Study Number 6427 - Understanding the Importance of Work Histories in Determining Poverty in Old Age: Variables Derived from the English Longitudinal Study of Ageing, 2002-2007
LEGAL AGREEMENT ON CONDITION OF USE
Users should note that these data are subject to the same special conditions of use as SN 5050, the main ELSA study. See
http://www.esds.ac.uk/orderingData/agreements/EnglishLongitudinalStudyofAgeing.pdf for further details.
Acknowledgement for ELSA data:
The ELSA depositor has supplied the following text for users as an example of the acknowledgement that should be used in publications resulting from use of the ELSA study:
"The data were made available through the UK Data Archive. ELSA was developed by a team of researchers based at the National Centre for Social Research, University College London and the Institute for Fiscal Studies. The data were collected by the National Centre for Social Research. The funding is provided by the National Institute of Aging in the United States, and a consortium of UK government departments coordinated by the Office for National Statistics. The developers and funders of ELSA and the Archive do not bear any responsibility for the analyses or interpretations presented here."
DATA PROCESSING NOTES
Data Archive Processing Standards
The data were processed to the UK Data Archive's A standard. A rigorous and
comprehensive series of checks was carried out to ensure the quality of the data
and documentation.�Firstly, checks were made that the number of cases and
variables matched the depositor's records. Secondly, checks were made that all
variables had variable labels and all nominal (categorical) variables had value
labels. Where possible, either with reference to the documentation and/or in
communication with the depositor, absent labels were created. Thirdly, logical
checks were performed to ensure that nominal (categorical) variables had values
within the range defined (either by value labels or in the depositor's
documentation). Lastly, any data or documentation that breached confidentiality
rules were altered or suppressed to preserve anonymity.
All notable and/or outstanding problems discovered are detailed under the 'Data
and documentation problems' heading below.
Data and documentation problems
None encountered.
Data conversion information
From January 2003 onwards, almost all data conversions have been performed
using software developed by the UKDA. This enables standardisation of the
conversion methods and ensures optimal data quality. In addition to its own data
processing/conversion code, this software uses the SPSS and Stat/Transfer
command processors to perform certain format translations. Although data
conversion is automated, all data files are also subject to visual inspection by
a UKDA data processing officer.
With some format conversions data, and more especially internal metadata (i.e.
variable labels, value labels, missing value definitions, data type
information), will inevitably be lost or truncated owing to the differential
limits of the proprietary formats.�A UKDA Data Dictionary file (in rich text
format), corresponding to each data file, is usually provided for viewing and
searching the internal metadata as it existed in the originating format. These
files are called:
[data file name]_UKDA_Data_Dictionary.rtf
Important information about the data format supplied
The links below provide important information about the format in which you have
been supplied the data. Some of this information is specific to the
ingest
format of the data, that is the format in which the UKDA was supplied the
data in. The ingest format for this study was
SAS
Please click below to find out information about the
format that you have
been supplied the data in.
SPSS (*.por)
SPSS portable (*.por files)
If SPSS portable was not the ingest format, this format will generally either
have been created via the SPSS command processor (e.g. if the ingest format is
SPSS .sav, SAS, Excel, or dBase), or if the ingest format was STATA, the SPSS
version will be created via the Stat/Transfer command processor. If the ingest
format was undelimited text, the data will have been read into SPSS using an
SPSS command file.
Issues: There is very seldom any loss of data or internal metadata when
importing data files into SPSS. Any problems will have been listed above in the
Data and Documentation Problems section of this file.
STATA (*.dta)
STATA (*.dta files)
If STATA was not the ingest format, all STATA files will have been created from
SPSS .sav format via the Stat/Transfer command processor. Importantly,
Stat/Transfer's optimisation routine is run so that variables with SPSS write
formats narrower than the data (e.g. numeric variables with 10 decimal places of
data formatted to FX.2) are not rounded upon conversion to STATA because they
are converted to 'doubles ' rather than floats. User missing values are copied
across into STATA (as opposed to being collapsed into a single system missing
code).
Issues: There are a number of data and metadata handling mismatches between SPSS
and STATA. Where any data or internal metadata has been lost or truncated, this
will have been automatically logged in this file:
6427_SPSS_to_STATA_conversion.rtf
Note that the complete internal metadata has been supplied�in the UKDA Data
Dictionary file(s): [data file name]_UKDA_Data_Dictionary.rtf
Tab-delimited text (*.tab)
If tab-delimited text was not the ingest format, tab-delimited files�will have
been�created from SPSS portable files via the SPSS command processor, and also
from Excel and MS Access files. When exporting from Access data tables to
tab-delimited text, the�potentially problematic�special characters (tabs,
carriage returns, line feeds, etc.) allowed by Access memo and text fields� are
stripped out by the UKDA.
Issues: Date formats in SPSS are always exported to mm/dd/yyyy in tab-delimited
text format - so�there be be a�mismatch with the documentation on such
variables. Variables that include both date and time such as dd-mm-yyyy hh:mm:ss
(e.g. 18-JUN-2001 13:28:00), will lose the time information and become
mm/dd/yyyy. If the time information is critical, a new variable will have been
created in the tab-delimited data file by the UKDA. All users of the data in
tab-delimited format should consult the UKDA Data Dictionary file(s): [data file name]_UKDA_Data_Dictionary.rtf
If the data was exported from MS Access, more limited 'data documenter'
information is suppied�in the file(s): [data table name]_variableinformation.rtf
These files may also contain SQL setup information.
MS Excel (*.xls files)
If MS Excel was not the ingest format, Excel files�will have�been�created via
the SPSS command processor. The date and time issues noted under tab-delimited
format�apply to SPSS to Excel conversion via the SPSS command processor.
SAS (supplied as *.dat and *.sas)
If SAS was not the ingest format, all SAS files will have been created from SPSS
.sav format via the Stat/Transfer command processor. The data files are provided
as a fixed-width text file (*.dat) and a SAS command file (*.sas), which when
run will create a SAS dataset. This enables the user to recreate the SAS dataset
and formats library in almost all versions of SAS and all operating systems.
Issues: The main loss of information when converting from SPSS to SAS is
user-missing value definitions. By editing the .sas file, the user can choose
whether to collapse all user-missing values into system missing or preserve
the�value and lose the user-missing definition. To achieve the latter�the
following section of the .sas file should be removed before running it:
/* User Missing Value Specifications */
Note that the complete internal metadata has been supplied�in the UKDA Data
Dictionary file(s): [data file name]_UKDA_Data_Dictionary.rtf
MS Access (*.mdb files)
Due to the substantial incompatibilities between versions of MS Access, the UKDA
only make data available in MS Access format if this is the ingest format and
the database contains important information in addition to the data tables
(coding information, forms, queries, etc.).
Conversion of documentation formats
Electronic and paper documentation supplied with this study is usually
incorporated into the UKDA User Guide (in PDF format). The conversion programmes
used are the latest versions of Adobe PDF Writer for electronic documentation
and Adobe Paper Capture (Acrobat 'plugin' version) for paper documentation.
Occasionally, some�of the electronic documentation cannot be usefully converted
to PDF (e.g. MS Excel files with wide worksheets) and this is supplied in�a more
appropriate format. All User Guides are fully bookmarked.