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Applying the Rasch Model
Recognised as the most influential publication in the field, ARM facilitates deep understanding of the Rasch model and its practical applications. The authors review the crucial properties of the model and demonstrate its use with examples across the human sciences. Readers will be able to understand and critically evaluate Rasch measurement research, perform their own Rasch analyses and interpret their results. The glossary and illustrations support that understanding, and the accessible approach means that it is ideal for readers without a mathematical background.
Intended as a text for graduate courses in measurement, item response theory, (advanced) research methods or quantitative analysis taught in psychology, education, human development, business and other social and health sciences. Professionals in these areas will also appreciate the book’s accessible introduction.
Highlights of the new edition include:
More learning tools to strengthen readers’ understanding including chapter introductions, boldfaced key terms, chapter summaries, activities and suggested readings.
Greater emphasis on the use of R packages; readers can download the R code from the Routledge website.
Explores the distinction between numerical values, quantity and units, to understand the measurement and the role of the Rasch logit scale (Chapter 4).
A new four-option data set from the IASQ (Instrumental Attitude toward Self-assessment Questionnaire) for the Rating Scale Model (RSM) analysis exemplar (Chapter 6).
Clarifies the relationship between Rasch measurement, path analysis and SEM, with a host of new examples of Rasch measurement applied across health sciences, education and psychology (Chapter 10).
eBook
Modeling, measuring and managing risk
This book is the first in the market to treat single- and multi-period risk measures (risk functionals) in a thorough, comprehensive manner. It combines the treatment of properties of the risk measures with the related aspects of decision making under risk.
eBook
Understanding The New Statistics
This is the first book to introduce the new statistics - effect sizes, confidence intervals, and meta-analysis - in an accessible way. It is chock full of practical examples and tips on how to analyze and report research results using these techniques. The book is invaluable to readers interested in meeting the new APA Publication Manual guidelines by adopting the new statistics - which are more informative than null hypothesis significance testing, and becoming widely used in many disciplines.
Accompanying the book is the Exploratory Software for Confidence Intervals (ESCI) package, free software that runs under Excel and is accessible at www.thenewstatistics.com. The book's exercises use ESCI's simulations, which are highly visual and interactive, to engage users and encourage exploration. Working with the simulations strengthens understanding of key statistical ideas. There are also many examples, and detailed guidance to show readers how to analyze their own data using the new statistics, and practical strategies for interpreting the results. A particular strength of the book is its explanation of meta-analysis, using simple diagrams and examples. Understanding meta-analysis is increasingly important, even at undergraduate levels, because medicine, psychology and many other disciplines now use meta-analysis to assemble the evidence needed for evidence-based practice.
The book's pedagogical program, built on cognitive science principles, reinforces learning:
Boxes provide \"evidence-based\" advice on the most effective statistical techniques.
Numerous examples reinforce learning, and show that many disciplines are using the new statistics.
Graphs are tied in with ESCI to make important concepts vividly clear and memorable.
Opening overviews and end of chapter take-home messages summarize key points.
Exercises encourage exploration, deep understanding, and practical app
eBook
Landslide susceptibility assessment on a large scale in the Podsljeme area, City of Zagreb (Croatia)
The study presents a landslide susceptibility assessment on a large scale in the City of Zagreb (Croatia). The susceptibility analysis was performed using the Weight of Evidence model in the pilot area (21 km
2
) and applying the obtained weight values for each class of conditioning factors in the study area (130 km
2
). The input data were LiDAR-based landslide inventory and six conditioning factors derived from 5 m LiDAR DTM, 5 m SfM DEM, and geological and land-use maps. The validation of the susceptibility assessment for the study area was evaluated with a ROC curve, which showed a high prediction rate (AUC = 84.4%), similar to the prediction rate for the pilot area (AUC = 86.9%). Based on the results, it can be concluded that the proposed method for large-scale landslide susceptibility assessment, where susceptibility conditions are defined in smaller pilot areas, can be applied to larger research areas with similar geomorphological and geological conditions.
Journal Article
Uncertainty Analysis of the Water Scarcity Footprint Based on the AWARE Model Considering Temporal Variations
The purpose of this paper is to compare the degree of uncertainty of the water scarcity footprint using the Monte Carlo statistical method and block bootstrap method. Using the hydrological data of a water drainage basin in Korea, characterization factors based on the available water remaining (AWARE) model were obtained. The uncertainties of the water scarcity footprint considering temporal variations in paddy rice production in Korea were estimated. The block bootstrap method gave five-times smaller percentage uncertainty values of the model output compared to that of the two different Monte Carlo statistical method scenarios. Incorrect estimation of the probability distribution of the AWARE characterization factor model is what causes the higher uncertainty in the water scarcity footprint value calculated by the Monte Carlo statistical method in this study. This is because AWARE characterization factor values partly follows discrete distribution with extreme value on one side. Therefore, this study suggests that the block bootstrap method is a better choice in analyzing uncertainty compared to the Monte Carlo statistical method when using the AWARE model to quantify the water scarcity footprint.
Journal Article
Study on Remelting of Crystal Under Extreme Conditions
The appearance of the maximum point on the melting curve has so far been considered an anomalous phenomenon found only in a few alkali metals and nonmetals. However, recent ab initio studies have shown that the above event is much more universal than we often think. The core problem is to reach the ultra-high pressure region where the melting gradient begins to change sign from positive to negative. This work requires a huge amount of computational resources. Therefore, we aim to build a simple but effective theoretical model to quickly collect important information about remelting. Our main idea is to combine the moment statistical method with the Lindemann criterion to appropriately describe the crystal melting process through the instability of lattice vibrations. In addition, the Morse pair interaction potential is utilized to parameterize the binding energy between atoms. On that basis, we conducted numerical calculations for W—a typical refractory material with many potential applications. We find that its melting gradient will be zero when the nearest neighbor distance between ions reaches 0.8976 Å which corresponds to a pressure of 1.6533
×
10
6
GPa and a temperature of 2.7567
×
10
5
K. Our finding is strongly supported by existing simulation results.
Journal Article
A genome-wide association study identifies new psoriasis susceptibility loci and an interaction between HLA-C and ERAP1
Richard Trembath, Peter Donnelly and colleagues report a genome-wide association study identifying six new psoriasis susceptibility loci. They also identify a statistical interaction between
HLA-C
and
ERAP1
in psoriasis susceptibility.
To identify new susceptibility loci for psoriasis, we undertook a genome-wide association study of 594,224 SNPs in 2,622 individuals with psoriasis and 5,667 controls. We identified associations at eight previously unreported genomic loci. Seven loci harbored genes with recognized immune functions (
IL28RA
,
REL, IFIH1, ERAP1, TRAF3IP2
,
NFKBIA
and
TYK2
). These associations were replicated in 9,079 European samples (six loci with a combined
P
< 5 × 10
−8
and two loci with a combined
P
< 5 × 10
−7
). We also report compelling evidence for an interaction between the
HLA-C
and
ERAP1
loci (combined
P
= 6.95 × 10
−6
).
ERAP1
plays an important role in MHC class I peptide processing.
ERAP1
variants only influenced psoriasis susceptibility in individuals carrying the
HLA-C
risk allele. Our findings implicate pathways that integrate epidermal barrier dysfunction with innate and adaptive immune dysregulation in psoriasis pathogenesis.
Journal Article
HOPS: a quantitative score reveals pervasive horizontal pleiotropy in human genetic variation is driven by extreme polygenicity of human traits and diseases
Horizontal pleiotropy, where one variant has independent effects on multiple traits, is important for our understanding of the genetic architecture of human phenotypes. We develop a method to quantify horizontal pleiotropy using genome-wide association summary statistics and apply it to 372 heritable phenotypes measured in 361,194 UK Biobank individuals. Horizontal pleiotropy is pervasive throughout the human genome, prominent among highly polygenic phenotypes, and enriched in active regulatory regions. Our results highlight the central role horizontal pleiotropy plays in the genetic architecture of human phenotypes. The HOrizontal Pleiotropy Score (HOPS) method is available on Github at
https://github.com/rondolab/HOPS
.
Journal Article
A Review of Studies Involving the Effects of Climate Change on the Energy Consumption for Building Heating and Cooling
The world is faced with significant climate change, rapid urbanization, massive energy consumption, and tremendous pressure to reduce greenhouse gases. Building heating and cooling is one primary source of energy consumption and anthropogenic carbon dioxide emissions. First, this review presents previous studies that estimate the specific amount of climate change impact on building heating and cooling energy consumption, using the statistical method, physical model method, comprehensive assessment model method, and the combination method of statistical and physical model methods. Then, because the heating and cooling degree days indices can simply and reliably indicate the effects of climate on building heating and cooling energy consumption, previous studies were reviewed from the aspects of heating and cooling degree days indices, regional spatial-temporal variations in degree days and related indices, influencing factors of the spatial distributions of degree days, and the impacts of urbanization on degree days. Finally, several potential key issues or research directions were presented according to the research gaps or fields that need to be studied further in the future, such as developing methods to simply and accurately estimate the specified amounts of climate change impact on building cooling and heating energy consumption; using more effective methods to analyze the daytime, nighttime, and all-day spatial-temporal changes in different seasons in the past and future under various environment contexts by considering not only the air temperature but also the relative humidity, solar radiation, population, etc., and further exploring the corresponding more kinds of driving forces, including the various remotely sensed indices, albedo, nighttime light intensity, etc.; estimating the daytime, nighttime, and all-day impacts of urbanization on heating degree days (HDDs), cooling degree days (CDDs), and their sum (HDDs + CDDs) for vast cities in different environmental contexts at the station site, city, regional and global scales; producing and sharing of the related datasets; and analyzing the subsequent effects induced by climate change on the energy consumption for building heating and cooling, etc.
Journal Article