It can help you and help us if you provide a toy example that
illustrates the problem. Consider the following:
df1 <- data.frame(x=1:6, y=rep(1:3, 2))
fit <- lm(y~x, df1)
In previous consideration of problems of this nature, I learned to
consider "summary" and "attributes(summary(fit))": :
> Sum <- summary(fit)
> attributes(Sum)
$names
[1] "call" "terms" "residuals"
"coefficients"
[5] "sigma" "df" "r.squared"
"adj.r.squared"
[9] "fstatistic" "cov.unscaled"
After trying several things, I discovered the following:
> as.matrix(coefficients(Sum))
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.2000000 0.8176622 1.467599 0.2161194
x 0.2285714 0.2099563 1.088662 0.3375019
Does this answer your question?
spencer graves
David Allen wrote:
> After calling function lm one can use the as.matrix function on anova
> to get the numbers
> out of an analysis of variance table and output latex code for a
> nicely formatted table.
>
> I would like to do a similar thing with regression coefficients,
> standard errors, and
> p-values, etc. I have not been able to. Is it possible?
>
> David Allen
>
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