"A correlation coefficient is a numerical measure of some type of correlation, meaning a statistical relationship between two variables."
Methods to measure the strength of the association between risk factors and diseases.
Measures of central tendency: A measure that indicates where the center of a distribution is located. These measures include mean, median, and mode.
Measures of dispersion: A measure that indicates the amount of variation or spread in a distribution. These measures include range, standard deviation, and variance.
Correlation: A statistical method that measures the strength and direction of the relationship between two variables.
Regression analysis: A statistical method used to determine the relationship between two or more variables and make predictions based on that relationship.
Odds ratio: A measure of association that compares the odds of an event occurring in one group to the odds of the same event occurring in another group.
Relative risk: A measure of association that compares the risk of an event occurring in one group to the risk of the same event occurring in another group.
Confidence interval: A range of values calculated using statistical methods that is believed to include the true value of a variable.
Chi-square test: A statistical test used to determine whether there is an association between two categorical variables.
T-test: A statistical test used to determine whether there is a significant difference between the means of two groups.
ANOVA: A statistical test used to determine whether there is a significant difference between the means of more than two groups.
Cramer’s V: A measure of association that is used to determine the strength of the association between two nominal variables.
Phi coefficient: A measure of association used to determine the strength of the association between two dichotomous variables.
Spearman’s rank correlation coefficient: A measure of association used to determine the strength of the relationship between two ranked variables.
Kendall’s tau: A measure of association that is used to determine the strength of the relationship between two ranked variables.
Point-biserial correlation coefficient: A measure of association used to determine the strength of the association between a dichotomous variable and a continuous variable.
Receiver operating characteristic (ROC) curve: A graphical representation of the performance of a binary classifier system.
Kappa coefficient: A measure of agreement between observers or raters for categorical items.
Intraclass correlation coefficient (ICC): A measure of reliability used to determine the consistency between ratings made by different raters or observers.
Concordance correlation coefficient (CCC): A measure of agreement between two quantitative measurements.
Effect size: A measure of the magnitude of an observed effect or relationship.
Relative Risk (RR): It measures the strength of the association between an exposure and a disease by dividing the incidence rate (number of cases in exposed/number of people exposed) by the incidence rate in unexposed individuals (number of cases in unexposed/number of people unexposed).
Odds Ratio (OR): It uses the odds of having an exposure among cases compared to the odds of having the exposure among non-cases. Simply, it represents the odds of being exposed to an activity or factor for disease development. ORs can be used instead of RRs when the prevalence of disease is high.
Hazard Ratio (HR): It is used for measuring associations between time-to-event data and exposures. It represents the chance of experiencing an event (such as death or morbidity) in the exposed group divided by the chance of experiencing the event in the unexposed group.
Prevalence Ratio (PR): It is used for cross-sectional studies in which the prevalence of a disease is compared between exposed and unexposed groups.
Risk Difference (RD): It provides the absolute difference in risk for disease occurrence between the exposed and unexposed groups.
Time Risk: It calculates the cumulative incidence of a given disease up to a specified period of time.
Attributable Risk (AR): It indicates the proportion of cases in the exposed group that would not have occurred if they had not been exposed.
Population Attributable Risk (PAR): It estimates the proportion of cases in the population whose exposure to a given risk factor has contributed to their illness.
Correlation Coefficient: It reflects the strength of the linear association between two variables.
Cohen's Kappa: It measures the level of agreement between two raters in the diagnosis of a condition.
"A correlation coefficient is a numerical measure of some type of correlation, meaning a statistical relationship between two variables."
"They all assume values in the range from −1 to +1, where ±1 indicates the strongest possible agreement and 0 the strongest possible disagreement."
"Several types of correlation coefficient exist, each with their own definition and own range of usability and characteristics."
"They all assume values in the range from −1 to +1, where ±1 indicates the strongest possible agreement and 0 the strongest possible disagreement."
"As tools of analysis, correlation coefficients present certain problems, including the propensity of some types to be distorted by outliers."
"The possibility of incorrectly being used to infer a causal relationship between the variables."
"As tools of analysis, correlation coefficients present certain problems, including the propensity of some types to be distorted by outliers."
"The variables may be two columns of a given data set of observations, often called a sample, or two components of a multivariate random variable with a known distribution."
"±1 indicates the strongest possible agreement and 0 the strongest possible disagreement."
"±1 indicates the strongest possible agreement"
"±1 indicates the strongest possible agreement"
"They all assume values in the range from −1 to +1, where ±1 indicates the strongest possible agreement"
"They all assume values in the range from −1 to +1, where ... 0 the strongest possible disagreement."
"As tools of analysis, correlation coefficients present certain problems, including the propensity of some types to be distorted by outliers."
"As tools of analysis, correlation coefficients present certain problems, including the propensity of some types to be distorted by outliers."
"...the possibility of incorrectly being used to infer a causal relationship between the variables (for more, see Correlation does not imply causation)."
"...the possibility of incorrectly being used to infer a causal relationship between the variables (for more, see Correlation does not imply causation)."
"±1 indicates the strongest possible agreement"
"0 the strongest possible disagreement"