Primary Data Collection
Primary data collection is the process of gathering data through surveys, interviews, or experiments. A typical example of primary data is household surveys. In this form of data collection, researchers can personally ensure that primary data meets the standards of quality, availability, statistical power and sampling required for a particular research question. With globally increasing access to specialized survey tools, survey firms, and field manuals, primary data has become the dominant source for empirical inquiry in development economics.
- The DIME Research Standards provide a comprehensive checklist to ensure that collection and handling of research data is in line with global best practices.
- Field surveys are one of the most effective medium for primary data collection. Depending on the research question, these interviews may take the form of household surveys, business (firm) surveys, or agricultural (farm) surveys.
- The research team must plan and prepare for primary data collection in advance.
iefieldkitis a Stata package that aids primary data collection. It currently supports three major components of this process: testing survey instruments; survey completion; and data-cleaning and survey harmonization.
While impact evaluations often benefit from secondary sources of data like administrative data, census data, or household data, these sources may not always be available. In such cases, the research team will need to collect data directly using well-designed interviews and surveys, and the research team typically owns the data that it collects. However, even then, the research team must keep in mind certain ethical concerns related to owning and handling sensitive, or personally identifiable information (PII).
Before moving on to the discussion of concerns about ownership and handling, however, it is important to understand the process of collecting primary data. The process of primary data collection consists of several steps, from questionnaire development, to enumerator training. Each of these steps are listed below, and require detailed planning, and coordination among the members of the research team.
Acquire approval from human subjects
There are strict rules about acquiring approval from human subjects. Researchers must understand the ethics and rules for security of sensitive data, and should use proper tools for encryption and de-identification of personally identifiable information (PII).
Compile the survey budget
Researchers must prepare a survey budget before procuring a survey firm. This step allows researchers to calculate expected costs of conducting a study, and compare these with the proposals of firms that submit an expression of interest (EOI).
Determine relevant parameters of a study
After agreeing upon a budget, researchers then decide upon factors like the adequate sampling frame (which is a list of individuals or units in a population from which a sample can be drawn), sample size, and statistical power based on which they can then randomize treatment.
Procure a survey firm
Carry out a pre-pilot
The first stage of the survey pilot, the pre-pilot involves two things: piloting content and piloting protocols. Clear protocols allow researchers to ensure that field collection is carried out consistently across teams and/or regions, and ensure that published research is reproducible.
Refine and review the survey design
The first stage of the survey pilot allows researchers to develop a design for the instrument. The researchers then conduct the second stage of the survey pilot, called content-focused pilot, to review and refine the structure of the instrument.
Translate the survey instrument
After the content-focused pilot, the research firm translates the instrument into all local languages. This step helps to ensure that the survey can be taken by more people, therefore making the study more effective.
Program the instrument
After obtaining IRB approval, researchers program the questionnaire. This step makes it easier to share surveys that rely on methods like Computer-Assisted Personal Interviews (CAPI) or Computer-Assisted Field Entry (CAFE).
Also refer to SurveyCTO coding practices to learn more about programming surveys.
Train enumerators and monitor data quality
After validating the programming of the questionnaire, the researchers train enumerators and monitor data quality to generate a final draft of the instrument. Monitoring can be done in the form of back checks, high frequency checks, as well as other methods.
Maintain an organized data folder
- Oxfam, Brief on Planning Survey Research
- DIME (World Bank), Guide on Planning, Preparing & Monitoring Household Surveys
- DIME Analytics (World Bank), Guidelines on Preparing for Data Collection
- Oxfam, Case study on using electronic data collection (SurveyCTO) and Stata to improve data quality in the field