R: Rao's Score Test Statistics Evaluated at the Null Values

score.stat {VGAM} | R Documentation

## Rao's Score Test Statistics Evaluated at the Null Values

### Description

Generic function that computes Rao's score test statistics evaluated at the null values (consequently they do not suffer from the Hauck-Donner effect).

### Usage

    score.stat(object, ...)
    score.stat.vlm(object, values0 = 0, subset = NULL, omit1s = TRUE,
              all.out = FALSE, iterate = TRUE, trace = FALSE, ...)

### Arguments

`object, values0, subset` | Same as in `wald.stat.vlm`.
`omit1s, all.out, iterate` | Same as in `wald.stat.vlm`.
`trace` | Same as in `wald.stat.vlm`.
`...` | Ignored for now.

### Details

The (Rao) score test (also known as the Lagrange multiplier test in econometrics) is a third general method for hypothesis testing under a likelihood-based framework (the others are the likelihood ratio test and Wald test; see `lrt.stat` and `wald.stat`). Asymptotically, the three tests are equivalent. The Wald test is not invariant to parameterization, and the usual Wald test statistics computed at the estimates make it vulnerable to the Hauck-Donner effect (HDE; see `hdeff`). This function is similar to `wald.stat` in that one coefficient is set to 0 (by default) and the other coefficients are iterated by IRLS to get their MLE subject to this constraint.

### Value

By default the signed square root of the Rao score statistics are returned. If `all.out = TRUE` then a list is returned with the following components: `score.stat` the score statistic, `SE0` the standard error of that coefficient, `values0` the null values. Approximately, the default score statistics output are standard normal random variates if each null hypothesis is true.

### Warning

See `wald.stat.vlm`.

### Author(s)

Thomas W. Yee

### See Also

`wald.stat`, `lrt.stat`, `summaryvglm`, `summary.glm`, `anova.vglm`, `vglm`, `hdeff`.

### Examples

    set.seed(1)
    pneumo <- transform(pneumo, let = log(exposure.time),
                                x3 = rnorm(nrow(pneumo)))
    (pfit <- vglm(cbind(normal, mild, severe) ~ let + x3,
                 propodds, data = pneumo))
    score.stat(pfit)  # No HDE here; should be similar to the next line:
    coef(summary(pfit))[, "z value"]  # Wald statistics computed at the MLE
    summary(pfit, score0 = TRUE)

[Package VGAM version 1.1-3 Index]