[ABE-L] Nossos estatísticos

[Basilio De Braganca Pereira]

Nossos estatísticos está fazendo coisas importantes!!!!
Basílio

Enviado do meu iPhone

Início da mensagem encaminhada

> De: Giulio Flore <giulio.flore em googlemail.com>
> Data: 2 de junho de 2015 12:09:44 GMT+2
> Para: medstats em googlegroups.com
> Assunto: Re: {MEDSTATS} Zero Inflated Cox Regression?
> Responder A: medstats em googlegroups.com
> 
> No worries,
> 
> Good luck with the task
> 
>> On 2 June 2015 at 12:09, Tzippy Shochat <tz.shochat em gmail.com> wrote:
>> Thanks Giulio.
>> 
>> 
>> 2015-06-02 11:33 GMT+03:00 Giulio Flore <giulio.flore em googlemail.com>:
>>> For what is worth, you might want to have a look at
>>> 
>>> Rodrigues, J., de Castro, M., Cancho, V. G., & Balakrishnan, N. (2009). COM–Poisson cure rate survival models and an application to a cutaneous melanoma data. Journal of Statistical Planning and Inference, 139(10), 3605-3611. Free download is available on Scholar 
>>> 
>>> The best bit about CMP is that it deals with zero inflated distribution as well as not over-dispered distributions like Poisson.  A seminal article on the subject is 
>>> 
>>> Cordeiro, G. M., Rodrigues, J., & de Castro, M. (2012). The exponential COM-Poisson distribution. Statistical papers, 53(3), 653-664.
>>> 
>>> It is available from Springer. There was a paper on CMP also on one of the RSS journals. 
>>> 
>>> The added bonus is that CMP regression is available in STATA and in R.
>>> 
>>> Best of luck,
>>> 
>>> Giulio
>> 
>> 
>>> On 2 June 2015 at 09:55, Tzippy Shochat <tz.shochat em gmail.com> wrote:
>>> Dear All.
>>> 
>>> A common situation in Cancer research is measuring the Duration of Response, which is measured as the time from clinical response to treatment till the time of disease progression or death.
>>> 
>>> The problem is that not all patients have a clinical response and there is no clear consensus how to treat these subjects.
>>> 
>>> One option I've seen used is to do a two part analysis: Logistic Regression for probability of reponse, followed by Cox regression, where non-responders are deleted from the model.
>>> 
>>> Another option is to assing  a zero duration of  response time to non-responders and treat these patients as censored at time "0".
>>> 
>>> I found one refference to a Zero Inflated Cox Regression (see below) but I'm not sure if this approach has gained acceptence in medical research.
>>> 
>>> http://sites.uclouvain.be/IAP-Stat-Phase-V-VI/PhaseVI/publications_2007/TR/TR07034.pdf
>>> 
>>> 
>>> Any thoughts, examples would be greatly appreciated.
>>> 
>>> Tzippy Shochat
>>> -- 
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>> 
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> 
> -- 
> -- 
> To post a new thread to MedStats, send email to MedStats em googlegroups.com .
> MedStats' home page is http://groups.google.com/group/MedStats .
> Rules: http://groups.google.com/group/MedStats/web/medstats-rules
> 
> --- 
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