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From |
Ricardo Ovaldia <ovaldia@yahoo.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Experimental design - ANOVA/GLM? - please help |

Date |
Thu, 26 Sep 2002 15:23:27 -0700 (PDT) |

Exactly what I needed. Thank you, Ken!!! Best, Ricardo. --- khigbee@stata.com wrote: > Ricardo Ovaldia <ovaldia@yahoo.com> asks: > > > I was approached by an investigator with the > following > > problem. He had two groups of experimental rats, > 10 > > diabetic and 10 non-diabetic. Each of these rats > had > > one liter of 10 pups (average). On each of the > pups a > > series of biochemicals were measured. He wants me > to > > compare the mean value of these biochemicals from > the > > pumps from diabetic moms to the pups from > non-diabetic > > pups. He then suggested that I do a simple t-test > > comparing the means of the two pup groups. I > pointed > > out that the observations are not independent > because > > of several pups from the same liter and that the > liter > > effect needs to be taken into account. > > > > How can I set this up in Stata? > > Assuming I understand your setup, you have a nested > ANOVA model. > I ran the following commands to create some fake > data that I think > has a similar form as yours. > > clear > set obs 2 > gen group = _n > expand 10 > sort group > qui gen mom = _n in 1/10 > qui replace mom = mom[_n-10] in 11/20 > set seed 32981 > gen z = 10 + round(uniform()*4-2,1) > expand z > drop z > bysort group mom : gen pup = _n > gen y = uniform()*8 + group > compress > > I then looked at a table of pup counts and y value > means for each > group (meaning diabetic & nondiabetic moms) and each > mom within > group. The nested ANOVA results are then shown. > > . table mom group, c(mean y freq) > > ------------------------------ > | group > mom | 1 2 > ----------+------------------- > 1 | 4.290885 5.353604 > | 11 8 > | > 2 | 5.389515 6.748766 > | 9 9 > | > 3 | 4.533185 6.990387 > | 9 12 > | > 4 | 4.732775 5.633358 > | 8 10 > | > 5 | 6.142506 4.981017 > | 10 8 > | > 6 | 5.124625 5.217069 > | 9 10 > | > 7 | 5.285787 5.418501 > | 11 11 > | > 8 | 5.234306 6.799588 > | 11 9 > | > 9 | 5.171794 6.379981 > | 8 9 > | > 10 | 6.112025 6.664215 > | 10 8 > ------------------------------ > > . anova y group / mom|group / > > Number of obs = 190 > R-squared = 0.1047 > Root MSE = 2.40589 Adj > R-squared = 0.0046 > > Source | Partial SS df MS > F Prob > F > > -----------+---------------------------------------------------- > Model | 115.021745 19 6.05377604 > 1.05 0.4119 > | > group | 31.203949 1 31.203949 > 6.80 0.0178 > mom|group | 82.6298147 18 4.59054526 > > -----------+---------------------------------------------------- > mom|group | 82.6298147 18 4.59054526 > 0.79 0.7065 > | > Residual | 984.009577 170 5.78829163 > > -----------+---------------------------------------------------- > Total | 1099.03132 189 5.81498054 > > > I added a little group effect into my fake data > (notice the > p-value of .0178). > > > Ken Higbee khigbee@stata.com > StataCorp 1-800-STATAPC > > * > * 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/ ===== Ricardo Statistician Center for Applied Research University Hospital Oklahoma City,OK __________________________________________________ Do you Yahoo!? New DSL Internet Access from SBC & Yahoo! http://sbc.yahoo.com * * 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/

**References**:**Re: st: Experimental design - ANOVA/GLM? - please help***From:*khigbee@stata.com

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