R: Compare two nested models using D1-statistic

D1 {mice} | R Documentation

## Compare two nested models using D1-statistic

### Description

The D1-statistics is the multivariate Wald test.

### Usage

    D1(fit1, fit0 = NULL, df.com = NULL, ...)

### Arguments

`fit1` | An object of class `mira`, produced by `with()`.
`fit0` | An object of class `mira`, produced by `with()`. The model in `fit0` is a nested within `fit1`. The default null model `fit0 = NULL` compares `fit1` to the intercept-only model.
`df.com` | A single number or a numeric vector denoting the complete-data degrees of freedom for the hypothesis test. If not specified, it is set equal to `df.residual` of model `fit1`.
`...` | Not used.

### References

Li, K. H., T. E. Raghunathan, and D. B. Rubin. 1991. Large-Sample Significance Levels from Multiply Imputed Data Using Moment-Based Statistics and an F Reference Distribution. Journal of the American Statistical Association, 86(416): 1065–73.

https://stefvanbuuren.name/fimd/sec-multiparameter.html#sec:wald

### See Also

`testModels`

### Examples

    # Compare two linear models:
    imp <- mice(nhanes2, seed = 51009, print = FALSE)
    mi1 <- with(data = imp, expr = lm(bmi ~ age + hyp + chl))
    mi0 <- with(data = imp, expr = lm(bmi ~ age + hyp))
    D1(mi1, mi0)

    # Compare two logistic regression models
    imp  <- mice(boys, maxit = 2, print = FALSE)
    fit1 <- with(imp, glm(gen > levels(gen)[1] ~ hgt + hc + reg, family = binomial))
    fit0 <- with(imp, glm(gen > levels(gen)[1] ~ hgt + hc, family = binomial))
    D1(fit1, fit0)

[Package mice version 3.8.0 Index]