Mode effect analysis in the case of daily passenger mobility survey
In the autumn 2017, The Statistical Office of the Republic of Slovenia (SURS) has conducted for the first time a survey on daily passenger mobility of Slovenian residents. The key statistics are on persons’ daily traveling habits, such as number of trips, travelled distance, time spent on traveling,...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Croatian Statistical Association
2020-12-01
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| Series: | Croatian Review of Economic, Business and Social Statistics |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/crebss-2020-0010 |
| _version_ | 1827265086668931072 |
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| author | Centrih Vasilij Viršček Andrej Smukavec Andreja Bučar Nataša Arnež Marta |
| author_facet | Centrih Vasilij Viršček Andrej Smukavec Andreja Bučar Nataša Arnež Marta |
| author_sort | Centrih Vasilij |
| collection | DOAJ |
| description | In the autumn 2017, The Statistical Office of the Republic of Slovenia (SURS) has conducted for the first time a survey on daily passenger mobility of Slovenian residents. The key statistics are on persons’ daily traveling habits, such as number of trips, travelled distance, time spent on traveling, and so on. Two independent samples were selected for the simultaneous collection of data by two modes, face-to-face interview (CAPI) and online questionnaire (WEB). The goal of this study is to identify the possible sources of mode measurement errors, with the objective to better design and thus improve the whole data collection process. The detailed mode effect analysis is performed by the comparison of the key statistic estimates and the use of regression models. Usually the measurement mode effect is an issue in surveys on the more sensitive topics or persons’ opinions. This work points out that, first, the mode measurement effect can be an issue also in a more factual survey content, and second, the corresponding statistical data processes can have an important contribution to minimising measurement errors. The results show that WEB respondents are inclined to join two or more trips into one reported, which gives lower estimate of average number of daily trips. The main reason is the demanding questionnaire content. Additionally, the complex data editing process was still insufficient to correct completely for such measurement error. The possible improvements of the data collection process are also discussed. |
| first_indexed | 2024-03-08T07:38:50Z |
| format | Article |
| id | doaj.art-214d1be663f34526b587228e4f98bb6c |
| institution | Directory Open Access Journal |
| issn | 2459-5616 |
| language | English |
| last_indexed | 2025-03-22T03:56:22Z |
| publishDate | 2020-12-01 |
| publisher | Croatian Statistical Association |
| record_format | Article |
| series | Croatian Review of Economic, Business and Social Statistics |
| spelling | doaj.art-214d1be663f34526b587228e4f98bb6c2024-04-28T10:58:51ZengCroatian Statistical AssociationCroatian Review of Economic, Business and Social Statistics2459-56162020-12-0162435710.2478/crebss-2020-0010Mode effect analysis in the case of daily passenger mobility surveyCentrih Vasilij0Viršček Andrej1Smukavec Andreja2Bučar Nataša3Arnež Marta4Statistical Office of the Republic of Slovenia, Ljubljana, SloveniaStatistical Office of the Republic of Slovenia, Ljubljana, SloveniaStatistical Office of the Republic of Slovenia, Ljubljana, SloveniaStatistical Office of the Republic of Slovenia, Ljubljana, SloveniaStatistical Office of the Republic of Slovenia, Ljubljana, SloveniaIn the autumn 2017, The Statistical Office of the Republic of Slovenia (SURS) has conducted for the first time a survey on daily passenger mobility of Slovenian residents. The key statistics are on persons’ daily traveling habits, such as number of trips, travelled distance, time spent on traveling, and so on. Two independent samples were selected for the simultaneous collection of data by two modes, face-to-face interview (CAPI) and online questionnaire (WEB). The goal of this study is to identify the possible sources of mode measurement errors, with the objective to better design and thus improve the whole data collection process. The detailed mode effect analysis is performed by the comparison of the key statistic estimates and the use of regression models. Usually the measurement mode effect is an issue in surveys on the more sensitive topics or persons’ opinions. This work points out that, first, the mode measurement effect can be an issue also in a more factual survey content, and second, the corresponding statistical data processes can have an important contribution to minimising measurement errors. The results show that WEB respondents are inclined to join two or more trips into one reported, which gives lower estimate of average number of daily trips. The main reason is the demanding questionnaire content. Additionally, the complex data editing process was still insufficient to correct completely for such measurement error. The possible improvements of the data collection process are also discussed.https://doi.org/10.2478/crebss-2020-0010data comparabilitymixed mode surveysmode measurement effectmode selection effectc10c18c83r41 |
| spellingShingle | Centrih Vasilij Viršček Andrej Smukavec Andreja Bučar Nataša Arnež Marta Mode effect analysis in the case of daily passenger mobility survey Croatian Review of Economic, Business and Social Statistics data comparability mixed mode surveys mode measurement effect mode selection effect c10 c18 c83 r41 |
| title | Mode effect analysis in the case of daily passenger mobility survey |
| title_full | Mode effect analysis in the case of daily passenger mobility survey |
| title_fullStr | Mode effect analysis in the case of daily passenger mobility survey |
| title_full_unstemmed | Mode effect analysis in the case of daily passenger mobility survey |
| title_short | Mode effect analysis in the case of daily passenger mobility survey |
| title_sort | mode effect analysis in the case of daily passenger mobility survey |
| topic | data comparability mixed mode surveys mode measurement effect mode selection effect c10 c18 c83 r41 |
| url | https://doi.org/10.2478/crebss-2020-0010 |
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