Comparing and Improving the Accuracy of Nonprobability Samples: Profiling Australian Surveys

There has been a great deal of debate in the survey research community about the accuracy of nonprobability sample surveys. This work aims to provide empirical evidence about the accuracy of nonprobability samples and to investigate the performance of a range of post-survey adjustment approaches (calibration or matching methods) to reduce bias, and lead to enhanced inference. We use data from five nonprobability online panel surveys and com­pare their accuracy (pre- and post-survey adjustment) to four probability surveys, including data from a probability online panel. This article adds value to the existing research by assessing methods for causal inference not previously applied for this purpose and dem­onstrates the value of various types of covariates in mitigation of bias in nonprobability online panels. Investigating different post-survey adjustment scenarios based on the avail­ability of auxiliary data, we demonstrated how carefully designed post-survey adjustment can reduce some bias in survey research using nonprobability samples. The results show that the quality of post-survey adjustments is, first and foremost, dependent on the avail­ability of relevant high-quality covariates which come from a representative large-scale probability-based survey data and match those in nonprobability data. Second, we found little difference in the efficiency of different post-survey adjustment methods, and inconsis­tent evidence on the suitability of 'webographics' and other internet-associated covariates for mitigating bias in nonprobability samples

Do We Have to Mix Modes in Probability-Based Online Panel Research to Obtain More Accurate Results?

Online probability-based panels often apply two or more data collection modes to cover both the online and offline populations with the aim of obtaining results that are more representative of the population of interest. This study used such a panel to investigate how necessary it is, from the coverage error standpoint, to include the offline population by mixing modes in online panel survey research. This study evaluated the problem from three different perspectives: undercoverage bias, bias related to survey item topics and vari­able characteristics, and accuracy of online-only samples relative to nationally representa­tive benchmarks. The results indicated that attitudinal, behavioral, and factual differences between the online and offline populations in Australia are, on average, minor. This means that, considering that survey research commonly includes a relatively low proportion of the offline population, survey estimates would not be significantly affected if probability-based panels did not mix modes and instead were online only, for the majority of topics. The benchmarking analysis showed that mixing the online mode with the offline mode did not improve the average accuracy of estimates relative to nationally representative bench­marks. Based on these findings, it is argued that other online panels should study this issue from different perspectives using the approaches proposed in this paper. There might also be an argument for (temporarily) excluding the offline population in probability-based on­line panel research in particular country contexts as this might have practical implications

Deciphering and Predicting Microscale Controls on Radon Production in Soils, Sediments and Rock

Soils, sediments and rock are natural sources of radon (Rn), which poses an ongoing threat to human health. Numerous studies have measured Rn release from bulk earth materials, yet few have examined microscale controls on Rn flux from solids (emanation), which is required to develop a process-based framework for predicting the rate and extent of production. Here, we use a novel closed loop flow-through system to measure Rn emanation from two crushed rock types with disparate physical and geochemical characteristics, shale and granitic pegmatite. We relate the extent of Rn emanation from each sample to microscale characteristics examined using conventional and synchrotron-based techniques, such as Rn parent radionuclide distribution within mineral grains, porosity, and surface area. Our results illustrate that the extent of Rn release from solids is primarily dependent on the position of parent radionuclides within host mineral grains relative to the “recoil range”—the maximum distance a daughter product (such as Rn) may traverse within a solid and into an adjacent pore owing to alpha-recoil—and is less dependent on the bulk parent radionuclide (e.g., radium) activity. We also present a simple model for predicting the emanation coefficient for pure solids based on mineralogical and physical parameters, which is an initial step toward developing a framework for predicting Rn efflux (exhalation) from soils. Keywords: radon; emanation; alpha-recoil; modeling; microscale characteristic

Deciphering and Predicting Spatial and Temporal Concentrations of Arsenic Within the Mekong Delta Aquifer

Unravelling the complex, coupled processes responsible for the spatial distribution of arsenic within groundwaters of South and South-East Asia remains challenging, limiting the ability to predict the subsurface spatial distribution of arsenic. Previous work illustrates that Himalayan-derived, near-surface (0 to 12 m) sediments contribute a substantial quantity of arsenic to groundwater, and that desorption from the soils and sediments is driven by the reduction of AsV and arsenic-bearing iron (hydr)oxides. However, the complexities of groundwater flow will ultimately dictate the distribution of arsenic within the aquifer, and these patterns will be influenced by inherent physical heterogeneity along with human alterations of the aquifer system. Accordingly, we present a unified biogeochemical and hydrologic description of arsenic release to the subsurface environment of an arsenic-afflicted aquifer in the Mekong Delta, Kandal Province, Cambodia, constructed from measured geochemical profiles and hydrologic parameters. Based on these measurements, we developed a simple yet dynamic reactive transport model to simulate one- and two-dimensional geochemical profiles of the near surface and aquifer environment to examine the effects of subsurface physical variation on the distribution of arsenic. Our results show that near-surface release (0–12 m) contributes enough arsenic to the aquifer to account for observed field values and that the spatial distribution of arsenic within the aquifer is strongly affected by variations in biogeochemical and physical parameters. Furthermore, infiltrating dissolved organic carbon and ample buried particulate organic carbon ensures arsenic release from iron (hydr)oxides will occur for hundreds to thousands of years

Approaches to dealing with survey errors in online panel research

Survey research is a relatively young field, and online surveys including online panel surveys are now routinely used for collecting survey data. We distinguish between different types of online panels, and this thesis is focused on both probability-based and nonprobability-based general population panels. To increase the quality of online panels in the era of nonresponse, more methodological research is needed, and that is the focus of the research in this thesis. To investigate approaches to dealing with survey errors, the Total Survey Error paradigm as a conceptual framework is applied, and both errors of representation and errors of measurement are the subject of this research. One of the contributions of this thesis is a review and discussion of a range of data sources and methodology which can be used in the study of survey errors. The other theoretical and practical contributions, presented within three groups, are related to the investigation of individual types of survey errors in online panel research. First, worldwide probability-based online panels are identified, and their methodological approaches to recruitment and data collection reviewed and compared as part of a meta-analysis. The study shows high levels of heterogeneity in both recruitment rates and recruitment solutions, as well as explains variability of recruitment rates. The other studies on errors of representation present evidence on how online panel paradata can be effectively transformed and used to identify about three in four nonrespondents in a subsequent panel wave, and answer the question of why people participate in online panel surveys while presenting evidence on how social-psychological theories can explain survey participation in a longitudinal design. Second, two studies focus on measurement error in probability-based online panel research due to mixing modes. The study on measurement mode effects shows how measurement error is present in the case of a lack of measurement equivalence between modes, and presents evidence on how applying matching methods (like coarsened exact matching) quite effectively controls for self-selection bias due to non-random assignment of online panellists to modes. The study on individual-level measurement mode effects presents a newly identified source of measurement error in online panel survey, that is, panel measurement mode effects. It also conceptualizes and showcases how panel conditioning can be a factor of two measurement aspects. These results are later related to a trade-off between representation (undercoverage) and measurement bias. Third, the thesis studies two cost- and time-efficient approaches to online data collection - nonprobability online panels and a fairly new combination of random digit dialing, text message invitations, and web-push methodology. The study on nonprobability panels, which are generally considered as less accurate but cheaper than probability-based panels, investigates post-survey adjustment methodology to improve inference in nonprobability samples. It presents evidence on how accuracy can be improved under different external data access scenarios. The study on a new approach to online survey data collection shows very low response rates, and outlines effective solutions to increase response (such as advance SMS and reminders). It also presents evidence on the fairly high accuracy of the proposed approach, which seems to be feasible for continuing recruitment to a probability-based online panel. In the final section of the thesis, the cost dimension of online survey research is discussed, the requirement of collecting data from the offline population in probability-based online panel research from different perspectives is challenged, and the theoretical contributions of this research are explained in more detail

A universal global measure of univariate and bivariate data utility for anonymised microdata

A universal global measure of univariate and bivariate data utility for anonymised microdata. This paper presents a new global data utility measure, based on a benchmarking approach. Data utility measures assess the utility of anonymised microdata by measuring changes in distributions and their impact on bias, variance and other statistics derived from the data. Most existing data utility measures have significant shortcomings – that is, they are limited to continuous variables, to univariate utility assessment, or to local information loss measurements. Several solutions are presented in the proposed global data utility model. It combines univariate and bivariate data utility measures, which calculate information loss using various statistical tests and association measures, such as two-sample Kolmogorov–Smirnov test, chi-squared test (Cramer’s V), ANOVA F test (eta squared), Kruskal-Wallis H test (epsilon squared), Spearman coefficient (rho) and Pearson correlation coefficient (r). The model is universal, since it also includes new local utility measures for global recoding and variable removal data reduction approaches, and it can be used for data protected with all common masking methods and techniques, from data reduction and data perturbation to generation of synthetic data and sampling. At the bivariate level, the model includes all required data analysis steps: assumptions for statistical tests, statistical significance of the association, direction of the association and strength of the association (size effect). Since the model should be executed automatically with statistical software code or a package, our aim was to allow all steps to be done with no additional user input. For this reason, we propose approaches to automatically establish the direction of the association between two variables using test-reported standardised residuals and sums of squares between groups. Although the model is a global data utility model, individual local univariate and bivariate utility can still be assessed for different types of variables, as well as for both normal and non-normal distributions. The next important step in global data utility assessment would be to develop either program code or an R statistical software package for measuring data utility, and to establish the relationship between univariate, bivariate and multivariate data utility of anonymised data

Exploring applicability of learner autonomy in Turkish EFL classrooms: how is learner autonomy perceived and practised in Turkish EFL classrooms at high school level?

In the Turkish context, the notion of learner autonomy has received increasing interest nationwide in the last decade through the efforts of the Ministry of Education. This research aimed to investigate and compare the applicability of learner autonomy in Turkish EFL classrooms in state and private schools at high school level. The findings of the current study reveal and compare Turkish EFL teachers’ understandings of learner autonomy and their practices in this area, including beyond the private and state school settings. Similarly, this research helps us to understand Turkish EFL students’ interpretations of and practices in learner autonomy. The participant of present study consisted of 20 EFL teachers and 66 students in 9th grade from private and state schools in one of the Turkish cities. Data were collected by using semi-structured interviews, focus groups and classroom observations. The data revealed that most of the participating teachers in state and private schools expressed some views about learner autonomy, however, many of the participants’ views were not clear and consistent. Also, the current study revealed some alignments and mismatches between teachers’ interpretations of learner autonomy and their practices relating to it. The data also indicated that, while some of the students share their interpretations of learner autonomy, as their teachers do, the rest of the students unfortunately do not have a clear understanding of learner autonomy. Moreover, the current research found that students in private and state schools engaged in autonomous learning activities

Modeling engineering change management process in virtual collaborative design environments

The globalization of the business world results in geographical dispersion of parties involved in design. One of the techniques proposed for providing early involvement of dispersed parties is utilizing Virtual Collaborative Design Environments for supporting conceptual and embodiment design. However, design is not restricted to development stage. A product's configuration goes through engineering changes for improving and refining design throughout the product's life-cycle. In this thesis, we focus on Engineering Change Management process and modeling this process within a Virtual Collaborative Design Environment. We propose an Active Distributed Virtual Change Environment named ADVICE for performing Engineering Change Management functions. This non-immersive environment offers a superior approach to the existing Engineering Change Management solutions by merging graphical and parametric data involved in the process into a virtual object, which improves comprehension of users and hence decreases the time required for review. ADVICE employs data mining techniques to process captured change history and provides user support with prioritization and change propagation mechanisms. The proposed environment is demonstrated through a sample application. For verifying the prioritization and change propagation mechanisms, experiments involving synthetic data are conducted. The experiments presented the capability of ADVICE to facilitate Engineering Change Managemen

Panel mixed-mode effects: does switching modes in probability-based online panels influence measurement error?

Online probability-based panels often apply two or more data collection modes to cover online and offline populations, and to collect data from onliners who do not respond online in time to contribute to a given wave. As a result, offline/ online status can change during the life of the panel for some individuals, which can improve response rates and representativeness, but may cause increased measurement error. In this study, we use Life in Australia™ survey data and online panel paradata to identify respondents who switched modes; almost 4% of the whole panel was interviewed using both online and offline modes in the first 2-years, and almost one-third of those 4% switched mode more than once. We selected all repeated substantive survey items, identified any relevant changes in responses that could be explained with mode effects, and determined the effect of mode switching on changes to answers, controlling for panel conditioning, panel fatigue and sociodemographic characteristics of panellists. This study identified a limited number of panel mode effects from panellists switching modes of data collection over time. We found evidence of recency and some social desirability, and established that measurement error may be more common when the proportion of mode switchers is higher. Moreover, panel conditioning had an effect on the frequency of changing answers; respondents provided more stable answers if they were more conditioned. We conclude that combining mode effects with panel conditioning, as well as an increasing representation bias over time, may lead to less accurate estimations in longitudinal surveys

Transfusion-transmitted virus prevalence in subjects at high risk of sexually transmitted infection in Turkey

ObjectiveTo assess the possible sexual transmission of virus and to identify the prevalence of TTV viremia in Turkey and its association with other hepatotropic viruses.MethodsSerum samples were collected from 81 subjects (74 prostitutes and seven homosexual men) at high risk of sexually transmitted infection and from 81 healthy controls (74 females and seven males). Sera of patients and controls were tested for TTV, hepatitis A virus, hepatitis B virus, hepatitis C virus, and human immunodeficiency virus. Also, serum alanine and aspartate aminotransferases were measured.ResultsThe prevalence rates of TTV viremia in the risk group and control group were 86.4% and 82.7%, respectively. There was a statistical difference in mean age between TTV-infected and uninfected subjects (38.6 ± 9.9 versus 32.2 ± 6.1 years, respectively, P < 0.001). Prevalence rates of TTV infection in subjects with positive anti-HAV and positive anti-HBc were high when compared with subjects who were negative for these.ConclusionWe suggest that TTV infection has a diverse route of transmission, and its prevalence increases with age; also, the prevalence rate of TTV is high in certain risk groups. The prevalence rates of TTV in the group at risk for sexual transmission (86.4%) and in the control group (82.7%) were among the highest ever reported in the world. Also, we suggest that TTV generally does not cause clinical disease, in spite of this high prevalence