help zerouse
-------------------------------------------------------------------------------

Title

    zerouse -- Tabulate the pattern of zero digits in a variable

Syntax

        zerouse varname [, pattern(#.#) digit(#) by(varname) generate(name)
               tabulate_options]

Description

    The zerouse function displays the patterns of zero and non-zero digits in
    a variable. The range of possible formats can be defined using an option,
    as can the 'zero' digit, and results can be tabulated against a different
    variable or stored in a new variable for later use.

Options

        +---------+
    ----+ General +----------------------------------------------------------

    pattern(#.#) indicates the number of digits to the left and to the right
        of the decimal point that should be examined. The default is 9.9 and
        often this is a reasonable starting value although it may capture
        rounding errors.  Otherwise, select a value that will look at one
        digit more to the left and to the right than you expect to find, and
        check that these extreme digits contain zeros rather than non-zero
        digits in the output.  You can also select a pattern that is smaller
        than the digits used.  For example, to tabulate records that do and
        do not have a zero in the first decimal place, use pattern(0.1).

    by(varname) displays results using a two way rather than one way
        frequency table, giving you digit pattern cross-classified against
        your variable of choice.

    digit(#) is provided so you can use this program to investigate the
        pattern of use of a digit other than zero.  For example, if you were
        to select the digit 2 then use of the digit 2 would be compared with
        the use of any digit other than 2 (including zero).

    generate(name) allows you to provide a name for a new variable into which
        the patterns will be stored.  This means you can save the zero digit
        use pattern for a number of variables and then cross tabulate them to
        identify consistent patterns of (for example) mistranscription.


        +------------------+
    ----+ Tabulate Options +-------------------------------------------------

    Additional options can be passed to the tabulate command used to format
    output.  If the by(varname) option is not specified the output will be
    displayed in a one way table and the tabulate oneway options are
    available.  If the by(varname) option has been used, output will be
    displayed in a two way table and the tabulate twoway options can be used.

Remarks

    This function is intended to assist with the identification of digit
    preferance problems when cleaning data, and to help identify any
    systematic relationship between digit use and other variables, typically
    the laboratory or instrument that generated the data or the clerk who
    transcribing the data.  It's use is most easily explained using an
    example:

    . zerouse y1, pattern(2.1) sort

          Digit |
        pattern |      Freq.     Percent        Cum.
    ------------+--------------------------------------
           0#.0 |     11,514       86.21       86.21
           ##.0 |        851        6.37       92.59
           #0.0 |        532        3.98       96.57
           0#.# |        424        3.17       99.75
           00.0 |         34        0.25      100.00
    ------------+--------------------------------------
          Total |     13,355      100.00

    The example above shows zero digit use for the variable y1, from which
    the following can be gathered:

    Most values are single digit integers (0#.0).  Some values have a tens
    digit of which about a third have a zero in the units position (#0.0) and
    two thirds have a digit in the units position (##.0).  This suggests the
    values are mainly below ten with a few values that are ten or above.

    Notice that only a few values are not integers and these are all below
    ten (0#.#).  These values may have been measured using greater precision
    but if this was the case we would expect at least a few values of ten or
    above (##.#).  Alternatively, it may be that some two digit values were
    incorrectly transcribed.  Perhaps a decimal point was inserted and this
    reduced these values by an order of magnitude.  Values with this digit
    pattern should probably be checked for transcription errors.  If there
    were multiple paths to the database (different data entry clerks, labs or
    instruments) and this is stored in the database it might also be useful
    to cross tabulate these digit formats with this information, to see if
    all the anomalous values originated in the same place.


Examples

    . zerouse y1
    . zerouse y1, pattern(3.2) sort
    . zerouse y1, pattern(3.2) by(group)
    . zerouse y1, pattern(3.2) by(group) nofreq row

    . zerouse y1, pattern(3.2) digit(2)

Author

    Richard J. Atkins
    London School of Hygiene and Tropical Medicine
    e-mail: richard.atkins@lshtm.ac.uk