regTest {causalDisco} R Documentation

## Regression-based information loss test

### Description

We test whether x and y are associated, given S using a generalized linear model.

### Usage

regTest(x, y, S, suffStat)


### Arguments

 x Index of x variable y Index of y variable S Index of S variable(s), possibly NULL suffStat Sufficient statistic; list with data, binary variables and order.

### Details

All included variables should be either numeric or binary. If y is binary, a logistic regression model is fitted. If y is numeric, a linear regression model is fitted. x and S are included as explanatory variables. Any numeric variables among x and S are modeled with spline expansions (natural splines, 3 df). This model is tested against a numeric where x (including a possible spline expansion) has been left out using a likelihood ratio test. The model is fitted in both directions (interchanging the roles of x and y). The final p-value is the maximum of the two obtained p-values.

### Value

A numeric, which is the p-value of the test.

[Package causalDisco version 0.9.1 Index]