MVLM (version 0.0.1)

summary.mvlm: Summarizing mvlm Results

Description

summary method for class mvlm

Usage

"summary"(object, ...)

Arguments

object

Output from mvlm

...

Further arguments passed to or from other methods.

Value

Calling summary(mvlm.res) produces a data frame comprised of: produces a data frame comprised of:In addition to the information in the three columns comprising summary(mvlm.res), the mvlm.res object also contains:Note that the printed output of summary(res) will truncate p-values to the smallest trustworthy values, but the object returned by summary(mvlm.res) will contain the p-values as computed. If the error bound of the Davies algorithm is larger than the p-value, the only conclusion that can be drawn with certainty is that the p-value is smaller than (or equal to) the error bound.

References

Davies, R. B. (1980). The Distribution of a Linear Combination of chi-square Random Variables. Journal of the Royal Statistical Society. Series C (Applied Statistics), 29(3), 323-333.

Duchesne, P., & De Micheaux, P.L. (2010). Computing the distribution of quadratic forms: Further comparisons between the Liu-Tang-Zhang approximation and exact methods. Computational Statistics and Data Analysis, 54(4), 858-862.

McArtor, D. B., Lubke, G. H., & Bergeman, C. S. (under review). The null distribution of the multivariate linear model test statistic. Manuscript submitted for publication.

Examples

data(mvlmdata)

Y <- as.matrix(Y.mvlm)

# Main effects model
mvlm.res <- mvlm(Y ~ Cont + Cat + Ord, data = X.mvlm)
summary(mvlm.res)

# Include two-way interactions
mvlm.res.int <- mvlm(Y ~ .^2, data = X.mvlm)
summary(mvlm.res.int)