On Fri, 2005-12-09 at 14:19 +0100, Patrick Kuss wrote:
> Dear list,
>
> I want to retrieve the p-value of a two-polynomial regression. For a
> one-polynomial lm I can easily do this with:
> summary(lm(b~a, data=c)[[4]][[8]].
>
> But how do I find the final p-value in the two-polynomial regression? Under
> $coefficients I don't find it
>
> Any suggestions?
Judging from your code, you mean p-value of the F-statistic for the
whole model - this isn't stored anywhere, see:
getAnywhere(print.summary.lm)
In particular this section:
cat("\nResidual standard error:", format(signif(x$sigma,
digits)), "on", rdf, "degrees of freedom\n")
if (!is.null(x$fstatistic)) {
cat("Multiple R-Squared:", formatC(x$r.squared, digits = digits))
cat(",\tAdjusted R-squared:", formatC(x$adj.r.squared,
digits = digits), "\nF-statistic:", formatC(x$fstatistic[1],
digits = digits), "on", x$fstatistic[2], "and", x$fstatistic[3],
"DF, p-value:", format.pval(pf(x$fstatistic[1],
x$fstatistic[2], x$fstatistic[3], lower.tail = FALSE),
digits = digits), "\n")
}
The relevant bit being:
format.pval(pf(x$fstatistic[1],
x$fstatistic[2], x$fstatistic[3], lower.tail = FALSE)
The reason this works for the first model is that with one covariate the
value in $coefficients is the overall model p-value, in that case. With
two covariates, the things in $coefficients relate to these, not to the
overall model - your assumption was wrong in the first usage, you just
lucked out that it gave the same result.
So,
p1 <- pf(lm.res$fstatistic[1],
lm.res$fstatistic[2], lm.res$fstatistic[3],
lower.tail = FALSE)
p2 <- pf(lm.res.2$fstatistic[1],
lm.res.2$fstatistic[2], lm.res.2$fstatistic[3],
lower.tail = FALSE)
Gives you the p-values:
> p1
value
0.01368545
> p2
value
0.0461472
HTH
G
>
> Patrick
>
> alt <-(2260,2183,2189,1930,2435,
> 2000,2100,2050,2020,2470,
> 1700,2310,2090,1560,2060,
> 1790,1940,2100,2250,2010)
>
> H <- c(0.2034,0.1845,0.2053,0.1788,0.2196,
> 0.2037,0.1655,0.2176,0.1844,0.2033,
> 0.1393,0.2019,0.1975,0.1490,0.1917,
> 0.2180,0.2064,0.1943,0.2139,0.1320)
>
> X <- data.frame(alt,H)
>
> lm.res <- summary(lm(H~alt,data=X))
> lm.res
> p1 <- lm.res[[4]][[8]]
> p1
>
> lm.res.2 <- summary(lm(H~alt+I(alt^2),data=X))
> lm.res.2
> str(lm.res.2) # where is p
>
> p2 <- lm.res.2[[???]][[????]]
>
> --
> Patrick Kuss
> PhD-student
> Institute of Botany
> University of Basel
> Schönbeinstr. 6
> CH-4056 Basel
> +41 61 267 2976
>
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Gavin Simpson [T] +44 (0)20 7679 5522
ENSIS Research Fellow [F] +44 (0)20 7679 7565
ENSIS Ltd. & ECRC [E] gavin.simpsonATNOSPAMucl.ac.uk
UCL Department of Geography [W] http://www.ucl.ac.uk/~ucfagls/cv/
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