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st: Re: creating composite measures


From   "Bo Cutter" <wcutter@ucla.edu>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: Re: creating composite measures
Date   Thu, 22 Aug 2002 13:25:41 -0700

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 <hannah@fas.harvard.edu>
To: <statalist@hsphsun2.harvard.edu>
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
>
>
>
>
> *
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*
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