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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 > > > > > * > * 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/

**Follow-Ups**:**st: RE: Re: creating composite measures***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**References**:**st: creating composite measures***From:*"Seth D. Hannah" <hannah@fas.harvard.edu>

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