Choice-Based Conjoint Analysis: A Bayesian Approach

This paper presents a Bayesian approach to Frequentist Logit Multinomial model used in Choice-based Conjoint Analysis. The analysis was conducted with data of choice for the assessment by 144 consumers, eight samples of light strawberry flavored yogurts, ranging information from three ingredients (sugar, fat and protein) in a full factorial design. the results and inferences obtained by the Bayesian approach are presented in terms of estimating the main effect of the attributes, the choice probabilities and choice ratio. The frequentist results are also reported and discussed. The Bayesian analysis showed similar results to frequentist and allowed the construction of credibility intervals for choice probabilities and choice ratio, allowing statistically compare such quantities. About the practical results, the most likely choice was associated with yoghurt containing strawberry flavor light information "0% sugar", "0% fat" and "bioactive proteins enriched"

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How many data clusters are in the Galaxy data set?

Advances in Data Analysis and Classification ◽

10.1007/s11634-021-00461-8 ◽

2021 ◽

Author(s):

Bettina Grün ◽

Gertraud Malsiner-Walli ◽

Sylvia Frühwirth-Schnatter

Keyword(s):

Mixture Model ◽

Bayesian Approach ◽

Clear Understanding ◽

Data Set ◽

Model Based Clustering ◽

The Galaxy ◽

Data Clusters ◽

The Impact ◽

Full Factorial ◽

The Bayesian Approach

AbstractIn model-based clustering, the Galaxy data set is often used as a benchmark data set to study the performance of different modeling approaches. Aitkin (Stat Model 1:287–304) compares maximum likelihood and Bayesian analyses of the Galaxy data set and expresses reservations about the Bayesian approach due to the fact that the prior assumptions imposed remain rather obscure while playing a major role in the results obtained and conclusions drawn. The aim of the paper is to address Aitkin’s concerns about the Bayesian approach by shedding light on how the specified priors influence the number of estimated clusters. We perform a sensitivity analysis of different prior specifications for the mixtures of finite mixture model, i.e., the mixture model where a prior on the number of components is included. We use an extensive set of different prior specifications in a full factorial design and assess their impact on the estimated number of clusters for the Galaxy data set. Results highlight the interaction effects of the prior specifications and provide insights into which prior specifications are recommended to obtain a sparse clustering solution. A simulation study with artificial data provides further empirical evidence to support the recommendations. A clear understanding of the impact of the prior specifications removes restraints preventing the use of Bayesian methods due to the complexity of selecting suitable priors. Also, the regularizing properties of the priors may be intentionally exploited to obtain a suitable clustering solution meeting prior expectations and needs of the application.

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Comparison Design of Experiment (DOE): Taguchi Method and Full Factorial Design in Surface Roughness

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.660.275 ◽

2014 ◽

Vol 660 ◽

pp. 275-279 ◽

Cited By ~ 3

Author(s):

Ali Rafidah ◽

A. Nurulhuda ◽

A. Azrina ◽

Y. Suhaila ◽

I.S. Anwar ◽

...

Keyword(s):

Surface Roughness ◽

Taguchi Method ◽

Factorial Design ◽

Optimal Parameter ◽

Full Factorial Design ◽

Taguchi Methods ◽

Main Effect ◽

Interaction Plot ◽

Full Factorial ◽

Better Than

Statistical quality improvement techniques such as design of experiments (DOE) and Taguchi methods form an essential part of the search for improved product performance. This paper applies both the Taguchi and full factorial design techniques to highlight the application and to compare the effectiveness of the Taguchi and full factorial design processes as applied on surface roughness. Besides that, to determine the optimal parameter setting for each factor in surface roughness. For this study, we used two different probes of Mahr Surf XR20 which was MFW 250 tracing arm 6851804 (25μm) and tracing arm 6851806 (50μm). The main effect and interaction plot had been analyzed by using MINITAB (software). The experiment result showed that full factorial design performs better than Taguchi method.

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REFINEMENT OF RELIABILITY INDICATORS BASED ON THE BAYESIAN APPROACH IN DESIGNING 10 KV AIR LINES

THE INTERNATIONAL TECHNICAL-ECONOMIC JOURNAL ◽

10.34286/1995-4646-2020-71-2-55-61 ◽

2020 ◽

pp. 55-61

Author(s):

TAMARA B. LESHINSKAY ◽

◽

SERGEY I. BELOV ◽

PAVEL S. PETROV ◽

◽

...

Keyword(s):

Bayesian Approach ◽

Reliability Indicators ◽

The Bayesian Approach

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Application of 32 Full Factorial Design and Desirability Function for Optimizing The Manufacturing Process for Directly Compressible Multi-Functional Co-Processed Excipient

Current Drug Delivery ◽

10.2174/1567201817666200508094743 ◽

2020 ◽

Vol 17 (6) ◽

pp. 523-539

Author(s):

Jalpa Patel ◽

Dhaval Mori

Keyword(s):

Factorial Design ◽

Spray Drying ◽

Desirability Function ◽

Full Factorial Design ◽

Angle Of Repose ◽

P Value ◽

Independent Variables ◽

Full Factorial ◽

32 Full Factorial Design ◽

Response Variables

Background: Developing a new excipient and obtaining its market approval is an expensive, time-consuming and complex process. Compared to that, the co-processing of already approved excipients has emerged as a more attractive option for bringing better characteristic excipients to the market. The application of the Design of Experiments (DoE) approach for developing co-processed excipient can make the entire process cost-effective and rapid. Objective: The aim of the present investigation was to demonstrate the applicability of the DoE approach, especially 32 full factorial design, to develop a multi-functional co-processed excipient for the direct compression of model drug - cefixime trihydrate using spray drying technique. Methods: The preliminary studies proved the significant effect of atomization pressure (X1) and polymer ratio (microcrystalline cellulose: mannitol - X2) on critical product characteristics, so they were selected as independent variables. The angle of repose, Carr’s index, Hausner’s ratio, tensile strength and Kuno’s constant were selected as response variables. Result: The statistical analysis proved a significant effect of both independent variables on all response variables with a significant p-value < 0.05. The desirability function available in Design Expert 11® software was used to prepare and select the optimized batch. The prepared co-processed excipient had better compressibility than individual excipients and their physical mixture and was able to accommodate more than 40 percent drug without compromising the flow property and compressibility. Conclusion: The present investigation successfully proved the applicability of 32 full factorial design as an effective tool for optimizing the spray drying process to prepare a multi-functional co-processed excipient.

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Formulation of Extended-Release Beads of Lamotrigine Based on Alginate and Cassia fistula Seed Gum by QbD Approach

Current Drug Delivery ◽

10.2174/1567201817666200317124022 ◽

2020 ◽

Vol 17 (5) ◽

pp. 422-437

Author(s):

Dixita Jain ◽

Akshay Sodani ◽

Swapnanil Ray ◽

Pranab Ghosh ◽

Gouranga Nandi

Keyword(s):

Drug Release ◽

Factorial Design ◽

Extended Release ◽

Polymer Concentration ◽

Green Manufacturing ◽

Full Factorial Design ◽

Cassia Fistula ◽

Negative Environmental Impact ◽

Seed Gum ◽

Full Factorial

Aim: This study was focused on the formulation of the multi-unit extended-release peroral delivery device of lamotrigine for better management of epilepsy. Background: The single-unit extended-release peroral preparations often suffer from all-or-none effect. A significant number of multi-unit delivery systems have been reported as a solution to this problem. But most of them are found to be composed of synthetic, semi-synthetic or their combination having physiological toxicity as well as negative environmental impact. Therefore, fabrication and formulation of multi-unit extended-release peroral preparations with natural, non-toxic, biodegradable polymers employing green manufacturing processes are being appreciated worldwide. Objective: Lamotrigine-loaded extended-release multi-unit beads have been fabricated with the incorporation of a natural polysaccharide Cassia fistula seed gum in calcium-cross-linked alginate matrix employing a simple green process and 23 full factorial design. Methods: The total polymer concentration, polymer ratio and [CaCl2] were considered as independent formulation variables with two different levels of each for the experiment-design. The extended-release beads were then prepared by the ionotropic gelation method using calcium chloride as the crosslinkerions provider. The beads were then evaluated for drug encapsulation efficiency and drug release. ANOVA of all the dependent variables such as DEE, cumulative % drug release at 2h, 5h, 12h, rate constant and dissolution similarity factor (f2) was done by 23 full factorial design using Design-Expert software along with numerical optimization of the independent variables in order to meet USP-reference release profile. Results: The optimized batch showed excellent outcomes with DEE of 84.7 ± 2.7 (%), CPR2h of 8.41± 2.96 (%), CPR5h of 36.8± 4.7 (%), CPR12h of 87.3 ± 3.64 (%) and f2 of 65.9. Conclusion: This approach of the development of multi-unit oral devices utilizing natural polysaccharides might be inspiring towards the world-wide effort for green manufacturing of sustained-release drug products by the QbD route.

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