DELIMITER= or SEPARATOR= data field delimiters = " ", fixed fields

It is often convenient to organize your data with delimiters, such as commas, semi-colons or spaces, rather than in fixed column positions. However, often the delimiter (a Tab, space or comma) only takes one column position. In which case, it may be easier to include it in the CODES= or use MFORMS= or FORMAT=.

 

To check that your data file has decoded properly, look at RFILE=

 

To do this, specify the following command DELIMITER= value (or SEPARATOR= value). This value is the separator.

 

Examples: DELIMITER= " "  fixed-field values

 DELIMITER= ","  comma-separated values CSV. The , must be ","

 DELIMITER=BLANK blank-separated values

or DELIMITER=SPACE space-separated values

 DELIMITER=TAB tab-separated values

 DELIMITER=";"  semi-colon separated values. The ; must be ";", otherwise it is treated as a comment.

 

When decoding delimited values, leading and trailing blanks, and leading and trailing quotation marks, " " and ' ' in each value field are ignored. Responses are left-aligned, and sized according to XWIDE=.

 

For NAME1= and ITEM1=, specify the value number in the data line, starting with 1 as the leftmost value. FORMAT= does not apply to this data design.

 

Combine your person name and demographic information into one field that is to be referenced by NAME1=.

 

Example 1 of a data line:

 

; the following is ONE data line:

 

 "01"; 02; "01"; "01"; "01"; 00; 02; 00; "01"; 02; 02; 02; 02; 00; 02; "01"; "01"; 02; 02 ; 00; 02; "01"; 00; 02; 00; ROSSNER, MARC DANIEL

 

;which decodes as:

 

01020101010002000102020202000201010202000201000200ROSSNER, MARC DANIEL

 

 ITEM1=1     ; item responses start in first field

 NI=25       ; there are 25 responses, i.e., 25 response fields

 NAME1=26    ; the person name is in the 26th field

 DELIMITER = ";" ; the field delimiters are semi-colons

 XWIDE=2     ; values are right-aligned, 2 characters wide.

 CODES=000102 ; the valid codes.

 NAMLEN=20   ; override standard person name length of 30 characters.

 

Example 2 of a data line:

 

; the following is ONE data line:

 

ROSSNER - MARC DANIEL, "01", 02 , "01", "01", "01", 00, 02, 00, "01", 02, 02, 02, 02, 00, 02, "01", "01", 02, 02, 00, 02, "01", 00, 02, 00

 

;which decodes as:

 

01020101010002000102020202000201010202000201000200ROSSNER - MARC DANIEL

 

 ITEM1=2     ; item responses start in second field

 NI=25       ; there are 25 responses, i.e., 25 response fields

 NAME1=1     ; the person name is in the 1st field

 DELIMITER = "," ; the field delimiters are commas (so no commas in names)

 XWIDE=2     ; values are right-aligned, 2 characters wide.

 CODES=000102 ; the valid codes

 NAMLEN=20   ; override standard person name length of 30 characters.

 

Example: Here is the data file, "Book1.txt"

 fred,1,0,1,0

 george,0,1,0,1

 

 Here is the control file:

 name1=1 ; first field

 item1=2 ; second field

 ni=4  ; 4 fields

 data=book1.txt

 codes=01

 delimiter = ","

 &END

 looking

 viewing

 peeking

 seeking

 END LABELS

 

 Here is the reformatted file from the Edit Pull-Down menu: View Delimiter File:

 1010fred

 0101george

 

Suggestion:

If you data file can be conveniently organized in columns:

 fred  ,1,0,1,0

 george,0,1,0,1

 

then process the data file as fixed width fields

 NAME1 = 1 ; start of person label "fred"

 NAMELENGTH = 6 ; up to first comma

 ITEM1 = 8  ; first column of numbers

 XWIDE = 2 ; number + comma

 CODES = "0,1,0 1 " ; the data codes "0 1 " are for the last codes on the line.

 

this will then analyze the data as a standard fixed-column rectangular data matrix.

Coming Rasch-related Events
July 31 - Aug. 3, 2017, Mon.-Thurs.	Joint IMEKO TC1-TC7-TC13 Symposium 2017: Measurement Science challenges in Natural and Social Sciences, Rio de Janeiro, Brazil, imeko-tc7-rio.org.br
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Jan. 5 - Feb. 2, 2018, Fri.-Fri.	On-line workshop: Practical Rasch Measurement - Core Topics (E. Smith, Winsteps), www.statistics.com
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May 25 - June 22, 2018, Fri.-Fri.	On-line workshop: Practical Rasch Measurement - Core Topics (E. Smith, Winsteps), www.statistics.com
June 29 - July 27, 2018, Fri.-Fri.	On-line workshop: Practical Rasch Measurement - Further Topics (E. Smith, Winsteps), www.statistics.com
Aug. 10 - Sept. 7, 2018, Fri.-Fri.	On-line workshop: Many-Facet Rasch Measurement (E. Smith, Facets), www.statistics.com
Oct. 12 - Nov. 9, 2018, Fri.-Fri.	On-line workshop: Practical Rasch Measurement - Core Topics (E. Smith, Winsteps), www.statistics.com
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