Difference between revisions of "Primary Data Collection"

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== Pilot Questionnaire ==
 
== Pilot Questionnaire ==
The '''first stage''' of the [[Survey Pilot|survey pilot]], the '''pre-pilot''' involves two things: [[Piloting Survey Content |piloting content]] and [[Piloting Survey Protocols| piloting protocols]]. Clear protocols allow researchers to ensure that [[Preparing for Field Data Collection|field collection]] is carried out consistently across teams and/or regions, and ensure that published [[Reproducible_Research|research is reproducible]].
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[[Survey Pilot|Survey pilot]] is the process of carrying out interviews and tests on different components of a survey, including [[Piloting Survey Content|content]] and [[Piloting Survey Protocols|protocols]]. A good '''pilot''' provides the research team with important feedback before they start the process of [[Primary Data Collection|data collection]]. This feedback can help the [[Impact Evaluation Team|research team]] review and improve [[Questionnaire Design|instrument design]], [[Questionnaire Translation|translations]], as well as [[Survey Protocols|survey protocols]] related to [[Piloting Survey Protocols#Interview scheduling|interview scheduling]], [[Sampling|sampling]], and [[Geo Spatial Data|geo data]].
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A '''pilot''' has [[Survey Pilot#Stages of a Survey Pilot|three stages]] - '''pre-pilot''', [[Piloting Survey Content|content-focused pilot]], and '''data-focused pilot'''. Typically, the '''pilot''' is carried out before [[Procuring a Survey Firm|hiring a survey firm]].
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== Pilot Recruitment Strategy ==
 
== Pilot Recruitment Strategy ==
 
== TOR and Procurement ==
 
== TOR and Procurement ==

Revision as of 01:18, 26 May 2020

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.

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Overview

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.

Develop Questionnaire

The first step of primary data collection is to design a survey instrument (or questionnaire). It is important to remember that drafting a questionnaire from scratch can be a time-consuming process, so the research team should try to use existing resources as far as possible. While developing the questionnaire, keep the following things in mind:

  • Modules. Divide the questionnaire into individual modules, each with a group of questions that are related to one aspect of the survey. Unless the context of the study is entirely new, perform a literature review of existing well-tested and reliable surveys to prepare the general structure of the questionnaire. One example of a resource for past studies and questionnaires is the World Bank Microdata Library.
  • Measurement challenges. Often, research teams face challenges in measuring certain outcomes, for instance, abstract concepts (like empowerment), or socially sensitive topics that people do not wish to talk about (like drug abuse). In such cases, try to use indicators that are easy to identify, or build a level of comfort with respondents before moving to the sensitive topics.
  • Translation. Translating the questionnaire is a very important step. The research team must hire only professional translators to translate the questionnaire into all local languages that are spoken in the study location.

Pilot Questionnaire

Survey pilot is the process of carrying out interviews and tests on different components of a survey, including content and protocols. A good pilot provides the research team with important feedback before they start the process of data collection. This feedback can help the research team review and improve instrument design, translations, as well as survey protocols related to interview scheduling, sampling, and geo data.

A pilot has three stages - pre-pilot, content-focused pilot, and data-focused pilot. Typically, the pilot is carried out before hiring a survey firm.

Pilot Recruitment Strategy

TOR and Procurement

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

The next step is to procure a survey firm after issuing detailed terms of reference (TOR), and performing due diligence among local research firm options.

Data Quality Assurance Plan

Obtain Ethical Approval

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).

Train Enumerators

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.

DIME Analytics has created a Stata command, iefolder. Part of the DIME Analytics Stata packageietoolkit , it helps increase project efficiency, and reduces the risk of error in a study.

Related Pages

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Additional Resources