scholarly journals Target estimands for efficient decision making: Response to comments on “Assessing the performance of population adjustment methods for anchored indirect comparisons: A simulation study”

2021 ◽  
Vol 40 (11) ◽  
pp. 2759-2763
Author(s):  
David M. Phillippo ◽  
Sofia Dias ◽  
Anthony E. Ades ◽  
Nicky J. Welton
Keyword(s):  
Decision Making ◽  
Simulation Study ◽  
Indirect Comparisons ◽  
Population Adjustment

scholarly journals Assessing the performance of population adjustment methods for anchored indirect comparisons: A simulation study

2020 ◽  
Vol 39 (30) ◽  
pp. 4885-4911
Author(s):  
David M. Phillippo ◽  
Sofia Dias ◽  
A. E. Ades ◽  
Nicky J. Welton
Keyword(s):  
Simulation Study ◽  
Indirect Comparisons ◽  
Population Adjustment

scholarly journals Dynamics of Military Conflict: an Economics Perspective

2014 ◽  
Vol 65 (2) ◽  
Author(s):  
Klaus B. Beckmann ◽  
Lennart Reimer
Keyword(s):  
Decision Making ◽  
Differential Games ◽  
Simulation Study ◽  
Economic Model ◽  
Dynamic Games ◽  
Rational Decision ◽  
Military Conflict ◽  
Rational Decision Making ◽  
Contest Success Functions ◽  
Military Theory

AbstractThis paper is concerned with methods for analysing patterns of conflict. We survey dynamic games, differential games, and simulation as alternative ways of extending the standard static economic model of conflict to study patterns of conflict dynamics, giving examples for each type of model.It turns out that computational requirements and theoretical difficulties impose tight limits on what can be achieved using the first two approaches. In particular, we appear to be forced to model the outcome of conflict as being decided in a single final confrontation if we employ non-linear contest success functions.A simulation study based on a new model of adaptive, boundedly rational decision making, however, is shown not to be subject to this limitation. Plausible patterns of conflict dynamics emerge, which we can link to both historical conflict and standard tenets of military theory.

scholarly journals Population Adjustment Methods for Indirect Comparisons: A Review of National Institute for Health and Care Excellence Technology Appraisals

2019 ◽  
Vol 35 (03) ◽  
pp. 221-228 ◽  
Author(s):  
David M. Phillippo ◽  
Sofia Dias ◽  
Ahmed Elsada ◽  
A. E. Ades ◽  
Nicky J. Welton
Keyword(s):  
Cross Validation ◽  
Individual Patient Data ◽  
Statistical Significance ◽  
Health Technology ◽  
Effective Sample Size ◽  
Simulation Studies ◽  
The United Kingdom ◽  
Treatment Comparisons ◽  
Indirect Comparisons ◽  
Population Adjustment

AbstractObjectivesIndirect comparisons via a common comparator (anchored comparisons) are commonly used in health technology assessment. However, common comparators may not be available, or the comparison may be biased due to differences in effect modifiers between the included studies. Recently proposed population adjustment methods aim to adjust for differences between study populations in the situation where individual patient data are available from at least one study, but not all studies. They can also be used when there is no common comparator or for single-arm studies (unanchored comparisons). We aim to characterise the use of population adjustment methods in technology appraisals (TAs) submitted to the United Kingdom National Institute for Health and Care Excellence (NICE).MethodsWe reviewed NICE TAs published between 01/01/2010 and 20/04/2018.ResultsPopulation adjustment methods were used in 7 percent (18/268) of TAs. Most applications used unanchored comparisons (89 percent, 16/18), and were in oncology (83 percent, 15/18). Methods used included matching-adjusted indirect comparisons (89 percent, 16/18) and simulated treatment comparisons (17 percent, 3/18). Covariates were included based on: availability, expert opinion, effective sample size, statistical significance, or cross-validation. Larger treatment networks were commonplace (56 percent, 10/18), but current methods cannot account for this. Appraisal committees received results of population-adjusted analyses with caution and typically looked for greater cost effectiveness to minimise decision risk.ConclusionsPopulation adjustment methods are becoming increasingly common in NICE TAs, although their impact on decisions has been limited to date. Further research is needed to improve upon current methods, and to investigate their properties in simulation studies.

Professional Competence and Intuitive Decision Making: A Simulation Study in the Domain of Emergency Medicine

2011 ◽  
Vol 5 (2) ◽  
pp. 119-136 ◽  
Author(s):  
Christian Harteis ◽  
Barbara Morgenthaler ◽  
Christine Kugler ◽  
Karl-Peter Ittner ◽  
Gabriel Roth ◽  
...  
Keyword(s):  
Decision Making ◽  
Emergency Medicine ◽  
Simulation Study ◽  
Professional Competence ◽  
Intuitive Decision Making

LEARNING DECISION FUNCTIONS IN THE FUZZY γ-MODELS

2000 ◽  
Vol 09 (04) ◽  
pp. 459-471 ◽  
Author(s):  
JUNG-HSIEN CHIANG
Keyword(s):  
Decision Making ◽  
Decision Analysis ◽  
Simulation Study ◽  
Information Aggregation ◽  
Aggregation Operator ◽  
Decision Making Process ◽  
Hierarchical Network ◽  
Numerical Examples ◽  
Fuzzy Models ◽  
Degree Of Satisfaction

In this approach, we investigate the fuzzy γ-models for decision analysis and making. This methodology utilizes fuzzy γ-model as an information aggregation operator. It provides several advantages due to the fact that the input to each model is the evidence supplied by the degree of satisfaction of sub-criteria and the output is the aggregated evidence. We also generalize fuzzy γ-models as a hierarchical network in this work. Thus, the decision making process is to aggregate and propagate the evidence information through such a hierarchical network. This trainable network is able to perceive and interpret complex decisions by using those fuzzy models. The simulation study examines the learning behaviors of the fuzzy γ-models using two numerical examples.

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