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Geometric data analysis -- Correspondence analysis -- Multiple correspondence analysis -- Passive and supplementary points, supplementary variables and structured data analysis -- MCA and ascending hierarchical cluster analysis -- Constructing spaces -- Analyzing sub-groups. Class specific MCA

Multiple correspondence analysis (MCA) is a statistical technique that first and foremost has become known through the work of the late Pierre Bourdieu (1930?2002) This book will introduce readers to the fundamental properties, procedures and rules of interpretation of the most commonly used forms of correspondence analysis. The book is written as a non-technical introduction, intended for the advanced undergraduate level and onwards. MCA represents and models data sets as clouds of points in a multidimensional Euclidean space. The interpretation of the data is based on these clouds of points. In seven chapters, this non-technical book will provide the reader with a comprehensive introduction and the needed knowledge to do analyses on his/her own: CA, MCA, specific MCA, the integration of MCA and variance analysis, of MCA and ascending hierarchical cluster analysis and class-specific MCA on subgroups. Special attention will be given to the construction of social spaces, to the construction of typologies and to group internal oppositions. This is a book on data analysis for the social sciences rather than a book on statistics. The main emphasis is on how to apply MCA to the analysis of practical research questions. It does not require a solid understanding of statistics and/or mathematics, and provides the reader with the needed knowledge to do analyses on his/her own.

A public safety answering point (PSAP) receives thousands of security alerts and attends a similar number of emergencies every day, and all the information related to those events is saved to be post-processed and scrutinized. Visualization and interpretation of emergency data can provide fundamental feedback to the first-response institutions, to managers planning resource distributions, and to all the instances participating in the emergency-response cycle. This paper develops the application of multiple correspondence analysis (MCA) of emergency responses in a PSAP, with the objective of finding informative relationships among the different categories of registered and attended events. We propose a simple yet statistically meaningful method to scrutinize the variety of events and recorded information in conventional PSAPs. For this purpose, MCA is made on the categorical features of the available report forms, and a statistical description is achieved from it by combining bootstrap resampling and Parzen windowing, in order to provide the user with the most relevant factors, their significance, and a meaningful representation of the event grouping trends in a given database. We analyzed the case of the 911-emergency database from Quito, Ecuador, which includes 1,078,846 events during 2014. Individual analysis of the first-response institutions showed that there are groups with very related categories, whereas their joint analysis showed significant relationships among several types of events. This was the case for fire brigades, military, and municipal services attending large-scale forest fires, where they work in a combined way. Independence could be established among actions in other categories, which was the case for specific police events (as drug selling and distribution) or fire brigades events (as fire threats). We also showed that a very low number of factors can be enough to accurately represent the dynamics of frequent events.

Educational institutions, as well as political, social and scientific discourses, have contributed towards discrimination and violence against people with non-normative sexual orientations. Acts of violence among peers (bullying) motivated by homophobia occur on a frequent basis in school contexts. This study aims to identify the patterns in which homophobic bullying (victim identified) takes place in Portuguese schools using Multiple Correspondence Analysis. This study involved the application of a questionnaire to people of both sexes before obtaining a total of 171 participants reporting themselves as victims of homophobic bullying in schools. Following the identification of eight indicators and the selection of two dimensions, while also structuring the axes in accordance with the representation space, four patterns of homophobic bullying could be identified: masculine violence, feminine violence, violence with less perceived impact, and violence with greater perceived impact. These different patterns have allowed us to learn about the different ways in which peer violence takes place in schools and its possible effects. Among the main study conclusions, it is highlighted how male participants were victims of violence at an earlier age than female participant victims. Another key finding is the complete lack of cases in which the aggressors were only female. Finally, a common conclusion to all participants, encapsulates how none of the victims reported the violence to their families for fear of losing family support by revealing a non-heterosexual orientation. ; info:eu-repo/semantics/publishedVersion

A public safety answering point (PSAP) receives thousands of security alerts and attends a similar number of emergencies every day, and all the information related to those events is saved to be post-processed and scrutinized. Visualization and interpretation of emergency data can provide fundamental feedback to the first-response institutions, to managers planning resource distributions, and to all the instances participating in the emergency-response cycle. This paper develops the application of multiple correspondence analysis (MCA) of emergency responses in a PSAP, with the objective of finding informative relationships among the different categories of registered and attended events. We propose a simple yet statistically meaningful method to scrutinize the variety of events and recorded information in conventional PSAPs. For this purpose, MCA is made on the categorical features of the available report forms, and a statistical description is achieved from it by combining bootstrap resampling and Parzen windowing, in order to provide the user with the most relevant factors, their significance, and a meaningful representation of the event grouping trends in a given database. We analyzed the case of the 911-emergency database from Quito, Ecuador, which includes 1,078,846 events during 2014. Individual analysis of the first-response institutions showed that there are groups with very related categories, whereas their joint analysis showed significant relationships among several types of events. This was the case for fire brigades, military, and municipal services attending large-scale forest fires, where they work in a combined way. Independence could be established among actions in other categories, which was the case for specific police events (as drug selling and distribution) or fire brigades events (as fire threats). We also showed that a very low number of factors can be enough to accurately represent the dynamics of frequent events.

Many authors report a positive relationship of education and political interest with political efficacy and trust, but it is well known that both of the former are associated with response styles, such as a tendency to "strongly agree." Since they are related to both a substantive concept (political efficacy and trust), and to methodological effects (agreement bias and a tendency to give non-substantive responses) it is important to assess whether the substantive relationship is due to methodological artifacts. Applying multiple correspondence analysis to the 1984 Canadian National Election Study, we will discuss a method which allows to test a set of items for measurement effects such as ordinality and response sets. In the given example, ordinality of the political efficacy and trust items could be confirmed only for politically interested respondents. For respondents with low political interest, there is clear evidence of a response set resulting in a tendency to "strongly agree" regardless of the direction of the items. Taken together, these findings call into question the substantive relationships reported in the literature.

The problem of the disaster becomes an important issue related to the resilience of an area in dealing with it. So it becomes the government's priority to determine excellent and appropriate disaster mitigation policies. Data is essential in supporting the mitigation policy. So the purpose of this study is to map the area in the form of plots of 34 provinces in Indonesia based on data on the number of villages that have disaster mitigation efforts and types of disasters. The data used is sourced from the Central Statistics Agency (CSA). Mapping uses the Multiple Correspondence Analysis (MCA) method. The results showed that the provincial MCA plot with the number of villages in disaster mitigation efforts explained 93.2% of the diversity of the data. The plot shows that some provinces have a high level of Mitigation efforts in their villages. Meanwhile, the Provincial MCA plot, with its type of disaster, explained the diversity of data at 78.6%. The plot shows that several provinces need attention because they have a large number of villages affected by the disaster. Masalah kebencanaan menjadi isu penting yang berhubungan dengan ketahanan suatu daerah dalam menghadapi bencana, sehingga hal tersebut menjadi prioritas pemerintah untuk menentukan kebijakan mitigasi bencana yang baik dan tepat. Oleh karena data merupakan hal penting dalam mendukung kebijakan mitigasi tersebut, sehingga tujuan penelitian ini adalah untuk memetakan daerah berupa plot 34 provinsi di Indonesia berdasarkan jumlah desa yang memiliki upaya mitigasi bencana dan jenis bencananya. Data yang digunakan bersumber dari Badan Pusat Statistik (BPS) dan pemetaan menggunakan metode Multiple Correspondence Analysis (MCA). Hasil penelitian menunjukan bahwa plot MCA provinsi dengan jumlah desa dalam upaya mitigasi bencana mampu menerangkan 93,2% keragaman data. Plot memperlihatkan bahwa beberapa provinsi telah memiliki tingkat upaya mitigasi yang tinggi di desanya. Sementara itu, plot MCA Provinsi dengan jenis bencananya mampu menerangkan keragaman data ...

Background: Previous works have shown that risk factors for some kinds of cancer depend on people's lifestyle (e.g. rural or urban residence). This article looks into this, seeking relationships between cancer, age group, gender and population in the region of Lleida (Catalonia, Spain) using Multiple Correspondence Analysis (MCA). Methods: The dataset analysed was made up of 3,408 cancer episodes between 2012 and 2014, extracted from the Population-based Cancer Registry (PCR) for Lleida province. The cancers studied were colon and rectal (1,059 cases), lung (551 cases), urinary bladder (446 cases), prostate (609 cases) and breast (743 cases). The MCA technique was applied and used to search relationships among the main qualitative features. The basic statistics were the percentage explaining (variance), the inertia and the contribution of each qualitative variable. Results: General outcomes showed a low and moderate contribution of living in rural areas to colorectal and male prostate cancer. Males in urban areas were slightly and heavily affected by lung and urinary bladder cancer respectively. The analysis of each cancer provided additional information. Colorectal cancer greatly affected males aged <60, urban residents aged 70-79, and rural females aged 80. The impact of lung cancer was high among urban females <60, moderate among males aged 70-79 and high among rural females aged 80. The results for urinary bladder cancer results were similar to those for lung cancer. Prostate cancer affected both the <60 and 80 age groups significantly in rural areas. Breast cancer hit the 70-79 group significantly and, somewhat less so, rural females aged 80. Conclusions: MCA was a significant help for detecting the contributions of qualitative variables and the associations between them. MCA has proven to be an effective technique for analyzing the incidence of cancer. The outcomes obtained help to corroborate suspected trends, as well as detecting and stimulating new hypotheses about the risk factors associated with a specific area and cancer. These findings will be helpful for encouraging new studies and prevention campaigns to highlight observed singularities. ; This work was supported by contract 2019-DI-43 of the Industrial Doctorate Program of the Government of Catalonia and by the Ministerio de Econom´ıa y Competitividad under contract TIN2017-84553-C2-2-R. Some of the authors are members of the research group 2014-SGR163, funded by the Generalitat de Catalunya.