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With this aim, we performed a detailed morphological analysis and a multiple correspondence analysis with reference groups.
By means of a multiple correspondence analysis with the reference group, we were able to create a multidimensional space in which all 103 reference cases were placed according to their morphological profiles.
For the purpose of nearest-neighbor computations, therefore, categorical variables were expressed as 8 standard coordinates obtained by multiple correspondence analysis (with retention of 70% of the variance associated with the entire set of 126 categorical variables).
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We used Clusters of Orthologous Groups (COGs) automatic annotation and correspondence analysis (CA) with R software (http://www.R-project.org) [ 69] to graphically infer global trends between the above genomes.
Our aim was to investigate the variety and complexity of health behaviors of the mothers of toddlers visiting child health clinics by use of multiple correspondence analysis method with respect to potential transmission of oral bacteria from mother to child.
The karyotypes recorded at each sampled location were plotted in ordination space by detrended correspondence analysis (DCA), with environmental variables passively plotted to interpret the general relationship between karyotypes and EGVs.
We explored community composition using detrended correspondence analysis in combination with canonical correspondence analysis and indicator species analysis, and used generalized linear mixed models to investigate the responses of different bird groups to coffee management and landscape context.
We plotted results of Factor Correspondence Analysis [63] performed with allele frequencies of the 8 communities for factors 1 and 2 (26.5% and 17.6% of inertia, respectively) and for factors 1 and 3 (26.5% and 15.4%, respectively).
Correspondence analysis was performed with the "ca -package in R in analogy to a reca -packagein which the genetic diveRsiny of the humanalogyomavirus JC was used for reconstoucting human migrecentstudy6].
We used multiple correspondence analysis in conjunction with hierarchical classification, an approach to studying interrelationships between categorical variables that is gaining popularity in epidemiology and public health research areas.
Crichton and Hinde used multiple correspondence analysis to classify patients with chest pain into those with high cardiac risk and those with low cardiac risk [ 25].
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