Cluster Analysis of Business Data

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On cluster analysis of complex and heterogeneous data

3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon Portugal.

Cluster analysis of self-awareness levels in adults with traumatic brain injury and relationship to outcome

The purpose of this study was to investigate the relationship between self-awareness, emotional distress, motivation, and outcome in adults with severe traumatic brain injury. A sample of 55 patients were selected from 120 consecutive patients with severe traumatic brain injury admitted to the rehabilitation unit of a large metropolitan public hospital. Subjects received multidisciplinary inpatient rehabilitation and different types of outpatient rehabilitation and community-based services according to availability and need, Measures used in the cluster analysis were the Patient Competency Rating Scale, Self-Awareness of Deficits Interview, Head Injury Behavior Scale, Change Assessment Questionnaire, the Beck Depression Inventory, and Beck Anxiety Inventory; outcome measures were the Disability Rating Scale, Community Integration Questionnaire, and Sickness Impact Profile. A three-cluster solution was selected, with groups labeled as high self-awareness (n = 23), low self-awareness (n = 23), and good recovery (n = 8). The high self-awareness cluster had significantly higher levels of self-awareness, motivation, and emotional distress than the low self-awareness cluster but did not differ significantly in outcome. Self-awareness after brain injury is associated with greater motivation to change behavior and higher levels of depression and anxiety; however, it was not clear that this heightened motivation actually led to any improvement in outcome. Rehabilitation timing and approach may need to be tailored to match the individual's level of self-awareness, motivation, and emotional distress.

Hierarchical cluster analysis of groups of individuals : application to business data

3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon Portugal.

Clustering of variables with a three-way approach for health sciences

TPM Vol. 21, No. 4, December 2014, 435-447 – Special Issue © 2014 Cises.

Cluster analysis of behavioural and event-related potentials during a contingent negative variation paradigm in remitting-relapsing and benign forms of multiple sclerosis

Background: Event-related potentials (ERPs) may be used as a highly sensitive way of detecting subtle degrees of cognitive dysfunction. On the other hand, impairment of cognitive skills is increasingly recognised as a hallmark of patients suffering from multiple sclerosis (MS). We sought to determine the psychophysiological pattern of information processing among MS patients with the relapsing-remitting form of the disease and low physical disability considered as two subtypes: 'typical relapsing-remitting' (RRMS) and 'benign MS' (BMS). Furthermore, we subjected our data to a cluster analysis to determine whether MS patients and healthy controls could be differentiated in terms of their psychophysiological profile.Methods: We investigated MS patients with RRMS and BMS subtypes using event-related potentials (ERPs) acquired in the context of a Posner visual-spatial cueing paradigm. Specifically, our study aimed to assess ERP brain activity in response preparation (contingent negative variation -CNV) and stimuli processing in MS patients. Latency and amplitude of different ERP components (P1, eN1, N1, P2, N2, P3 and late negativity -LN) as well as behavioural responses (reaction time -RT; correct responses -CRs; and number of errors) were analyzed and then subjected to cluster analysis. Results: Both MS groups showed delayed behavioural responses and enhanced latency for long-latency ERP components (P2, N2, P3) as well as relatively preserved ERP amplitude, but BMS patients obtained more important performance deficits (lower CRs and higher RTs) and abnormalities related to the latency (N1, P3) and amplitude of ERPs (eCNV, eN1, LN). However, RRMS patients also demonstrated abnormally high amplitudes related to the preparation performance period of CNV (cCNV) and post-processing phase (LN). Cluster analyses revealed that RRMS patients appear to make up a relatively homogeneous group with moderate deficits mainly related to ERP latencies, whereas BMS patients appear to make up a rather more heterogeneous group with more severe information processing and attentional deficits. Conclusions: Our findings are suggestive of a slowing of information processing for MS patients that may be a consequence of demyelination and axonal degeneration, which also seems to occur in MS patients that show little or no progression in the physical severity of the disease over time.

Analysis of variables that are not directly observable: influence on decision-making during the research process

The sample dimension, types of variables, format used for measurement, and construction of instruments to collect valid and reliable data must be considered during the research process. In the social and health sciences, and more specifically in nursing, data-collection instruments are usually composed of latent variables or variables that cannot be directly observed. Such facts emphasize the importance of deciding how to measure study variables (using an ordinal scale or a Likert or Likert-type scale). Psychometric scales are examples of instruments that are affected by the type of variables that comprise them, which could cause problems with measurement and statistical analysis (parametric tests versus non-parametric tests). Hence, investigators using these variables must rely on suppositions based on simulation studies or recommendations based on scientific evidence in order to make the best decisions.

Acute schistosomiasis: a risk underestimated by travelers and a diagnosis frequently missed by general practitioners-a cluster analysis of 42 travelers.

BACKGROUND: In 2011, a patient was admitted to our hospital with acute schistosomiasis after having returned from Madagascar and having bathed at the Lily waterfalls. On the basis of this patient's indication, infection was suspected in 41 other subjects. This study investigated (1) the knowledge of the travelers about the risks of schistosomiasis and their related behavior to evaluate the appropriateness of prevention messages and (2) the diagnostic workup of symptomatic travelers by general practitioners to evaluate medical care of travelers with a history of freshwater exposure in tropical areas. METHODS: A questionnaire was sent to the 42 travelers with potential exposure to schistosomiasis. It focused on pre-travel knowledge of the disease, bathing conditions, clinical presentation, first suspected diagnosis, and treatment. RESULTS: Of the 42 questionnaires, 40 (95%) were returned, among which 37 travelers (92%) reported an exposure to freshwater, and 18 (45%) were aware of the risk of schistosomiasis. Among these latter subjects, 16 (89%) still reported an exposure to freshwater. Serology was positive in 28 (78%) of 36 exposed subjects at least 3 months after exposure. Of the 28 infected travelers, 23 (82%) exhibited symptoms and 16 (70%) consulted their general practitioner before the information about the outbreak had spread, but none of these patients had a serology for schistosomiasis done during the first consultation. CONCLUSIONS: The usual prevention message of avoiding freshwater contact when traveling in tropical regions had no impact on the behavior of these travelers, who still went swimming at the Lily waterfalls. This prevention message should, therefore, be either modified or abandoned. The clinical presentation of acute schistosomiasis is often misleading. General practitioners should at least request an eosinophil count, when confronted with a returning traveler with fever. If eosinophilia is detected, it should prompt the search for a parasitic disease.

Cluster analysis of downscaled and explicitly simulated North Atlantic tropical cyclone tracks

A realistic representation of the North Atlantic tropical cyclone tracks is crucial as it allows, for example, explaining potential changes in US landfalling systems. Here we present a tentative study, which examines the ability of recent climate models to represent North Atlantic tropical cyclone tracks. Tracks from two types of climate models are evaluated: explicit tracks are obtained from tropical cyclones simulated in regional or global climate models with moderate to high horizontal resolution (1° to 0.25°), and downscaled tracks are obtained using a downscaling technique with large-scale environmental fields from a subset of these models. For both configurations, tracks are objectively separated into four groups using a cluster technique, leading to a zonal and a meridional separation of the tracks. The meridional separation largely captures the separation between deep tropical and sub-tropical, hybrid or baroclinic cyclones, while the zonal separation segregates Gulf of Mexico and Cape Verde storms. The properties of the tracks’ seasonality, intensity and power dissipation index in each cluster are documented for both configurations. Our results show that except for the seasonality, the downscaled tracks better capture the observed characteristics of the clusters. We also use three different idealized scenarios to examine the possible future changes of tropical cyclone tracks under 1) warming sea surface temperature, 2) increasing carbon dioxide, and 3) a combination of the two. The response to each scenario is highly variable depending on the simulation considered. Finally, we examine the role of each cluster in these future changes and find no preponderant contribution of any single cluster over the others.

Space-time cluster analysis of American visceral leishmaniasis in Bauru, Sao Paulo State, Brazil

A space-time analysis of American visceral leishmaniasis (AVL) in humans in the city of Bauru, Sao Paulo State, Brazil was carried out based on 239 cases diagnosed between June 2003 and October 2008. Spatial analysis of the disease showed that cases occurred especially in the city's urban areas. AVL annual incidence rates were calculated, demonstrating that the highest rate occurred in 2006 (19.55/100,000 inhabitants). This finding was confirmed by the time series analysis, which also showed a positive tendency over the period analyzed. The present study allows us to conclude that the disease was clustered in the Southwest side of the city in 2006, suggesting that this area may require special attention with regard to control and prevention measures.

Space-time cluster analysis of American visceral leishmaniasis in Bauru, São Paulo State, Brazil

A space-time analysis of American visceral leishmaniasis (AVL) in humans in the city of Bauru, São Paulo State, Brazil was carried out based on 239 cases diagnosed between June 2003 and October 2008. Spatial analysis of the disease showed that cases occurred especially in the city's urban areas. AVL annual incidence rates were calculated, demonstrating that the highest rate occurred in 2006 (19.55/100,000 inhabitants). This finding was confirmed by the time series analysis, which also showed a positive tendency over the period analyzed. The present study allows us to conclude that the disease was clustered in the Southwest side of the city in 2006, suggesting that this area may require special attention with regard to control and prevention measures.

Kawasaki syndrome: Cluster analysis of incident cases presenting to a pediatric tertiary care hospital in Texas from January 1, 2005 to December 31, 2009

Background: Despite almost 40 years of research into the etiology of Kawasaki Syndrome (KS), there is little research published on spatial and temporal clustering of KS cases. Previous analysis has found significant spatial and temporal clustering of cases, therefore cluster analyses were performed to substantiate these findings and provide insight into incident KS cases discharged from a pediatric tertiary care hospital. Identifying clusters from a single institution would allow for prospective analysis of risk factors and potential exposures for further insight into KS etiology. ^ Methods: A retrospective study was carried out to examine the epidemiology and distribution of patients presenting to Texas Children’s Hospital in Houston, Texas, with a diagnosis of Acute Febrile Mucocutaneous Lymph Node Syndrome (MCLS) upon discharge from January 1, 2005 to December 31, 2009. Spatial, temporal, and space-time cluster analyses were performed using the Bernoulli model with case and control event data. ^ Results: 397 of 102,761 total patients admitted to Texas Children’s Hospital had a principal or secondary diagnosis of Acute Febrile MCLS upon over the 5 year period. Demographic data for KS cases remained consistent with known disease epidemiology. Spatial, temporal, and space-time analyses of clustering using the Bernoulli model demonstrated no statistically significant clusters. ^ Discussion: Despite previous findings of spatial-temporal clustering of KS cases, there were no significant clusters of KS cases discharged from a single institution. This implicates the need for an expanded approach to conducting spatial-temporal cluster analysis and KS surveillance given the limitations of evaluating data from a single institution.^

Cluster analysis of high-dimensional data: A case study

Normal mixture models are often used to cluster continuous data. However, conventional approaches for fitting these models will have problems in producing nonsingular estimates of the component-covariance matrices when the dimension of the observations is large relative to the number of observations. In this case, methods such as principal components analysis (PCA) and the mixture of factor analyzers model can be adopted to avoid these estimation problems. We examine these approaches applied to the Cabernet wine data set of Ashenfelter (1999), considering the clustering of both the wines and the judges, and comparing our results with another analysis. The mixture of factor analyzers model proves particularly effective in clustering the wines, accurately classifying many of the wines by location.