PAPER ON ZERO-INFLATED NEGATIVE bINOM
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From: David L Cassell on 9 Apr 2007 01:53 oslo(a)yahoo.com wrote: > >Does any one konow any referance on bayesian multilevel zero-inflated >negative binom? > >all the best, > >Oslo Are your data really suited to such an analysis? Please write back to SAS-L first and explain what your data are, and where they come from, and how they were collected, and what you want to do with them, and what the project goals are. Then people here can give more helpful suggestions. HTH, David -- David L. Cassell mathematical statistician Design Pathways 3115 NW Norwood Pl. Corvallis OR 97330 _________________________________________________________________ Download Messenger. Join the i�m Initiative. Help make a difference today. http://im.live.com/messenger/im/home/?source=TAGHM_APR07
From: Shawn Haskell on 9 Apr 2007 11:08 On Apr 9, 12:53 am, davidlcass...(a)MSN.COM (David L Cassell) wrote: > o...(a)yahoo.com wrote: > > >Does any one konow any referance on bayesian multilevel zero-inflated > >negative binom? > > >all the best, > > >Oslo > > Are your data really suited to such an analysis? > > Please write back to SAS-L first and explain what your data are, and > where they come from, and how they were collected, and what you > want to do with them, and what the project goals are. Then people > here can give more helpful suggestions. > > HTH, > David > -- > David L. Cassell > mathematical statistician > Design Pathways > 3115 NW Norwood Pl. > Corvallis OR 97330 > > _________________________________________________________________ > Download Messenger. Join the i'm Initiative. Help make a difference today.http://im.live.com/messenger/im/home/?source=TAGHM_APR07 Don't mean to hijack your thread, but I was actually wondering about this myself the other day. Zero-inflated Poisson exists, does zero- inflated NegBin? If so, how so in SAS? i have used PROC GENMOD for negbin GLM with offset before. In wildlife studies we often examine habitat selection - i.e., resource selection functions that are often modeled with logistic regression as 'used' vs either 'unused' or 'available'. Those last 2 words carry a lot of baggage that we need not get into. Anyhow, sometimes the study area is broken into small plots using GIS or some other means. With new satellite and GPS technologies for tracking animals - you could end up with some used plots having 10, 20, 50, etc animal locations. A situation where the variance becomes much larger than the mean b/c you typically have many many more plots with zero uses - hence, a zero-inflated negative binomial? Also, you can use mixed models to deal with dependency of observations in order to separate individualistic effects vs population level effects. thanks. Shawn H
From: Jeff Miller on 9 Apr 2007 11:30 There is a lot of literature of ZINB models. The model is formulated in: Lambert, D. (1992). Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics, 34, 1-14. For more on mixed models refer to: Min, Y., Agresti, A. (2004). Random effects models for repeated measures of zero- inflated count data. (Technical Report 2004-026), Department of Statistics, University of Florida, Retrieved May 8, 2006 from second author. Min, Y. (2003). Modeling data with clumps. Dissertation Abstracts International - B, 64(12). (UMI3117356). The authors below used priors: Pardoe, I., & Durham, C. A. (2003). Model choice applied to consumer preferences. In Proceedings of the 2003 Joint Statistical Meetings, Alexandria, VA, American Statistical Association. Also http://floliveweb.free.fr/doc/zipmcmc.pdf Best, Jeff Miller University of Florida -----Original Message----- From: SAS(r) Discussion [mailto:SAS-L(a)LISTSERV.UGA.EDU] On Behalf Of Shawn Haskell Sent: Monday, April 09, 2007 11:08 AM To: SAS-L(a)LISTSERV.UGA.EDU Subject: Re: PAPER ON ZERO-INFLATED NEGATIVE bINOM On Apr 9, 12:53 am, davidlcass...(a)MSN.COM (David L Cassell) wrote: > o...(a)yahoo.com wrote: > > >Does any one konow any referance on bayesian multilevel zero-inflated > >negative binom? > > >all the best, > > >Oslo > > Are your data really suited to such an analysis? > > Please write back to SAS-L first and explain what your data are, and > where they come from, and how they were collected, and what you want > to do with them, and what the project goals are. Then people here can > give more helpful suggestions. > > HTH, > David > -- > David L. Cassell > mathematical statistician > Design Pathways > 3115 NW Norwood Pl. > Corvallis OR 97330 > > _________________________________________________________________ > Download Messenger. Join the i'm Initiative. Help make a difference > today.http://im.live.com/messenger/im/home/?source=TAGHM_APR07 Don't mean to hijack your thread, but I was actually wondering about this myself the other day. Zero-inflated Poisson exists, does zero- inflated NegBin? If so, how so in SAS? i have used PROC GENMOD for negbin GLM with offset before. In wildlife studies we often examine habitat selection - i.e., resource selection functions that are often modeled with logistic regression as 'used' vs either 'unused' or 'available'. Those last 2 words carry a lot of baggage that we need not get into. Anyhow, sometimes the study area is broken into small plots using GIS or some other means. With new satellite and GPS technologies for tracking animals - you could end up with some used plots having 10, 20, 50, etc animal locations. A situation where the variance becomes much larger than the mean b/c you typically have many many more plots with zero uses - hence, a zero-inflated negative binomial? Also, you can use mixed models to deal with dependency of observations in order to separate individualistic effects vs population level effects. thanks. Shawn H
From: David L Cassell on 10 Apr 2007 01:49 shawn.haskell(a)TTU.EDU wrote: > >On Apr 9, 12:53 am, davidlcass...(a)MSN.COM (David L Cassell) wrote: > > o...(a)yahoo.com wrote: > > > > >Does any one konow any referance on bayesian multilevel zero-inflated > > >negative binom? > > > > >all the best, > > > > >Oslo > > > > Are your data really suited to such an analysis? > > > > Please write back to SAS-L first and explain what your data are, and > > where they come from, and how they were collected, and what you > > want to do with them, and what the project goals are. Then people > > here can give more helpful suggestions. > > > > HTH, > > David > > -- > > David L. Cassell > > mathematical statistician > > Design Pathways > > 3115 NW Norwood Pl. > > Corvallis OR 97330 > > > > _________________________________________________________________ > > Download Messenger. Join the i'm Initiative. Help make a difference >today.http://im.live.com/messenger/im/home/?source=TAGHM_APR07 > >Don't mean to hijack your thread, but I was actually wondering about >this myself the other day. Zero-inflated Poisson exists, does zero- >inflated NegBin? If so, how so in SAS? i have used PROC GENMOD for >negbin GLM with offset before. > >In wildlife studies we often examine habitat selection - i.e., >resource selection functions that are often modeled with logistic >regression as 'used' vs either 'unused' or 'available'. Those last 2 >words carry a lot of baggage that we need not get into. Anyhow, >sometimes the study area is broken into small plots using GIS or some >other means. With new satellite and GPS technologies for tracking >animals - you could end up with some used plots having 10, 20, 50, etc >animal locations. A situation where the variance becomes much larger >than the mean b/c you typically have many many more plots with zero >uses - hence, a zero-inflated negative binomial? Also, you can use >mixed models to deal with dependency of observations in order to >separate individualistic effects vs population level effects. thanks. > >Shawn H You know, it's so rare that someone starts out with a scientific model that leads to a logical investigation of a ZINB model. Thanks. I needed that. :-) The place to look is in the SAS-L archives. Look up Dale McLerran's tomes on PROC NLMIXED for ZIP and ZINB models. Oh, and when you do, don't look for his name in the 'author' box, because he uses the 'from' name stringplayer2 . HTH, David -- David L. Cassell mathematical statistician Design Pathways 3115 NW Norwood Pl. Corvallis OR 97330 _________________________________________________________________ Exercise your brain! Try Flexicon. http://games.msn.com/en/flexicon/default.htm?icid=flexicon_hmemailtaglineapril07
From: Shawn Haskell on 10 Apr 2007 10:16
On Apr 10, 12:49 am, davidlcass...(a)MSN.COM (David L Cassell) wrote: > shawn.hask...(a)TTU.EDU wrote: > > >On Apr 9, 12:53 am, davidlcass...(a)MSN.COM (David L Cassell) wrote: > > > o...(a)yahoo.com wrote: > > > > >Does any one konow any referance on bayesian multilevel zero-inflated > > > >negative binom? > > > > >all the best, > > > > >Oslo > > > > Are your data really suited to such an analysis? > > > > Please write back to SAS-L first and explain what your data are, and > > > where they come from, and how they were collected, and what you > > > want to do with them, and what the project goals are. Then people > > > here can give more helpful suggestions. > > > > HTH, > > > David > > > -- > > > David L. Cassell > > > mathematical statistician > > > Design Pathways > > > 3115 NW Norwood Pl. > > > Corvallis OR 97330 > > > > _________________________________________________________________ > > > Download Messenger. Join the i'm Initiative. Help make a difference > >today.http://im.live.com/messenger/im/home/?source=TAGHM_APR07 > > >Don't mean to hijack your thread, but I was actually wondering about > >this myself the other day. Zero-inflated Poisson exists, does zero- > >inflated NegBin? If so, how so in SAS? i have used PROC GENMOD for > >negbin GLM with offset before. > > >In wildlife studies we often examine habitat selection - i.e., > >resource selection functions that are often modeled with logistic > >regression as 'used' vs either 'unused' or 'available'. Those last 2 > >words carry a lot of baggage that we need not get into. Anyhow, > >sometimes the study area is broken into small plots using GIS or some > >other means. With new satellite and GPS technologies for tracking > >animals - you could end up with some used plots having 10, 20, 50, etc > >animal locations. A situation where the variance becomes much larger > >than the mean b/c you typically have many many more plots with zero > >uses - hence, a zero-inflated negative binomial? Also, you can use > >mixed models to deal with dependency of observations in order to > >separate individualistic effects vs population level effects. thanks. > > >Shawn H > > You know, it's so rare that someone starts out with a scientific model > that leads to a logical investigation of a ZINB model. Thanks. I needed > that. :-) > > The place to look is in the SAS-L archives. Look up Dale McLerran's > tomes on PROC NLMIXED for ZIP and ZINB models. Oh, and when > you do, don't look for his name in the 'author' box, because he uses > the 'from' name stringplayer2 . > > HTH, > David > -- > David L. Cassell > mathematical statistician > Design Pathways > 3115 NW Norwood Pl. > Corvallis OR 97330 > > _________________________________________________________________ > Exercise your brain! Try Flexicon.http://games.msn.com/en/flexicon/default.htm?icid=flexicon_hmemailtag...- Hide quoted text - > > - Show quoted text - David, thanks for the tip, I'll check it out. The situation I gave was pretty particular b/c it was on my mind at the time. However, a ZINB model may actually be fairly common for a lot of wildife surveys. The reason is that many wildlife species are gregarious but not terribly common. Say you want to model factors affecting duck use of ponds. You visit 30 ponds and find no ducks, but when you do find a pond with ducks there might be 50, 500, or 1000. You might standardize the model by using pond area as an offset to get density but that is another matter. Anyhow, thanks for the help. Shawn Haskell Texas Tech Univ PhD candidate, Wildlife Science |