Hi all,

I’d like to model emotional dynamics in a highly arousing firewalk ritual. 

Four judges rated images from 42 participants for arousal and valence. The predictor variables are ritual “phase” and “role.”

Question 1
Any thoughts about how best to handle the rater assessments?  

Specifically, is it nuts to explicitly include a component for raters in the random component of the model? 

E.g.

library(MCMCglmm)
prior.fw.0 = list(  
  B = list(mu=rep(0,4),V = diag(4)*1e+10),
  R = list(V =diag(2), fix = 1),
  G = list(G1 = list(V = diag(2), n = 2, alpha.mu = c(0,0), alpha.V = diag(2)*1000), 
           G2 = list (V = diag(2),n = 2, alpha.mu = c(0,0), alpha.V = diag(2)*1000),
           G3 = list (V = diag(2),  fix=1)))


firemodel.test <-MCMCglmm(cbind(arousal, valence) ~ trait:role:trait:phase -1,  
                          random = ~us(trait):phase:id 
                          + idh(trait):event:id 
                          + idh(trait):rater, 
                          rcov= ~ idh(trait):units, 
                          family = rep("ordinal",2), 
                          data=Firewalkdata, burnin=5000, 
                          thin = 10, 
                          nitt=20000, 
                          prior=prior.fw.0)



Thanks everyone. Very grateful for and advice.

Joseph


Disclaimer
I'm new to GLMMs,so apologies if this doesn't make sense.

Data sample below
(Only 20 data points, just to get a sense of the structure)

Firewalkdata <- structure(list(obs = c("1", "2", "3", "4", "5", "6", "7", "8", 
"9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", 
"20"), id = structure(c(24L, 4L, 26L, 37L, 32L, 3L, 20L, 9L, 
3L, 2L, 5L, 19L, 23L, 28L, 29L, 8L, 3L, 18L, 40L, 26L), .Label = c("a", 
"b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", 
"o", "p", "pa", "pb", "pc", "pd", "pe", "pf", "pg", "ph", "pi", 
"pj", "pk", "pl", "pm", "pn", "po", "pp", "q", "r", "s", "t", 
"u", "v", "w", "x", "y"), class = "factor"), phase = c(1, 2, 
5, 5, 2, 3, 1, 4, 5, 2, 5, 1, 5, 4, 3, 4, 5, 3, 2, 4), event = structure(c(11L, 
4L, 13L, 21L, 22L, 3L, 4L, 9L, 3L, 2L, 5L, 3L, 9L, 16L, 17L, 
8L, 3L, 2L, 24L, 13L), .Label = c("a", "b", "c", "d", "e", "f", 
"g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", 
"t", "u", "v", "w", "x", "y"), class = "factor"), role = structure(c(2L, 
1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 
2L, 1L, 2L), .Label = c("FW", "PS"), class = "factor"), dyad = structure(c(2L, 
2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 1L, 2L), .Label = c("n", "y"), class = "factor"), gender = structure(c(1L, 
2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 
1L, 2L, 2L), .Label = c("f", "m"), class = "factor"), rater = structure(c(4L, 
1L, 3L, 1L, 3L, 4L, 1L, 2L, 4L, 3L, 4L, 3L, 4L, 1L, 1L, 4L, 4L, 
1L, 4L, 4L), .Label = c("rat1", "rat2", "rat3", "rat4"), class = "factor"), 
    arousal = c(4, 5, NA, 6, 6, 6, 4, 4, 7, 4, 3, 7, 5, 5, 5, 
    6, 5, NA, 4, 6), valence = c(4, 3, NA, 2, 6, 1, 2, 6, 3, 
    5, 5, 7, 5, 2, 2, 1, 4, NA, 4, 6)), .Names = c("obs", "id", 
"phase", "event", "role", "dyad", "gender", "rater", "arousal", 
"valence"), row.names = c(3977L, 83L, 2996L, 525L, 3134L, 3213L, 
726L, 1267L, 3221L, 2134L, 3273L, 2801L, 3975L, 944L, 964L, 3344L, 
3223L, 688L, 3758L, 4041L), class = "data.frame")


IMAGE SAMPLE (for the curious)
https://www.dropbox.com/s/xmbci5814h73i0l/4_MF_e5.png

GRAPH bootstrapped means
https://www.dropbox.com/s/509sgh5zqxq18tn/Figure_FireWalk.pdf

Crude overview of the design
https://www.dropbox.com/s/0o0a9kkrh5ttsd2/plot.plan.emotions_firewalk.pdf



–
Joseph Bulbulia
Senior Lecturer, Religious Studies
Faculty of Humanities and Social Sciences
Victoria University, New Zealand
+64 21 95 94 23
http://www.metaphysicalclub.com




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