362 research outputs found
Small Area with Multiply Imputed Survey Data
In this article, we propose a framework for small area estimation with multiply imputed survey data. Many statistical surveys suffer from (a) high nonresponse rates due to sensitive questions and response burden and (b) too small sample sizes to allow for reliable estimates on (unplanned) disaggregated levels due to budget constraints. One way to deal with missing values is to replace them by several plausible/imputed values based on a model. Small area estimation, such as the model by Fay and Herriot, is applied to estimate regionally disaggregated indicators when direct estimates are imprecise. The framework presented tackles simultaneously multiply imputed values and imprecise direct estimates. In particular, we extend the general class of transformed Fay-Herriot models to account for the additional uncertainty from multiple imputation. We derive three special cases of the Fay-Herriot model with particular transformations and provide point and mean squared error estimators. Depending on the case, the mean squared error is estimated by analytic solutions or resampling methods. Comprehensive simulations in a controlled environment show that the proposed methodology leads to reliable and precise results in terms of bias and mean squared error. The methodology is illustrated by a real data example using European wealth data
Variable selection using conditional AIC for linear mixed models with data-driven transformations
When data analysts use linear mixed models, they usually encounter two practical problems: (a) the true model is unknown and (b) the Gaussian assumptions of the errors do not hold. While these problems commonly appear together, researchers tend to treat them individually by (a) finding an optimal model based on the conditional Akaike information criterion (cAIC) and (b) applying transformations on the dependent variable. However, the optimal model depends on the transformation and vice versa. In this paper, we aim to solve both problems simultaneously. In particular, we propose an adjusted cAIC by using the Jacobian of the particular transformation such that various model candidates with differently transformed data can be compared. From a computational perspective, we propose a step-wise selection approach based on the introduced adjusted cAIC. Model-based simulations are used to compare the proposed selection approach to alternative approaches. Finally, the introduced approach is applied to Mexican data to estimate poverty and inequality indicators for 81 municipalities
PISA 2018: Reporting Australia’s Results. Volume I Student Performance
The Programme for International Student Assessment (PISA) is an international comparative study of student performance directed by the Organisation for Economic Co-operation and Development (OECD). PISA measures the cumulative outcomes of education by assessing how well 15-year-olds, who are nearing the end of their compulsory schooling in most participating educational systems, are prepared to use the knowledge and skills in particular areas to meet real-life opportunities and challenges. The term literacy is attached to the assessment domains of reading, mathematics and science to reflect the focus on these broader skills and as a concept it is used in a much broader sense than simply being able to read and write. The OECD considers that mathematics and science are so pervasive in modern life that it is important for students to be literate in these areas as well. This report presents the results for Australia as a whole, for the Australian states and territories and for the other participants in PISA 2018, so that Australia’s results can be viewed in an international context, and student performance can be monitored over time
Highlights from PIRLS 2016: Australia\u27s perspective
The Progress in International Reading Literacy Study (PIRLS) is an international study of reading literacy directed by the IEA (International Association for the Evaluation of Educational Achievement). In Australia, PIRLS is implemented by the Australian Council for Educational Research (ACER), which is Australia’s representative to the IEA. In Australia, PIRLS is part of the National Assessment Program. PIRLS has been conducted internationally at Year 4 on a five-year cycle since 2001, however, Australia participated for the first time in 2011. The main goal of PIRLS is to assist countries to monitor and evaluate their teaching of reading across time. Year 4 students are the focus of the PIRLS assessment because they are usually at a key transition point in their schooling, during which they move from learning how to read, to reading in order to learn. PIRLS aims to inform policies and practice while there still is an opportunity to improve students’ performance in reading. Reading literacy is one of the most important abilities students acquire as they progress through their early school years. PIRLS defines reading literacy as ‘the ability to understand and use those written language forms required by society and/or valued by the individual’. PIRLS focuses on three aspects of students’ reading literacy: purposes for reading, processes of comprehension, and reading behaviours and attitudes. This highlights report presents selected findings from the full report \u27Reporting Australia\u27s results PIRLS 2016\u27
La demande en soja et en lupin est lÃ
Les décisions de Bio Suisse concernant l’alimentation des ruminants ont déjà des conséquences avec notamment une demande accrue pour le soja et le lupin en raison de leur forte teneur en protéines
Progress in Reading Literacy Study: Australia’s results from PIRLS 2021
Progress in International Reading Literacy Study (PIRLS) is a large-scale assessment that measures how effective countries are in teaching reading literacy. Conducted every five years since 2001 (with Australia participating since 2011), PIRLS provides information about how to improve teaching and learning so that young students become accomplished and self-sufficient readers. In Australia, almost 5,500 Year 4 students participated in PIRLS 2021. These students completed tests in reading comprehension and answered questionnaires on their background and experiences in learning reading at school. To inform educational policy in the participating countries, alongside the assessment of reading literacy, PIRLS also routinely collects extensive background information that addresses concerns about the quantity, quality and content of instruction. This background information is collected through a series of questionnaires for students, teachers, principals and curriculum specialists
Des opportunités de diversification existent dans les grandes cultures
En bio, la diversité des cultures de la rotation joue un rôle essentiel.
Pour accompagner le développement de nouvelles cultures ou variétés, le FiBL met en place des dispositifs expérimentaux. Tour d’horizon des essais 2020
Etude de l’importance des paramètres sol permettant d’évaluer l’aptitude agricole d’un site
La classe d'aptitude (CA) est une méthode de référence qui définit la qualité d'un sol pour l'utilisation agricole. Elle se base sur trois facteurs: le climat, le sol et la topographie La méthode ayant été décrite en 1997 (Brunner et al., 1997), il apparait important d’étudier si l’importance des facteurs utilisés pour définir l’aptitude agricole d’un site a évolué et si certains facteurs essentiels font défaut. Cette étude se concentre sur les facteurs sol mais donne également des indications sur un certain nombre de facteurs climatiques et de terrain. Elle a pour objectif de répondre aux questions suivantes:
1. Quelle est l'importance des variables d'entrée de la méthode CA pour déterminer l'aptitude à l'utilisation agricole d’un site selon les pratiques agricoles actuelles?
2. L'importance de ces variables d'entrée a-t-elle changé par rapport à la période précédente considérée dans la description de la CA?
3. Quels changements peut-on s'attendre à l'avenir en ce qui concerne l'importance des variables d'entrée?
4. Quels paramètres ne sont pas actuellement pris en compte dans la CA mais seraient également pertinentes pour une évaluation de l'aptitude des exploitations agricoles à l'avenir
High-heeled walking decreases lumbar lordosis.
An estimated 78% of women regularly walk in high heels. However, up to 58% complain about low back pain, which is commonly thought to be caused by increased lumbar lordosis. However, the extent to which a subject’s posture is modified by high-heeled shoes during dynamic activities remains unknown. Therefore, we sought to evaluate whether low- or high-heeled shoes influence the kinematics of the pelvis and the spine during walking. Twenty-three inexperienced women, and seventeen women experienced in wearing high-heeled shoes, all aged 20–55 years, were measured barefoot and while wearing low- (4 cm) and high-heeled (10 cm) shoes during gait at a self-selected speed. A 22-camera motion capture system was used to assess the gait patterns for each condition.
No significant inter-experience-group kinematic differences were found. In contrast to the results of some studies, our results show that the heels’ height does indeed influence the motion of the pelvis and the spine during walking, whereby low-heeled shoes influenced the subjects’ trunk kinematics during gait less than high-heeled shoes compared to barefooted walking. However, inexperienced high-heel wearers showed less thoracic curvature angle while wearing high-heels than while wearing low-heels. Importantly, both groups exhibited significantly lower maximum and minimal lumbar and thoracic curvature angles when wearing high-heeled shoes compared to the barefoot condition. As a result, it seems that low back pain might be associated with other factors induced by high-heels
RelA regulates CXCL1/CXCR2-dependent oncogene-induced senescence in murine Kras-driven pancreatic carcinogenesis
Tumor suppression that is mediated by oncogene-induced senescence (OIS) is considered to function as a safeguard during development of pancreatic ductal adenocarcinoma (PDAC). However, the mechanisms that regulate OIS in PDAC are poorly understood. Here, we have determined that nuclear RelA reinforces OIS to inhibit carcinogenesis in the Kras mouse model of PDAC. Inactivation of RelA accelerated pancreatic lesion formation in Kras mice by abrogating the senescence-associated secretory phenotype (SASP) gene transcription signature. Using genetic and pharmacological tools, we determined that RelA activation promotes OIS via elevation of the SASP factor CXCL1 (also known as KC), which activates CXCR2, during pancreatic carcinogenesis. In Kras mice, pancreas-specific inactivation of CXCR2 prevented OIS and was correlated with increased tumor proliferation and decreased survival. Moreover, reductions in CXCR2 levels were associated with advanced neoplastic lesions in tissue from human pancreatic specimens. Genetically disabling OIS in Kras mice caused RelA to promote tumor proliferation, suggesting a dual role for RelA signaling in pancreatic carcinogenesis. Taken together, our data suggest a pivotal role for RelA in regulating OIS in preneoplastic lesions and implicate the RelA/CXCL1/CXCR2 axis as an essential mechanism of tumor surveillance in PDAC
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