Chapter A paradata-driven statistical approach to improve fieldwork monitoring: the case of the Non-Profit Institutions census
A complex process requires relevant information on the crucial nodes of the process itself to make more effective decisions. This is the case for large complex surveys where among the several causes of wrong or inappropriate interviewers’ behaviors only the crucial ones have to be identified and cor...
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| Format: | Online |
| Jezik: | angleščina |
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Firenze University Press, Genova University Press
2023
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| Online dostop: | ONIX_20230803_9791221501063_121 |
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| _version_ | 1869530334483185664 |
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| author | Nuccitelli, Alessandra Arlotta, Luigi Giacummo, Maura Fazzi, Gabriella Murgia, Manuela Rossetti , Francesca Parisi, Valentino Piergiovanni, Roberta |
| author_browse | Arlotta, Luigi Fazzi, Gabriella Giacummo, Maura Murgia, Manuela Nuccitelli, Alessandra Parisi, Valentino Piergiovanni, Roberta Rossetti , Francesca |
| author_facet | Nuccitelli, Alessandra Arlotta, Luigi Giacummo, Maura Fazzi, Gabriella Murgia, Manuela Rossetti , Francesca Parisi, Valentino Piergiovanni, Roberta |
| author_sort | Nuccitelli, Alessandra |
| collection | Directory of Open Access Books |
| description | A complex process requires relevant information on the crucial nodes of the process itself to make more effective decisions. This is the case for large complex surveys where among the several causes of wrong or inappropriate interviewers’ behaviors only the crucial ones have to be identified and corrected to avoid a knock-on effect. An example of such a survey is the Non-Profit Institutions Census (NPIC), for which fieldwork monitoring is improved using a paradata-driven approach based on the use of quality control tools. The complexity of NPIC is not only due to the large amount of units it involves but also to the great variety of unit-typologies: from large and structured institutions to very small associations. Complexity depends also on the different data collection modes and on the wide variety of communication channels. Besides, two questionnaires with different research aims – to assess the quality of statistical registers (short questionnaire) and to collect information (long questionnaire) – contribute to boosting complexity. The use of computer-assisted survey instruments offers the opportunity to automatically record paradata, making it possible to apply statistical procedures that allow for near real-time monitoring. To this end, a set of performance indicators is defined to assess the adequacy and observance of the survey protocols and to uncover any problematic situations that need to be addressed quickly. Once indicators are defined, control charts can be used to display them. Control charts help balance cost and thoroughness of monitoring activities by using statistical principles to differentiate potentially problematic cases from those that vary naturally around a process average. In this way, survey managers can make targeted interventions, without spending time exploring false alarms. The work will describe the experience made with the NPIC and how it can be applied to other Censuses or to any other interviewer-based survey. |
| format | Online |
| id | doab-20.500.12854ir-112085 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Firenze University Press, Genova University Press |
| publisherStr | Firenze University Press, Genova University Press |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1120852025-07-17T10:01:34Z Chapter A paradata-driven statistical approach to improve fieldwork monitoring: the case of the Non-Profit Institutions census Nuccitelli, Alessandra Arlotta, Luigi Giacummo, Maura Fazzi, Gabriella Murgia, Manuela Rossetti , Francesca Parisi, Valentino Piergiovanni, Roberta computer-assisted survey Non-Profit Institutions Census performance indicators thema EDItEUR::J Society and Social Sciences thema EDItEUR::J Society and Social Sciences A complex process requires relevant information on the crucial nodes of the process itself to make more effective decisions. This is the case for large complex surveys where among the several causes of wrong or inappropriate interviewers’ behaviors only the crucial ones have to be identified and corrected to avoid a knock-on effect. An example of such a survey is the Non-Profit Institutions Census (NPIC), for which fieldwork monitoring is improved using a paradata-driven approach based on the use of quality control tools. The complexity of NPIC is not only due to the large amount of units it involves but also to the great variety of unit-typologies: from large and structured institutions to very small associations. Complexity depends also on the different data collection modes and on the wide variety of communication channels. Besides, two questionnaires with different research aims – to assess the quality of statistical registers (short questionnaire) and to collect information (long questionnaire) – contribute to boosting complexity. The use of computer-assisted survey instruments offers the opportunity to automatically record paradata, making it possible to apply statistical procedures that allow for near real-time monitoring. To this end, a set of performance indicators is defined to assess the adequacy and observance of the survey protocols and to uncover any problematic situations that need to be addressed quickly. Once indicators are defined, control charts can be used to display them. Control charts help balance cost and thoroughness of monitoring activities by using statistical principles to differentiate potentially problematic cases from those that vary naturally around a process average. In this way, survey managers can make targeted interventions, without spending time exploring false alarms. The work will describe the experience made with the NPIC and how it can be applied to other Censuses or to any other interviewer-based survey. 2023-08-08T05:09:34Z 2023-08-08T05:09:34Z 2023-08-03T15:07:03Z 2023 chapter ONIX_20230803_9791221501063_121 2704-5846 https://library.oapen.org/handle/20.500.12657/74925 9791221501063 https://directory.doabooks.org/handle/20.500.12854/112085 eng Proceedings e report open access image/png image/jpeg Attribution 4.0 International Attribution 4.0 International https://library.oapen.org/bitstream/20.500.12657/74925/1/9791221501063-53.pdf https://library.oapen.org/bitstream/20.500.12657/74925/1/9791221501063-53.pdf Firenze University Press, Genova University Press 10.36253/979-12-215-0106-3.53 10.36253/979-12-215-0106-3.53 74113d79-2268-4658-88bb-6e8757c543b0 ASA 2022 Data-Driven Decision Making 9791221501063 6 Florence open access |
| spellingShingle | computer-assisted survey Non-Profit Institutions Census performance indicators thema EDItEUR::J Society and Social Sciences thema EDItEUR::J Society and Social Sciences Nuccitelli, Alessandra Arlotta, Luigi Giacummo, Maura Fazzi, Gabriella Murgia, Manuela Rossetti , Francesca Parisi, Valentino Piergiovanni, Roberta Chapter A paradata-driven statistical approach to improve fieldwork monitoring: the case of the Non-Profit Institutions census |
| title | Chapter A paradata-driven statistical approach to improve fieldwork monitoring: the case of the Non-Profit Institutions census |
| title_full | Chapter A paradata-driven statistical approach to improve fieldwork monitoring: the case of the Non-Profit Institutions census |
| title_fullStr | Chapter A paradata-driven statistical approach to improve fieldwork monitoring: the case of the Non-Profit Institutions census |
| title_full_unstemmed | Chapter A paradata-driven statistical approach to improve fieldwork monitoring: the case of the Non-Profit Institutions census |
| title_short | Chapter A paradata-driven statistical approach to improve fieldwork monitoring: the case of the Non-Profit Institutions census |
| title_sort | chapter a paradata driven statistical approach to improve fieldwork monitoring the case of the non profit institutions census |
| topic | computer-assisted survey Non-Profit Institutions Census performance indicators thema EDItEUR::J Society and Social Sciences thema EDItEUR::J Society and Social Sciences |
| topic_facet | computer-assisted survey Non-Profit Institutions Census performance indicators thema EDItEUR::J Society and Social Sciences thema EDItEUR::J Society and Social Sciences |
| url | ONIX_20230803_9791221501063_121 |
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