| 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.