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From |
"Joseph Coveney" <stajc2@gmail.com> |

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

Subject |
st: Re: Is there a better way of allocating individuals into different categories based on the probability of an event? |

Date |
Sat, 23 Mar 2013 12:40:43 +0900 |

Gwinyai Masukume wrote: Is there a better way of executing the code below which assigns individuals into the Non-smoker and Smoker categories based on the probability of smoking in pregnancy? ****0=Non-smoker, 1=Smoker*** **** Assuming 84% of women do not smoke during pregnancy **** Johnston V, Thomas DP, McDonnell J, Andrews RM. Maternal smoking and smoking in the household during pregnancy and postpartum: findings from an Indigenous cohort in the Northern Territory. Med J Aust. 2011 May 16;194(10):556-9. gen smoker1=int(1+(50000-1)*runiform()) gen smoker=0 if smoker1 < 42000 replace smoker=1 if smoker1 >= 42000 label define smoker_label 0"Non-smoker" 1"Smoker" label values smoker smoker_label label variable smoker "Smoking status" drop smoker1 -------------------------------------------------------------------------------- How about the following? generate byte smoker = runiform() > 0.84 Or if you're maintaining left-to-right smaller-to-larger order of comparisons:* generate byte smoker = 0.84 < runiform() Joseph Coveney P.S. Be sure to set the seed in order to assure reproducibility. *Recommended, as I recall, by Steve McConnell in his _Code Complete: A Practical Handbook of Software Construction_ Second Edition. (Redmond, Wash.: Microsoft, 2004). * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Re: Is there a better way of allocating individuals into different categories based on the probability of an event?***From:*Gwinyai Masukume <parturitions@gmail.com>

**References**:**st: Is there a better way of allocating individuals into different categories based on the probability of an event?***From:*Gwinyai Masukume <parturitions@gmail.com>

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