ciTest-array: Test for conditional independence in a contingency table In hojsgaard/gRim: Graphical Interaction Models

Description

Test for conditional independence in a contingency table represented as an array.

Usage

 ```1 2``` ```ciTest_table(x, set = NULL, statistic = "dev", method = "chisq", adjust.df = TRUE, slice.info = TRUE, L = 20, B = 200, ...) ```

Arguments

 `x` An array of counts with named dimnames. `set` A specification of the test to be made. The tests are of the form u and v are independent condionally on S where u and v are variables and S is a set of variables. See 'details' for details about specification of `set`. `statistic` Possible choices of the test statistic are `"dev"` for deviance and `"X2"` for Pearsons X2 statistic. `method` Method of evaluating the test statistic. Possible choices are `"chisq"`, `"mc"` (for Monte Carlo) and `"smc"` for sequential Monte Carlo. `adjust.df` Logical. Should degrees of freedom be adjusted for sparsity? `slice.info` Logical. Should slice info be stored in the output? `L` Number of extreme cases as stop criterion if method is `"smc"` (sequential Monte Carlo test); ignored otherwise. `B` Number (maximum) of simulations to make if method is `"mc"` or `"smc"` (Monte Carlo test or sequential Monte Carlo test); ignored otherwise. `...` Additional arguments.

Details

`set` can be 1) a vector or 2) a right-hand sided formula in which variables are separated by '+'. In either case, it is tested if the first two variables in the `set` are conditionally independent given the remaining variables in `set`. (Notice an abuse of the '+' operator in the right-hand sided formula: The order of the variables does matter.)

If `set` is `NULL` then it is tested whether the first two variables are conditionally independent given the remaining variables.

Value

An object of class 'citest' (which is a list).

Author(s)

Søren Højsgaard, [email protected]

`ciTest`, `ciTest.data.frame`, `ciTest_df`, `ciTest.list`, `ciTest_mvn`, `chisq.test`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30``` ```data(lizard) ## lizard is has named dimnames names( dimnames( lizard )) ## checked with is.named.array( lizard ) ## Testing for conditional independence: # the following are all equivalent: ciTest(lizard, set=~diam + height + species) # ciTest(lizard, set=c("diam", "height", "species")) # ciTest(lizard, set=1:3) # ciTest(lizard) # (The latter because the names in lizard are as given above.) ## Testing for marginal independence ciTest(lizard, set=~diam + height) ciTest(lizard, set=1:2) ## Getting slice information: ciTest(lizard, set=c("diam", "height", "species"), slice.info=TRUE)\$slice ## Do Monte Carlo test instead of usual likelihood ratio test. Different # options: # 1) Do B*10 simulations divided equally over each slice: ciTest(lizard, set=c("diam", "height", "species"), method="mc", B=400) # 2) Do at most B*10 simulations divided equally over each slice, but stop # when at most L extreme values are found ciTest(lizard, set=c("diam", "height", "species"), method="smc", B=400) ```