Statistical Measures to Quantify the Benefit from Screening: a Case Study on Cholesterol Screening

1994 ◽  
pp. 436-444
Author(s):  
Olaf Gefeller ◽  
Rainer Muche
Keyword(s):  
Cholesterol Screening ◽  
Statistical Measures

scholarly journals Development and Evaluation of Geostatistical Methods for Estimating Weather Related Collisions: A Large-Scale Case Study

2021 ◽  
pp. 036119812110200
Author(s):  
Andy H. Wong ◽  
Tae J. Kwon
Keyword(s):  
Large Scale ◽  
Mean Squared Error ◽  
Hot Spot ◽  
High Ratio ◽  
Contributing Factors ◽  
Geostatistical Methods ◽  
Road Users ◽  
Statistical Measures ◽  
Weather Events

Winter driving conditions pose a real hazard to road users with increased chance of collisions during inclement weather events. As such, road authorities strive to service the hazardous roads or collision hot spots by increasing road safety, mobility, and accessibility. One measure of a hot spot would be winter collision statistics. Using the ratio of winter collisions (WC) to all collisions, roads that show a high ratio of WC should be given a high priority for further diagnosis and countermeasure selection. This study presents a unique methodological framework that is built on one of the least explored yet most powerful geostatistical techniques, namely, regression kriging (RK). Unlike other variants of kriging, RK uses auxiliary variables to gain a deeper understanding of contributing factors while also utilizing the spatial autocorrelation structure for predicting WC ratios. The applicability and validity of RK for a large-scale hot spot analysis is evaluated using the northeast quarter of the State of Iowa, spanning five winter seasons from 2013/14 to 2017/18. The findings of the case study assessed via three different statistical measures (mean squared error, root mean square error, and root mean squared standardized error) suggest that RK is very effective for modeling WC ratios, thereby further supporting its robustness and feasibility for a statewide implementation.

scholarly journals Bayesian network-based methodology for selecting a cost-effective sewer asset management model

2020 ◽  
Author(s):  
Julián Guzmán-Fierro ◽  
Sharel Charry ◽  
Ivan González ◽  
Felipe Peña-Heredia ◽  
Nathalie Hernández ◽  
...  
Keyword(s):  
Asset Management ◽  
Kappa Coefficient ◽  
Wilcoxon Test ◽  
Cohen’S Kappa ◽  
Validation Data ◽  
Statistical Measures ◽  
Proactive Management ◽  
Cohen's Kappa ◽  
Cohen’S Kappa Coefficient

Abstract This paper presents a methodology based on Bayesian Networks (BN) to prioritise and select the minimal number of variables that allows predicting the structural condition of sewer assets to support the strategies in proactive management. The integration of BN models, statistical measures of agreement (Cohen's Kappa coefficient) and a statistical test (Wilcoxon test) were useful for a robust and straightforward selection of a minimum number of variables (qualitative and quantitative) that ensure a suitable prediction level of the structural conditions of sewer pipes. According to the application of the methodology to a specific case study (Bogotás sewer network, Colombia), it found that with only two variables (age and diameter) the model could achieve the same capacity of prediction (Cohen's Kappa coefficient = 0.43) as a model considering several variables. Furthermore, the methodology allows finding the calibration and validation percentage subsets that best fit (80% for calibration and 20% for validation data in the case study) in the model to increase the capacity of prediction with low variations. Furthermore, it found that a model, considering only pipes in critical and excellent conditions, increases the capacity of successful predictions (Cohen's Kappa coefficient from 0.2 to 0.43) for the proposed case study.

scholarly journals STUDENTS’ EMERGENT MODELLING OF STATISTICAL MEASURES – A CASE STUDY

2017 ◽  
Vol 16 (2) ◽  
pp. 144-162
Author(s):  
CHRISTIAN BÜSCHER ◽  
SUSANNE SCHNELL
Keyword(s):  
Conceptual Development ◽  
Statistics Education ◽  
School Students ◽  
Frequency Distributions ◽  
Research Journal ◽  
Statistical Measures ◽  
Statistical Knowledge ◽  
Learning Pathways ◽  
Teaching Learning

The present study investigates the processes of how German middle school students (age 14) interpret, contrast and evaluate different (informal) statistical measures in order to summarise and compare frequency distributions. To trace the developing insights into the properties of these measures, this paper uses the ‘emergent modelling’ perspective: measures are understood as models, which can either be used to make sense of a given situation or to reason about the statistical measures themselves, e.g. in terms of when they can be applied adequately. The emergent modelling approach is used (1) as a theoretical framework for describing students’ conceptual development, and (2) as a design heuristic for developing a teaching-learning arrangement aiming at developing insights about (frequency) distributions and statistical measures. In the qualitative analysis of a design experiment, two students’ emerging contextual and statistical knowledge is identified, revealing the intertwined nature of both types of knowledge. Overall, this paper illustrates the important role the emergent modelling perspective can play for designing as well as describing students’ learning pathways in statistics education. First published November 2017 at Statistics Education Research Journal Archives

scholarly journals Economic Rationale, Trade Impact and Extent of Antidumping – A Case Study of Pakistan

2007 ◽  
Vol 12 (1) ◽  
pp. 79-98
Author(s):  
Ahmed Nawaz Hakro ◽  
Syed Hasanat Shah
Keyword(s):  
Trade Diversion ◽  
Trade Barriers ◽  
Total Import ◽  
Predatory Behaviour ◽  
Statistical Measures ◽  
Economic Rationale ◽  
Intensive Use ◽  
Import Share ◽  
Antidumping Measures

This paper has analyzed the economic and political justification, trade impact and extent of antidumping measures initiated by Pakistan. Screening models for anti-predatory behaviour, Herfindahl-Hireshmann Index (HHI) for concentration and descriptive statistical measures are used to test the antidumping (AD) behaviour. The results are consistent with the earlier literature that AD duties have both a trade reduction and diversion effect. It is evident from the results in half of the cases studied that an economic rationale has been followed in the application of AD duties in Pakistan. Although the number of AD cases is limited, Pakistan has emerged as one of the intensive users of AD, relative to its total import share. It is also evident from the fact that intensive use of AD reduces trade and increases trade barriers, similarly, trade diversion reduces the chances of trade reduction. The key message emerging from this research is that trade diversion persists and in some cases trade diversion is substantial and it offsets the effect of AD measures on named countries to the benefit of non-named countries.

scholarly journals An Analytical Study on Adoption of Resistive Economy as a Political Strategy in Urban Management and Municipalities (Case Study: Zahedan Municipality)

2016 ◽  
Vol 10 (4) ◽  
pp. 88
Author(s):  
Seyed Moslem Seyedhosseini
Keyword(s):  
Human Resources ◽  
Citizen Participation ◽  
Geographical Location ◽  
Eastern Region ◽  
Political Strategy ◽  
Economic Policies ◽  
Statistical Measures ◽  
Laws And Regulations

Nowadays, municipalities provide services to more than 70 percent of countries around the world, particularly the developing countries. Nevertheless, the important role of such nongovernmental institutions has not been adequately recognized in realization of resistive economic policies. As a large Iranian city, Zahedan has the capability to become an economic hub in the eastern region of the country due to its unique geographical location. Thus, the municipality of Zahedan can play an invaluable role in achieving such a goal. This paper attempts to discuss the most important challenges facing municipalities, including the municipality of Zahedan in line with fulfillment of the resistive economic policy. These challenges are categorized into four areas including: Laws and regulations, administrational issues, human resources and citizen participation. The methodology is descriptive-analytical. Moreover, the data were analyzed in terms of statistical measures through SPSS. The results indicates that the greatest challenge concerning the faded role of municipalities in the urban economy originates respectively from laws and regulations, administrational issues, human resources and citizen participation.

scholarly journals Dynamic Villages in the Hinterland of a Polycentric Region: Case Study of the Górnośląsko-Zagłębiowska Metropolis in Poland

Land ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 779
Author(s):  
Elżbieta Zuzańska-Żyśko ◽  
Marlena Dyszy
Keyword(s):  
Labour Market ◽  
Metropolitan Area ◽  
Rural Areas ◽  
Economies Of Scale ◽  
Local Economy ◽  
Statistical Measures ◽  
Urban Complex ◽  
And Migration ◽  
Post Industrial

This article examines the growth of the labour market and entrepreneurship in a metropolitan area. In particular, the study attempts to answer how the economy of the rural regions is developing in the hinterland of a large urban complex in Southern Poland, which is transforming from a post-industrial conurbation into a metropolitan area. The study applied Florence’s local specialization index, statistical measures, dynamics indexes, and Pearson’s correlation index. The research results show that the local economy, including the labour market, is systematically growing. Rural communes refer to multifunctional development based on services, and they represent diverse economic specializations. They are subject to economies of scale and benefit from the proximity and impact of a large urban complex. The economic growth of rural areas in the hinterland is related to entrepreneurship, convenient location in relation to cities, and migration from cities to villages.

scholarly journals Video content analysis based on statistical modeling

2021 ◽  
Author(s):  
Jian Zhou
Keyword(s):  
Content Analysis ◽  
Statistical Modeling ◽  
Sequential Data ◽  
Video Content ◽  
Video Content Analysis ◽  
Statistical Measures ◽  
Video Parsing ◽  
Parsing Algorithm ◽  
Semantic Event

This thesis is aimed at finding solutions and statistical modeling techniques to analyze the video content in a way such that intelligent and efficient interaction with video is possible. In our work, we investigate several fundamental tasks for content analysis of video. Specifically, we propose an outline video parsing algorithm using basic statistical measures and an off-line solution using Independent Component Analysis (ICA). A spatiotemporal video similarity model based on dynamic programming is developed. For video object segmentation and tracking, we develop a new method based on probabilistic fuzzy c-means and Gibbs random fields. Theoretically, we develop a generic framework for sequential data analysis. The new framework integrates both Hidden Markov Model and ICA mixture model. The re-estimation formulas for model parameter learning are also derived. As a case study, the new model is applied to golf video for semantic event detection and recognition.

scholarly journals Video content analysis based on statistical modeling

2021 ◽  
Author(s):  
Jian Zhou
Keyword(s):  
Content Analysis ◽  
Statistical Modeling ◽  
Sequential Data ◽  
Video Content ◽  
Video Content Analysis ◽  
Statistical Measures ◽  
Video Parsing ◽  
Parsing Algorithm ◽  
Semantic Event

This thesis is aimed at finding solutions and statistical modeling techniques to analyze the video content in a way such that intelligent and efficient interaction with video is possible. In our work, we investigate several fundamental tasks for content analysis of video. Specifically, we propose an outline video parsing algorithm using basic statistical measures and an off-line solution using Independent Component Analysis (ICA). A spatiotemporal video similarity model based on dynamic programming is developed. For video object segmentation and tracking, we develop a new method based on probabilistic fuzzy c-means and Gibbs random fields. Theoretically, we develop a generic framework for sequential data analysis. The new framework integrates both Hidden Markov Model and ICA mixture model. The re-estimation formulas for model parameter learning are also derived. As a case study, the new model is applied to golf video for semantic event detection and recognition.

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