[R-lang] Weird outcome logit mixed-effect model

[Laura de Ruiter]

Dear R-users and -experts,

I am performing a rather simple analysis on a small data set (pasted 
below this email) and keep getting a to me inexplicable result. Perhaps 
I am missing something here - it would be great if someone could point 
out to me what I am doing wrong.

I want to test whether the factor "Info" (which has three levels: "new", 
"given", "accessible") is a significant predictor for the binary 
variable "DeaccYN". The random factor is "Subject". The distribution of 
the data looks as follows:

-----------------------------------------------------------------------------
xtabs (~ DeaccYN + Info, data = dat)
Info
DeaccYN given new accessible
no 25 42 21
yes 11 0 1
------------------------------------------------------------------------------

This is the model:

----------------------------------------------------------------------------------------------------------
deacc.lmer = lmer (DeaccYN ~ Info + (1|Subject), data = dat, family = 
"binomial")
-----------------------------------------------------------------------------------------------------------------

However, given the distribution above, this outcome seems rather weird 
to me:

---------------------------------------------------------------------------------------------------------
summary (deacc.lmer)
Generalized linear mixed model fit using Laplace
Formula: DeaccYN ~ Info + (1 | Subject)
Data: dat
Family: binomial(logit link)
AIC BIC logLik deviance
60.4 70.82 -26.2 52.4
Random effects:
Groups Name Variance Std.Dev.
Subject (Intercept) 0.18797 0.43356
number of obs: 100, groups: Subject, 21

Estimated scale (compare to 1 ) 0.7316067

Fixed effects:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -0.8635 0.3795 -2.2754 0.0229 *
Infonew -18.7451 2764.2445 -0.0068 0.9946
Infoaccessible -2.2496 1.1186 -2.0110 0.0443 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
(Intr) Infonw
Infonew 0.000
Infoaccssbl -0.315 0.000
----------------------------------------------------------------------------------------------------

Why should the difference between 25/11 and 21/1 be significant, but the 
difference between 25/11 and 42/0 not? Very odd to me seems the standard 
error of 2764!
First I was wondering whether the problem had sth. to do with the fact 
that I had read in an SPSS file, but I keep getting this result even 
when I first save the SPSS file as a tabdelim. text and read it into R 
then. I couldn't find anything strange going on with the Subject factor 
either (and I have also tried the model with "Item" as random factor, 
which didn't change anything).

I was wondering: Is it perhaps a problem for the model that there are no 
cases in the DeaccYN == "yes" category for Info == "given"? And if this 
is the case, why?
Am I overlooking something here?

Any help with this would be very much appreciated!

Thanks a lot in advance for your answers & happy holidays,

Laura de Ruiter

---------------------------------------
The data set:

dat
Subject Info Deacc
1 93 new no
2 93 new no
3 93 given yes
4 93 new no
5 93 given no
6 94 new no
7 94 new no
8 94 given no
9 94 new no
10 94 given no
11 94 given no
12 94 accessible no
13 95 given no
14 95 new no
15 95 accessible no
16 95 new no
17 95 accessible no
18 95 new no
19 97 new no
20 98 new no
21 98 new no
22 98 given yes
23 98 given no
24 101 new no
25 101 new no
26 101 given yes
27 101 accessible no
28 101 new no
29 101 given yes
30 101 given no
31 101 accessible no
32 102 new no
33 102 new no
34 102 given no
35 102 given no
36 102 accessible no
37 104 new no
38 104 accessible no
39 104 new no
40 104 given yes
41 104 new no
42 104 given no
43 104 accessible no
44 107 new no
45 107 given no
46 107 accessible no
47 107 new no
48 109 new no
49 109 given yes
50 109 new no
51 110 accessible no
52 110 new no
53 110 new no
54 110 given no
55 113 new no
56 113 given yes
57 113 new no
58 113 given yes
59 114 new no
60 114 accessible no
61 114 new no
62 114 given no
63 114 accessible no
64 114 new no
65 114 given yes
66 114 accessible yes
67 115 accessible no
68 115 given no
69 115 given no
70 116 accessible no
71 116 new no
72 116 given no
73 116 new no
74 116 new no
75 116 accessible no
76 117 accessible no
77 117 given no
78 117 new no
79 117 new no
80 117 given no
81 117 accessible no
82 118 new no
83 118 accessible no
84 118 given no
85 118 new no
86 118 given no
87 118 accessible no
88 119 given no
89 119 given yes
90 119 given no
91 119 accessible no
92 121 given no
93 121 given no
94 131 new no
95 131 new no
96 131 new no
97 131 new no
98 132 given yes
99 132 given no
100 132 accessible no
------------------------------------------------

-- 
//////////////////////////////////////////////////////

Laura de Ruiter
PhD student
Language Acquisition Group
Max Planck Institute for Psycholinguistics
P.O. Box 310
6500 AH Nijmegen
Netherlands

Phone: 0031-24-3521 456
Homepage: http://www.mpi.nl/Members/LauradeRuiter

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