The Satisfaction With Democracy (SWD) indicator is very often used in social sciences’ research. However, while there is debate about which concept it measures, the discussion about the size of its measurement errors (how well it measures the underlying concept ‘satisfaction with the way democracy works’) is scarce. Nonetheless, measurement errors can affect the results and threaten comparisons across studies, countries and languages. Thus, in this paper, we estimated the measurement quality (complement of measurement errors) of the SWD indicator for 7 response scales across 38 country-language groups, using three multitrait-multimethod experiments from the European Social Survey. Results show that measurement errors explain from 16% (11-point scale) to 54% (4-point scale) of the variance in the observed responses. Additionally, we provide insights to improve questionnaire design and evaluate the indicator’s comparability across scales, countries and languages.

There are statistical methods that remove the within-person random error and estimate the usual intake when there is a second 24-h recall (24HR) for at least a subsample of the study population. We aimed to compare the distribution of usual food intake estimated by statistical models with the distribution of observed usual intake. A total of 302 individuals from Rio de Janeiro (Brazil) answered twenty, non-consecutive 24HR; the average length of follow-up was 3 months. The usual food intake was considered as the average of the 20 collection days of food intake. Using data sets with a pair of 2 collection days, usual percentiles of intake of the selected foods using two methods were estimated (National Cancer Institute (NCI) method and Multiple Source Method (MSM)). These estimates were compared with the percentiles of the observed usual intake. Selected foods comprised a range of parameter distributions: skewness, percentage of zero intakes and within- and between-person intakes. Both methods performed well but failed in some situations. In most cases, NCI and MSM produced similar percentiles between each other and values very close to the true intake, and they better represented the usual intake compared with 2-d mean. The smallest precision was observed in the upper tail of the distribution. In spite of the underestimation and overestimation of percentiles of intake, from a public health standpoint, these biases appear not to be of major concern.

A standardised, national, 160-item FFQ, the FFQ-NL 1.0, was recently developed for Dutch epidemiological studies. The objective was to validate the FFQ-NL 1.0 against multiple 24-h recalls (24hR) and recovery and concentration biomarkers. The FFQ-NL 1.0 was filled out by 383 participants (25–69 years) from the Nutrition Questionnaires plus study. For each participant, one to two urinary and blood samples and one to five (mean 2·7) telephone-based 24hR were available. Group-level bias, correlation coefficients, attenuation factors, de-attenuated correlation coefficients and ranking agreement were assessed. Compared with the 24hR, the FFQ-NL 1.0 estimated the intake of energy and macronutrients well. However, it underestimated intakes of SFA and trans-fatty acids and alcohol and overestimated intakes of most vitamins by >5 %. The median correlation coefficient was 0·39 for energy and macronutrients, 0·30 for micronutrients and 0·30 for food groups. The FFQ underestimated protein intake by an average of 16 % and K by 5 %, relative to their urinary recovery biomarkers. Attenuation factors were 0·44 and 0·46 for protein and K, respectively. Correlation coefficients were 0·43–0·47 between (fatty) fish intake and plasma EPA and DHA and 0·24–0·43 between fruit and vegetable intakes and plasma carotenoids. In conclusion, the overall validity of the newly developed FFQ-NL 1.0 was acceptable to good. The FFQ-NL 1.0 is well suited for future use within Dutch cohort studies among adults.

Eating out is often recorded through short-term measurements and the large within-person variability in intakes may not be adequately captured. The present study aimed to understand the effect of measurement error when using eating-out data from one or two 24 h dietary recalls (24hDR), in order to describe intakes and assess associations between eating out and personal characteristics. In a sample of 366 adults from Potsdam, Germany, two 24hDR and a FFQ were collected. Out-of-home intakes were estimated based on either one 24hDR or two 24hDR or the Multiple Source Method (MSM) combining the two 24hDR and the questionnaire. The distribution of out-of-home intakes of energy, macronutrients and selected foods was described. Multiple linear regression and partial correlation coefficients were estimated to assess associations between out-of-home energy intake and participants' characteristics. The mean daily out-of-home intakes estimated from the two 24hDR were similar to the usual intakes estimated through the MSM. The out-of-home energy intake, estimated through either one or two 24hDR, was positively associated with total energy intake, inversely with age and associations were stronger when using the two 24hDR. A marginally significant inverse association between out-of-home energy intake and physical activity at work was observed only on the basis of the two 24hDR. After applying the MSM, all significant associations remained and were more precise. Data on eating out collected through one or two 24hDR may not adequately describe intake distributions, but significant associations between eating out and participants' characteristics are highly unlikely to appear when in reality these do not exist.

La rétro-conception géométrique est un processus permettant l'obtention d'un modèle numérique à partir d'un objet réel préexistant. Le processus de prise de mesures est l'étape initiale conditionnant cette démarche. Plusieurs solutions commerciales performantes existent, mais sont trop souvent des boîtes noires pour l'utilisateur. Les limites inhérentes aux principes physiques utilisés ne sont pas directement perceptibles. Dans le cadre de travaux pratiques de rétro-conception, les étudiants expérimentent la mesure 3D d'un élément de carrosserie avec un montage simple qui se compose d'un vidéoprojecteur et d'un appareil photo numérique. La méthode testée est celle de la lumière structurée avec codage en binaire réfléchi de la position des franges. À partir de la disposition spatiale du dispositif expérimental et des prises de vue, les étudiants doivent analyser le contenu 3D des images à l'aide de logiciels génériques non dédiés. Ceci leur permet d'estimer les sources d'erreurs expérimentales ou de traitement des images. L'étape ultime est l'intégration des données numérisées dans une solution CAO où une comparaison avec un modèle numérique est possible.

The Generalized Axiom of Revealed Preference (GARP) can be violated because of random measurement errors in the observed quantity data. We study two tests proposed by Varian (1985) and de Peretti (2004), which test GARP within an explicit stochastic framework. Both tests compute adjusted quantity data that are compliant with GARP. We compare and contrast the two tests in theoretical terms and in an empirical application. The empirical application is based on testing a large group of monetary assets for the United States over multiple sample periods spanning 1960–1992. We found that both tests provided reasonable results and were largely consistent with each other.