Verification of Compliance for Multilevel Models in Individual Trace Semantics

2021 ◽  
Vol 47 (7) ◽  
pp. 515-521
Author(s):  
A. V. Khoroshilov
Keyword(s):  
Multilevel Models ◽  
Trace Semantics

scholarly journals Verification of Compliance for Multilevel Models in Individual Trace Semantics

2020 ◽  
Vol 32 (6) ◽  
pp. 19-30
Author(s):  
Alexey Vladimirovich Khoroshilov
Keyword(s):  
Multilevel Models ◽  
Transition System ◽  
Abstract Model ◽  
Detailed Model ◽  
Industrial Systems ◽  
Reasonable Approach ◽  
Trace Semantics ◽  
Initial States ◽  
Verification Techniques ◽  
Labelled Transition System

The paper considers the problem of verification of compliance between models representing the same system on different level of abstraction. The existing approaches are mostly based on refinement relation. But the models representing industrial systems are quite big and complex, while semantics gap between the level is quite big. As a result, the existing methods became too complex and labour intensive. The paper presents new verification techniques that targets to prove multimodel compliance in terms of individual trace semantics. The techniques assume that each model is verified, i.e. it is proved that starting from initial states of labelled transition system is not possible to reach unsafe states by using valid transitions. The first proposed technique allows to prove that the detailed model satisfies to requirements of the abstract model, i.e. reachable states of detailed model do not include states corresponding to unsafe states of the abstract model. The second proposed technique allows to prove that the detailed model satisfies to behaviour specification of the abstract model, i.e. all reachable transitions of the detailed model do not include transitions corresponding to invalid transitions of the abstract model. For each technique the correspondence relation is defined in terms of the models, i.e. the relations are formally defined and they can be used for analysis with interactive or automated provers. At the same time, there are some requirements to that relations that are expressed in terms of low level events that exist hypothetically only and can be analyzed theoretically only. As a result, the proposed techniques provides a reasonable approach to prove compliance between mulilevel models in more approachable way for industrial settings.

scholarly journals Verification of Compliance for Multilevel Models in Individual Trace Semantics

2020 ◽  
Vol 32 (6) ◽  
pp. 19-30
Author(s):  
Alexey Vladimirovich Khoroshilov
Keyword(s):  
Multilevel Models ◽  
Transition System ◽  
Abstract Model ◽  
Detailed Model ◽  
Industrial Systems ◽  
Reasonable Approach ◽  
Trace Semantics ◽  
Initial States ◽  
Verification Techniques ◽  
Labelled Transition System

The paper considers the problem of verification of compliance between models representing the same system on different level of abstraction. The existing approaches are mostly based on refinement relation. But the models representing industrial systems are quite big and complex, while semantics gap between the level is quite big. As a result, the existing methods became too complex and labour intensive. The paper presents new verification techniques that targets to prove multimodel compliance in terms of individual trace semantics. The techniques assume that each model is verified, i.e. it is proved that starting from initial states of labelled transition system is not possible to reach unsafe states by using valid transitions. The first proposed technique allows to prove that the detailed model satisfies to requirements of the abstract model, i.e. reachable states of detailed model do not include states corresponding to unsafe states of the abstract model. The second proposed technique allows to prove that the detailed model satisfies to behaviour specification of the abstract model, i.e. all reachable transitions of the detailed model do not include transitions corresponding to invalid transitions of the abstract model. For each technique the correspondence relation is defined in terms of the models, i.e. the relations are formally defined and they can be used for analysis with interactive or automated provers. At the same time, there are some requirements to that relations that are expressed in terms of low level events that exist hypothetically only and can be analyzed theoretically only. As a result, the proposed techniques provides a reasonable approach to prove compliance between mulilevel models in more approachable way for industrial settings.

Modeling Intraindividual Variability in Three-Level Multilevel Models

Methodology ◽  
2018 ◽  
Vol 14 (3) ◽  
pp. 95-108 ◽  
Author(s):  
Steffen Nestler ◽  
Katharina Geukes ◽  
Mitja D. Back
Keyword(s):  
Multilevel Model ◽  
Multilevel Models ◽  
Mixed Effects ◽  
Repeated Measurements ◽  
Scale Model ◽  
Suggested Approach ◽  
Psychological Study ◽  
Level Data ◽  
Ecological Momentary ◽  
Momentary Assessment

Abstract. The mixed-effects location scale model is an extension of a multilevel model for longitudinal data. It allows covariates to affect both the within-subject variance and the between-subject variance (i.e., the intercept variance) beyond their influence on the means. Typically, the model is applied to two-level data (e.g., the repeated measurements of persons), although researchers are often faced with three-level data (e.g., the repeated measurements of persons within specific situations). Here, we describe an extension of the two-level mixed-effects location scale model to such three-level data. Furthermore, we show how the suggested model can be estimated with Bayesian software, and we present the results of a small simulation study that was conducted to investigate the statistical properties of the suggested approach. Finally, we illustrate the approach by presenting an example from a psychological study that employed ecological momentary assessment.

The impact of participant pathways on the effectiveness of a community-based physical activity intervention grounded in motivational interviewing

2020 ◽  
Author(s):  
Matthew Wade ◽  
Nicola Brown ◽  
James Steele ◽  
Steven Mann ◽  
Bernadette Dancy ◽  
...  
Keyword(s):  
Physical Activity ◽  
Primary Care ◽  
Motivational Interviewing ◽  
Social Action ◽  
Multilevel Models ◽  
Physical Activity Intervention ◽  
Mental Wellbeing ◽  
Community Based ◽  
The Impact ◽  
Time Point

Background: Brief advice is recommended to increase physical activity (PA) within primary care. This study assessed change in PA levels and mental wellbeing after a motivational interviewing (MI) community-based PA intervention and the impact of signposting [SP] and Social Action [SA] (i.e. weekly group support) pathways. Methods: Participants (n=2084) took part in a community-based, primary care PA programme using MI techniques. Self-reported PA and mental wellbeing data were collected at baseline (following an initial 30-minute MI appointment), 12-weeks, six-months, and 12-months. Participants were assigned based upon the surgery they attended to the SP or SA pathway. Multilevel models were used to derive point estimates and 95%CIs for outcomes at each time point and change scores. Results: Participants increased PA and mental wellbeing at each follow-up time point through both participant pathways and with little difference between pathways. Retention was similar between pathways at 12-weeks, but the SP pathway retained more participants at six-months and 12-months. Conclusions: Both pathways produced similar improvements in PA and mental wellbeing, suggesting the effectiveness of MI based PA interventions. However, due to lower resources required yet similar effects, SP pathways are recommended over SA to support PA in primary care settings.

Justifying the data analytical choice in single case research in relation to the expected data pattern

2019 ◽  
Author(s):  
Rumen Manolov
Keyword(s):  
Data Analysis ◽  
Visual Analysis ◽  
Multilevel Models ◽  
Single Case ◽  
Analytical Techniques ◽  
Real Data ◽  
Small Scale ◽  
Data User ◽  
Single Case Research ◽  
User Friendly

The lack of consensus regarding the most appropriate analytical techniques for single-case experimental designs data requires justifying the choice of any specific analytical option. The current text mentions some of the arguments, provided by methodologists and statisticians, in favor of several analytical techniques. Additionally, a small-scale literature review is performed in order to explore if and how applied researchers justify the analytical choices that they make. The review suggests that certain practices are not sufficiently explained. In order to improve the reporting regarding the data analytical decisions, it is proposed to choose and justify the data analytical approach prior to gathering the data. As a possible justification for data analysis plan, we propose using as a basis the expected the data pattern (specifically, the expectation about an improving baseline trend and about the immediate or progressive nature of the intervention effect). Although there are multiple alternatives for single-case data analysis, the current text focuses on visual analysis and multilevel models and illustrates an application of these analytical options with real data. User-friendly software is also developed.

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