As a first step you may want to look at a factor analysis (Principal
components). This analysis will look at how and whether you can reduce your
5 variables into one or more variables.
Bo Cutter
----- Original Message -----
From: Seth D. Hannah <[email protected]>
To: <[email protected]>
Sent: Thursday, August 22, 2002 11:54 AM
Subject: st: creating composite measures
> Can someone help me with creating a composite measure of prejudice from
> four individual variables in my data set which measure prejudice.
> the variables are:
>
> deasyblk: perception of blacks as easy to get along with
> dwelfblk: perception of blacks as likely to be on welfare
> dintlblk: perception of blacks as intelligent
> drichblk: perception of blacks as rich or poor
>
> the variables are distributed as follows:
>
> . tab deasyblk
>
> easy to get along |
> w/blacks | Freq. Percent Cum.
> ---------------------+-----------------------------------
> easy to get along w/ | 915 10.26 10.26
> 2 | 1052 11.80 22.06
> 3 | 1379 15.47 37.53
> neither | 2722 30.53 68.06
> 5 | 1143 12.82 80.88
> 6 | 638 7.16 88.03
> hard to get along w/ | 547 6.14 94.17
> don't know... | 418 4.69 98.86
> missing | 102 1.14 100.00
> ---------------------+-----------------------------------
> Total | 8916 100.00
>
> . tab dwelfblk
>
> self-supporting: |
> blacks | Freq. Percent Cum.
> --------------------+-----------------------------------
> prefer self-support | 754 8.46 8.46
> 2 | 521 5.84 14.30
> 3 | 879 9.86 24.16
> neither | 2132 23.91 48.07
> 5 | 1723 19.32 67.40
> 6 | 1332 14.94 82.34
> prefer welfare | 1046 11.73 94.07
> don't know... | 425 4.77 98.83
> missing | 104 1.17 100.00
> --------------------+-----------------------------------
> Total | 8916 100.00
>
> . tab dintlblk
>
> intelligence: |
> blacks | Freq. Percent Cum.
> --------------+-----------------------------------
> intelligent | 723 8.11 8.11
> 2 | 807 9.05 17.16
> 3 | 1597 17.91 35.07
> neither | 3259 36.55 71.62
> 5 | 1255 14.08 85.70
> 6 | 479 5.37 91.0
> unintelligent | 207 2.32 93.39
> don't know... | 481 5.39 98.79
> missing | 108 1.21 100.00
> --------------+-----------------------------------
> Total | 8916 100.00
>
> . tab drichblk
>
> rich-poor: |
> blacks | Freq. Percent Cum.
> --------------+-----------------------------------
> rich | 59 0.66 0.66
> 2 | 193 2.16 2.83
> 3 | 499 5.60 8.42
> neither | 2101 23.56 31.99
> 5 | 2506 28.11 60.09
> 6 | 2137 23.97 84.06
> poor | 970 10.88 94.9
> don't know... | 371 4.16 99.10
> missing | 80 0.90 100.00
> --------------+-----------------------------------
> Total | 8916 100.00
>
> What I want to do is combine these four variables into one measure of
> prejudice, which will become a dependent variable in some of my models.
>
> The only way I could think to do it was to create a new variable prejblk
> with numerical values 1 through 7 that equal the sums of the respective
> 1 through 7's
> from my four variables...
>
> gen prejblk=.
> replace prejblk=1 if drichblk==1|dwelfblk==1|deasyblk==1|dintlblk==1
> replace prejblk=2 if drichblk==2|dwelfblk==2|deasyblk==2|dintlblk==2
> etc.
>
> somehow this doesn't seem right, please help!
>
> Seth
>
>
>
>
> *
> * For searches and help try:
> * http://www.stata.com/support/faqs/res/findit.html
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
