Hi all,
I want to make a comparison between two different variables across waves, indicators of dissatisfaction,
Usually I would simply code this as:
But, here's the rub. Measure 1 is a standard measure, higher numbers equal higher levels of dissatisfaction, meanwhile Measure 2 is awkward, a score of 7-20 is low satisfaction, 20-27 is moderate satisfaction, and 28-35 is high satisfaction.
Thus I'm not sure what to do with Measure 2, sure I can do the above and run a continous regression, but if I get a positive result of 0.06*** then what does that mean? If they both moved in the same direction I would say the probability of poor satisfaction increased by 0.06 standard deviations, significant at the *** level, however, the second is such that it could be better or worse if individuals score increases, i..e. their dissatisfaction may be increasing past the low satisfaction and into the high satisfaction...
I tried reverse coding measure 2 but that didn't work well as you can see below:
I'm not even sure that reversing this would actually do much to fix this problem.
Similarly, I include descriptives on the first var below to make things a bit clearer:
I would be grateful if someone could please advise?
Very best,
John
I want to make a comparison between two different variables across waves, indicators of dissatisfaction,
Usually I would simply code this as:
Code:
egen dissatisfaction_wave1=std(dissatisfactionmeas1) , mean(0) std(1) egen dissatisfaction_wave2=std(dissatisfactionmeas2) , mean(0) std(1)
Thus I'm not sure what to do with Measure 2, sure I can do the above and run a continous regression, but if I get a positive result of 0.06*** then what does that mean? If they both moved in the same direction I would say the probability of poor satisfaction increased by 0.06 standard deviations, significant at the *** level, however, the second is such that it could be better or worse if individuals score increases, i..e. their dissatisfaction may be increasing past the low satisfaction and into the high satisfaction...
I tried reverse coding measure 2 but that didn't work well as you can see below:
Code:
revv dissatisfactionwave2 . tab dissatisfactionwave2 Warwick-Edi | nburgh | Scale | Post-Transf | ormation | Freq. Percent Cum. ------------+----------------------------------- 16.36 | 3 0.66 0.66 16.88 | 1 0.22 0.88 17.43 | 3 0.66 1.54 17.98 | 5 1.10 2.64 19.25 | 19 4.19 6.83 19.98 | 11 2.42 9.25 20.73 | 22 4.85 14.10 21.54 | 36 7.93 22.03 22.35 | 30 6.61 28.63 23.21 | 34 7.49 36.12 24.11 | 60 13.22 49.34 25.03 | 66 14.54 63.88 26.02 | 41 9.03 72.91 27.03 | 30 6.61 79.52 28.13 | 23 5.07 84.58 29.31 | 20 4.41 88.99 30.7 | 24 5.29 94.27 32.55 | 8 1.76 96.04 35 | 18 3.96 100.00 ------------+----------------------------------- Total | 454 100.00 . tab rvdissatisfactionwave2 Warwick-Edi | nburgh | Scale | Post-Transf | ormation | Freq. Percent Cum. ------------+----------------------------------- 16.36 | 18 3.96 3.96 16.88 | 8 1.76 5.73 17.43 | 24 5.29 11.01 17.98 | 20 4.41 15.42 19.25 | 23 5.07 20.48 19.98 | 30 6.61 27.09 20.73 | 41 9.03 36.12 21.54 | 66 14.54 50.66 22.35 | 60 13.22 63.88 23.21 | 34 7.49 71.37 24.11 | 30 6.61 77.97 25.03 | 36 7.93 85.90 26.02 | 22 4.85 90.75 27.03 | 11 2.42 93.17 28.13 | 19 4.19 97.36 29.31 | 5 1.10 98.46 30.7 | 3 0.66 99.12 32.55 | 1 0.22 99.34 35 | 3 0.66 100.00 ------------+----------------------------------- Total | 454 100.00 .
Similarly, I include descriptives on the first var below to make things a bit clearer:
Code:
. tab dissatisfactionwave1 GHQ Score A | Freq. Percent Cum. ------------+----------------------------------- 0 | 470 44.63 44.63 1 | 207 19.66 64.29 2 | 105 9.97 74.26 3 | 54 5.13 79.39 4 | 60 5.70 85.09 5 | 35 3.32 88.41 6 | 33 3.13 91.55 7 | 24 2.28 93.83 8 | 24 2.28 96.11 9 | 11 1.04 97.15 10 | 12 1.14 98.29 11 | 9 0.85 99.15 12 | 9 0.85 100.00 ------------+----------------------------------- Total | 1,053 100.00
I would be grateful if someone could please advise?
Very best,
John
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