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Health Market Science (HMS), located in King of Prussia, Pennsylvania, USA has an opening for a statistician. The responsibilities of this position include research and new product development, and building client deliverables involving complex analytical methods.? The position will leverage the candidates? skills in data analysis to drive value. Preferred educational background: ?MS with

...to figure this out but I haven't found any solution. I am running a generalised mixed effect model, gamm4, for an ecology project. Below is the code for the model: model<-gamm4(LIFE.OE_spring~s(Q95, by=super.end.group)+Year+Hms_Rsctned+Hms_Poaching+X.broadleaved_woodland? ? ? ? ? ? ?+X.urban.suburban+X.CapWks, data=spring, random=~(1|WATERBODY_ID/SITE_ID)) plot(model$gam, page=1, font.lab=2, xlab="Residual Q95") I am trying to plot the results in lattice for publication purposes so I need to figure this out. I have been struggling but I think I have reached a dead end.? Here is what...

..... $ Q95 : num 100 100 80 80 80 98 98 98 105 105 ... $ LIFE.OE_spring : num 1.02 1.03 1.02 1.06 1.06 1.07 1.12 1.05 1.14 1.05 ... $ super.end.group : Factor w/ 6 levels "B","C","D","E",..: 1 1 3 3 3 2 2 2 4 4 ... $ X.urban.suburban : num 0 0 0.07 0.07 0.07 0.53 0.53 0.53 8.07 8.07 ... $ X.broadleaved_woodland: num 2.83 2.83 10.39 10.39 10.39 ... $ X.CapWks : num 0 0 0 0 0 0 0 0 0 0 ... $ Hms_Poaching : int 0 0 10 10 10 0 0 0 0 0 ... $ Hms_Rsctned : int 0 0 0 0 0 0 0 0 0 0 ... mod...

...0 80 98 98 98 105 105 101 101 130 120 120 ... #$ LIFE.OE_spring : num 1.02 1.03 1.02 1.06 1.06 1.07 1.12 1.05 1.14 1.05 1.09 1.14 1.04 0.97 0.98 ... #$ super.end.group : Factor w/ 6 levels "B","C","D","E",..: 1 1 3 3 3 2 2 2 4 4 ... #$ X.urban.suburban : num 0 0 0.07 0.07 0.07 0.53 0.53 0.53 8.07 8.07 0.27 0.27 0.27 0.27 0.27 0.72 ... #$ X.broadleaved_woodland: num 2.83 2.83 10.39 10.39 10.39 7.72 7.72 21.15 21.15 14.44 14.44 ... #$ X.CapWks : num 0 0 0 0 0 0 0 0 0 0 8.11 8.11 8.11 0 0 0 42.06 42.06 7.08 0.2 ... #$ Hms_Poa...

Hi, I am trying to do a statistical analysis of a SPSS data set, which has 7 different parameters, 4 of which are Yes/No. When I try to select in one of the parameters all the rows with a Yes it always gives me the same error : object 'Yes' not found although: > suburban [1] No No Yes No No Yes No Yes No No No No No No No No No No [19] No No Yes No Yes Yes No No No No Yes No Yes No No Yes Yes Yes [37] Yes No No No No Yes Yes No No No Yes No No Yes Yes Yes Yes Yes [55] Yes Yes No No No Yes No Yes Yes No No No No Yes...

Hello. I would try to explain what I would like to implement so to suggest me what to try out. I would like to create an area of X*X km that would be used to "Simulate" an area map (eg. city's area, suburban area). -X would be a parameter so I do not want it to be fixed -In this map I would like to place users (people), thus I do not know in advance if in one place there would be one,two, or more users.. -I would also like to not have fixed resolution in my map and specify it as a parameter during...

Must have event-driven processing expertise. Linux environment. Mobile apps dvlpmt. NW suburban location. Recruiter: Liz Klein 469-223-4900 adfwrecruiter-Re5JQEeQqe8AvxtiuMwx3w@public.gmane.org or lizk-IElRh2z3wdXDP7Uc+MJFAgC/G2K4zDHf@public.gmane.org www.talentlegends.com LinkedIn profile at *www.linkedin.com/in/elizabethmklein/*<http://www.linkedin.com/in/elizabethmklein/> --...

Could you please help me on the following ANCOVA issue? This is a part of my dataset: sampling dist h 1 wi 200 0.8687212 2 wi 200 0.8812909 3 wi 200 0.8267464 4 wi 0 0.8554508 5 wi 0 0.9506721 6 wi 0 0.8112781 7 wi 400 0.8687212 8 wi 400 0.8414646 9 wi 400 0.7601675 10 wi 900 0.6577048 11 wi 900

...s = "factor"), usr = structure(c(2L, 2L, 1L, 3L, 1L, 3L, 3L, 3L, 2L, 2L, 3L, 2L, 1L, 3L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 3L, 3L, 3L, 1L, 2L, 2L, 3L, 2L, 1L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 1L, 2L, 1L, 3L, 2L, 3L, 2L, 2L, 2L), .Label = c("Rural", "Suburban", "Urban"), class = "factor"), pial1a = structure(c(NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_,...

...usr = structure(c(2L, 2L, 1L, 3L, 1L, 3L, 3L, 3L, 2L, 2L, > + 3L, 2L, 1L, 3L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, > + 3L, 3L, 3L, 1L, 2L, 2L, 3L, 2L, 1L, 2L, 2L, 2L, 2L, 3L, 2L, > + 2L, 1L, 2L, 1L, 3L, 2L, 3L, 2L, 2L, 2L), .Label = c("Rural", > + "Suburban", "Urban"), class = "factor"), pial1a = > + structure(c(NA_integer_, > + NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, > + NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, > + NA_integer_, NA_integer_, NA_integer_,...

...factor"), + usr = structure(c(2L, 2L, 1L, 3L, 1L, 3L, 3L, 3L, 2L, 2L, + 3L, 2L, 1L, 3L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, + 3L, 3L, 3L, 1L, 2L, 2L, 3L, 2L, 1L, 2L, 2L, 2L, 2L, 3L, 2L, + 2L, 1L, 2L, 1L, 3L, 2L, 3L, 2L, 2L, 2L), .Label = c("Rural", + "Suburban", "Urban"), class = "factor"), pial1a = + structure(c(NA_integer_, + NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, + NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, + NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_inte...