A Canonical Correlation Analysis of Relationships Between Growth, Compositional Traits and Longevity, Lifetime Productivity and Efficiency in Polish Landrace Sows

Abstract Relationships between performance test traits (growth rate, backfat thickness, loin depth, lean meat percentage, exterior, phenotypic selection index) and longevity traits (length of productive life, number of litters, total number of weaned pigs, number of weaned piglets per year, number of litters per year) in Landrace sows were evaluated using canonical correlation analysis. The data set consisted of 23,012 purebred sows that farrowed from 1994 to 2011 in 161 herds. The first three canonical correlations (0.37, 0.25, 0.07) were highly significant (P<0.0001). Correlations of the first canonical variate with the original measured variables indicated that sows with high values for this variate had lower growth rate (r=-0.31) and loin depth (r=-0.43), greater backfat thickness (r=0.23), as well as being older at birth of their last litter (r=0.98). These sows also had a greater number of litters (r=0.94) and better lifetime efficiency (r=0.61 and r=0.70 for number of weaned piglets per year and number of litters per year, respectively). Canonical loadings for the second canonical function indicate that sows with high values for the second set of variates had high growth rate (r=0.79) and phenotypic selection index (r=0.83), excellent conformation (r=0.62), as well as better efficiency in pig production (r=0.67). The squared multiple correlations show that the first canonical variate of the performance traits is a poor predictor of longevity (0.13) and nearly useless for predicting efficiency traits (0.07). Performance test traits explain 11% of the variance in the variables of longevity and lifetime productivity, whereas dependent variables explain only 3% of the variance in performance test traits. The relationships between performance test data and subsequent lifetime productivity or longevity were significant and unfavourable but low for Polish Landrace population

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Analysis of Soil-Vegetation Interrelationships in a South-Southern Secondary Forest of Nigeria

International Journal of Forestry Research ◽

10.1155/2012/469326 ◽

2012 ◽

Vol 2012 ◽

pp. 1-8 ◽

Cited By ~ 4

Author(s):

D. D. Eni ◽

A. I. Iwara ◽

R. A. Offiong

Keyword(s):

Organic Matter ◽

Correlation Analysis ◽

Canonical Correlation Analysis ◽

State Government ◽

Canonical Correlation ◽

Secondary Forest ◽

Principal Component ◽

Tree Density ◽

Tree Size ◽

Canonical Variate

Soil-vegetation interrelationships in a secondary forest of South-Southern Nigeria were studied using principal component analysis (PCA) and canonical correlation analysis (CCA). The grid system of vegetation sampling was employed to randomly collect vegetation and soil data from fifteen quadrats of 10 m × 10 m. PCA result showed that exchangeable sodium, organic matter, cation exchange capacity, exchangeable calcium, and sand content were the major soil properties sustaining the regenerative capacity and luxuriant characteristics of the secondary forest, while tree size and tree density constituted the main vegetation parameters protecting and enriching the soil for its continuous support to the vegetation after decades of anthropogenic disturbance (food crop cultivation and illegal logging activities) before its acquisition and subsequent preservation by the Cross River State government in 2003. In addition, canonical correlation analysis showed result similar to PCA, as it indicated a pattern of relationship between soil and vegetation. The only retained canonical variate revealed a positive interrelationship between organic matter and tree size as well as an inverse relationship between organic matter and tree density. These extracted soil and vegetation variables are indeed significantly important in explaining soil-vegetation interrelationships in the highly regenerative secondary forest.

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Canonical correlation analysis of the career attitudes and strategies inventory and the adult career concerns inventory

SA Journal of Industrial Psychology ◽

10.4102/sajip.v32i3.436 ◽

2006 ◽

Vol 32 (3) ◽

Cited By ~ 1

Author(s):

Charlene C Lew ◽

Gideon P De Bruin

Keyword(s):

Correlation Analysis ◽

Canonical Correlation Analysis ◽

Canonical Correlation ◽

Career Concerns ◽

Canonical Variate ◽

Career Attitudes ◽

Family Commitment ◽

Adult Career ◽

Adult Career Concerns Inventory ◽

High Level

This study investigated the relationships between the scales of the Adult Career Concerns Inventory (ACCI) and those of the Career Attitudes and Strategies Inventory (CASI). The scores of 202 South African adults for the two inventories were subjected to a canonical correlation analysis. Two canonical variates made statistically significant contributions to the explanation of the relationships between the two sets of variables. Inspection of the correlations of the original variables with the first canonical variate suggested that a high level of career concerns in general, as measured by the ACCI, is associated with high levels of career worries, more geographical barriers, a low risk-taking style and a non-dominant interpersonal style, as measured by the CASI. The second canonical variate suggested that concerns with career exploration and advancement of one’s career is associated with low job satisfaction, low family commitment, high work involvement, and a dominant style at work.

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A-157 How Important Is Sustained Attention in Reversal Learning and Visual Task Shifting Abilities: A Canonical Correlation Analysis in Adults

Archives of Clinical Neuropsychology ◽

10.1093/arclin/acaa068.157 ◽

2020 ◽

Vol 35 (6) ◽

pp. 951-951

Author(s):

Gracian E ◽

Mathew A ◽

Jimenez T ◽

Oleson S ◽

Kaufman D ◽

...

Keyword(s):

Correlation Analysis ◽

Canonical Correlation Analysis ◽

Reversal Learning ◽

Sustained Attention ◽

Canonical Correlation ◽

Performance Test ◽

Task Shifting ◽

Visual Task ◽

Data Set ◽

And Task

Abstract Objective We used canonical correlation analysis (CCA) to examine the relationship between performance on cognitive neuroscience measures of sustained attention, deterministic reversal learning (DRLT), and visual task-shifting (VTS). We evaluated whether DRLT and VTS predicted performance on the Continuous Performance Test-II (CPT-II). Method Participants were 1011 adults from the Consortium for Neuropsychiatric Phenomics. The first CCA was conducted between four VST variables (set 1) and three CPT-II variables (set 2). The second CCA was conducted using eight Reversal Learning variables (set 1) and three CPT-II variables (set 2). Results Our first CCA suggests that accuracy of performance in VTS predicts CPT-II measures, Rc = 0.33, Wilks’s λ = 0.86, F(12, 2646) = 1.92, p < .001. The analysis revealed a positive relationship with Hits (=0.87) and a negative relationship with FA (= − 0.76), consistent with sustained attention. The second CCA revealed that acquisition trials and RT on reversal trials significantly predicted less FA and more hits on the CPT-II, Rc = 0.23, Wilks’s λ = 0.90, F(24, 1273) = 1.92, p = .005. Conclusion Our multivariate findings confirm that attention is significantly involved in executive and mnemonic processes. To our knowledge, we are the first neuroscientific group to report multivariate evidence from a large data set that confirms sustained attention plays a significant role in reversal learning and task-shifting. Our results show that the CPT-II FA and mean RT variables specifically are important predictors of reversal learning and task-shifting, strengthening the concurrent validity of our experimental measures.

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Structure of the Coolidge Axis II Inventory Personality Disorder Scales from the Five-Factor Model Perspective

Psychological Reports ◽

10.2466/pr0.1998.83.3.947 ◽

1998 ◽

Vol 83 (3) ◽

pp. 947-952 ◽

Cited By ~ 5

Author(s):

Nerella V. Ramanaiah ◽

J. Patrick Sharpe

Keyword(s):

Correlation Analysis ◽

Personality Disorders ◽

Canonical Correlation Analysis ◽

Canonical Correlation ◽

Simple Structure ◽

Factor Model ◽

Five Factor Model ◽

Canonical Variate ◽

Axis Ii ◽

Canonical Variates

Coolidge, et al. in 1994 tested the generality and comprehensiveness of the five-factor model of personality as applied to personality disorders by performing a canonical correlation analysis for the scales from the Coolidge Axis II Inventory and the NEO Personality Inventory testing 178 undergraduates (106 men and 72 women). Their results did not support the generality and comprehensiveness of the five-factor model for interpreting the structure of personality disorders. A major problem with this study was that the data did not show good simple structure and meaningfulness because no rotation was performed for the canonical variates. The present study tested the hypothesis that the results of Coolidge, et al. might be attributed to the failure to rotate canonical variates to obtain good simple structure. For 220 students in introductory psychology (104 men and 116 women), canonical correlation analysis with varimax rotation was performed for scores on the Coolidge Axis II Inventory scales and the NEO Five-Factor Inventory scales. The analysis indicated five canonical variate pairs which were interpreted as Neuroticism, Extraversion, Openness, Disagreeableness, and Conscientiousness, supporting the tested hypothesis as well as the generality and comprehensiveness of this model for describing the structure of personality disorders.

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A Canonical Analysis on the Relationship between Banking Sector and Stock Market Development in Bangladesh

International Journal of Economics and Finance ◽

10.5539/ijef.v10n1p167 ◽

2017 ◽

Vol 10 (1) ◽

pp. 167

Author(s):

Suman Biswas ◽

Altaf Hossain ◽

Arnab Kumar Podder ◽

Md. Nasif Hossain

Keyword(s):

Correlation Analysis ◽

Stock Market ◽

Private Sector ◽

Canonical Correlation Analysis ◽

Canonical Correlation ◽

Banking Sector ◽

Market Development ◽

Canonical Variate ◽

Economic Activities ◽

Stock Market Development

This study examines the structural dependency between the developments of banking sector and stock market of Bangladesh using canonical correlation analysis. The main objective is to check whether the developments of these two financial sectors independently behave in the economic activities of Bangladesh using monthly data from 2006 to 2015. The development of banking sector is measured by a set of four indicators or variables, private sector credit, total number of branches of scheduled banks, interest rate spread and non-performing loan. Similarly another set of indicators, stock market capitalization, number of listed companies, turnover ratio and stock price volatility are used to explain the development of stock market. The multivariate time series of the two set of indicators are ensured first to be the stationary one. Then the canonical correlation analysis between the two set of indicators show that private sector credit, total No. of branches of scheduled banks are the first set of variables contribute more to construct the first canonical variate of banking sector. Market capitalization and number of listed companies are the second set of variables contribute more to construct the first canonical variate of stock market development. Finally, the correlation between the first pair of canonical variates is 0.293. Since the correlation is positive but not significant, banking and stock market developments do not significantly complement each other. Thus it is concluded that the developments of the two financial systems have been independently running during the period in financing economic activities of Bangladesh from 2006 to 2015.

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Canonical Correlation Analysis of Mid- and Near-Infrared Oil Spectra

Applied Spectroscopy ◽

10.1366/0003702934415435 ◽

1993 ◽

Vol 47 (7) ◽

pp. 1024-1029 ◽

Cited By ~ 24

Author(s):

M. F. Devaux ◽

P. Robert ◽

A. Qannari ◽

M. Safar ◽

E. Vigneau

Keyword(s):

Correlation Analysis ◽

Canonical Correlation Analysis ◽

Infrared Spectra ◽

Canonical Correlation ◽

Near Infrared ◽

Principal Component ◽

Canonical Variate ◽

Mid Infrared ◽

Highly Correlated ◽

Spectral Patterns

A mathematical procedure based on Canonical Correlation Analysis (CCA) was used in order to assign the wavelengths of the near-infrared spectra through knowledge of the mid-infrared spectra. The relevance of the treatment was tested on commercial oils that mainly differ in their level of unsaturation. Initially, two separated Principal Component Analyses (PCAs) were performed on the near- and mid-infrared data to overcome the high intercorrelations across the wavelengths. CCA was then applied to the resulting principal components. Near- and mid-infrared canonical variates were assessed so that they achieved maximum correlation. The procedure makes it possible to draw CCA spectral patterns that exhibit significant positive and negative peaks. The first near-infrared canonical variate was highly correlated with the first mid-infrared canonical variate ( r2 = 0.97). The corresponding near- and mid-infrared CCA spectral patterns were therefore given the same interpretation. The mid-infrared pattern opposed negative peaks characteristic of CH2 groups to the positive peaks of CH3 and =CH groups. Consequently, in the near-infrared pattern, the positive peaks at 1708, 2140, 2170, and 2480 nm were assigned to CH3 or =CH groups, and the negative peaks at 2304, 2344, and 2445 nm were assigned to CH2 groups. A more precise interpretation was obtained by comparing the wavelengths observed to theoretical values and to previous assignments.

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Canonical-correlation analysis applied to selection-index methodology in quails

Livestock Science ◽

10.1016/j.livsci.2014.09.021 ◽

2014 ◽

Vol 169 ◽

pp. 35-41 ◽

Cited By ~ 2

Author(s):

André Marubayashi Hidalgo ◽

Luciano Pinheiro da Silva ◽

Rodrigo Reis Mota ◽

Elias Nunes Martins

Keyword(s):

Correlation Analysis ◽

Canonical Correlation Analysis ◽

Canonical Correlation ◽

Selection Index

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Analysis of Maximum Expiratory Flow Volume Curves Using Canonical Correlation Analysis

Methods of Information in Medicine ◽

10.1055/s-0038-1635359 ◽

1985 ◽

Vol 24 (02) ◽

pp. 91-100 ◽

Cited By ~ 3

Author(s):

W. van Pelt ◽

Ph. H. Quanjer ◽

M. E. Wise ◽

E. van der Burg ◽

R. van der Lende

Keyword(s):

Correlation Analysis ◽

Canonical Correlation Analysis ◽

Canonical Correlation ◽

Flow Volume ◽

Non Linear ◽

Maximum Expiratory Flow ◽

Expiratory Flow ◽

Relationship Of ◽

The Relationship ◽

Age And Sex

SummaryAs part of a population study on chronic lung disease in the Netherlands, an investigation is made of the relationship of both age and sex with indices describing the maximum expiratory flow-volume (MEFV) curve. To determine the relationship, non-linear canonical correlation was used as realized in the computer program CANALS, a combination of ordinary canonical correlation analysis (CCA) and non-linear transformations of the variables. This method enhances the generality of the relationship to be found and has the advantage of showing the relative importance of categories or ranges within a variable with respect to that relationship. The above is exemplified by describing the relationship of age and sex with variables concerning respiratory symptoms and smoking habits. The analysis of age and sex with MEFV curve indices shows that non-linear canonical correlation analysis is an efficient tool in analysing size and shape of the MEFV curve and can be used to derive parameters concerning the whole curve.

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