Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
"Carmine Rossi, Mr" <[email protected]> |

To |
"<[email protected]>" <[email protected]> |

Subject |
Re: st: Recency Weighted cumulative exposures |

Date |
Thu, 14 Nov 2013 00:42:28 +0000 |

Hi Mr. Radyakin, Thank you very much for your email and help. However, the code is not correct. There are two issues: 1) The number of observations per ID is not constant, so for the macro `mt', it would need to be specific per id. For example, ID==1 has 5 time points, and ID==2 has 4 time points. 2) The weights are not fixed. This is more difficult for me to explain, but I will try. To get the "result" for ID==1 and time==5, I used the spreadsheet calculations shown in the previous email. However, if I was to calculate the "result" at time==4, I would use the following weights: id time dose delta_t w(t) dose(t)*weight(t) cumulative_sum 1 1 0 3 0.88 0 0 1 2 0 2 0.94 0 0 1 3 2.6 1 0.99 2.574 2.574 1 4 2.6 0 1 2.6 5.174 Notice how, now the weight, w(t), at time==4 is equal to 1, when I want to calculate the cumulative sum at time==4. For this reason, I thought I would need loops, and this is why I am asking the STATA community for help. My major issue is that the weight’s are not fixed and they change depending on the cumulative sum that I want to calculate at each time point. Thank you again for trying to help, -Carmine Rossi PhD Candidate, Epidemiology [email protected] On 2013-11-13, at 5:23 PM, Sergiy Radyakin <[email protected]> wrote: > Carmine, no loops are really necessary: > > do http://radyakin.org/statalist/2013111301/recencyw.do > > Hope this helps, Sergiy Radyakin > > > On Wed, Nov 13, 2013 at 5:08 PM, Carmine Rossi, Mr > <[email protected]> wrote: >> Dear STATA listers, >> >> I have the following repeated measures data on two subjects with a dose exposure variable. I am interested in creating a variable called “result” that is a recency-weighted cumulative sum. >> >> id time dose result >> 1 1 0 0 >> 1 2 0 0 >> 1 3 2.6 2.6 >> 1 4 2.6 5.174 >> 1 5 3.2 8.218 >> 2 1 0 0 >> 2 2 0 0 >> 2 3 0.7 0.7 >> 2 4 0.7 1.393 >> >> The “result” variable is obtained as a cumulative sum using a weight function: >> Summation of (Dose(i) x weight(t)), where the weight function is: >> >> W(t) = exp((-(delta time)2)/70.70) >> >> So to get the weighted cumulative sum value of 8.218 (for subject 1 at time 5), rather than 8.4, which would have been the un-weighted cumulative sum, I did the following in a spreadsheet. >> >> >> Id time dose delta_t w(t) dose(t)*weight(t) cumulative_sum >> 1 1 0 4 0.80 0 0 >> 1 2 0 3 0.88 0 0 >> 1 3 2.6 2 0.94 2.444 2.444 >> 1 4 2.6 1 0.99 2.574 5.018 >> 1 5 3.2 0 1 3.2 8.218 >> >> Is there a way to do this in STATA with loops? Can anyone provide any suggestions? >> >> >> Carmine Rossi >> PhD Candidate, Epidemiology >> McGill University >> [email protected] >> * >> * 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/ > > * > * 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/ * * 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: Recency Weighted cumulative exposures***From:*Sergiy Radyakin <[email protected]>

**References**:**st: Recency Weighted cumulative exposures***From:*"Carmine Rossi, Mr" <[email protected]>

**Re: st: Recency Weighted cumulative exposures***From:*Sergiy Radyakin <[email protected]>

- Prev by Date:
**st: RE: ivreg2 warning, even after "partialling out"** - Next by Date:
**st: CDF plot with normal probability axis** - Previous by thread:
**Re: st: Recency Weighted cumulative exposures** - Next by thread:
**Re: st: Recency Weighted cumulative exposures** - Index(es):