Novel Approach for Statistical Interpretation: A Case Study from Long-Term Crop Production Experiments (Hungary)

In recent decades, the agricultural sector has witnessed rapid technological interventions from field to the production stage. Thus, the importance of these technological interventions must be strictly evaluated. The traditional statistical method often deems low statistical differences as a significant one, which cannot be considered effective from different perspectives. In this sense, the aim of this research was to develop a new statistical method for evaluating agricultural experiments based on different criteria; hence, the significant importance of the technological interventions can be clearly determined. Data were collected from of a long-term (13-year) crop production experiment (Central Europe, Hungary), which involved five different fertilization levels, along with non-fertilized treatment (control), two irrigation treatments (irrigated and non-irrigated), and 15–20 genotypes of maize. The output of this research showed that the classic statistical approach for testing the significant differences among treatments should be accompanied with our new suggested approach (i.e., professional test), which reflect whether treatments were professionally effective or not. Also, results showed that good statistical background is not enough for interoperating the analysis of agricultural experiments. This research suggested that erroneous conclusions can be avoided by merging classical and professional statistical tests, and correct recommendations could be provided to decision makers and farmers based on their financial resources.

The Basis for Reliability-Based Mechanical Properties of Structural Aluminium Alloys

Adequate knowledge of mechanical properties and their statistical description is the basis for performing reliable verification of design methods and design of structures in general. The probabilistic design approach implemented in Eurocodes requires statistical data on all variables used in the design procedure. Although aluminium was introduced in structural Eurocodes more than four decades ago (ENV), the statistical database of mechanical properties is still inadequate. To provide a reliable statistical background, data collection was performed concerning aluminium products mainly found in the European market, within the last 20 years regarding certificates from the aluminium industry and 30 years regarding data from the research community. The collected data include aluminium alloy series 1xxx, 5xxx, 6xxx, and 7xxx, mainly extruded, and relevant mechanical properties such as 0.2% proof strength, ultimate strength, Young’s modulus, and Poisson’s ratio. They were fit to distributions, and relevant fractiles were determined, along with an analysis of nominal to characteristic and design value ratios. Variation of ratios obtained shows that that the majority of nominal values are economical and reliable. However, certain adjustments to nominal values are required to achieve a uniform reliability level in terms of the choice of alloy and temper.

SHORT-TERM RENTALS: HOW MUCH IS TOO MUCH – SPATIAL PATTERNS IN PORTUGAL AND LISBON

Purpose - This paper analyses the growth of tourism in Portugal and in the municipality of Lisbon, with a focus on short-term rentals. Design - The paper begins with the statistical background of the tourism boom that occurred in Portugal in the 2010s. The central part of the paper concentrates on an analysis of the spatial distribution of short-term rental properties, consisting of two parts: i) observation of spatial patterns in Portugal, by NUTS II region; ii) analysis of the municipality of Lisbon, which accounts for 22% of all short-term rentals units registered in Portugal. Methodology - The spatial analysis was carried out within GIS, using an approach based on spatial statistics, with research that involves geographic data and big data. Approach - This study combines a qualitative and quantitative approach. It begins with a theoretical review on the growth of tourism and short-term rental in the last decade, followed by a quantitative-spatial analysis to the case of Portugal and the municipality of Lisbon, and ending with reflections that combine the results of the practical analysis with the most recent literature on the impacts of tourism in Lisbon Findings - The paper ends with some reflections on the excessive concentration of short-term rentals in urban areas and their positive and negative externalities on urban life. The results suggest that the city center presents the highest concentration of short-time rentals, but not the highest concentration of beds. It also shows that the excessive concentration of short-term rentals units may cause serious negative externalities that affect the quality of life in its multiple dimensions. Originality - The results and the final discussion of this paper contributes to a greater knowledge of the spatial distribution of short-term rentals in Portugal and Lisbon and to debate the future of short-term rentals in cities that are among the world’s leading tourism destinations.

Systematic review of education and practical guidance on regression modeling for medical researchers who lack a strong statistical background: Study protocol

In the last decades, statistical methodology has developed rapidly, in particular in the field of regression modeling. Multivariable regression models are applied in almost all medical research projects. Therefore, the potential impact of statistical misconceptions within this field can be enormous Indeed, the current theoretical statistical knowledge is not always adequately transferred to the current practice in medical statistics. Some medical journals have identified this problem and published isolated statistical articles and even whole series thereof. In this systematic review, we aim to assess the current level of education on regression modeling that is provided to medical researchers via series of statistical articles published in medical journals. The present manuscript is a protocol for a systematic review that aims to assess which aspects of regression modeling are covered by statistical series published in medical journals that intend to train and guide applied medical researchers with limited statistical knowledge. Statistical paper series cannot easily be summarized and identified by common keywords in an electronic search engine like Scopus. We therefore identified series by a systematic request to statistical experts who are part or related to the STRATOS Initiative (STRengthening Analytical Thinking for Observational Studies). Within each identified article, two raters will independently check the content of the articles with respect to a predefined list of key aspects related to regression modeling. The content analysis of the topic-relevant articles will be performed using a predefined report form to assess the content as objectively as possible. Any disputes will be resolved by a third reviewer. Summary analyses will identify potential methodological gaps and misconceptions that may have an important impact on the quality of analyses in medical research. This review will thus provide a basis for future guidance papers and tutorials in the field of regression modeling which will enable medical researchers 1) to interpret publications in a correct way, 2) to perform basic statistical analyses in a correct way and 3) to identify situations when the help of a statistical expert is required.

Fundamentals of Clinical Prediction Modeling for the Neurosurgeon

Clinical prediction models in neurosurgery are increasingly reported. These models aim to provide an evidence-based approach to the estimation of the probability of a neurosurgical outcome by combining 2 or more prognostic variables. Model development and model reporting are often suboptimal. A basic understanding of the methodology of clinical prediction modeling is needed when interpreting these models. We address basic statistical background, 7 modeling steps, and requirements of these models such that they may fulfill their potential for major impact for our daily clinical practice and for future scientific work.

The more the merrier? Multivariate approaches to genome-wide association analysis

The vast majority of genome-wide association (GWA) studies analyze a single trait while large-scale multivariate data sets are available. As complex traits are highly polygenic, and pleiotropy seems ubiquitous, it is essential to determine when multivariate association tests (MATs) outperform univariate approaches in terms of power. We discuss the statistical background of 19 MATs and give an overview of their statistical properties. We address the Type I error rates of these MATs and demonstrate which factors can cause bias. Finally, we examine, compare, and discuss the power of these MATs, varying the number of traits, the correlational pattern between the traits, the number of affected traits, and the sign of the genetic effects. Our results demonstrate under which circumstances specific MATs perform most optimal. Through sharing of flexible simulation scripts, we facilitate a standard framework for comparing Type I error rate and power of new MATs to that of existing ones.