summarylm: Summary table for a linear model

In Deducer: A Data Analysis GUI for R

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

Details

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

Value

A summary table

Examples

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)

Deducer documentation built on May 2, 2019, 8:35 a.m.