Study Number 4803 - Family Resources Survey, 2002-2003
NEW EDITION INFORMATION
For the fifth edition (October 2014) the data have been re-grossed following revision of the FRS grossing methodology to take account of the 2011 Census mid-year population estimates. New variable GROSS4 added to the dataset.
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
All editions:
Date Variables:
In SAS format (in which the UKDA is supplied with the data) dates are held as a number representing the number of days elapsed since 1st January 1960. The value -1 is used to donate missing data. Upon conversion to SPSS, -1 is treated as the day before January 1st 1960, ie 31st December 1959. As a result, dates of 31.12.59 should be treated as missing data.
Missing Values:
Missing values within the SAS files are defined as A's, B's and C's and relate to 'Skipped', 'Refused' and 'Don't know'. In SPSS these can only be represented as negative numbers and are, therefore, assigned as -1, -8 and -9.
File: transact.por
This file contains information on the imputations and edits carried out by DWP. The information contained within it is meant to be used as an extension of the documentation and not for analysis.
Data conversion information
From January 2003 onwards, almost all data conversions have been performed using software developed by the UK Data Archive. 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 StatTransfer command processors to perform certain format translations. Although data conversion is automated, all data files are also subject to visual inspection by a member of the Archive�s Data Services team.
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 UK Data Archive Data Dictionary file (generally in Rich Text Format (RTF)) is usually provided for each data file, enabling viewing and searching of 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 Archive's data
supply formats. Some of this information is specific to the
ingest
format of the data, i.e. the format in which the Archive received the data
from the depositor. The ingest format for this study was
SPSS
Please follow the appropriate link below to see information on your chosen supply (download)
format.
SPSS (*.sav)
SPSS files (*.sav files)
If SPSS 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 STATA, SAS, Excel, or dBase). If the ingest format was non-delimited or fixed-width text, SPSS files will have been created using SPSS command syntax.
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, STATA files will generally have been created from SPSS via the StatTransfer command processor. Importantly, StatTransfer'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. Discrete 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, it will be logged in the study's SPSS_to_STATA_conversion RTF file.
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)
Tab-delimited text (*.tab files)
If tab-delimited text was not the ingest format, tab-delimited files will have been created from 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 may have been removed by the Archive if necessary.
Issues: Date formats in SPSS are always exported to mm/dd/yyyy in tab-delimited text format. There may 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-2011 13:28:00), will lose the time information and become mm/dd/yyyy. All users of the data in tab-delimited format should consult the UK Data Archive Data Dictionary RTF file(s).
If the data was exported from MS Access, more limited 'data documenter' information is generally available in the RTF variable information files. These files may also contain SQL setup information.
MS Excel (*.xls/*.xslx)
MS Excel (*.xls/*xslx files)
If MS Excel was not the ingest format, Excel files may have been created via StatTransfer. The date and time issues noted under tab-delimited format may also apply here.
SAS (*.sas7bdat and *.sas)
SAS (*.sas7bdat and *sas files)
If SAS was not the ingest format, SAS files will usually have been created via StatTransfer or SPSS. SAS is not one of the Archive's standard supply formats, and the files are likely to have been created in response to a user request. The usual format is *.sas7bdat files plus a .sas proc formats file. Note that the complete internal metadata has been supplied in the accompanying UK Data Archive Data Dictionary file(s).
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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/*.mdbx)
MS Access (*.mdb/*.mdbx files)
Due to substantial incompatibilities between versions of MS Access, the Archive will only make data available in MS Access format if this is the ingest format and/or the database contains important information in addition to the data tables (coding information, forms, queries, etc.).
Conversion of documentation formats
The documentation supplied with Archive studies is usually converted to Adobe Portable Document Format (PDF), with documents bookmarked to aid navigation. The vast majority of PDF files are generated from MS Word, RTF, Excel or plain text (.txt) source files, though PDF documentation for older studies in the collection may have been created from scanned paper documents. Occasionally, some documentation cannot be usefully converted to PDF (e.g. MS Excel files with wide worksheets) and this is usually supplied in the original or a more appropriate format.