% | 19.6% | 100.0% | |
1990 | 25.8% | 24.4% | 24.3% | 25.5% | 100.0% | |
1991 | 24.9% | 22.4% | 24.3% | 28.3% | 100.0% | |
1993 | 29.6% | 23.9% | 24.6% | 21.9% | 100.0% | |
1994 | 27.2% | 21.0% | 24.4% | 27.4% | 100.0% | |
1995 | 25.8% | 20.5% | 31.0% | 22.6% | 100.0% | |
1996 | 25.2% | 19.3% | 29.7% | 25.8% | 100.0% | |
1997 | 26.0% | 18.9% | 29.3% | 25.8% | 100.0% | |
1998 | 26.1% | 29.6% | 16.5% | 27.8% | 100.0% | |
1999 | 22.3% | 30.0% | 24.0% | 23.8% | 100.0% | |
2000 | 27.2% | 22.6% | 22.9% | 27.3% | 100.0% | |
2001 | 23.8% | 30.2% | 21.8% | 24.1% | 100.0% | |
2002 | 21.2% | 29.0% | 27.5% | 22.3% | 100.0% | |
2003 | 28.9% | 21.2% | 23.0% | 26.9% | 100.0% | |
2004 | 28.1% | 19.8% | 27.7% | 24.4% | 100.0% | |
2005 | 27.0% | 21.7% | 27.2% | 24.2% | 100.0% | |
2006 | 23.3% | 25.1% | 28.8% | 22.8% | 100.0% | |
2007 | 25.1% | 24.7% | 27.1% | 23.1% | 100.0% | |
2008 | 22.6% | 23.2% | 28.3% | 25.9% | 100.0% | |
2009 | 23.4% | 24.5% | 27.6% | 24.5% | 100.0% | |
2010 | 24.4% | 22.9% | 27.2% | 25.6% | 100.0% | |
2015 | 25.2% | 25.1% | 26.7% | 23.1% | 100.0% | |
Total | 25.3% | 24.0% | 26.1% | 24.6% | 100.0% | |
Quartile points calculated within years. Exactly what I wanted. Just got to slot in existing [rearnq] for years 2011 – 2014.
Year of Interview * Respondent earnings quartiles (dv) Crosstabulation | ||||||
% within Year of Interview | ||||||
Respondent earnings quartiles (dv) | Total | |||||
Q1 | Q2 | Q3 | Q4 | |||
Year of Interview | 2008 | 22.6% | 23.2% | 28.3% | 25.9% | 100.0% |
2009 | 23.4% | 24.5% | 27.6% | 24.5% | 100.0% | |
2010 | 24.4% | 30.3% | 25.4% | 19.9% | 100.0% | |
2011 | 25.0% | 28.6% | 24.9% | 21.5% | 100.0% | |
2012 | 26.7% | 26.6% | 24.5% | 22.2% | 100.0% | |
2013 | 25.3% | 28.4% | 22.4% | 23.9% | 100.0% | |
2014 | 22.6% | 27.8% | 24.7% | 25.0% | 100.0% | |
2015 | 22.5% | 26.6% | 26.0% | 25.0% | 100.0% | |
Total | 23.9% | 26.7% | 25.7% | 23.7% | 100.0% | |
*Check.
CRO rearnq by newrearnq.
Respondent earnings quartiles (dv) * Percentile Group of REarn Crosstabulation | ||||||
Count | ||||||
Percentile Group of REarn | Total | |||||
Q1 | Q2 | Q3 | Q4 | |||
Respondent earnings quartiles (dv) | Q1 | 1697 | 0 | 0 | 0 | 1697 |
Q2 | 102 | 1688 | 110 | 0 | 1900 | |
Q3 | 0 | 119 | 1776 | 83 | 1978 | |
Q4 | 0 | 0 | 183 | 1590 | 1773 | |
Total | 1799 | 1807 | 2069 | 1673 | 7348 | |
CORR rearnq xrearnq newrearnq.
Correlations | ||||
Respondent earnings quartiles (dv) | Percentile Group of REarn | Percentile Group of REarn | ||
Respondent earnings quartiles (dv) | Pearson Correlation | 1 | 0.946 | 0.966 |
Sig. (2-tailed) | 0.000 | 0.000 | ||
N | 12975 | 7348 | 7348 | |
Percentile Group of REarn | Pearson Correlation | 0.946 | 1 | 0.889 |
Sig. (2-tailed) | 0.000 | 0.000 | ||
N | 7348 | 42208 | 42208 | |
Percentile Group of REarn | Pearson Correlation | 0.966 | 0.889 | 1 |
Sig. (2-tailed) | 0.000 | 0.000 | ||
N | 7348 | 42208 | 42208 | |
John F Hall MA (Cantab) Dip Ed (Dunelm)
[Retired academic survey researcher]
Email: [hidden email]
Website: Journeys in Survey Research
Course: Survey Analysis Workshop (SPSS)
From: SPSSX(r) Discussion <[hidden email]> On Behalf Of Rich Ulrich
Sent: 13 October 2018 19:40
To: [hidden email]
Subject: Re: Estimating actual earnings from earnings groups
Can't you use RANK and its options to get quartiles by year,
regardless of the units for that year?
--
Rich Ulrich
From: SPSSX(r) Discussion <[hidden email]> on behalf of John F Hall <[hidden email]>
Sent: Saturday, October 13, 2018 4:18 AM
To: [hidden email]
Subject: Estimating actual earnings from earnings groups
I have a variable "Gross earnings from paid work" coded in 11 to 20 groups for each year in which it is used. The coding scheme used was changed twice, so the earnings intervals are not the same for each year.
In some years the variable [REarn] is not used: [REarnQ] "Earnings quartile group" is used instead. For years when [REarnQ] is not calculated I can get an approximation by recoding [REarn] ~ ~ INTO [REarnQ] but I'd like to estimate a mean/median for actual gross earnings for each category of [REarn] by something like:
DO IF (year = 1983) .
RECODE (<value(s)> = 1) (<value(s)> = 2) etc (else = copy)
INTO newrearn.
ELSE IF (year = 1984) etc.
~ ~ ~
ELSE IF (year = 2015)
~ ~ ~
END IF.
However, I would like to take account of the distribution of earnings for each year. For the centre of the distribution I can take a mid-point, but what should I do about the intervals further away from the centre, especially the outer ends "Under £x" and "£x or more"?
Oh, and variable [year] is not present for every year, so that has had to be inserted manually.
Sorry if there's too much detail below, but it gives a clearer idea of the problem.
Thanks in advance for any suggestions.
John F Hall MA (Cantab) Dip Ed (Dunelm)
[Retired academic survey researcher]
Email: [hidden email]
Website: Journeys in Survey Research
Course: Survey Analysis Workshop (SPSS)
Research: Subjective Social Indicators (Quality of Life)
Value | 1983 |
0 | SKIPPED |
1 | < 2000 POUNDS |
2 | 2000-2999 POUNDS |
3 | 3000-3999 POUNDS |
4 | 4000-4999 POUNDS |
5 | 5000-5999 POUNDS |
6 | 6000-6999 POUNDS |
7 | 7000-7999 POUNDS |
8 | 8000-9999 POUNDS |
9 | 10000-11999 POUNDS |
10 | 12000-14999 POUNDS |
11 | 15000+ POUNDS |
12 | ~ ~ ~ ~ |
13 | ~ ~ ~ ~ |
98 | DK |
99 | NA |
[NB: No £ sign in 1983]
Value | 1996 |
| ~New letter codes introduced~ |
-1 | Skp,not 10+hr employed |
0 | ~Dropped ~ |
1 | ~Dropped ~ |
2 | ~Dropped ~ |
3 | Q ls thn 3999 |
4 | ~Dropped ~ |
5 | T 4000- 5999 |
6 | ~Dropped ~ |
7 | O 6000- 7999 |
8 | K 8000- 9999 |
9 | L 10000- 11999 |
10 | B 12000- 14999 |
11 | Z 15000- 17999 |
12 | M 18000- 19999 |
13 | F 20000- 22999 |
14 | J 23000- 25999 |
15 | D 26000- 28999 |
16 | H 29000- 31999 |
17 | C 32000- 34999 |
18 | G 35000- 37999 |
19 | P 38000- 40999 |
20 | N 41000 or more |
21 | ~ ~ ~ ~ |
98 | Don't know |
99 | Not answered |
Value | 2002 |
-1 | Skp,not paid work |
1 | Q ls thn 3999 |
2 | T 4000- 5999 |
3 | O 6000- 7999 |
4 | K 8000- 9999 |
5 | L 10000- 11999 |
6 | B 12000- 14999 |
7 | Z 15000- 17999 |
8 | M 18000- 19999 |
9 | F 20000- 22999 |
10 | J 23000- 25999 |
11 | D 26000- 28999 |
12 | H 29000- 31999 |
13 | A 32000- 37999 |
14 | W 38000- 43999 |
15 | G 44000- 49999 |
16 | N 50000- 55999 |
17 | E 56000 or more |
97 | Refused information |
98 | Don't know |
99 | Not answered |
| |
Value | 2006 |
Code letters dropped | |
-1 | Not work/wait work |
1 | ls thn 4000 |
2 | 4000- 5999 |
3 | 6000- 7999 |
4 | 8000- 9999 |
5 | 10000- 11999 |
6 | 12000- 14999 |
7 | 15000- 17999 |
8 | 18000- 19999 |
9 | 20000- 22999 |
10 | 23000- 25999 |
11 | 26000- 28999 |
12 | 29000- 31999 |
13 | 32000- 37999 |
14 | 38000- 43999 |
15 | 44000- 49999 |
16 | 50000- 55999 |
17 | 56000 or more |
| |
97 | Refused information |
98 | Don't know |
99 | Not answered |
| 2009-2010 |
Value | Coding changed to ££ per month |
| |
-1 | Skp,not paid work |
1 | Less than £270 p.m |
2 | £271 - 430 p.m |
3 | £431 - 590 p.m |
4 | £591 - 780 p.m |
5 | £781 - 930 p.m |
6 | £931 - 1,100 p.m |
7 | £1,101 - 1,200 p.m |
8 | £1,201 - 1,300 p.m |
9 | £1,301 - 1,400 p.m |
10 | £1,401 - 1,600 p.m |
11 | £1,601 - 1,700 p.m |
12 | £1,701 - 1,800 p.m |
13 | £1,801 - 2,000 p.m |
14 | £2,001 - 2,200 p.m |
15 | £2,201 - 2,500 p.m |
16 | £2,501 - 2,700 p.m |
17 | £2,701 - 3,100 p.m |
| £3,101 - 3,600 p.m |
| £3,601 - 4,900 p.m |
| £4,901 or more p.m |
97 | |
98 | Refused information |
99 | Don't know |
| ~ ~ ~ ~ |
2011-2014 |
Gross earnings not used |
Quartiles only |
Value | 2015 |
| |
-2 | Schedule not applicable |
-1 | Item not applicable |
1 | £271 - 430 pcm |
2 | £431 - 590 pcm |
3 | £591 - 780 pcm |
4 | £781 - 930 pcm |
5 | £931 - 1,100 pcm |
6 | £1,101 - 1,200 pcm |
7 | £1,201 - 1,300 pcm |
8 | £1,301 - 1,400 pcm |
9 | £1,401 - 1,600 pcm |
10 | £1,601 - 1,700 pcm |
11 | £1,701 - 1,800 pcm |
12 | £1,801 - 2,000 pcm |
13 | £2,001 - 2,200 pcm |
14 | £2,201 - 2,500 pcm |
15 | £2,501 - 2,700 pcm |
16 | £2,701 - 3,100 pcm |
17 | £3,101 - 3,600 pcm |
18 | £3,601 - 4,900 pcm |
19 | £4,901 or more pcm |
| |
97 | Refused information |
98 | (Don't know) |
99 | (Refusal) |
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