Classification of evidence in decision-analytic models of cost-effectiveness: A content analysis of published reports

2010 ◽  
Vol 26 (4) ◽  
pp. 458-462 ◽  
Author(s):  
Suzy Paisley
Keyword(s):  
Content Analysis ◽  
Cost Effectiveness ◽  
Methodological Approach ◽  
Model Development ◽  
Three Dimensions ◽  
Model Parameters ◽  
Modeling Framework ◽  
Diverse Range ◽  
Analytic Models

Objectives: The aim of this study was to assess systematically the scope of evidence and purposes for which evidence is used in decision-analytic models of cost-effectiveness and to assess the implications for search methods.Methods: A content analysis of published reports of models was undertaken. Details of cited sources were extracted and categorized according to three dimensions; type of information provided by the evidence, type of source from which the evidence was drawn and type of modeling activity supported by the evidence. The analysis was used to generate a classification of evidence. Relationships within and between the categories within the classification were sought and the implications for searching considered.Results: The classification generated fourteen types of information, seven types of sources of evidence and five modeling activities supported by evidence. A broad range of evidence was identified drawn from a diverse range of sources including both research-based and non–research-based sources. The use of evidence was not restricted to the population of model parameters but was used to inform the development of the modeling framework and to justify the analytical and methodological approach.Conclusions: Decision-analytic models use evidence to support all aspects of model development. The classification of evidence defines in depth the role of evidence in modeling. It can be used to inform the systematic identification of evidence.

scholarly journals The Model of Basic Education Curriculum Administration according to Buddhist Principles in Eastern Economic Corridor

2021 ◽  
Vol 58 (1) ◽  
pp. 1599-1604
Author(s):  
Rungtawee Panrana Et al.
Keyword(s):  
Content Analysis ◽  
Quantitative Research ◽  
Basic Education ◽  
Group Discussion ◽  
Model Development ◽  
Education Institution ◽  
School Curriculum ◽  
Three Dimensions ◽  
Education Curriculum ◽  
High Level

The purposes of this research were 1) study the current states of the school curriculum administration 2) to develop the model of basic education curriculum administration according to Buddhist principles in Eastern Economic Corridor and 3) to evaluate the model. Quantitative research and qualitative research were used and research tools were interview form and questionnaires. Data were collected from in-depth interview, focus group discussion and document analysis. Qualitative data from 20 key informants was analyzed by using content analysis whereas quantitative data collected from 265 samples was analyzed by using content analysis, percentage, mean, and standard deviation. Results indicated that 1) the current states of the school curriculum administration of basic education institution in Eastern Economic Corridor in 5 variables found that overall it was appropriate at a high level. When considered individually, it was found that there were two most appropriate levels, namely supervision, monitoring and promotion. 2) The results of the model development that consists of 4 parts: 1. Educational curriculum management process consists of three dimensions. 2. The application of Buddhist principles in the school curriculum administration consists of three principles of the Threefold Training. 3. The key players of the school curriculum administration and 4. The7  results of the using of the model. 3) The model evaluation with 4-sided: Utility, Accuracy, Propriety and Feasibility found that the overall were appropriate at the highest level in all aspects. Sorted as follows: The Utility aspect was the highest, followed by the Accuracy, Propriety and Feasibility.

Sense of Place and Gender Perceptions

2021 ◽  
pp. 253-276
Author(s):  
Hakan Sezerel ◽  
Özlem Güzel
Keyword(s):  
Content Analysis ◽  
Data Analysis ◽  
Sense Of Place ◽  
Relevant Literature ◽  
Three Dimensions ◽  
Theoretical Context ◽  
Gender Perceptions ◽  
Cultural Conditioning ◽  
And Gender

Cultural conditioning aligns with gendered preconceptions permeating all aspects of life, including the tourists' experiences. However, the literature on gendered gazes to destinations is limited. The purpose of this research is to find the gendered characteristics of the destinations. The theoretical context that the research is set within the context of the sense of place and the gender conceptions attributed to a certain destination. The qualitative method was adopted to identify the part of the participants' experience of Bangkok destination as the search area via interviews. The content analysis was used for the data analysis and codes were grouped into themes according to the masculine, feminine, and/or neutral categories. Elucidating the relevant literature in tourism on gendered experiences, the findings have given ideas for the gendered characteristic of a destination within the classification of masculine, feminine, and neutral. Furthermore, three dimensions have been determined within the context of the sense of place, namely “visual, psychological, and spiritual.”

A Three Dimensional Model of Zebrafish Swimming

2016 ◽  
Author(s):  
Violet Mwaffo ◽  
Sachit Butail ◽  
Maurizio Porfiri
Keyword(s):  
Ethical Issues ◽  
Three Dimensional ◽  
Coupled System ◽  
Ease Of Use ◽  
Three Dimensions ◽  
Alternative Methods ◽  
Model Parameters ◽  
Three Dimensional Model ◽  
Modeling Framework ◽  
Speed Modulation

Zebrafish is becoming an important animal model in pre-clinical studies for its genetic similarity to humans and ease of use in the laboratory. In recent years, animal experimentation has faced several ethical issues, calling for alternative methods that capitalize on dynamical systems theory. Here, we propose a computational modeling framework to simulate zebrafish swimming in three dimensions (3D) in the form of a coupled system of stochastic differential equations. The model is capable of reproducing the burst-and-coast swimming style of zebrafish, speed modulation, and avoidance of tank boundaries. Model parameters are calibrated on an experimental dataset of zebrafish swimming in 3D and validated by comparing established behavioral measures obtained from both synthetic and experimental data. We show that the model is capable of accurately predicting fish locomotion in terms of the swimming speed and number of entries in different sections of the tank. The proposed model lays the foundations for in-silico experiments of zebrafish neurobehavioral research.

A Framework for Addressing Structural Uncertainty in Decision Models

2011 ◽  
Vol 31 (4) ◽  
pp. 662-674 ◽  
Author(s):  
Christopher H. Jackson ◽  
Laura Bojke ◽  
Simon G. Thompson ◽  
Karl Claxton ◽  
Linda D. Sharples
Keyword(s):  
Cost Effectiveness ◽  
Probability Distributions ◽  
Predictive Ability ◽  
Decision Models ◽  
Data Uncertainty ◽  
Model Parameters ◽  
Biologic Drugs ◽  
Uncertain Model ◽  
Alternative Scenarios ◽  
Analytic Models

Decision analytic models used for health technology assessment are subject to uncertainties. These uncertainties can be quantified probabilistically, by placing distributions on model parameters and simulating from these to generate estimates of cost-effectiveness. However, many uncertain model choices, often termed structural assumptions, are usually only explored informally by presenting estimates of cost-effectiveness under alternative scenarios. The authors show how 2 recent research proposals represent parts of a framework to formally account for all common structural uncertainties. First, the model is expanded to include parameters that encompass all possible structural choices. Uncertainty can then arise because these parameters are estimated imprecisely from data, for example, a treatment effect of doubtful significance. Uncertainty can also arise if there are no relevant data. If there are relevant data, uncertainty can be addressed by averaging expected costs and effects generated from probabilistic analysis of the models with and without the parameter. The weights used for averaging are related to the predictive ability of each model, assessed against the data. If there are no data, additional parameters can often be informed by eliciting expert beliefs as probability distributions. These ideas are illustrated in decision models for antiplatelet therapies for vascular disease and new biologic drugs for the treatment of active psoriatic arthritis.

Of Frames and Cultures - A Cross-Cultural Comparison of TV Newscasts

2006 ◽  
Vol 18 (4) ◽  
pp. 160-173 ◽  
Author(s):  
Maria Senokozlieva ◽  
Oliver Fischer ◽  
Gary Bente ◽  
Nicole Krämer
Keyword(s):  
Content Analysis ◽  
Arab World ◽  
Methodological Approach ◽  
Cross Cultural ◽  
Cultural Comparison ◽  
Explorative Study ◽  
Cross Cultural Comparison ◽  
Tv News ◽  
The Usa ◽  
The Relationship

Abstract. TV news are essentially cultural phenomena. Previous research suggests that the often-overlooked formal and implicit characteristics of newscasts may be systematically related to culture-specific characteristics. Investigating these characteristics by means of a frame-by-frame content analysis is identified as a particularly promising methodological approach. To examine the relationship between culture and selected formal characteristics of newscasts, we present an explorative study that compares material from the USA, the Arab world, and Germany. Results indicate that there are many significant differences, some of which are in line with expectations derived from cultural specifics. Specifically, we argue that the number of persons presented as well as the context in which they are presented can be interpreted as indicators of Individualism/Collectivism. The conclusions underline the validity of the chosen methodological approach, but also demonstrate the need for more comprehensive and theory-driven category schemes.

An Information-theoretical Model for Breast Cancer Detection

2008 ◽  
Vol 47 (04) ◽  
pp. 322-327 ◽  
Author(s):  
D. Blokh ◽  
N. Zurgil ◽  
I. Stambler ◽  
E. Afrimzon ◽  
Y. Shafran ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Hamming Distance ◽  
Formal Model ◽  
Methodological Approach ◽  
Breast Cancer Detection ◽  
Receptor Expression ◽  
Diagnostic Model ◽  
Model Parameters ◽  
Two Stages

Summary Objectives: Formal diagnostic modeling is an important line of modern biological and medical research. The construction of a formal diagnostic model consists of two stages: first, the estimation of correlation between model parameters and the disease under consideration; and second, the construction of a diagnostic decision rule using these correlation estimates. A serious drawback of current diagnostic models is the absence of a unified mathematical methodological approach to implementing these two stages. The absence of aunified approach makesthe theoretical/biomedical substantiation of diagnostic rules difficult and reduces the efficacyofactual diagnostic model application. Methods: The present study constructs a formal model for breast cancer detection. The diagnostic model is based on information theory. Normalized mutual information is chosen as the measure of relevance between parameters and the patterns studied. The “nearest neighbor” rule is utilized for diagnosis, while the distance between elements is the weighted Hamming distance. The model concomitantly employs cellular fluorescence polarization as the quantitative input parameter and cell receptor expression as qualitative parameters. Results: Twenty-four healthy individuals and 34 patients (not including the subjects analyzed for the model construction) were tested by the model. Twenty-three healthy subjects and 34 patients were correctly diagnosed. Conclusions: The proposed diagnostic model is an open one,i.e.it can accommodate new additional parameters, which may increase its effectiveness.

scholarly journals The ICON Single-Column Mode

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 906
Author(s):  
Ivan Bašták Ďurán ◽  
Martin Köhler ◽  
Astrid Eichhorn-Müller ◽  
Vera Maurer ◽  
Juerg Schmidli ◽  
...  
Keyword(s):  
Data Storage ◽  
Model Development ◽  
Computational Cost ◽  
Three Dimensional ◽  
Shallow Convection ◽  
Modeling Framework ◽  
Additional Tool ◽  
Eddy Simulation ◽  
Single Column ◽  
Stratocumulus Clouds

The single-column mode (SCM) of the ICON (ICOsahedral Nonhydrostatic) modeling framework is presented. The primary purpose of the ICON SCM is to use it as a tool for research, model evaluation and development. Thanks to the simplified geometry of the ICON SCM, various aspects of the ICON model, in particular the model physics, can be studied in a well-controlled environment. Additionally, the ICON SCM has a reduced computational cost and a low data storage demand. The ICON SCM can be utilized for idealized cases—several well-established cases are already included—or for semi-realistic cases based on analyses or model forecasts. As the case setup is defined by a single NetCDF file, new cases can be prepared easily by the modification of this file. We demonstrate the usage of the ICON SCM for different idealized cases such as shallow convection, stratocumulus clouds, and radiative transfer. Additionally, the ICON SCM is tested for a semi-realistic case together with an equivalent three-dimensional setup and the large eddy simulation mode of ICON. Such consistent comparisons across the hierarchy of ICON configurations are very helpful for model development. The ICON SCM will be implemented into the operational ICON model and will serve as an additional tool for advancing the development of the ICON model.

scholarly journals Cost-effectiveness of TAS-102 plus bevacizumab versus TAS-102 monotherapy in patients with metastatic colorectal cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kiyoaki Sugiura ◽  
Yuki Seo ◽  
Takayuki Takahashi ◽  
Hideyuki Tokura ◽  
Yasuhiro Ito ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Health Care ◽  
Sensitivity Analysis ◽  
Cost Effectiveness ◽  
Combination Therapy ◽  
Metastatic Colorectal Cancer ◽  
Cost Effective ◽  
Model Parameters ◽  
Combination Regimen ◽  
The Cost

Abstract Background TAS-102 plus bevacizumab is an anticipated combination regimen for patients who have metastatic colorectal cancer. However, evidence supporting its use for this indication is limited. We compared the cost-effectiveness of TAS-102 plus bevacizumab combination therapy with TAS-102 monotherapy for patients with chemorefractory metastatic colorectal cancer. Method Markov decision modeling using treatment costs, disease-free survival, and overall survival was performed to examine the cost-effectiveness of TAS-102 plus bevacizumab combination therapy and TAS-102 monotherapy. The Japanese health care payer’s perspective was adopted. The outcomes were modeled on the basis of published literature. The incremental cost-effectiveness ratio (ICER) between the two treatment regimens was the primary outcome. Sensitivity analysis was performed and the effect of uncertainty on the model parameters were investigated. Results TAS-102 plus bevacizumab had an ICER of $21,534 per quality-adjusted life-year (QALY) gained compared with TAS-102 monotherapy. Sensitivity analysis demonstrated that TAS-102 monotherapy was more cost-effective than TAS-102 and bevacizumab combination therapy at a willingness-to-pay of under $50,000 per QALY gained. Conclusions TAS-102 and bevacizumab combination therapy is a cost-effective option for patients who have metastatic colorectal cancer in the Japanese health care system.

EM Algorithm Based on Fuzzification and its Application

2012 ◽  
Vol 532-533 ◽  
pp. 1445-1449
Author(s):  
Ting Ting Tong ◽  
Zhen Hua Wu
Keyword(s):  
Em Algorithm ◽  
Mixed Model ◽  
Image Data ◽  
Training Sample ◽  
Model Parameters ◽  
Parameter Learning ◽  
Weighted Degree ◽  
The Em Algorithm ◽  
The Impact

EM algorithm is a common method to solve mixed model parameters in statistical classification of remote sensing image. The EM algorithm based on fuzzification is presented in this paper to use a fuzzy set to represent each training sample. Via the weighted degree of membership, different samples will be of different effect during iteration to decrease the impact of noise on parameter learning and to increase the convergence rate of algorithm. The function and accuracy of classification of image data can be completed preferably.

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