Logistic regression for questionnaires on 7 points Likert scale I want to analyze some data of a questionnaire on presence (I deal with experiments on virtual reality). 
The questionnaire was provided twice to particpants performing the experiment, after each of the two provided conditions.
The 6 questions of the questionnaire were evaluated by participants on a 7-points Likert scale.
Following what I found in bibliography, I have to analyze the data in the following way in order to find if the differences between the two conditions are significant:
I have to count the number of answers that have a score of 6 or 7, then I will have for each condition
a variable equal to the mean of the count of 6 and 7 scores among all the 6 questions. Afterwards, I have to treat those two variables as binomially distributed for a logistic regression on group.
My problem is that I don´t know how to perform the logistic regression.
I tried to study but I do not understood how to 
apply it to my case. In addition I have also problems in undestanding how to perform it in R.
Do you also have an example in R?
Let's say that the two variables are (meand +-std): 
Count_condition1 = 1 +- 1.7 and Count_condition1 = 2 +- 2.0  

 A: *

*Under most circumstances I would calculate the scale score as the mean of the items. This is generally a more desirable coding because you don't lose information. You could then just use a t-test to assess the effect of condition. 

*Even if you binary code each item, and calculate the mean or sum of items, you are still left with a variable with 7 different values (i.e., 0,1,2,3,4,5,6 if you used the sum). If you were willing to accept an approximation, you could consider still using a t-test in this case. However, you couldn't use standard binary logistic regression. Perhaps, generalised estimating equations (GEE) might be suitable for predicting repeated measures of proportions. R packages include gee and geepack. Here are some GEE resources that I prepared.


UPDATE
After reading the paper mentioned "Using Presence Questionnaires in Reality", I still think that the scale should be the sum or mean of the six items coded 1 to 7, and that a t-test is the most straightforward tool for group comparison of means.
A: At the end I solved the problem with a  simple chi-square, since I had just to compare two variables whose possible values are 0 or 1.
Still I have not understood the need of having a logistic regression to be honest....
