Tips for Collecting, Reviewing, and Analyzing Secondary Data
WHAT IS SECONDARY DATA REVIEW AND ANALYSIS?
Secondary data analysis can be literally defined as second-hand analysis. It is the analysis of data or information that was either gathered by someone else (e.g., researchers, institutions, other NGOs, etc.) or for some other purpose than the one currently being considered, or often a combination of the two (Cnossen 1997).
If secondary research and data analysis is undertaken with care and diligence, it can provide a cost-effective way of gaining a broader understanding of specific phenomena and/or conducting preliminary needs assessments.
Secondary data are also helpful in designing subsequent primary research and, as well, can provide a baseline with which to compare your primary data collection results. Therefore, it is always wise to begin any research activity with a review of the secondary data (Novak 1996).
RESEARCH DESIGN AND PURPOSE
Secondary data analysis and review involves collecting and analyzing a vast array of information. To help you stay focused, your first step should be to develop a statement of purpose – a detailed definition of the purpose of your research – and a research design.
Statement of Purpose: Having a well-defined purpose – a clear understanding of why you are collecting the data and of what kind of data you want to collect, analyze, and better understand – will help you remain focused and prevent you from becoming overwhelmed with the volume of data.
Research Design: A research design is a step-by-step plan that guides data collection and analysis. In the case of secondary data reviews it might simply be an outline of what you want
the final report to look like, a list of the types of data that you need to collect, and a preliminary list of data sources.
WHAT TYPES OF DATA AND/OR INFORMATION ARE NEEDED?
The specific types of information and/or data needed to conduct a secondary analysis will depend, obviously, on the focus of your study. For CARE purposes, secondary data analysis is usually conducted to gain a more in-depth understanding of the food and livelihood security status of people living in various countries and/or regions where CARE works. This type of socioeconomic characterization is commonly referred to as a country or poverty profile. It involves collecting information, statistics, and other relevant data at various levels of aggregation in order to conduct a situational analysis of the area (see Data & Indicator List in Appendix 1; refer to the LRSP Guidelines, Annex 5, July 1997). The types of secondary data and information to be collected and summarized should include data related to the following areas:
Demographic (population, population growth rate, rural/urban, ethnic groups, migration trends, etc.), Agroecological climatic zones,
Poverty levels (poverty and absolute),
Employment and wages (formal and informal),
Livelihood systems (rural, urban, on-farm, off-farm, informal, etc), Agricultural variables and practices (rainfall, crops, soil types, and uses, irrigation, etc.), Health (malnutrition, infant mortality, immunization rate, fertility rate, contraceptive prevalence rate, etc.), Health services (#/level, services by level, facility-to-population ratio. etc.), Education (adult literacy rate, school enrollment, drop-out rates, male-to-female ratio, etc), Schools (#/level, school-to-population ratio, etc.),
Infrastructure (roads, electricity, communication, water, sanitation, etc.), Environmental status and problems, and
Local political environment and access.
Special attention should be given to collecting disaggregated data. That is, data that is broken down in the following ways: gender, age, ethnicity, location, etc..
Even when highly disaggregated; however, these “raw” data points alone are often only static or indirect measures of the situation or problems that exist in countries and regions – partial or...
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