Everything about Partial correlation
Concept in probability theory and statistics
In probability theory and statistics, partial correlation measures the degree of association between two random variables, with the effect of a set of controlling random variables removed. When determining the numerical relationship between two variables of interest, using their correlation coefficient will give misleading results if there is another confounding variable that is numerically related to both variables of interest. This misleading information can be avoided by controlling for the confounding variable, which is done by computing the partial correlation coefficient. This is precisely the motivation for including other right-side variables in a multiple regression; but while multiple regression gives unbiased results for the effect size, it does not give a numerical value of a measure of the strength of the relationship between the two variables of interest. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Partial correlationA 5-minute orientation
- Skim a recent paper: Global-Local Label Correlation for Partial Multi-Label LearningInfluential work since 2022
- Pick up a classic book: Spectral methods in surface superconductivityThe most-reprinted book on the subject
- Read the landmark paper: Variable Screening via Quantile Partial CorrelationCited 70 times
- Go sideways: Bayesian multivariate linear regressionA closely related topic
- Go sideways: Prais–Winsten estimationA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
Variable Screening via Quantile Partial Correlation
On Conditional and Partial Correlation
PARTIAL RANK CORRELATION
Hub Discovery in Partial Correlation Graphs
Dichotomization, Partial Correlation, and Conditional Independence
Partial martingale difference correlation
Clustering stocks using partial correlation coefficients
Completion problem with partial correlation vines
🆕 Influential since 2022
Global-Local Label Correlation for Partial Multi-Label Learning
Meta‐analyzing partial correlation coefficients using Fisher's z transformation
Dual Noise Elimination and Dynamic Label Correlation Guided Partial Multi-Label Learning
A partial correlation-based connectedness approach: Extreme dependence among commodities and portfolio implications
Partial-Dimensional Correlation-Aided Convex-Hull Uncertainty Set for Robust Unit Commitment
📚 Books worth reading
Spectral methods in surface superconductivitySøren Fournais · 2010
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
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