Frames2: A package for estimation in dual frame surveys

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Authors Antonio Arcos, David Molina, Maria Giovanna Ranalli, María del Mar Rueda
Journal/Conference Name The R Journal
Paper Category
Paper Abstract Data from complex survey designs require special consideration with regard to estimation of finite population parameters and corresponding variance estimation procedures, as a consequence of significant departures from the simple random sampling assumption. In the past decade a number of statistical software packages have been developed to facilitate the analysis of complex survey data. All these statistical software packages are able to treat samples selected from one sampling frame containing all population units. Dual frame surveys are very useful when it is not possible to guarantee a complete coverage of the target population and may result in considerable cost savings over a single frame design with comparable precision. There are several estimators available in the statistical literature but no existing software covers dual frame estimation procedures. This gap is now filled by package Frames2. In this paper we highlight the main features of the package. The package includes the main estimators in dual frame surveys and also provides interval confidence estimation. In practice, the assumption that the sampling frame contains all population units is rarely met. Often, one finds that sampling from a frame which is known to cover approximately all units in the population is quite expensive while other frames (e.g. special lists of units) are available for cheaper sampling methods. However, the latter usually only cover an unknown or only approximately known fraction of the population. A common example of frame undercoverage is provided by telephone surveys. Estimation could be affected by serious bias due to the lack of a telephone in some households and the generalised use of mobile phones, which are sometimes replacing fixed (land) lines entirely. The potential for coverage error as a result of the exponential growth of the cell-phone only population has led to the development of dual-frame surveys. In these designs, a traditional sample from the landline frame is supplemented with an independent sample from a register of cell-phone numbers. The dual frame sampling approach assumes that two frames are available for sampling and that, overall, they cover the entire target population. The most common situation is the one represented in Figure 1 where the two frames, say frame A and frame B, show a certain degree of overlapping, so it is possible to distinguish three disjoint non-empty domains: domain a, containing units belonging to frame A but not to frame B; domain b, containing units belonging to frame B but not to frame A and domain ab, containing units belonging to both frames. As an example, consider a telephone survey where both landline and cell phone lists are available; let A be the landline frame and B the cell phone frame. Then, it is possible to distinguish three types of individuals: landline only units, cell-only units and units with both landline and cell phone, which will compose domain a, b and ab, respectively. Nevertheless, one can face some other situations depending on the relative positions of the frames. For example, Figure 2 shows the case in which frame B is totally included in frame A, that is, frame B is a subset of frame A. Here domain b is empty. We also may find scenarios where the two sampling frames exactly match, as depicted in Figure 3, where ab is the only non-empty domain. Finally, the scenario where domain ab is empty has no interest from a dual frame perspective, since it can be
Date of publication 2015
Code Programming Language R

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