help mapch
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 Title

    mapch -- map chains of events


Syntax

    mapch begin end [time] [if] [in]


 Description

    mapch maps chains of events. A 'chain' consists of at least one event; an
    'event' in this context is a change of information contained in the
    variable begin into information contained in the variable end.
    Optionally, the time at which the event took place can be stored in the
    variable time and used to map the chains chronologically. It is assumed
    that both begin and end contain unique information, i.e., each value in
    both variables can only appear once. It is also assumed that events in a
    chain can not occur at the same time and that chains are not circular,
    i.e., the begin value of a chain must not be the same as the end value of
    that chain. mapch creates a dataset mapping that contains maps of each
    chain and two or three additional variables: recent, whose value is equal
    to the end value of the chain for each step in that chain; date (only in
    case real time is not available), a fictitious time when the event took
    place allowing to sort the information; and NoOfEvents, the number of
    events per chain. mapch also tabulates the frequency of n-step chains
    with 1<=n<=N (N=total number of events in your dataset). Consider the
    following two examples.

Example 1:

 begin              end
 A                  B
 B                  C
 G                  H
 C                  D
 X                  Y
 H                  I
 Z                  Z1
 Z1                 Z2
 X2                 X3
 Z2                 Z3

mapch will map the chains and create the dataset mapping as follows:

begin         end            recent         date           NoOfEvents
A             B              D              1              3
B             C              D              2              3
C             D              D              3              3
G             H              I              1              2
H             I              I              2              2
X             Y              Y              .              1
X2            X3             X3             .              1
Z             Z1             Z3             1              3
Z1            Z2             Z3             2              3
Z2            Z3             Z3             3              3

Example 2:

 begin              end                time
 A                  B                  17004
 B                  C                  17203
 G                  H                  15000
 C                  D                  18999
 X                  Y                  17034
 H                  I                  16000
 Z                  Z1                 14333
 Z1                 Z2                 14334
 X2                 X3                 15001
 Z2                 Z3                 14335

mapch will map the chains and create the dataset mapping as follows:

begin         end            time           recent         NoOfEvents
A             B              17004          D              3
B             C              17203          D              3
C             D              18999          D              3
G             H              15000          I              2
H             I              16000          I              2
X             Y              17034          Y              1
X2            X3             15001          X3             1
Z             Z1             14333          Z3             3
Z1            Z2             14334          Z3             3
Z2            Z3             14335          Z3             3


Remarks

    mapch was written based on a do-file that was used to overcome the
    challenge of merging datasets in which unique key identifiers changed
    over time, more precisely driver license numbers. A substantial portion
    of the driver license numbers changed over time because this variable's
    format was alpha-numeric and based on the driver's name. In order to
    capture all accident records when merging datasets in which the updated
    number was used with datasets in which the original number was used, the
    name changes had to be mapped in order to create a cross-reference
    dataset. To this end, a solution consisting of a combination of
    appending, indexing and merging was developed, which proved to be
    considerably faster than simply looping; e.g., a dataset containing
    86,000 events with chains of length of up to five events (i.e., drivers
    who changed their name ergo driver's license number up to five times in a
    period of ten years) is mapped in a couple of seconds using mapch, while
    it may take numerous hours in case a simpler combination of looping
    procedures would be used.

Author: Ward Vanlaar (wardv@trafficinjuryresearch.com)