R: Compare two nested models using D2-statistic

D2 {mice} | R Documentation

## Compare two nested models using D2-statistic

### Description

The D2-statistic pools test statistics from the repeated analyses. The method is less powerful than the D1- and D3-statistics.

### Usage

    D2(fit1, fit0 = NULL, use = "wald")

### 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.
`use` | A character string denoting Wald- or likelihood-based based tests. Can be either `"wald"` or `"likelihood"`. Only used if `method = "D2"`.

### References

Li, K. H., X. L. Meng, T. E. Raghunathan, and D. B. Rubin. 1991. Significance Levels from Repeated p-Values with Multiply-Imputed Data. Statistica Sinica 1 (1): 65–92.

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

### 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))
    D2(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))
    D2(fit1, fit0)

[Package mice version 3.14.0 Index]