The purpose of this article is to reduce potential statistical barriers and open doors to canonical correlation analysis (CCA) for applied behavioral scientists and personality researchers. CCA was selected for discussion, as it represents the highest level of the general linear model (GLM) and can be rather easily conceptualized as a method closely linked with the more widely understood Pearso...

A novel method for detecting neural activity in functional magnetic resonance imaging (fMRI) data is introduced. It is based on canonical correlation analysis (CCA), which is a multivariate extension of the univariate correlation analysis widely used in fMRI. To detect homogeneous regions of activity, the method combines a subspace modeling of the hemodynamic response and the use of spatial rel...

A method of reconstructing perceived or imagined music by analyzing brain activity has not yet been established. As a first step toward developing such a method, we aimed to reconstruct the imagery of rhythm, which is one element of music. It has been reported that a periodic electroencephalogram (EEG) response is elicited while a human imagines a binary or ternary meter on a musical beat. Howe...

This analysis was conducted to explore the association between 5 birth size measurements (weight, length and head, chest and mid-upper arm [MUAC] circumferences) as dependent variables and 10 maternal factors as independent variables using canonical correlation analysis (CCA). CCA considers simultaneously sets of dependent and independent variables and, thus, generates a substantially reduced t...

The aim of this study was to determine changes in composition, abundance and richness of species along a forest gradient with varying soils and flood regimes. The forests are located on the left bank of the lower Jucu River, in Jacarenema Natural Municipal Park, Espírito Santo. A survey of shrub/tree species was done in 80 plots, 5x25 m, equally distributed among the forests studied. We include...

Low-dimensional vector representations are widely used as stand-ins for the text of words, sentences, and entire documents. These embeddings are used to identify similar words or make predictions about documents. In this work, we consider embeddings for social media users and demonstrate that these can be used to identify users who behave similarly or to predict attributes of users. In order to...

Although many studies collect biomedical time series signals from multiple subjects, there is a dearth of models and methods for assessing the association between frequency domain properties of time series and other study outcomes. This article introduces the random Cramér representation as a joint model for collections of time series and static outcomes where power spectra are random functions...

We propose a method for estimating face depth maps from color face images. The method is based on Canonical Correlation Analysis (CCA) which exploits the correlation between face color texture and surface depth. The results of experiments conducted on a database of 218 3D scans with corresponding color images show that only a small number of canonical factors are needed to describe the function...

BACKGROUND The perceived responsiveness of a healthcare system reflects its ability to satisfy reasonable expectations of the public with respect to non-medical services. Recently, there has been increasing attention paid to responsiveness in evaluating the performance of a healthcare system in a variety of service settings. However, the factors that affect the responsiveness have been inconclu...

BACKGROUND Infection of the CNS is considered to be the major cause of encephalitis and more than 100 different pathogens have been recognized as causative agents. Despite being identified worldwide as an important public health concern, studies on encephalitis are very few and often focus on particular types (with respect to causative agents) of encephalitis (e.g. West Nile, Japanese, etc.). M...