

Hi All,

Sorry to bother with a
basic question.

I was wondering how R
manages dummy variables when computing factors with more than 2 levels. For
instance in my study I have the variable ‘stress’ with 3 levels (‘pre-tonic’, ‘tonic’,
and ‘pos-tonic’ coded, ‘1’, 2’ and ‘3’ respectively). 

Programs such as SPSS transform
nominal and ordinal categories into sets of dichotomies ( dummy variables) in
such a way that a computed dummy variable 1 (dummy pre-tonic) will assign 1 to
all pre-tonic stress and ‘0’ to all the others. Dummy variable 2 (dummy tonic)
assigns ‘1’ to all tonic data and ‘0’ to the rest. By default SPSS leaves the
last level as the ‘reference category’ (in this case post-tonic) for comparison.
Using what is called the ‘indicator contrast’. Thus, the coding ends up being
something like the example below

 

------------------------------------------------                            Dummy variables              Value     Coding                         (1)    (2)Stress                  1     1.000   .000                  2      .000  1.000                  3      .000   .000

 

Thus, in the outcome,  Beta (B) and Exp (B) do not present the odds
ratio of the dependent variable in relation to the independent variable but odds
ratio of the dummy variables with respect to the reference category (post-tonic
in this case). 

 

 When I run the mix log model in R I get an
outpost like the following.

 

Generalized linear
mixed model fit using Laplace 

Formula: Identif ~ (1
| Subj) + (1 | Item) + Place +  Stress
+      Voicing 

   Data: idcrg1 

 Family: binomial(logit link)

  AIC 
BIC logLik deviance

 1163 1211 -572.6     1145

Random effects:

 Groups Name        Variance Std.Dev.

 Subj  
(Intercept) 0.63178  0.79485 

 Item  
(Intercept) 0.88192  0.93910 

number of obs: 1476,
groups: Subj, 41; Item, 36



 Estimated scale
(compare to  1 )  0.888108 



 Fixed effects:

            Estimate Std. Error z value Pr(>|z|)    

(Intercept)   1.9920    
0.4948   4.026 5.67e-05 ***

Place2       -0.7253     0.4376 
-1.658   0.0974 .  

Place3       -0.1389     0.4478 
-0.310   0.7565    

Stress2       0.8765     0.4493  
1.951   0.0511 .  

Stress3      -0.2386     0.4298 
-0.555   0.5788    

Voicing2      0.6937    
0.3601   1.927   0.0540 . 


---

Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’
1 



 
Correlation of Fixed
Effects:

         (Intr) Place2 Place3  Strss2 Strss3

Place2   -0.466                                   

Place3   -0.447 
0.511                            

Stress2  -0.426 -0.035 -0.002  0.026              

Stress3  -0.451 
0.004 -0.006  0.017  0.485      


Voicing2 -0.356  0.004 -0.023 
0.008  0.020  0.011



  


Based on the index
that appears on Stress in the Fixed Effects outcome (Stress2 and Stress3; same
for Place2 and Place3) . 

Am I correct to assume
that the reference category in this case was the first level and not the last
as it is done in SPSS?

Does R create dummy
variables to calculate the regression?



 
Thanks for your time. I’d
appreciate any help you could provide.

Sincerely,Carlos


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