D1: Compare two nested models using D1-statistic

In mice: Multivariate Imputation by Chained Equations

Compare two nested models using D1-statistic

Description

The D1-statistics is the multivariate Wald test.

Usage

D1(fit1, fit0 = NULL, dfcom = 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.
dfcom	A single number denoting the complete-data degrees of freedom of model fit1. If not specified, it is set equal to df.residual of model fit1. If that cannot be done, the procedure assumes (perhaps incorrectly) a large sample.
df.com	Deprecated

Note

Warning: 'D1()' assumes that the order of the variables is the same in different models. See https://github.com/amices/mice/issues/420 for details.

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)
## Not run: 
# 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)

## End(Not run)

mice documentation built on June 7, 2023, 5:38 p.m.