Using auxiliary information in indirect questioning techniques

• Autores: Beatriz Cobo Rodríguez
• Directores de la Tesis: María del Mar Rueda García (dir. tes.) , Francesco Perri Pier (dir. tes.)
• Lectura: En la Universidad de Granada ( España ) en 2018
• Idioma: inglés
• ISBN: 9788491639572
• Número de páginas: 292
• Tribunal Calificador de la Tesis: Ana María Aguilera del Pino (presid.) , María Jesús García Ligero Ramírez (secret.) , Domingo Morales González (voc.) , Anne Ruiz Gazen (voc.) , Vidal Díaz de Rada Igúzquiza (voc.)
• Enlaces
  • Tesis en acceso abierto en: DIGIBUG
• Resumen

  • A survey is a research method that is based on questioning a sample of individuals. The interest in sample surveys studies often focuses on sensitive or confidential aspects of the interviewees. Because of this, the typical problem that arises is social desirability, which is defined as the tendency of respondents to answer based on what is socially acceptable. For this reason, many respondents refuse to participate in the survey or provide false or conditioned answers, altering the accuracy and reliability of the estimations in a major way.

    Randomized response (RR) technique (RRT) introduced by Warner is a possible solution for protecting the anonymity of the respondent and is used to reduce the risk of escape or no response to sensitive questions. Warner's study generated a rapidly-expanding body of research literature on alternative techniques for eliciting suitable RR schemes in order to estimate a population proportion. Standard RR methods are used primarily in surveys which require a binary response to a sensitive question, and seek to estimate the proportion of people presenting a given sensitive characteristic. On the other hand, some studies have addressed situations in which the response to a sensitive question results in a quantitative variable.

    The methodology of RR has advanced considerably in recent years, but the most research in this area concerns only simple random sampling and the real studies are based on complex surveys.

    Data from complex survey designs require special consideration with regard to estimation for parameters and corresponding variance estimation. Recently some authors have developed R-packages for estimation with RR surveys under the assumption on simple random sampling. In order to estimate parameters for sensitive characteristics, no existing software covers the estimation of these procedures from complex surveys. This gap is now filled by RRTCS package. The package includes the estimators for means and totals with several RR techniques and also provides confidence interval estimation.

    Most research into RRT deals exclusively with the interest variable and does not make explicit use of auxiliary variables in the construction of estimators. We introduce auxiliary variables for a general class of estimators to improve sampling design and to achieve higher precision in population parameter estimates.

    Warner's work originated a huge literature and has been used in many areas, but these techniques have difficulties and limitations. Due to this, other indirect techniques emerged as an alternative to RRT, among them we find the item count technique (ICT). This technique was conceived for surveys which require the study of a qualitative variable, but many practical situations may deal with sensitive variables which are quantitative in nature. So, the item sum technique (IST) was proposed as a generalization of ICT.

    To contribute to the development of the IST in real-world studies, we suggest some methodological advances, as IST estimation under a generic sampling design, the use of auxiliary information to improve the efficiency of the estimates and we extend this calibration approach to the estimation for domain. We also investigate the impact on the estimates of including an increased number of innocuous questions in the list of items.

    Traditionally, indirect questioning techniques (IQTs) deal with one sensitive variable. However, in real surveys, the researcher may be interested in investigating more than one sensitive variable. We discuss some estimation methods for multiple sensitive questions under different approaches.

    A key design decision in an IST survey is how to split the total sample into the long list sample and short list sample. A simple solution is to allocate the same number of units to each sample irrespective of the variability of the items in the two lists. Clearly, this intuitive and basic solution is not efficient because responses in the long list sample are tendentially affected by high variability due to the presence of innocuous items. We achieve the optimal sample size allocation by minimizing the variance of the IST estimates under a budget constraint. Optimal allocation results are finally extended to the multiple sensitive estimation setting.

    Finally, we use the IQTs for investigating some sensitive variables, drug addiction, sexual behavious and support for female genital cutting, in real studies and we compare these results with those get by direct question, obtaining in all cases higher estimates of the sensitive characteristics when we use IQTs.

    Note: This thesis is presented as a compendium of seven publications in relation with the contents of the thesis. The full version of the papers is included in Appendices A1 - A7.