[R-sig-ME] MCMCglmm interpretation with contrast coding and multinomial IVs and DV
Adriana Guevara Rukoz
adriana.guevara.rukoz at ens.fr
Tue Apr 26 18:19:45 CEST 2016
Dear all,
I would like to analyze some data from an identification task, in which
subjects hear a V1h[V2]pV1 stimulus (e.g. ah[i]pa), where [V2]
designates the coarticulation within the /hp/ cluster (V1 != V2 when the
stimuli have been spliced). Subjects are asked what vowel they perceived
between the consonants of the cluster (vowel epenthesis).
In particular, I'm interested in the relative contributions of V1 and V2
on the choice of each response vowel (e.g., do subjects choose /i/ more
often than other vowels when V1=/i/? Even more or less so when
COART=[i]? Which contribution is more important between V1 and V2 for
each vowel?)
First, here is a recap of my variables (baseline = u ; as that is the
"default" epenthetic vowel):
** RV: *
- RESP (categorical, 5 levels): {u, o, i, e, a}
** IV: *
- V1 (categorical, 5 levels): {u, o, i, e, a} - sum-contrast coded
- V2, henceforth named COART for easier reading, (categorical, 5
levels): {u, o, i, e, a} - sum-contrast coded
** Random effects: *subject id (SUBJ), item id (ITEM).
Which gives me the following model:
k <- length(levels(h.epenth$RESP))
I <- diag(k-1)
J <- matrix(rep(1, (k-1)^2), c(k-1, k-1))
prior3 = list(R = list(fix=1, V=(1/k) * (I + J), n = k),
G = list(G1=list(V = diag(k-1), n = k),
G1=list(V = diag(k-1), n = k)))
mh1 <- MCMCglmm(RESP ~ - 1 + trait + V1:trait + COART:trait,
random = ~us(trait):SUBJ + us(trait):ITEM,
rcov = ~ us(trait):units,
prior = prior3,
burnin = nburnin,
nitt = nnitt,
thin = nthin,
family="categorical",
data=epenth)
I'm currently running the model on pilot data and with 20000 iterations
only, so the actual values of the estimated coefficients are not
important, but here is the output from summary(mh1), for location effects:
Location effects: RESP ~ -1 + trait + V1:trait + COART:trait
post.mean l-95% CI u-95% CI eff.samp pMCMC
traitRESP.o -3.59168 -6.51885 -0.40005 340.00 0.03529 *
traitRESP.i -6.97617 -10.20436 -3.63351 340.00 < 0.003 **
traitRESP.e -7.58867 -10.16525 -4.44600 17.06 < 0.003 **
traitRESP.a -6.32136 -8.75020 -3.92369 170.22 < 0.003 **
----
traitRESP.o:V1o 0.96720 -1.91595 4.68645 57.00 0.57059
traitRESP.i:V1o 0.34601 -3.13529 3.65788 275.27 0.81176
traitRESP.e:V1o 0.01064 -2.31169 2.48395 179.78 0.94706
traitRESP.a:V1o -0.08993 -2.52314 2.14315 134.33 0.97059
traitRESP.o:V1i -0.57546 -3.82799 2.97239 18.85 0.81765
traitRESP.i:V1i 5.34557 2.23693 8.74984 398.06 0.01176 *
traitRESP.e:V1i 2.43926 0.20358 5.15729 68.81 0.07059 .
traitRESP.a:V1i 1.65012 -1.21129 3.84189 177.83 0.17647
traitRESP.o:V1e -1.16602 -4.16428 2.01458 86.38 0.46471
traitRESP.i:V1e 4.68686 1.38014 7.48422 202.13 < 0.003 **
traitRESP.e:V1e 5.03065 2.33411 7.25455 17.88 < 0.003 **
traitRESP.a:V1e 0.55748 -2.02347 3.63707 4.68 0.74706
traitRESP.o:V1a -0.49801 -4.05488 2.82815 340.00 0.78824
traitRESP.i:V1a 1.20223 -2.48158 4.27902 252.94 0.53529
traitRESP.e:V1a 1.41483 -1.13591 3.77316 254.96 0.28235
traitRESP.a:V1a 3.04426 0.49008 5.59015 340.00 0.01765 *
----
traitRESP.o:COARTo -0.30663 -3.86220 2.94796 287.64 0.88824
traitRESP.i:COARTo 0.92669 -2.28283 4.60833 340.00 0.56471
traitRESP.e:COARTo -0.05533 -2.61372 2.40955 140.88 0.96471
traitRESP.a:COARTo 0.13161 -2.46333 2.22642 340.00 0.92353
traitRESP.o:COARTi -1.37804 -5.35041 1.66590 51.21 0.42353
traitRESP.i:COARTi 5.54896 1.53047 8.69056 340.00 0.00588 **
traitRESP.e:COARTi 2.37792 -0.33337 4.73054 340.00 0.08824 .
traitRESP.a:COARTi 0.59577 -1.90546 2.99576 175.13 0.61176
traitRESP.o:COARTe -1.90106 -5.67091 1.52474 33.76 0.33529
traitRESP.i:COARTe 5.57507 2.15612 8.66226 340.00 0.00588 **
traitRESP.e:COARTe 2.44821 -0.28758 4.69727 340.00 0.05882 .
traitRESP.a:COARTe 0.53713 -1.72573 2.66476 340.00 0.64118
traitRESP.o:COARTa -1.16952 -4.53311 2.54438 45.44 0.52353
traitRESP.i:COARTa 0.96946 -3.23285 4.17157 206.69 0.61765
traitRESP.e:COARTa 0.76110 -1.74846 3.68853 340.00 0.54118
traitRESP.a:COARTa 1.98751 -0.73148 4.65783 29.15 0.15294
1) Knowing that I sum-contrast coded the independent variables V1 and
COART, is it correct for me to interpret
post.mean l-95% CI u-95% CI eff.samp
pMCMC
/traitRESP.i:COARTe 5.57507 2.15612 8.66226 340.00 0.00588 **
/as: "there is a significant increase in "i" responses relative to "u"
responses when the coarticulation in the cluster (i.e. COART) is [e],
for an 'average' V1" (as opposed to only comparing the change in "i" vs
"u" responses when going from uh[u]pu to uh[e]pu, since /u/ is the
baseline for V1 and COART)
2) Following up on this, would contrast coding the response variable
RESP (if there is any sense in doing that, model-wise) allow me to
change the statement above to: "there is a significant increase in "i"
responses relative to any other response vowel when the coarticulation
in the cluster (i.e. COART) is [e], for an 'average' V1", or does the
trait always take "u" as a baseline?
3) Also, I guess I am a confused about how to interpret the significance
codes. Basically, for
post.mean l-95% CI u-95% CI eff.samp pMCMC
traitRESP.o -3.59168 -6.51885 -0.40005 340.00 0.03529 *
traitRESP.i -6.97617 -10.20436 -3.63351 340.00 < 0.003 **
traitRESP.e -7.58867 -10.16525 -4.44600 17.06 < 0.003 **
traitRESP.a -6.32136 -8.75020 -3.92369 170.22 < 0.003 **
I understand this as: subjects responded "u" significantly more often
than "o", "i", "e" and "a", in general (because of contrast coding). Is
this correct?
If so, are these significance tests "independent" from the significance
testing for V1:trait and for COART:trait?
I hope that my explanations are not too unclear...
Thank you in advance for your help!
Best,
Adriana
--
Adriana Guevara Rukoz
PhD Student
Laboratoire de Sciences Cognitives et Psycholinguistique
École Normale Supérieure
29 rue d’Ulm
75005 Paris, France
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