[R-sig-ME] MCMCglmm priors for multi-response multi-level model
rafter sass ferguson
liberationecology at gmail.com
Thu May 28 20:32:11 CEST 2015
Dear MCMCglmm'ers,
I'm attempting to model several related social behaviors (in humans) using
individual- and group-level predictor variables. I'll describe the
situation and then supply code and data following. The grouping variable is
very unbalanced.
The model I'm attempting to fit has...
• 3 continuous response variables (correlated)
• 2 continuous + 3 categorical predictors at the individual level (1 of
which is very unbalanced)
• 3 continuous predictors at the group level
• 4 interactions between individual- & group-level predictors
• 1 grouping variable - very unbalanced
I haven't succeeded yet in specifying the priors so that MCMCglmm won't
choke - and if I had, I would still be concerned
to make sure the model makes sense. I'd be grateful for any guidance.
When I attempt to fit it w/o priors, MCMCglmm gives this error:
"Mixed model equations singular: use a (stronger) prior"
With any of the prior specifications I've tried, MCMCglmm throws
"Error in priorformat(if (NOpriorG) { :
V is the wrong dimension for some prior$G/prior$R elements"
Here are the two prior specifications that I've pieced together:
### my attempt at inverse-wishart
priors <- list(
R=list(V=diag(3), nu=3),
G=list(
G1=list(V=diag(3), nu=3),
G2=list(V=diag(3), nu=3)
))
# attempt at inverse-wishart w/ expanded parameters
epriors <- list(
R=list(V=diag(3), nu=3.02),
G=list(
G1=list(V=diag(3), nu=3.02, alpha.mu=rep(0,3), alpha.V=1000*diag(3)),
G2=list(V=diag(3), nu=3.02, alpha.mu=rep(0,3), alpha.V=1000*diag(3))
))
# As described above, I've tried fitting (1) w/o priors, and (2,3) with
each of the above specifications
mod1 <- MCMCglmm(cbind(y1, y2, y3) ~
-1 + trait +
trait:income + trait:age + trait:ethnicity +
trait:gender + trait:residence +
trait:education + trait:blvl1 + trait:blvl2 +
trait:blvl3 +
trait:blvl2:gender + trait:blvl3:gender +
trait:blvl3:ethnicity + trait:blvl3:income,
random = ~ idh(trait):ID + idh(trait:block),
rcov = ~us(trait):units,
data = df,
# prior= epriors,
singular.ok=T,
family = c("gaussian", "gaussian", "gaussian"),
verbose = T)
dput() output is below...
Thanks so much for any help.
Warmly,
Rafter
# Here is a reduced sample of the data. The actual data N=727.
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3L, 9L, 9L, 2L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 4L, 2L, 9L,
2L, 9L, 9L, 9L, 9L, 9L, 9L, 9L), .Label = c("1", "2", "3",
"4", "5", "6", "7", "8", "9"), class = "factor"), ID = c("245",
"423", "603", "601", "305", "560", "713", "638", "715", "393",
"673", "553", "634", "465", "528", "666", "574", "175", "606",
"567", "9", "383", "354", "719", "45", "416", "369", "43",
"670", "401", "642", "372", "211", "227", "210", "409", "399",
"380", "344", "513", "717", "691", "293", "576", "184", "29",
"231", "99", "246", "556", "548", "313", "726", "293", "507",
"224", "306", "163", "465", "107", "462", "196", "626", "569",
"672", "561", "512", "615", "190", "2", "288", "526", "369",
"608", "264", "579", "280", "702", "305", "303", "182", "698",
"345", "597", "358", "80", "521", "111", "274", "125", "301",
"511", "130", "653", "17", "157", "403", "159", "348", "434",
"374", "27", "368", "179", "137", "691", "11", "247", "390",
"14", "114", "270", "170", "582", "722", "244", "564", "230",
"355", "711", "621", "54", "718", "422", "284", "200", "78",
"208", "286", "611", "528", "251", "411", "657", "115", "28",
"60", "701", "376", "605", "730", "138", "574", "275", "259",
"529", "12", "238", "163", "563", "678", "229", "123")), row.names =
c("1",
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13",
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24",
"25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35",
"36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "291",
"231", "99", "246", "552", "544", "313", "722", "293", "505",
"224", "306", "163", "464", "107", "461", "196", "622", "565",
"668", "557", "510", "611", "190", "210", "288", "522", "368",
"604", "264", "575", "280", "698", "305", "303", "182", "694",
"344", "593", "357", "80", "517", "111", "274", "125", "301",
"509", "130", "649", "171", "157", "402", "159", "347", "433",
"373", "271", "367", "179", "137", "687", "112", "247", "389",
"141", "114", "270", "170", "578", "718", "244", "560", "230",
"354", "707", "617", "54", "714", "421", "284", "200", "78",
"208", "286", "607", "524", "251", "410", "653", "115", "281",
"60", "697", "375", "601", "726", "138", "570", "275", "259",
"146", "147", "148", "149", "150", "151", "152", "153"), .Names = c("y1",
"y2", "y3", "age", "income", "ethnicity", "gender", "residence",
"education", "blvl1", "blvl2", "blvl3", "block", "ID"), class =
"data.frame")
Rafter Sass Ferguson, MS
PhD Candidate | Crop Sciences Department
University of Illinois in Urbana-Champaign
liberationecology.org
518 567 7407
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