getWaldTest {CGEN} | R Documentation

## Compute a Wald test

### Description

Computes a univariate or multivariate Wald test

### Usage

     getWaldTest(fit, parmNames, method=NULL)

### Arguments

`fit` | Return object from `snp.logistic`, `snp.matched`, `glm()` or a list with names "parms" and "cov" (see details). No default.
`parmNames` | Vector of parameters to test. This vector can be a character vector of parameter names or a numeric vector of positions. No default.
`method` | Vector of values from "UML", "CML", "EB" or "CCL", "HCL", "CLR". The default is NULL.

### Details

If `fit` is a list, then "parms" should be the vector of coefficients, and "cov" should be the covariance matrix. If `parmNames` is a character vector, then "parms" should be a named vector and the names must match the rownames and colnames of "cov". A chi-squared test is computed.

### Value

List containing the value of the test statistic (`test`), degrees of freedom (`df`), and p-value (`pvalue`).

### Examples

      set.seed(123)
      n <- 100
      y <- rbinom(n, 1, 0.5)
      x <- runif(n*5)
      dim(x) <- c(n, 5)
      x <- data.frame(x)
      colnames(x) <- c("x", "x2", "x3", "z", "z2")
      fit <- glm(y ~ ., data=x, family=binomial())

      # Chi-squared test
      getWaldTest(fit, c("x", "z"))

      beta <- c(-2.5, 2.5)
      cov  <- diag(1:2)
      getWaldTest(list(parms=beta, cov=cov), 1:2)

[Package CGEN version 3.20.0 Index]