Sensitivity Analysis and Robust Approach in Multidimensional Scaling: An Evaluation of Customer Satisfaction

Solaro, Nadia

doi:10.1080/16843703.2010.11673226

Cited by 5 publications

(5 citation statements)

References 13 publications

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“…1, with the grouping of accessions was developed based on Gower's general similarity coefficient. This coefficient is suitable for the data with mixed of qualitative and quantitative attributes (Solaro, 2010). The dendrogram constructed using UPGMA method showed that two main clusters were formed.…”

Section: Resultsmentioning

confidence: 99%

ASSESSMENT OF TAXONOMIC AFFINITY OF INDONESIAN PUMMELO (<i>CITRUS MAXIMA</i> (BURM.) MERR.) BASED ON MORPHOLOGICAL CHARACTERS

Susandarini

Subandiyah

Rugayah³

et al. 2013

American Journal of Agricultural and Biological Sciences

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Citrus maxima is a tropical fruit species with high morphological variability on fruit characters, including shape, size, thickness of peel, flesh color and taste. This variability has been used by breeders and common people to practically distinguish different pummelo cultivars. Despite such well known variation, so far there is no published study specifically addressed the extent of phenotypic variability and taxonomy of pummelo in Indonesia. This study was, therefore, aiming at assessing phenotypic variability and taxonomic affinity of Indonesian pummelo cultivars and landraces using multivariate analysis methods. A total of 60 accessions from six provinces were collected, including some representatives of registered cultivars. Twenty one morphological characters were subjected to cluster analysis and principal component analysis. Results showed that two major clusters were formed, in which each group was characterized by combination of distinctive morphological features leading to recognition of two cultivar groups. Based on the fact that the morphology of individuals from intensively cultivated orchards showed similar level of variability to those from sporadically distributed areas, there was strong indication that the morphological variation has genetic background.

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Section: Resultsmentioning

confidence: 99%

ASSESSMENT OF TAXONOMIC AFFINITY OF INDONESIAN PUMMELO (<i>CITRUS MAXIMA</i> (BURM.) MERR.) BASED ON MORPHOLOGICAL CHARACTERS

Susandarini

Subandiyah

Rugayah³

et al. 2013

American Journal of Agricultural and Biological Sciences

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“…Weighting is used to handle the missing values, a weight w ijl = 0 when the observation between points i and j is not available. Finally, GCS give much weights to the qualitative variables, when the variables are heterogeneous, such as Gini's or Shannon's heterogeneity [Solaro 2010].…”

Section: Input Data For Mdsmentioning

confidence: 99%

A Survey on Multidimensional Scaling

et al. 2018

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This survey presents multidimensional scaling (MDS) methods and their applications in real world. MDS is an exploratory and multivariate data analysis technique becoming more and more popular. MDS is one of the multivariate data analysis techniques, which tries to represent the higher dimensional data into lower space. The input data for MDS analysis is measured by the dissimilarity or similarity of the objects under observation. Once the MDS technique is applied to the measured dissimilarity or similarity, MDS results in a spatial map. In the spatial map, the dissimilar objects are far apart while objects which are similar are placed close to each other. In this survey paper, MDS is described fairly in comprehensive fashion by explaining the basic notions of classical MDS and how MDS can be helpful to analyze the multidimensional data. Later on various MDS based special models are described in a more mathematical way.

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“…DeLeeuw and Meulman (1986) have implemented a viable solution based on leave-one-out crossvalidation for tackling sensitivity issues in MDS as well as Linting et al (2007), and there is not much literature on this matter to date. Solaro (2010) presents an interesting application to customer satisfaction which is based on the latter approach for variables measured at different levels, for example, nominal, ordinal, or ratio scale. Despite a sensitivity study can also reveal possible influences of ''abnormal'' observations in a multivariate data analysis, there is a body of specific tools developed to search for multivariate outliers in data analysis.…”

Section: Are These Mds Configurations Stable and Robust?mentioning

confidence: 99%

“…However, when outliers come in batches the problem of masking may arise. In this sense, Solaro (2010) proposed to go deeper inside the structure of the data through the FS algorithm (Atkinson and Riani 2000;Riani et al 2009). As far as we know, there are still no contributions in literature which extend the applicability of FS to mixed-type data.…”

Section: Contaminating the Data Setmentioning

confidence: 99%

“…This topic has been scarcely addressed in the framework of mixed-type data. In this sense, Solaro (2010) and Riani, Torti, and Zani (2012) present interesting applications of the forward search (FS) procedure (Atkinson and Riani 2000;Riani, Atkinson, and Ceroli 2009) in the context of customer satisfaction analysis. As far as we know, the FS is still not extended to mixed-type data, hence it requires to assume an MDS configuration as the starting data matrix.…”

Section: Introductionmentioning

confidence: 99%

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On Visualizing Mixed-Type Data

Grané

Romera

2016

Sociological Methods & Research

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Survey data are usually of mixed type (quantitative, multistate categorical, and/or binary variables). Multidimensional scaling (MDS) is one of the most extended methodologies to visualize the profile structure of the data. Since the past 60s, MDS methods have been introduced in the literature, initially in publications in the psychometrics area. Nevertheless, sensitivity and robustness of MDS configurations have been topics scarcely addressed in the specialized literature. In this work, we are interested in the construction of robust profiles for mixed-type data using a proper MDS configuration. To this end, we propose to compare different MDS configurations (coming from different metrics) through a combination of sensitivity and robust analysis. In particular, as an alternative to classical Gower's metric, we propose a robust joint metric combining different distance matrices, avoiding redundant information, via related metric scaling. The search for robustness and identification of outliers is done through a distance-based procedure related to geometric variability notions. In this sense, we propose a statistic for detecting multivariate outliers in the context of mixed-type data and evaluate its performance through a simulation study. Finally, we apply these Downloaded from techniques to a real data set provided by the largest humanitarian organization involved in social programs in Spain, where we are able to find in a robust way the most relevant factors defining the profiles of people that were under risk of being socially excluded in the beginning of the 2008 economic crisis.

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Sensitivity Analysis and Robust Approach in Multidimensional Scaling: An Evaluation of Customer Satisfaction

Cited by 5 publications

References 13 publications

ASSESSMENT OF TAXONOMIC AFFINITY OF INDONESIAN PUMMELO (<i>CITRUS MAXIMA</i> (BURM.) MERR.) BASED ON MORPHOLOGICAL CHARACTERS

ASSESSMENT OF TAXONOMIC AFFINITY OF INDONESIAN PUMMELO (<i>CITRUS MAXIMA</i> (BURM.) MERR.) BASED ON MORPHOLOGICAL CHARACTERS

A Survey on Multidimensional Scaling

On Visualizing Mixed-Type Data

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