Description Usage Arguments Details Value Author(s) References

Returns an approximate quantile for a weighted sum of independent
*χ^2(1)* random variables.

1 2 3 4 5 | ```
dr.pvalue(coef,f,chi2approx=c("bx","wood"),...)
bentlerxie.pvalue(coef, f)
wood.pvalue(coef, f, tol=0.0, print=FALSE)
``` |

`coef` |
a vector of nonnegative weights |

`f` |
Observed value of the statistic |

`chi2approx` |
Which approximation should be used? |

`tol` |
tolerance for Wood's method. |

`print` |
Printed output for Wood's method |

`...` |
Arguments passed from |

For Bentler-Xie, we approximate *f* by *c χ^2(d)* for values of *c*
and *d* computed by the function. The Wood approximation is more
complicated.

Returns a data.frame with four named components:

`test` |
The input argument |

`test.adj` |
For Bentler-Xie, returns |

`df.adj` |
For Bentler-Xie, returns |

`pval.adj` |
Approximate p.value. |

Sanford Weisberg <sandy@stat.umn.edu>

Peter M. Bentler and Jun Xie (2000), Corrections to test
statistics in principal Hessian directions. *Statistics and
Probability Letters*, 47, 381-389.

Wood, Andrew T. A. (1989)
An *F* approximation to the distribution of a linear combination of
chi-squared variables.
*Communications in Statistics: Simulation and Computation*, 18, 1439-1456.

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