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summarylm: Summary table for a linear model

Description

Computes the coefficients, std. errors, t values, and p-values for a linear model in the presence of possible heteroskedasticity.

Usage

summarylm(object,correlation=FALSE,symbolic.cor = FALSE,white.adjust=FALSE,...)

Arguments

object
an object of class lm.
correlation
a logical value indicating whether parameter correlations should be printed.
symbolic.cor
logical. If TRUE, print the correlations in a symbolic form (see symnum) rather than as numbers. Effective only if white.adjust is FALSE.
white.adjust
value passed to hccm indicating the type of robust adjustment to be used. If TRUE, type is assumed to be 'hc3'
...
additional parameters passed to stats::summary.lm

Value

A summary table

Details

If white.adjust is false, the function returns a value identical to stats::summary.lm. Otherwise, robust summaries are computed

Examples

Run this code
ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
group <- gl(2,10,20, labels=c("Ctl","Trt"))
weight <- c((ctl-mean(ctl))*10+mean(ctl), trt)
lm.D9 <- lm(weight ~ group)
summarylm(lm.D9,white.adjust=TRUE)

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