IPA's Research Protocols

Every research project at IPA is required to follow the below research protocols, or "Minimum Must Dos," in order to ensure that IPA produces high-quality research. IPA maintains a suite of technical tools, trainings and support staff so that researchers can maintain compliance with these research protocols.
 
Please email researchsupport@poverty-action.org if your research project requires support from IPA's Global Research & Data Support team in order to meet these requirements.

Data Quality

  • Create survey plan before launch: The survey plan is an operational plan that covers timelines, staffing needs, logistics, and procurement for your survey, for all stages including questionnaire development, training, piloting, tracking, interviews, and quality assurance. Your survey plan must be in line with your budget(s); for example, you cannot survey more respondents in the baseline than your budget estimated — without overspending during your endline.
  • Create data quality assurance plan and materials before launch: The data quality assurance plan lays out in detail the requirements for backchecks, high frequency checks, accompaniments, spot checks, and any other data quality assurance activities. The scope of the data quality assurance plan should not only include technical products (e.g. customizing the high frequency check template), but also data flow, roles and responsibilities, reporting schedules, actionable items based on output, and incentive programs for the field team. It also includes your staffing needs, which may change over the course of the survey (e.g., accompaniments become less frequent later in the survey).    
  • Bench test survey (ideally at least two weeks in advance): Bench testing means testing your survey in the office with a minimum of three different testers. You will save time and money by making sure your survey works well BEFORE launching field data collection. Bench testing is an iterative process wherein testers run the survey in different scenarios and provide feedback, while the programmer(s) make changes; note that even small changes to a survey must go through the bench testing process again, as it is easy to make mistakes that affect other parts of the survey. This process works best if the "paper" survey is considered mostly complete and has already been reviewed by central decision-makers on the project.
  • Pilot survey (ideally at least one week in advance): Every survey must be piloted prior to the beginning of the survey in communities outside your study sample. Your pilot should look as close to actual surveying as possible — you may even decide not to tell your field team it is a pilot. Ideally, every question that is included in the final survey should be piloted prior to launch. For surveys using DDC, a pilot should include field testing of both the survey program and devices. Remember to leave time to make corrections to errors you identified during piloting.
  • Accompany surveyors in first week of survey: Field supervisors must accompany a subset of field officers' interviews to monitor field officer performance and to check for survey issues. All field officers must be personally accompanied at least once during the first week of the survey. Accompaniments can be scaled down as the survey progresses, especially by leveraging digital supplements like audio recordings and meta-data. 
  • Implement and act on high frequency checks: High frequency checks provide insight into ongoing field team and data quality concerns before they become too entrenched or too late to manage. By running HFCs, you can regularly analyze (comparative) field officer performance, compliance with ethics requirements, response frequencies and outliers, duplicates, and other project-specific data quality issues. HFCs are meant to provide the evidence needed to successfully guide and manage a field team on a daily basis, and thus must be accompanied by strict guidance on roles and responsibilities, reporting schedules, and triggered actions (e.g. what outliers would trigger re-interviewing a household).
  • Implement and act on backchecks: A backcheck (also known as a field audit or re-interview) refers to when a highly qualified field officer (also known as a backchecker) visits a respondent a second time to re-administer a selection of questions from the original questionnaire. Those backcheck responses are then compared to the original responses. The bcstats program helps you to identify discrepancies between answers, and thus to identify problems with your questionnaire, your field team, or both. Your quality assurance plan should have included a backcheck randomization plan, as well as an action plan for what to do when you encounter discrepancies.
  • Double enter & reconcile paper surveys: Although paper surveying is now uncommon, there are strict protocols for data entry from paper surveys. Each survey must be entered by two separate data entry operators who cannot compare responses. When there are discrepancies between their entries, they must be reconciled by a third data entry operator who looks at the original survey closely. In-house data entry can be replaced by online firms, which also provide double entry and allow for you to review discrepancies against the original survey responses. 

Data Security & Research Ethics

  • Maintain IRB approval throughout project lifecycle (e.g. submissions, renewals, amendments, human subjects certificates): Any study conducting human subjects research must have the approval of at least one Institutional Review Board (IRB); note that each project is different, so you should consult with your PIs and IRB Coordinator about how best to get IRB coverage for your project. A typical lifecycle includes approval of the initial research protocol, annual renewals, and amendments when critical items change, such as the questionnaire, staffing, research protocol, or risk level. All project staff, partners and investigators who can see encrypted personally identifying information (PII) must have up-to-date human subjects certificates. Any deviation from the protocol, or any unexpected risk to respondents, must be reported as unexpected events to the IRB. Use Salesforce to keep track of all IRB approvals and upcoming renewal dates.
  • Create data security plan and set up encryption before launch: Respondents' confidential data should be encrypted at all stages, starting at the moment of data collection. This includes while it is on the data collection device, during wireless transmission, while on an external server (e.g., SurveyCTO), when it is on a cloud storage system (e.g., Box or Dropbox), and while on laptops and removable media (hard drives, flash drives). Any time the data is stored on a server that is not controlled by IPA, it must be separately encrypted so that the company that controls the server cannot access the data. You must plan beforehand how you will ensure encryption at each of these steps, and how it will be maintained after your project has been officially closed if you are retaining any PII. If any un-encrypted data is uploaded to the cloud or e-mailed, you must file an unexpected event report to your IRB(s) and comply with any ruling they make.
  • Maintain data security plan (especially encryption) throughout project lifecycle: At every stage of the project lifecycle, data should be properly protected. Among other things, this means personally identifying information (PII) should remain encrypted during storage and transmission, and passwords should be restricted to the critical members of your IRB research staff.
  • Use new UID in deidentified dataset: When you share or publish un-encrypted data, it must be deidentified, i.e. there must be no identifying information in the dataset, such as name or address, or a combination of variables that can be used to identify a respondent. You should also replace your original unique identifier (UID) with a new unique identifier. You should do this at the end stage of your project, when you have finished matching across waves or different data collection activities.
  • Retire your project with all IRBs once the project is complete: Once your study is complete, you should retire or otherwise officially close out your IRB with all the reviewing IRBs. For IPA IRB, you should retire your study when (A) all study interventions and activities are complete, and (B) you are no longer actively, regularly working with identified data. Other IRB(s) may have slightly different standards or procedures, so you should check with your reviewing IRB administrator(s) where relevant as well.

Knowledge Management & Transparency

  • Back up data in at least two locations: You must have at least two copies of the data available at all times. During data collection, this will likely mean on a SurveyCTO server, as well as on a laptop and synced to Box; do not delete server data until it has fully synced to Box, as laptop theft is somewhat common. Post data collection, this could mean backing up your data on an external hard drive on the extremely rare chance that a major cloud service like Box or Dropbox fails.
  • Save ALL project files to Box: IPA project files must be stored in the IPA_Country Programs/CP_Projects superstructure on Box. This includes in particular: raw data files, final versions of questionnaires, back check questionnaires, survey manual, project log and survey notes, high frequency check files, analysis do-files, IRB documentation, and replication code. (If your project uses Dropbox, the files must be synced to Box through a MIST sync program.)
  • Register project with AEA: All IPA studies must register with the American Economic Association (AEA)'s database for social science randomized controlled trials. A pre-analysis plan is not required.