Kenya - Nairobi Urban Health and Demographic Surveillance System 2002-2010

Reference ID

INDEPTH.KE031.2.v6

Year

2002

Country

Kenya

Producer(s)

Dr.Alex Ezeh - Site Leader, KE031
Dr.Donatien Beguy - Site Representative, KE031

Sponsor(s)

Bill and Melinda Gates Foundation, USA - - Current Funder
William and Flora Hewlett Foundation, USA - - Current Funder
Swedish International Development Cooperation Agency - - Current Funder
Wellcome Trust, UK - - Previous Funder
Rock

Collection(s)

Africa Region – Release 2013

Metadata

Documentation in PDF

Created on

Jul 01, 2013

Last modified

Jul 22, 2015

Page views

154427

Data Dictionary

Data File: KE031.2.v6

Content	This file contains the INDEPTH Core Microdataset. The file was generated using ETL through Pentaho Kettle.
Cases	637510
Variable(s)	20
Version	2.6
Producer	Statistics and Surveys Unit (SSU)
Missing Data	Missing Data is coded as follows: -Missing Data: No data or a missing data is assigned the code(95,995,etcetera). All missing values should be coded as 5,95,995, etcetera, depending on the value of the largest valid code in that variable. - Response Not Within the Pre-Defined Range/Domain: A data code(96,996,etcetera) provided where response was outside the range/domain pre-defined during study design. A variable that contains this code is often succeeded by a variable that contains the specific response. Check the succeeding variable to ensure no missing values exist where a response was expected. -Refusals: A data code (97,997,etcetera) is used to indicate that the respondent refused to respond to this question. -"Don't Know" Responses: A data code(98,998,etcetera) is used to indicate that the respondent did not know the answer to the question. -Skipped Questions: A data code(99,999,etcetera) is used to indicate that the respondent was not eligible to answer the particular question.
Processing Checks	The following processing checks are carried out during the ETL process:- -Range Checks: This ensures that every variable contains only data within a predefined domain of valid values -Skip Checks: This will verify that skip patterns have been followed appropriately during data collection and data entry. -Consistency Checks: These checks ensure that values from one question are consistent with values from another question. This is especially important where two or more variables contain similar or interlinked information. -Typographical Checks: These checks are necessary to identify and correct typographical and spelling errors in variables. -Checks Against Reference Data: These checks ensure that newly added data is consistent with existing data about the statistical unit under survey. This is especially important for longitudinal surveys and embedded studies. This check could be done by pre-printing information on questionnaires during pre-survey activities. Some corrections are made automatically by the program(80%) , others by visual control of the questionnaires (20%) Detailed documentation of the editing of data can be found in the "Standard Procedures Manual" document provided as an external resource.

Variables

Name	Label	Question
RecNr	RecNr

CountryId	CountryId

CentreId	CentreId

IndividualId	IndividualId

Sex	Sex

DoB	DoB

EventCount	EventCount

EventNr	EventNr

EventCode	EventCode

EventDate	EventDate

ObservationDate	ObservationDate

LocationId	LocationId

MotherId	MotherId

DeliveryId	DeliveryId

Cause1	Cause1

Cause2	Cause2

Cause3	Cause3

Likelihood1	Likelihood1

Likelihood2	Likelihood2

Likelihood3	Likelihood3