How do we make sure that MICS data are of high quality? How can we avoid bias in answers that lead us to the wrong conclusions later? And how can we eliminate and improve questions that just “don’t make sense” to the respondent?
The answer is pre-testing -- the process of gauging the meaning attributed to survey questions ‘before it is too late’, i.e. before a substantial investment is made. The best sampling schemes and estimation strategies will not yield accurate data if the answers provided by the respondent are not meaningful.
Pre-testing involves a number of steps including:
• establishing the intended referential and connotative meaning of each question
• agreeing upon a set of criteria to judge the appropriateness of survey questions
• selecting the methods for judging appropriateness and undertaking research
• reviewing questions for inclusion, revising (the question or intended meaning) or exclusion
Pre-testing a questionnaire is one of the critical components in data collection efforts. This is why in the last two decades, MICS has placed increasing emphasis on building quality into the questionnaire design process through pre-testing.
A pre-test of the 2017 Multiple Indicator Cluster Survey was organized in Freetown, Sierra Leone by Statistics Sierra Leone and UNICEF Sierra Leone , between Jan 23th and Feb 5th. Interviewers were trained on the new MICS6 tools and instruments, including water quality testing and a new questionnaire covering topics such as child functioning, foundational learning skills. More than 100 households were interviewed from 5-10th February in both rural and urban areas leading to substantial improvements in the questionnaire design. The data collection is planned to start in the first week of the month of May 2017.