I read through the import/export manual a few times and did not see this
mentioned and checked the archives as well.  I am dealing with data sheets
generated by Eprime (a software package for generating experimental
psychology paradigms) that output subject responses in a proprietary Edat
file format.  All individual subject response spread sheets can be merged to
form one long file of all subjects.  As an example, if an experiment has 240
responses per subject (120 for each condition, say), each subject will
generate a spreadsheet with 240 rows.  After merging 10 subjects then, a
merged spreadsheet will have 2400 rows, with each subject's responses
starting every 240 rows.  Formally being an SPSS user, I would do a datalist
command that would pick out the columns and rows of interest, and using a
rows command, indicate how many rows were equal to one subject.

Is there an equivalent way to do this directly from a text file to import
into R?  That is, give R one long spread sheet composed of all subjects'
responses, tell R how many rows make up a subject, which rows make up a
discrete condition, and import and flag only the data that I need, and then
organize these as discrete variables so that each subject will have 240
columns of responses and only one row (instead of 240 rows and one column as
in the original text file).  Sorry for the long-winded email, and thanks in
advance for any help on this.

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