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Statistics Netherlands' social surveys are based on a sequential mixed-mode data collection approach using web, telephone, and face-to-face interviewing. This article illustrates how Statistics Netherlands addressed the sudden, unforeseen loss of face-to-face interviews in social surveys amidst the COVID-19 pandemic. At the beginning of the pandemic, survey processes were immediately adjusted in several ways to mitigate the negative effects of respondent attrition. Where possible, sampled people initially assigned to face-to-face interviewing were motivated to respond through web or telephone to minimize the loss of response. At the same time regression analysis and simulation were conducted to obtain quantitative insight into the effects of losing face-to-face responses in the sequential mixed-mode designs. Furthermore, alternative model-based estimation procedures based on structural time series models were implemented to compensate for the bias that is a result of the loss of face-to-face responses. These initiatives are illustrated with applications to the Dutch Labor Force Survey, the Housing Survey, and the Health Survey. [ABSTRACT FROM AUTHOR]

Within the field of official statistics, we are often interested in the relative change of statistical indicators through time. A typical example is economic growth measured as the ratio of gross domestic product at two consecutive time periods. In this article, we investigate the accuracy of such ratios when the numerator and denominator describe a subpopulation. Subpopulations are always identified by a classification variable, which might contain classification errors. Our main objective is to quantify the bias and variance of statistical estimates of ratios of statistical indicators that are affected by classification errors. Previous studies have already shown how to estimate the bias and variance of statistical indicators for a single subpopulation as affected by classification errors. For estimated ratios, such results are not yet available in the academic literature. In this article, we will provide those results. More specifically, we will investigate three situations: the classification errors for the numerator and denominator are (1) completely dependent, (2) completely independent, or (3) partially dependent. For these three cases, we derive estimators of the bias and variance using a Taylor expansion and a bootstrap approach. By means of a simulation study, we show that the Taylor expansion is valid unless the distribution of the target variable of the numerator or the denominator is highly skewed. The methods are applied to two widely differing case studies: one on classification errors made by a machine learning classifier (independent errors) and one on classification errors in register data (partially dependent errors). This illustrates that our method can be useful for a wide range of applications. [ABSTRACT FROM AUTHOR]

Burger and coworkers developed a dynamic state variable model to understand host-handling behavior in the whitefly parasitoid Encarsia formosa from an adaptive viewpoint. The model predicts that when the function of host feeding is to gain nutrients for egg maturation, the host-feeding gain does not offset the loss of an opportunity to oviposit under presumably field conditions.

As national statistical offices (NSOs) modernize, interest in integrating machine learning (ML) into official statisticians' toolbox is growing. Two challenges to such an integration are the potential loss of transparency from using "black-boxes" and the need to develop a quality framework. In 2019, the High-Level Group for the Modernisation of Official Statistics (HLG-MOS) launched a project on machine learning with one of the objectives being to address these two challenges. One of the outputs of the HLG-MOS project is a Quality Framework for Statistical Algorithms (QF4SA). While many quality frameworks exist, they have been conceived with traditional methods in mind, and they tend to target statistical outputs. Currently, machine learning methods are being looked at for use in processes producing intermediate outputs, which lead to a final statistical output. Therefore, the QF4SA does not replace existing quality frameworks; it complements them. As the QF4SA targets intermediate outputs and not necessarily the final statistical output, it should be used in conjunction with existing quality frameworks to ensure that high-quality outputs are produced. This paper presents the QF4SA, as well as some recommendations for NSOs considering the use of machine learning in the production of official statistics. [ABSTRACT FROM AUTHOR]

Capture-recapture (CRC) is currently considered a promising method to integrate big data in official statistics. We previously applied CRC to estimate road freight transport with survey data (as the first capture) and road sensor data (as the second capture), using license plate and time-stamp to identify re-captured vehicles. A considerable difference was found between the single-source, design-based survey estimate, and the multiple-source, model-based CRC estimate. One possible explanation is underreporting in the survey, which is conceivable given the response burden of diary questionnaires. In this paper, we explore alternative explanations by quantifying their effect on the estimated amount of underreporting. In particular, we study the effects of 1) reporting errors, including a mismatch between the reported day of loading and the measured day of driving, 2) measurement errors, including false positives and OCR failure, 3) considering vehicles reported not owned as nonresponse error instead of frame error, and 4) response mode. We conclude that alternative hypotheses are unlikely to fully explain the difference between the survey estimate and the CRC estimate. Underreporting, therefore, remains a likely explanation, illustrating the power of combining survey and sensor data. [ABSTRACT FROM AUTHOR]

This paper aims to elicit a discussion of the existence of a paradigm shift in official statistics through the emergence of new (unstructured) data sources and methods that may not adhere to established and existing statistical practices and quality frameworks. The paper discusses strengths and weaknesses of several data sources. Furthermore, it discusses methodological, technical and cultural barriers in dealing with new data and methods in data science; cultural as in the culture that reigns in an area of expertise or approach. The paper concludes with suggestions of updating the existing quality frameworks. We take the position that there is no paradigm shift but that the existing production processes should be adjusted and that existing quality frameworks should be updated in order for official statistics to benefit from the fusion of data, knowledge and skills among survey methodologists and data scientists. [ABSTRACT FROM AUTHOR]

Adaptive survey designs (ASDs) optimize design features, given 1) the interactions between the design features and characteristics of sampling units and 2) a set of constraints, such as a budget and a minimum number of respondents. Estimation of the interactions is subject to both random and systematic error. In this article, we propose and evaluate four viewpoints to assess robustness of ASDs to inaccuracy of design parameter estimates: the effect of both imprecision and bias on both ASD structure and ASD performance. We additionally propose three distance measures to compare the structure of ASDs. The methodology is illustrated using a simple simulation study and a more complex but realistic case study on the Dutch Travel Survey. The proposed methodology can be applied to other ASD optimization problems. In our simulation study and case study, the ASD was fairly robust to imprecision, but not to realistic dynamics in the design parameters. To deal with the sensitivity of ASDs to changing design parameters, we recommend to learn and update the design parameters. [ABSTRACT FROM AUTHOR]

Publications in official statistics are increasingly based on a combination of sources. Although combining data sources may result in nearly complete coverage of the target population, the outcomes are not error free. Estimating the effect of nonsampling errors on the accuracy of mixed-source statistics is crucial for decision making, but it is not straightforward. Here we simulate the effect of classification errors on the accuracy of turnover-level estimates in car-trade industries. We combine an audit sample, the dynamics in the business register, and expert knowledge to estimate a transition matrix of classification-error probabilities. Bias and variance of the turnover estimates caused by classification errors are estimated by a bootstrap resampling approach. In addition, we study the extent to which manual selective editing at micro level can improve the accuracy. Our analyses reveal which industries do not meet preset quality criteria. Surprisingly, more selective editing can result in less accurate estimates for specific industries, and a fixed allocation of editing effort over industries is more effective than an allocation in proportion with the accuracy and population size of each industry. We discuss how to develop a practical method that can be implemented in production to estimate the accuracy of register-based estimates. [ABSTRACT FROM AUTHOR]

For policymakers and other users of official statistics, it is crucial to distinguish real differences underlying statistical outcomes from noise caused by various error sources in the statistical process. This has become more difficult as official statistics are increasingly based upon a mix of sources that typically do not involve probability sampling. In this article, we apply a resampling method to assess the sensitivity of mixed-source statistics to sourcespecific classification errors. Classification errors can be seen as coverage errors within a stratum. The method can be used to compare relative accuracies between strata and releases, it can assist in deciding how to optimally allocate resources in the statistical process, and it can be applied in evaluating potential estimators. A case study on short-term business statistics shows that bias occurs especially for those strata that deviate strongly from the mean value in other strata. It also suggests that shifting classification resources from small and mediumsized enterprises to large enterprises has virtually no net effect on accuracy, because the gain in precision is offset by the creation of bias. The resampling method can be extended to include other types of nonsampling error. [ABSTRACT FROM AUTHOR]

Insect parasitoids lay their eggs in arthropods. Some parasitoid species not only use their arthropod host for oviposition but also for feeding. Host feeding provides nutrients to the adult female parasitoid. However, in many species, host feeding destroys an opportunity to oviposit. For parasitoids that attack Homoptera, honeydew is a nutrient-rich alternative that can be directly imbibed from the host anus without injuring the host. A recent study showed that feeding on host-derived honeydew can be an advantageous alternative in terms of egg quantity and longevity. Here we explore the conditions under which destructive host feeding can provide an advantage over feeding on honeydew. For 5 days, Encarsia formosa Gahan (Hymenoptera: Aphelinidae) parasitoids were allowed daily up to 3 h to oviposit until host feeding was attempted. Host feedings were either prevented or allowed and parasitoids had ad libitum access to honeydew between foraging bouts. Even in the presence of honeydew, parasitoids allowed to host feed laid more eggs per hour of foraging per host-feeding attempt than parasitoids that were prevented from host feeding. The higher egg-laying rate was not compromised by survival or by change in egg volume over time. In conclusion, host feeding can provide an advantage over feeding on honeydew. This applies most likely under conditions of high host density or low extrinsic mortality of adult parasitoids, when alternative food sources cannot supply enough nutrients to prevent egg limitation. We discuss how to integrate ecological and physiological studies on host-feeding behavior [ABSTRACT FROM AUTHOR]

Host feeding is the consumption of host tissue by the adult female parasitoid. We studied the function of destructive host feeding and its advantage over non-destructive feeding on host-derived honeydew in the whitefly parasitoid Encarsia formosa Gahan (Hymenoptera: Aphelinidae). We allowed parasitoids to oviposit until they attempted to host feed. We either prevented or allowed host feeding. Parasitoids had access to sucrose solution, with or without additional access to honeydew. Parasitoids that were allowed to host feed did not have a higher egg load 20 or 48 h after host feeding than parasitoids prevented from host feeding. Host feeding did not increase the number of eggs matured within these periods, nor did the time spent host feeding positively affect any of these response variables. On the other hand, the presence of honeydew did have a positive effect on egg load 20 and 48 h after host feeding compared with parasitoids deprived of honeydew. Parasitoids with access to honeydew matured more eggs within these periods than honeydew-deprived parasitoids. Host feeding increased life expectancy, but this effect was nullified when honeydew was supplied after the host-feeding attempt. In conclusion, feeding on honeydew could be an advantageous alternative to host feeding in terms of egg quantity and longevity. This applies especially to parasitoids exploiting Homoptera, because these parasitoids can obtain honeydew from the host itself. It is possible that destructive host feeding has evolved to enable females to sustain the production of high-quality anhydropic eggs, which may be important in the parasitoid's natural environment. We argue that future studies should take natural alternative food sources into more consideration. [ABSTRACT FROM AUTHOR]

1. To understand evolution of foraging behaviour in the whitefly parasitoid Encarsia formosa (Hymenoptera, Aphelinidae), natural densities and distributions of whitefly (Homoptera, Aleyrodidae) were quantified in E. formosa's presumed area of origin, the Neotropics. 2. Leaves were collected in Costa Rican nature areas along long transects (2–4 km), short transects (100 m), within 3-D plots (50 dm3−2.3 m3) and along suspension bridges within the canopy, and checked for presence of whitefly nymphs. 3. Generalised linear mixed modelling revealed that the number of hosts on the lower side of a leaflet of an average plant within an average spot of an average transect could be described by a Poisson distribution with mean and variance equal to 0.241, in a ratio of I1:I2:I3:I4 = 0.14:0.23:0.26:0.37. The Poisson mean was affected largely by the plant and less by the spot or transect. Variation in leaf area explained little of the variation between plants. Based on the shape of the opening in vacated puparia, the probability that a whitefly became parasitised eventually was 12% on an average leaflet. Whitefly density was much lower in the canopy than at the forest floor in the same area. 4. Semivariance analyses showed that in one of the three short transects, the numbers of whiteflies on leaves were spatially dependent. In four of seven 3-D plots at least one level of spatial dependence could be detected. 5. Results are discussed in the context of understanding evolution of foraging behaviour by E. formosa. [ABSTRACT FROM AUTHOR]

Genetic and environmental interventions that extend life span are a current focus in research on the biology of aging. Most of this work has focused on differences among genotypes and species. A recent study on fruit flies shows that life span extension because of dietary restriction can be highly sex-specific. Here we review the literature on sex-specific effects of 56 genetic and 41 environmental interventions that extend life span in Drosophila melanogaster. We found that only one-sixth of the experiments provided statistical tests of differences in response between males and females, suggesting that sex-specific effects have been largely ignored. When measured, the life span extension was female-biased in 8 of 16 cases, male-biased in 5 of 16 cases, and not significantly different in only 3 of 16 cases. We discuss possible explanations for the sex-specific differences and suggest various ways in which we might test these hypotheses. We argue that understanding sex differences in the response to life span-extending manipulations should lead to new insights about the basic mechanisms that underlie the biology of aging in both sexes.