This file contains the online help available that is also available from inside the SDA subset program (by selecting the corresponding word highlighted on the screens for selecting options).

CONTENTS OF ONLINE HELP

• Subset Data File Characteristics
  • Type of data file
  • Order of variables on the file

• Codebook for Subset Data

• Data Definitions for Statistical Programs
  • SAS data definitions
  • SPSS data definitions
  • Stata data definitions
  • XML definitions for DDI-2
  • DDL definitions for SDA

• Filter(s) for Selecting Cases
  • Numeric filter variables
    • Open-ended Ranges using '*' and '**'
  • Character variables as filters
  • Pre-set selection filters

  • Specifying Variables to Include in the Subset
    • Specifying names of individual variables
    • Specifying groups of variables
      • To see what is in a group
      • Select ALL variables from a group
      • Select SOME variables from a group
        Tips on selecting multiple variables from a list
        • Windows
        • Macintosh

  ---

  Data File to Produce

  Data File Characteristics

  The data file produced by the subsetting procedure is a simple text file (an ASCII file). The file has one line (record) per case, and each variable is placed into a fixed set of columns.

  The values of each variable are placed into adjacent columns in the data record. By default, there are no extra blanks or commas between adjacent variables. As an option, the user may specify that adjacent variables be separated either by a blank space or by a comma.

  Type of data file

  The data file can be one of the following:
  1. Text file, with no added blanks between variables
  2. Text file, with a blank inserted between each variable
  3. CSV (Comma Separated Values) file, with a comma inserted between each variable, and a header record containing the names of the variables.

  Having a blank or a comma between variables may facilitate reading of the data file by database or spreadsheet programs (like Excel). Note that delimiters do not matter for SAS, SPSS, Stata, SDA, or other statistical packages. They can read a data file in fixed-column format either with or without delimiters between variables.

  Order of variables on the file

  The first variable in the subset file will be the CASEID variable. If individual variables have been specified in the appropriate text box, those variables will come next, in the order specified. Finally, the remaining variables will be output in the same order found in the codebook.

  ---

  Codebook for Subset Data

  A codebook can be generated that documents the variables included in the subset data file. For each variable, the codebook typically includes:
  • the name and the long label of the variable
  • the text of the question that produced the variable
  • the category codes and labels
  • the column location of the variable in the data record
  • certain properties of the variable such as the number of decimal places and the missing-data codes (if any).
  A table of contents listing the name and long label of each variable is included at the front of the codebook.

  The codebook is a text file formatted for printing. It should be printed with a fixed width (non-proportional) font such as Courier. Since the codebooks generally use between 70 and 80 characters per line, a 10-point font is a good choice.

  The codebook file has a new-page character (form-feed) every 60 lines. Note, however, that not all printers will recognize that character and skip to a new page. In such cases you may have to hand-edit the file to produce the page breaks you want.

  ---

  Data Definitions for Statistical Programs

  SAS data definitions

  The SAS data definitions include all the necessary information to create a SAS data library for the subset of variables selected on this run. Before using this file on your computer, however, it will be necessary to add the name of the subset data file and the directory name for the data library on your computer to be used as input to this run. The place to put those names is clearly indicated near the top of the file of data definitions.

  The SAS data definitions include the 'DATA IN' command, with location information, and the 'LABEL' section with variable labels, There is also a 'PROC FORMAT' section with category labels; the corresponding 'FORMAT' command associates each label with a variable. There is also a section of 'IF' statements, which set missing-data and out-of-range values of each variable to the SAS missing-data code '.' (a period). A 'PROC DATASETS' command is added after the data definitions; this will generate a list of variables created by SAS.

  ---

  SPSS data definitions

  The SPSS data definitions include all the necessary information to create an SPSS system file for the subset of variables selected on this run. Before using this file on your computer, however, it will be necessary to add the name of the subset data file on your computer to be used as input to this run. The name is put after the 'DATA LIST' command in the place indicated in the file; replace the 'x' with the name you gave the data file. For example, if you saved the data file as 'mydata.txt' in the directory 'C:\mywork', replace 'x' in the SPSS data definitions with "C:\mywork\mydata.txt". It is best to specify the entire pathname for the data file, and to put it in double quotes, so that SPSS can find it on your computer.

  If you will be running SPSS under Windows, there is a simple way to use the file of SPSS syntax commands: First, change the extension of this file from '.txt' (with which it was downloaded) to '.sps'. Then in Windows, simply double-clicking on the '.sps' file will open SPSS and put this file in a syntax window. You can edit this file so that it contains the name of the data file that you saved. Note that you should include the entire pathname for the data file (for example: C:\mywork\mydata.txt) so that SPSS can find it. Then highlight the whole syntax file and click 'run'. This generates the system file. Switch to the data window to view it. If you get a warning about an obsolete specifier or 'set' command, just ignore it. You can then proceed to analyze the data.

  The SPSS data definitions generated by the subset procedure include the 'DATA LIST' command, with location information, the 'VARIABLE LABEL' section with variable labels, and the 'VALUE LABELS' section with category labels. There is also a section with 'MISSING VALUES' statements, which may define certain values of each variable as missing-data values. There may also be some 'IF' statements which set out-of-range values of each variable to the SPSS system-missing code.

  To create a system file, it will be necessary to specify the name to assign to the system file; that name is put in the 'SAVE' command in the indicated place near the end of the file. Replace 'y' with the file name you want. The 'SAVE' command at the end of the file includes the 'MAP' option, in order to generate a list of variables created by SPSS. The 'COMPRESSED' option is also specified for the system file, since many users prefer to save disk space; that line can be removed, if you prefer to save the file as an uncompressed file.

  Note that if you are running SPSS under Windows, you can create a '.sav' file interactively. However, you may find that a file named 'y' has been saved on your disk (probably in the 'C:\Program_Files\SPSS' directory), unless you delete the 'SAVE' command from the SPSS syntax file before you click on 'run'.

  ---

  Stata data definitions

  The Stata data definitions include all the necessary information to create a Stata system file for the subset of variables selected on this run. However, you will have to do two things to use the file generated by the subset routine:
  1. Split the file into two files, using an editor.
     • The first part of the file generated by the subset program is a Stata do file, which is a file of commands for Stata to execute. Save this part of a file in a new file with any name you like; it should have the suffix '.do'.

       The 'do file' contains category labels and missing-data codes.

     • The second part of the file generated by the subset program is a Stata dictionary file, (the part beginning with 'dictionary using Y'). Save this second part of the file in another file with any name you like; it should have the suffix '.dct'.

       The 'dictionary file' contains, for each variable, the type, input format, and label.

  2. Insert actual file names into the files you have created.
     • The 'do' file refers to the dictionary file as 'X' on the line containing 'infile using X'. Change the 'X' to the name of the dictionary file you created (from the second part of the file generated by the subset program).

     • The first line of the 'dictionary' file contains 'dictionary using Y'. Change the 'Y' to the name of the text (ASCII) data file generated by the subset program; this will be the name you used when you saved the data file.
  Once you have broken up the file into two parts and inserted the appropriate file names, you can use the files within Stata. For example, if you gave your do-file the name 'myfile.do', you would start up Stata and give the command 'do myfile'. Stata would then execute the commands in 'myfile.do' and set up the variables as a Stata data file. You could then run any of the available analyses.

  ---

  XML definitions for DDI-2

  The Data Documentation Initiative (DDI) is a standard for documenting data files using XML. The subset procedure can generate documentation for your subset using the conventions of the DDI, version 2.

  For more information on the DDI, see the main DDI Web site.

  ---

  DDL definitions for SDA

  A DDL file contains information on each variable written in the Data Description Language. The DDL file, together with the subset data file, can be used to generate an SDA dataset (or an older CSA dataset).

  A DDL file is produced automatically by the subset procedure, even if you do not request that it be sent to you. The DDL file is the basic source of documentation for the subset. The codebook and the data definitions for SAS, SPSS, Stata, and DDI are all derived from the DDL file.

  ---

  Filter(s) for Selecting Cases

  If no filter variables are specified, the subset data file will include a record for every case in the original data file. If you want to include only a subset of the cases in the full data file, you must specify one or more filter variables and indicate which codes of those variables to include.

  Some filter variables may be set up ahead of time by the data archive. That type of filter variable is discussed below.

  Numeric variables as selection filters

  Basic filter use
  The name of each filter variable is followed, in parentheses, by a single value such as 'gender(2)' or a range of codes such as 'age(30-50)', to limit the analysis to cases having those codes.

  Multiple ranges and codes may be specified.
  For example: age(1-17, 25, 95-100)

  Multiple filter variables
  If you specify more than one filter variable, a case must satisfy ALL of the conditions in order to be included in the table.
  For example: gender(1), age(30-50)

  Open-ended Ranges using '*' and '**'
  A single asterisk, '*', can be used to specify that all cases with VALID codes for a variable will pass the filter.
  For example: age(*) includes all cases with valid data on the variable 'age'.

  In a range, the '*' can be used to signify the lowest or highest VALID value. For example: age(*-25,75-*). This filter would include all VALID values less than or equal to 25 and all VALID values greater than or equal to 75. However, any missing-data values within those ranges would still be excluded.

  In a range, two asterisks '**' can be used to signify the lowest or highest numeric value, regardless of whether or not the codes are defined as missing data. For example: age(50-**) would include ALL numeric values greater than or equal to 50, including data values like 98 or 99, even if they had been defined as missing-data codes. However, any character missing-data values would still be excluded. Note that '**' cannot be used alone in a filter variable. It can only be used as part of a range.

  Character variables as selection filters

  The syntax for specifying character variable filters is similar to the syntax for numeric variables but with a few differences. Like numeric variable filters, character variable filters specify the variable name followed by the filter value(s) in parentheses.
  For example: city( Atlanta )

  Multiple filter values can be specified, separated by spaces or commas:
  city( Chicago,Atlanta Seattle)

  Character variable filters are case-insensitive. For example, the following filters are functionally identical:
  city( Atlanta )
  city( ATLANTA )
  city( AtLAnta )

  If a filter value contains internal spaces or commas, it must be enclosed in matching quotation marks (either single or double):
  city( "New York" )
  state("Cal, Calif")

  A filter value containing a single quote (apostrophe) can be specified by enclosing it in double quotes:
  city( "Knot's Landing" )

  Or, conversely, a filter value containing double quotes can be specified by enclosing it in single quotes:
  name( 'William "Bill" Smith' )

  Leading and trailing spaces, and multiple internal spaces, are NOT significant. The following filters are all functionally equivalent:
  city( "New York    " )
  city( "New    York" )
  city( "   New York    " )

  Note that ranges, which are legal for numeric variables, are not allowed for character variables:
  The following syntax is NOT legal: city( Atlanta-Seattle)

  Pre-set selection filters

  One or more filter variables may be pre-set by the archive so that they appear automatically on the option screen for the various analysis programs. The user can then select the desired filter-variable categories from a drop-down menu.

  For example, the variable 'gender' might be set up as a pre-set filter variable. The user could then choose 'Males' or 'Females' (or 'Both genders') from the drop-down list.

  Pre-set filter variables are only a convenience for the user. The same result can be obtained by using the regular selection filter option to specify the filter variable(s) and the desired code categories to include in the analysis.

  One possible difference between the pre-set filters and the regular user-defined selection filter specifications concerns cases with missing-data on the filter variable. A user-defined filter specification of 'gender(*)' would include all cases with a valid code on the variable 'gender', excluding any cases with missing-data on that variable, if there are any. On the other hand, selecting the '(Both genders)' option (or whatever the '##none' specification is labeled) for a pre-set filter would generally include cases with missing-data on the filter variable. (The '##none' specification has the same effect as not using that variable as a filter at all.)

  ---

  Specifying Variables to Include in the Subset

  Specifying names of INDIVIDUAL variables

  One way that variables can be selected for inclusion in the subset is by entering their names in the text box. Multiple variable names must be separated by spaces or commas. You can now include variables created by RECODE and COMPUTE in a subset, by specifying the individual names of the created variables.

  To select more than a few variables, you will probably want to use the group selection procedure. However, the group selection procedure is available only for the original variables set up with the dataset, and is not available for the variables created by RECODE or COMPUTE. Note that both individually specified variables and groups of variables can be combined together in the same subset.

  Variables named individually will be output onto the data file immediately after the CASEID variable (which is always the first variable put into the subset data file). Then the variables specified by group follow, in the order they are found in the codebook.

  ---

  Specifying GROUPS of variables

  TO SEE what is in a group

  To view the contents of each group, click on the group's name. This will take you to the listing of the group's variables in the Standard Variable List of the codebook for the study. Clicking on the name of a variable in that list will take you to the codebook entry for that variable.

  TO SELECT variables from a group

  • Select ALL variables from a group
    If you select 'All' for a particular group, ALL of the variables in that group will be included in the subset.

  • Select SOME variables from a group
    If you want to include in your subset SOME, but not all, variables in a particular group, select 'Some' for that group. On a subsequent screen you will be asked to indicate which variables in the group you want to include, by selecting variable names from a scrolling list of all variables in the group.

  • Tips on selecting multiple variables from a list

    Windows PCs

    • To select multiple SEQUENTIAL items in a list:
      • Click the first item you want to select, and then drag the cursor to the last item you want to select.
      • To cancel the selection, click any item in the list.
      • Or click the first item you want to select, press and hold down SHIFT, and click the last item you want to select. Both items, and all items in between, are selected.
      • To cancel the selections, release SHIFT and click any item.

    • To select multiple NONSEQUENTIAL items in a list
      • Press and hold down CTRL, and click each item you want to select.
      • To cancel a selection, press and hold down CTRL, and click the item again.

    Macintosh

    • To select multiple SEQUENTIAL items in a list:
      • Click the first item you want to select, press and hold down SHIFT, and click the last item you want to select. Both items, and all items in between, are selected.
      • To cancel the selections, hold down SHIFT and click any selected item.

    • To select multiple NONSEQUENTIAL items in a list
      • Press and hold down the Command/Apple key, and click each item you want to select.
      • To cancel a selection, press and hold down Command, and click the item again.

  ---