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• 1. Data collection: Experiences and lessons learned by asking sensitive questions in a remote coca growing region in Peru Archived

  Articles and reports: 12-001-X201200211752

  Description:

  Coca is a native bush from the Amazon rainforest from which cocaine, an illegal alkaloid, is extracted. Asking farmers about the extent of their coca cultivation areas is considered a sensitive question in remote coca growing regions in Peru. As a consequence, farmers tend not to participate in surveys, do not respond to the sensitive question(s), or underreport their individual coca cultivation areas. There is a political and policy concern in accurately and reliably measuring coca growing areas, therefore survey methodologists need to determine how to encourage response and truthful reporting of sensitive questions related to coca growing. Specific survey strategies applied in our case study included establishment of trust with farmers, confidentiality assurance, matching interviewer-respondent characteristics, changing the format of the sensitive question(s), and non enforcement of absolute isolation of respondents during the survey. The survey results were validated using satellite data. They suggest that farmers tend to underreport their coca areas to 35 to 40% of their true extent.

  Release date: 2012-12-19

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• 2. Why one should incorporate the design weights when adjusting for unit nonresponse using response homogeneity groups Archived

  Articles and reports: 12-001-X201200111689

  Description:

  When there is unit (whole-element) nonresponse in a survey sample drawn using probability-sampling principles, a common practice is to divide the sample into mutually exclusive groups in such a way that it is reasonable to assume that each sampled element in a group were equally likely to be a survey nonrespondent. In this way, unit response can be treated as an additional phase of probability sampling with the inverse of the estimated probability of unit response within a group serving as an adjustment factor when computing the final weights for the group's respondents. If the goal is to estimate the population mean of a survey variable that roughly behaves as if it were a random variable with a constant mean within each group regardless of the original design weights, then incorporating the design weights into the adjustment factors will usually be more efficient than not incorporating them. In fact, if the survey variable behaved exactly like such a random variable, then the estimated population mean computed with the design-weighted adjustment factors would be nearly unbiased in some sense (i.e., under the combination of the original probability-sampling mechanism and a prediction model) even when the sampled elements within a group are not equally likely to respond.

  Release date: 2012-06-27

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• 1. Data collection: Experiences and lessons learned by asking sensitive questions in a remote coca growing region in Peru Archived

  Articles and reports: 12-001-X201200211752

  Description:

  Coca is a native bush from the Amazon rainforest from which cocaine, an illegal alkaloid, is extracted. Asking farmers about the extent of their coca cultivation areas is considered a sensitive question in remote coca growing regions in Peru. As a consequence, farmers tend not to participate in surveys, do not respond to the sensitive question(s), or underreport their individual coca cultivation areas. There is a political and policy concern in accurately and reliably measuring coca growing areas, therefore survey methodologists need to determine how to encourage response and truthful reporting of sensitive questions related to coca growing. Specific survey strategies applied in our case study included establishment of trust with farmers, confidentiality assurance, matching interviewer-respondent characteristics, changing the format of the sensitive question(s), and non enforcement of absolute isolation of respondents during the survey. The survey results were validated using satellite data. They suggest that farmers tend to underreport their coca areas to 35 to 40% of their true extent.

  Release date: 2012-12-19

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• 2. Why one should incorporate the design weights when adjusting for unit nonresponse using response homogeneity groups Archived

  Articles and reports: 12-001-X201200111689

  Description:

  When there is unit (whole-element) nonresponse in a survey sample drawn using probability-sampling principles, a common practice is to divide the sample into mutually exclusive groups in such a way that it is reasonable to assume that each sampled element in a group were equally likely to be a survey nonrespondent. In this way, unit response can be treated as an additional phase of probability sampling with the inverse of the estimated probability of unit response within a group serving as an adjustment factor when computing the final weights for the group's respondents. If the goal is to estimate the population mean of a survey variable that roughly behaves as if it were a random variable with a constant mean within each group regardless of the original design weights, then incorporating the design weights into the adjustment factors will usually be more efficient than not incorporating them. In fact, if the survey variable behaved exactly like such a random variable, then the estimated population mean computed with the design-weighted adjustment factors would be nearly unbiased in some sense (i.e., under the combination of the original probability-sampling mechanism and a prediction model) even when the sampled elements within a group are not equally likely to respond.

  Release date: 2012-06-27

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