Significance of Correlation matrix
A correlation matrix is a table displaying correlation coefficients between variables, revealing the strength and direction of relationships. Used across psychiatry, health sciences, religion, and environmental science, it helps analyze interrelationships between quality attributes, religious orientations, and environmental factors. It identifies patterns, assesses discriminant validity, and aids in data reduction. In essence, it's a statistical tool quantifying variable relationships, facilitating pattern identification and dependency analysis across diverse fields.
Synonyms: Correlation table, Relationship matrix
The below excerpts are indicatory and do represent direct quotations or translations. It is your responsibility to fact check each reference.
The concept of Correlation matrix in scientific sources
A correlation matrix is a table displaying correlation coefficients between variables, revealing relationships. It helps detect multicollinearity, reduce model complexity, and understand variable interactions in various fields like environmental science and risk assessment.
From: Sustainability Journal (MDPI)
(1) A table displaying the correlation coefficients between different variables, providing insights into the relationships and dependencies among them.[1] (2) The "correlation matrix" for Equation (2) indicates that no correlation greater than 0.7 or less than − 0.7 was found between the variables, suggesting that multicollinearity is not a significant issue in the model.[2] (3) It displays the correlation coefficients between variables, helping to assess the relationships between CSR score, TMT stability, aspiration gap, and other factors.[3] (4) The correlation matrix between variables is shown, revealing the relationships between different variables and indicating the likelihood of multicollinearity in the dataset.[4] (5) Figure 6 depicts it, including 544 features. The features are the original ones represented in the dataset (such as weather data and current and historic groundwater levels).[5]
From: International Journal of Environmental Research and Public Health (MDPI)
(1) A correlation matrix is a table showing correlation coefficients between sets of variables, and it is used to analyze the relationships between socio-demographic factors, flood risk perception, flood risk knowledge, and protective coping behaviors.[6] (2) Spearman’s correlation matrix among outcomes was calculated to understand relationships.[7] (3) The examination of the correlation matrix showed that several items were correlated with correlation coefficients ranging from r = 0.32 to r = 85.[8] (4) It is a visualization tool used to identify relationships between variables, such as time spent on the internet, psychosomatic symptoms, and mental wellbeing scores, among a group of students.[9] (5) It is a matrix for the bedtime voiding frequency, PSQI, ICIQ-NqoL, and AMS variables amongst respondents with nocturia[10]
From: The Malaysian Journal of Medical Sciences
(1) A correlation matrix was used to determine the relationship between suicidal ideation, reasons for living, and coping skills, showing the strength and direction of the associations between these variables.[11]
From: Onderstepoort Journal of Veterinary Research
(1) This is a tool which shows the linear relationships between different variables, such as milk yield, SCC, CMCT, and withdrawal periods, and is used in the study.[12]
From: Religions Journal (MDPI)
(1) The correlation matrix, controlling for sex differences, reveals a negative correlation between emotional exhaustion and satisfaction, suggesting an inverse relationship.[13] (2) The correlation matrix in Table 1 was checked to address multicollinearity, which refers to the correlation among independent variables in a multiple regression model.[14] (3) The text refers to a correlation matrix, which was visually inspected to assess multicollinearity among the variables being studied.[15] (4) The text refers to the correlation matrix, which shows the correlations between positive religious coping and negative religious coping, providing information about the relationship between these two constructs and their potential overlap or independence.[16] (5) It is a table showing correlation coefficients between sets of variables, used to assess the relationships among the independent and control variables.[17]
From: South African Journal of Psychiatry
(1) It is the table that shows the weak positive correlation between social support and resilience.[18] (2) This was used to represent the findings of multiple correspondence analysis, with values below 0.30 indicating a weak correlation.[19]