Presentation on theme: "Elements of Survey Methodology Documentation MICS3 Data Analysis and Report Writing Workshop."— Presentation transcript:
Elements of Survey Methodology Documentation MICS3 Data Analysis and Report Writing Workshop
Why is survey documentation important? International standards – it is an expected component of rigorous reporting Facilitates comparison of results with other data sources Lends credibility to the results Demonstrates confidence in survey methodology, implementation and results Provides guidance for future surveys
What should be documented in survey reports? Objectives Survey organization – actors in planning and implementation Target population and sample design Sample design Questionnaires Other survey tools Data collection – fieldwork Data processing Analysis
Objectives To provide up-to-date information for assessing the situation of children and women in [Country]; To furnish data needed for monitoring progress toward goals established by the Millennium Development Goals and the goals of A World Fit For Children (WFFC) as a basis for future action; To contribute to the improvement of data and monitoring systems in [Country] and to strengthen technical expertise in the design, implementation, and analysis of such systems. ???
Survey Organization Implementing agency(ies) Funding agencies Steering committee, advisory/technical committees All actors in planning and implementation
Target Population and Sample Design Planned coverage of the survey Sample frame used Stratification – design features Design stages Sample allocation and selection
Questionnaires Types of questionnaires and data collected with each questionnaire (modules) How questionnaires were customized, translated, back-translated Languages used Pretesting, major revisions [Provide questionnaires as an appendix in Final report]
Other Survey Tools Other survey tools used in the survey Salt test kits Anthropometric equipment GPS Other?
Data collection Selection and training of field staff Field staff organization Data collection in the field Quality control in the field – editing, supervision etc Dates Problems, challenges
Data processing Data processing staff – selection, type of staff, supervision Training of data processing staff Software used The data entry process Editing, recoding, exporting, sample weight calculation, finalization of data sets
Data analysis Organization of analysis Staff involved in analysis Review process
Other Always include information on dates, timelines Use your data quality assessment as a background, even if you do not report on them Assess strengths, weaknesses Problems, challenges, solutions