retrieving p-values in lm

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
SchÃ¶nbeinstr. 6
CH-4056 Basel
+41 61 267 2976

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