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The term coverage, as used in survey research, indicates how well the sampling units included in a particular sampling frame account for a survey's denned target population. If a sampling frame does not contain all the units in the target population, then there is undercoverage of the population. If the frame contains duplicate units or other units beyond those contained in the population, then there is overcoverage. Undercover-age and overcoverage do not necessarily mean there will be coverage error associated with the frame.

Overcoverage occurs when members of the survey population are erroneously included in the survey sampling frame more than once or are included erroneously. Noncoverage (including undercoverage) occurs when members of the targeted population are erroneously excluded from the survey sampling frame. The meaning of the term noncoverage is not the same as the meaning of unit nonresponse, which is the failure to obtain complete survey data because of issues such as noncontacts, refusals, lost questionnaires, and so on.

Both overcoverage and noncoverage can occur at several junctures during the survey process. For example, in population surveys in which the sample is selected in two or more stages to obtain estimates of persons within households, coverage errors may occur at any or all stages when creating the sampling frame of primary sampling units, during field listing of housing units, or when creating a household roster of persons within a given family. Noncoverage that occurs during field listing can result if members of the survey sample are excessively expensive to locate or are part of multi-unit structures, or if maps do not accurately display the sampling area. Survey coverage is affected by the amount of time that has lapsed between obtaining the information for constructing the frame, creating the frame, drawing the sample, and finally collecting the data by methods such as personal visit, telephone, mail, Web, or by abstracting records. Several months or years may have passed during this time period, and many changes may have occurred to the units in the initial sampling frame that will not be reflected in the final sample.

Noncoverage

Noncoverage can occur when sampling units are omitted or missing from the sampling frame. For example, a sampling frame of business establishments may omit newly created businesses, or an administrative system may exclude units that failed to submit reports, or newly constructed buildings may be omitted from a housing survey. This will result in an incomplete frame from which the sample is drawn. Biases in the resulting survey estimates can occur when it is incorrectly assumed that the frame is complete or that the missing units are similar to those included in the frame, if units are actually known to be missing from the sampling frame.

A special case of noncoverage can be attributed to sampling units that are misclassified with respect to key variables of interest, such as a person's race-ethnicity or a household's vacancy status. When these key variables are missing, the sampling units cannot be properly classified in order to determine their eligibility status for the survey. In population household surveys, groups such as homeless persons or constant travelers are generally excluded from coverage. Special procedures may be necessary to account for these groups to prevent understating these populations in the survey estimates. Alternatively, if this is not feasible, it is important that published survey results document the limitations in coverage and possible errors in the survey estimates associated with imperfect coverage.

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