Hi Andy, I was just reading something you wrote about spBayes and was thinking about emailing you for advice!
The data I currently have is 1000's of village locations with counts of human disease (and population data, so I could calculate rates/prevalence) over about 20 years - I'll probably take a sample of these villages for use in the analysis rather than use all of them as there are probably too many. I also have a number of locations (far less - probably about 30) with livestock (reservoir for the parasite) prevalence data from various time points. So the human data is more flexible - could be used as counts or rates, but the animal data is a proportion, so would have to be used as a binomial variable which might constrain the analysis to a binomial GLM. My ideal scenario would be the ability to create a multivariate spatio-temporal model with the primary aim of predicting human disease (spatially, and also perhaps forecasting if possible) based on environmental/climatic covariates, and also with the input of animal prevalence information. I'm only at the grant writing stage at the moment, so wanted to check this is something which I can do before committing myself to it! My supervisor is very keen on the temporal aspect of the work. Personally I'm more interested in incorporating animal sampling data to improve the predictions as there is a big problem of under-reporting for this disease (particularly in areas far from health centres), and I hope that the use of animal sampling data could improve predictions. I was hoping that we'd be able to combine these two aims in one model...is that not possible? Also, do you know what the limitations of the model fitting is in terms of number of observation locations? Sorry if my questions are a bit niave, but I have no experience of spatio-temporal modelling and am just trying to get my head around what is possible for this grant! Thanks very much for your input, Nicola -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. -----Original Message----- From: Andrew Finley [mailto:finl...@msu.edu] Sent: 24 March 2010 18:13 To: n.a.batche...@sms.ed.ac.uk Subject: [R-sig-Geo] Multivariate spatio-temporal modelling Hi Nicola, Sorry to answer you off the list. One of my grad students forwarded your posting to me. So based on your description you should be able to use spMvGLM to fit this model for any given time point (in its current state this function will not be able to fit a full space-time model). So at a given location you have disease counts for humans and animals (assuming humans != animals ;-)? Or do you have disease rates. If so would you want to fit a multivariate spatial binomial regression? Also how many data points do you have? Feel free to answer back on the list (I'm now an official subscriber). Kind regards- Andy -- Andrew Finley, PhD Natural Resources Building Michigan State University East Lansing, MI 48824-1222 Phone: 517-432-7219 Fax: 517-432-1143 web: http://blue.for.msu.edu Dear list. I've completed a spatial GLM analysis of a dataset with one outcome variable (binomial) using geoRglm. I now want to go on to extend this analysis in 2 ways: 1) incorporating a temporal element and 2) using a second (related) outcome variable. As far as I am aware, geoRglm doesn't have the functionality for spatio-temporal modelling, or for multivariate modelling. Is this correct? >From a brief look around on the web it seems like spBayes could be the thing for the job. Can anyone give me a wee bit of advice as to whether spBayes could potentially be right for what I want to do (or if there is anything else which I could use)? Basically, I want to carry out spatio-temporal modelling of joint distribution data for 2 related disease measures (will be disease prevalence or counts in humans and animals). The outputs I want (if possible) are estimates of covariate effects on both human and animal disease, the relationship between human and animal disease and a spatio-temporal prediction. Please forgive me if I use the wrong technical terms as my first analysis with geoRglm was my first ever introduction to geostatistics and spatial modelling...perhaps I am being overambitious! Many thanks in advance, Nicola Batchelor University of Edinburgh and University of Southampton _______________________________________________ R-sig-Geo mailing list R-sig-Geo@stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-geo
