We propose a default Bayesian hypothesis test for the presence of a correlation or a partial correlation. The test is a direct application of Bayesian techniques for variable selection in regression models. The test is easy to apply and yields practical advantages that the standard frequentist tests lack; in particular, the Bayesian test can quantify evidence in favor of the null hypothesis and allows researchers to monitor the test results as the data come in. We illustrate the use of the Bayesian correlation test with three examples from the psychological literature. Computer code and example data are provided in the journal archives
In hypothesis testing, the conclusions from Bayesian and Frequentist approaches can differ markedly,...
In the field of cognitive psychology, the p-value hypothesis test has established a stranglehold on ...
In the field of cognitive psychology, the p-value hypothesis test has established a stranglehold on ...
In this paper, we develop Bayes factor based testing procedures for the presence of a correlation or...
Harold Jeffreys pioneered the development of default Bayes factor hypothesis tests for standard stat...
In order to quantify the relationship between multiple variables, researchers often carry out a medi...
In modern statistical and machine learning applications, there is an increasing need for developing ...
In this article, we present a Bayes factor solution for inference in multiple regression. Bayes fact...
Background Despite its popularity as an inferential framework, classical null hypoth...
Hypothesis testing is a model selection problem for which the solution proposed by the two main stat...
Tests for dependence of continuous, discrete and mixed continuous-discrete variables are ubiquitous ...
Tests for dependence of continuous, discrete and mixed continuous-discrete variables are ubiquitous...
To estimate causal relationships, time series econometricians must be aware of spurious correlation,...
This chapter explains why the logic behind p‐value significance tests is faulty, leading researchers...
Bayesian hypothesis testing presents an attractive alternative to p value hypothesis testing. Part I...
In hypothesis testing, the conclusions from Bayesian and Frequentist approaches can differ markedly,...
In the field of cognitive psychology, the p-value hypothesis test has established a stranglehold on ...
In the field of cognitive psychology, the p-value hypothesis test has established a stranglehold on ...
In this paper, we develop Bayes factor based testing procedures for the presence of a correlation or...
Harold Jeffreys pioneered the development of default Bayes factor hypothesis tests for standard stat...
In order to quantify the relationship between multiple variables, researchers often carry out a medi...
In modern statistical and machine learning applications, there is an increasing need for developing ...
In this article, we present a Bayes factor solution for inference in multiple regression. Bayes fact...
Background Despite its popularity as an inferential framework, classical null hypoth...
Hypothesis testing is a model selection problem for which the solution proposed by the two main stat...
Tests for dependence of continuous, discrete and mixed continuous-discrete variables are ubiquitous ...
Tests for dependence of continuous, discrete and mixed continuous-discrete variables are ubiquitous...
To estimate causal relationships, time series econometricians must be aware of spurious correlation,...
This chapter explains why the logic behind p‐value significance tests is faulty, leading researchers...
Bayesian hypothesis testing presents an attractive alternative to p value hypothesis testing. Part I...
In hypothesis testing, the conclusions from Bayesian and Frequentist approaches can differ markedly,...
In the field of cognitive psychology, the p-value hypothesis test has established a stranglehold on ...
In the field of cognitive psychology, the p-value hypothesis test has established a stranglehold on ...