`R/pval_funs.R`

`correctPVal.Rd`

Based on the similar function from the Outference package,
which accomplishes a similar task. Code modified from code found at
https://github.com/shuxiaoc/outference.
This function shouldn't be
needed by most users (it is called internally by `branchInference()`

), but is needed to reproduce our paper simulations.

correctPVal(phiInterval, nu, y, sigma)

phiInterval | the conditioning set (truncation interval). An object of class |
---|---|

nu | the vector that defines the parameter of interest. We are testing the hypothesis that nu^T mu = 0. |

y | the response data y. |

sigma | the (assumed known) noise standard deviation. The assumption is that y_i ~ N(mu_i, sigma^2). |

a p-value.

data(blsdata, package="treevalues") bls.tree <-rpart::rpart(kcal24h0~hunger+disinhibition+resteating+rrvfood+liking+wanting, model = TRUE, data = blsdata, cp=0.02) branch <- getBranch(bls.tree, 2) left_child <- getRegion(bls.tree,2) right_child <- getRegion(bls.tree,3) nu_sib <- left_child/sum(left_child) - right_child/sum(right_child) S_sib <- getInterval(bls.tree, nu_sib,branch) correctPVal(S_sib, nu_sib, blsdata$kcal24h0, sd(blsdata$kcal24h0))#> [1] 0.4425364#> [1] 0.4425364