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From |
"Wendell Joice" <wjoice@erols.com> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: Re: RE: Re: RE: one-sample chi square test |

Date |
Sat, 1 Feb 2003 14:53:14 -0500 |

Nick, Thanks so much for your advice. Your second (sequel) approach mentioned at the bottom of this message works fine. For folks like me, this assistance is a KEY reason why I chose and stick with Stata. My attempts to use your first approach, immediately below, yielded an error message as you can see. chitest rep78, count count invalid r(198); But I have been successful using your second approach; it took me a while since this is my first experience with macros and multi-step commands like -forvalues-. But this was bonus learning for me. As you suggested, I added a couple of things and now have a do file [listed below] (with arguments) that has been working fine, especially since I have no data with '0' observed values. DO FILE .do chitest SEX "& racewbh==3 & csample==1" .forval i = 0/5 { 2. qui count if `1'== `i' `2' 3. if r(N)==0 { 4. continue 5. } 6. local counts "`counts' `r(N)'" 7. } . di "`counts' 950 767 . chitesti `counts' Chi-square test: observed frequencies from keyboard expected frequencies equal Pearson chi2(1) = 19.5044 Pr = 0.000 likelihood-ratio chi2(1) = 19.5415 Pr = 0.000 residuals observed expected classic Pearson 1. 950 858.500 91.500 3.123 2. 767 858.500 -91.500 -3.123 . macro drop _counts . end of do-file ----- Original Message ----- From: "Nick Cox" <n.j.cox@durham.ac.uk> To: <statalist@hsphsun2.harvard.edu> Sent: Thursday, January 30, 2003 5:31 AM Subject: st: RE: Re: RE: one-sample chi square test > Wendell Joice > > > -chitesti- works fine; I need to tabulate the variables of > > interest and then key in the frequencies to -chitesti-. > > > > Perchance, however, is there a command (other than and not > > as elaborate > > as -collapse-), that will produce a variable B containing > > the frequencies of > > the values in variable A? That way, I can place variable B directly > > into -chitest- . > > > > Unless, of course, you know of a one-sample test that will > > carry out the > > entire process of calculating the frequencies of the > > values of a specified > > categorical variable and then provide a one-sample > > chi-square over those > > frequencies? (Analogous to -tabulate- for two sample chi square) > > > > -chitest- is able to do this for you. Here is > a silly example for the simplest case of equal > expected frequencies. > > . chitest rep78, count > > Chi-square test: > observed frequencies from rep78 > expected frequencies equal > > Pearson chi2(4) = 33.3913 Pr = 0.000 > likelihood-ratio chi2(4) = 34.7183 Pr = 0.000 > > residuals > +-----------------------------------------+ > | observed expected classic Pearson | > |-----------------------------------------| > 1. | 2 13.800 -11.800 -3.176 | > 2. | 8 13.800 -5.800 -1.561 | > 3. | 30 13.800 16.200 4.361 | > 4. | 18 13.800 4.200 1.131 | > 5. | 11 13.800 -2.800 -0.754 | > +-----------------------------------------+ > > What -chitest- can't do is count values which > could be there in principle but which in > practice don't occur (cells with observed 0, > in short). > > I suspect there are other problems, but at worst > you need to type a few numbers at -chitesti-. > > If this doesn't solve the problem, please give > a clear example of the data structure you have in > mind. > > Nick SECOND APPROACH As a sequel to my previous reply, here is one technique illustrated: . forval i = 1/5 { 2. qui count if rep78 == `i' 3. local counts "`counts' `r(N)'" 4. } . di "`counts' 2 8 30 18 11 . chitesti `counts' One advantage of this technique is that will work fine when observed frequencies are 0. You just have to use -forvalues- or -foreach- to cycle over the possible values of a variable relevant to your test. This could also be automated in a program. Nick * * * 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: RE: Re: RE: one-sample chi square test***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**st: Percentiles: Identify of smallest observation closet to percentilevalue***From:*Rod Hunter <info@hunarch.com.au>

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