Standardized calibration adjustment index (SCAI): A new measure of survey data quality

2021 ◽  
pp. 1-8
Author(s):  
Burton Levine ◽  
Taylor Lewis ◽  
Jim Nonnemaker ◽  
Matthew Farrelly
Keyword(s):  
Data Quality ◽  
Survey Data ◽  
Auxiliary Information ◽  
Target Population ◽  
Sample Survey ◽  
Dual Frame ◽  
Sampling Frame ◽  
Quality Metric ◽  
Nonprobability Sample ◽  
The Difference

In this article, we introduce a new indicator of survey data quality called the standardized calibration adjustment index (SCAI). The SCAI quantifies the difference in the distributions of variables used in the calibration of survey respondents to the target population, accounting for the study design. It does so by a function of the change in respondent-level weights developed to calibrate the survey data to known population totals. A key feature of the SCAI is that it does not require auxiliary information to exist on the sampling frame. The SCAI can be used as a survey data quality metric in both probability and nonprobability sample settings, which we show through example applications with an outbound dual-frame random digit dialing telephone survey, an address-based sample survey, and a redirected inbound call sampling survey.

Survey Data Quality in Analyzing Harmonized Indicators of Protest Behavior: A Survey Data Recycling Approach

2021 ◽  
pp. 000276422110216
Author(s):  
Kazimierz M. Slomczynski ◽  
Irina Tomescu-Dubrow ◽  
Ilona Wysmulek
Keyword(s):  
Data Processing ◽  
Data Quality ◽  
Survey Data ◽  
A Priori ◽  
Data Sets ◽  
New Approach ◽  
Survey Quality ◽  
Survey Error ◽  
Ex Post ◽  
The Impact

This article proposes a new approach to analyze protest participation measured in surveys of uneven quality. Because single international survey projects cover only a fraction of the world’s nations in specific periods, researchers increasingly turn to ex-post harmonization of different survey data sets not a priori designed as comparable. However, very few scholars systematically examine the impact of the survey data quality on substantive results. We argue that the variation in source data, especially deviations from standards of survey documentation, data processing, and computer files—proposed by methodologists of Total Survey Error, Survey Quality Monitoring, and Fitness for Intended Use—is important for analyzing protest behavior. In particular, we apply the Survey Data Recycling framework to investigate the extent to which indicators of attending demonstrations and signing petitions in 1,184 national survey projects are associated with measures of data quality, controlling for variability in the questionnaire items. We demonstrate that the null hypothesis of no impact of measures of survey quality on indicators of protest participation must be rejected. Measures of survey documentation, data processing, and computer records, taken together, explain over 5% of the intersurvey variance in the proportions of the populations attending demonstrations or signing petitions.

scholarly journals Cognitive load reduction strategies in questionnaire design

2021 ◽  
pp. 147078532098679
Author(s):  
Kylie Brosnan ◽  
Bettina Grün ◽  
Sara Dolnicar
Keyword(s):  
Cognitive Load ◽  
Data Quality ◽  
Survey Data ◽  
Task Difficulty ◽  
Questionnaire Design ◽  
Load Reduction ◽  
The Past ◽  
Load Theory ◽  
Learning Tasks ◽  
Reduction Strategies

Survey data quality suffers when respondents have difficulty completing complex tasks in questionnaires. Cognitive load theory informed the development of strategies for educators to reduce the cognitive load of learning tasks. We investigate whether these cognitive load reduction strategies can be used in questionnaire design to reduce task difficulty and, in so doing, improve survey data quality. We find that this is not the case and conclude that some of the traditional survey answer formats, such as grid questions, which have been criticized in the past lead to equally good data and do not frustrate respondents more than alternative formats.

Efektivitas Konseling Individual melalui Pendekatan Konseling Rasional Emotif dalam Mengatasi Kecemasan

2021 ◽  
Vol 8 (1) ◽  
pp. 19
Author(s):  
Indah Etika Putri ◽  
Zulfani Sesmiarni ◽  
Alfi Rahmi
Keyword(s):  
Statistical Tests ◽  
Target Population ◽  
Wilcoxon Test ◽  
P Value ◽  
Test Calculation ◽  
Individual Counseling ◽  
Data Collection Instrument ◽  
Calculation Results ◽  
The Difference ◽  
Class Iib

<em>The aim of this research is to find out the effectiveness of individual counseling through emotive rational counseling approach in overcoming anxiety in Payakumbuh Class IIB Penitentiary. The population is fostered citizens before the criminal period ends as many as 20 people, while the study sample is fostered citizens before the criminal period ends as many as 5 people and who are indicated to have high anxiety based on non-rondom sampling techniques and recommendations from employees. The data collection instrument is a Likert scale. Data analysis techniques using non-parametric statistical tests using Wilcoxon rack test, hypothesis testing using Statistical Product and Service Solution (SPSS) version 22. The results showed the difference between the pretest and posttest values. From the Wilcoxon test calculation results obtained a significant sip-value of 2.023. Based on the applicable provisions, it is known that the Wilcoxon Sig p-value test result is 0.043 &lt;α (α = 0.05) which means that Ha is accepted and Ho is rejected. From the results of the Wilcoxon test calculation it can be concluded that it is effective to overcome anxiety in the target population before the criminal period expires.</em>

Medics as a Channel for Worksite Health Promotion in Remote Global Locations

2012 ◽  
Vol 26 (6) ◽  
pp. 352-355 ◽  
Author(s):  
Piroska A. Bisits Bullen
Keyword(s):  
Health Promotion ◽  
Survey Data ◽  
Comparison Group ◽  
Intervention Group ◽  
Target Population ◽  
Monthly Basis ◽  
Remote Environment ◽  
Worksite Health ◽  
Barriers To Implementation ◽  
Language And Education

Purpose. In the energy and mining sectors, it is common for employees to work in geographically remote locations, often with a medic for emergency response. This study evaluated an intervention to increase the number of medics conducting health promotion in remote worksites. Design. Interviews were conducted to gather data for informing intervention and survey development. The intervention was evaluated in a quasiexperimental posttest-only comparison group design using survey data collected at baseline and again after 12 months. Setting. The intervention was implemented in remote worksites (N = 201). There were 96 worksites in the intervention condition and 105 sites in the control condition. Subjects. The target population was medics, including nurses, doctors, and paramedics, operating in remote worksites in 44 countries. Intervention. The intervention was a series of campaign tool kits. The tool kits were adapted to the remote environment and could be customized for culture, language, and education level. Measures. The survey assessed frequency of health promotion activities, satisfaction with the intervention, and barriers to implementation. Analysis. Survey data were analyzed using descriptive statistics and χ2 tests. Interview results were coded to identify themes. Results. Most medics (88%) in the intervention group reported running “tool box talks” (short education sessions) on at least a monthly basis, compared with 78% in the comparison group (p = .056). The trend was similar for displaying posters (71% vs. 55%; p = .021) and advocating for policy changes (84% vs. 71%; p = .027). Medic satisfaction was high. Difficulty distributing tool kits was the main barrier to implementation. Conclusions. When provided with appropriate tools, medics may be an ideal channel for health promotion in remote worksites.

Restricted quasi-score estimating functions for sample survey data

2004 ◽  
Vol 41 (A) ◽  
pp. 119-130
Author(s):  
Y.-X. Lin ◽  
D. Steel ◽  
R. L Chambers
Keyword(s):  
Maximum Likelihood ◽  
Survey Data ◽  
Sample Survey ◽  
Likelihood Method ◽  
Sample Surveys ◽  
Estimating Functions ◽  
Limit Theory ◽  
Normal Probability ◽  
Probability Structure ◽  
Sample Survey Data

This paper applies the theory of the quasi-likelihood method to model-based inference for sample surveys. Currently, much of the theory related to sample surveys is based on the theory of maximum likelihood. The maximum likelihood approach is available only when the full probability structure of the survey data is known. However, this knowledge is rarely available in practice. Based on central limit theory, statisticians are often willing to accept the assumption that data have, say, a normal probability structure. However, such an assumption may not be reasonable in many situations in which sample surveys are used. We establish a framework for sample surveys which is less dependent on the exact underlying probability structure using the quasi-likelihood method.

scholarly journals Crowdsourcing LUCAS: Citizens Generating Reference Land Cover and Land Use Data with a Mobile App

2020 ◽  
Author(s):  
Juan Carlos Laso Bayas ◽  
Linda See ◽  
Hedwig Bartl ◽  
Tobias Sturn ◽  
Mathias Karner ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Survey Data ◽  
Target Location ◽  
Low Cost ◽  
Mobile App ◽  
Sample Survey ◽  
In Situ Data

There are many new land use and land cover (LULC) products emerging yet there is still a lack of in-situ data for training, validation, and change detection purposes. The LUCAS (Land Use Cover Area frame Sample) survey is one of the few authoritative in-situ field campaigns, which takes place every three years in European Union member countries. More recently, a study has considered whether citizen science and crowdsourcing could complement LUCAS survey data, e.g., through the FotoQuest Austria mobile app and crowdsourcing campaign. Although the data obtained from the campaign were promising when compared with authoritative LUCAS survey data, there were classes that were not well classified by the citizens, and the photographs submitted through the app were not always of sufficient quality. For this reason, in the latest FotoQuest Go Europe 2018 campaign, several improvements were made to the app to facilitate interaction with the citizens contributing and to improve their accuracy in LULC identification. In addition to extending the locations from Austria to Europe, a change detection component (comparing land cover in 2018 to the 2015 LUCAS photographs) was added, as well as an improved LC decision tree and a near real-time quality assurance system to provide feedback on the distance to the target location, the LULC classes chosen and the quality of the photographs. Another modification was the implementation of a monetary incentive scheme in which users received between 1 to 3 Euros for each successfully completed quest of sufficient quality. The purpose of this paper is to present these new features and to compare the results obtained by the citizens with authoritative LUCAS data from 2018 in terms of LULC and change in LC. We also compared the results between the FotoQuest campaigns in 2015 and 2018 and found a significant improvement in 2018, i.e., a much higher match of LC between FotoQuest Go Europe and LUCAS. Finally, we present the results from a user survey to discuss challenges encountered during the campaign and what further improvements could be made in the future, including better in-app navigation and offline maps, making FotoQuest a model for enabling the collection of large amounts of land cover data at a low cost.

scholarly journals Method for Dissemination of Results from Sample Survey of Innovation Activities at Enterprises for Population

2017 ◽  
pp. 6-14
Author(s):  
I. A. Zhukovych ◽  
G. I. Tereshchenko
Keyword(s):  
General Population ◽  
Survey Data ◽  
International Comparisons ◽  
Sample Survey ◽  
Community Innovation Survey ◽  
Innovation Activities ◽  
Analogous Data ◽  
Statistical Survey ◽  
Dissemination Of Results ◽  
Methodological Guidelines

The procedure for application of survey results on general population, which is a key phase in the official statistical survey of innovation activities at enterprises, conducted on sample basis, is analyzed. The tool for conducting the survey in Ukraine is the questionnaire “Survey of Innovation Activities at Enterprises”, the analogue of the questionnaire used by the Community Innovation Survey. The survey is conducted once in two years by the methodological recommendations of the Community Innovation Survey. The sample survey of innovation activities at enterprises and application of its results for the general population involves computation of statistical weights as part of the indicators assessment. The following issues are reviewed: computation of basic weights of reporting units; editing of data obtained from the survey; correction of statistical weights to account for non-response and change of key parameters of enterprises. A central issue under discussion is quality control of the statistical weights system. Approaches to indicators assessment using the survey data are highlighted. Elaborated within the framework of the Strategy for Development of Official Statistics till 2017, this method is part of the methodological guidelines on the innovation statistics. Once used by the State Statistics Service of Ukraine, the method will enable for producing high quality statistical data on innovation activities at enterprises from the survey data, adapted to the standards of European statistics and fit for international comparisons, first and foremost with the analogous data of EU countries.

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