Extract p-value from aov

Question

I am looking to extract the p-value generated from an anova in R.

Here is what I am running:

test <- aov(asq[,9] ~ asq[,187]) summary(test) 

Yields:

              Df Sum Sq Mean Sq F value    Pr(>F)     asq[, 187]     1   3.02 3.01951  12.333 0.0004599 *** Residuals   1335 326.85 0.24483                       --- Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1  12 observations deleted due to missingness 

When I look a the structure, this is what I see. I usually can work through lists to get what I need, but I am having a hard time with this one. A Google searched also seemed to reveal much simpler structures than I am getting.

NOTE: ASQ is my data frame.

str(test)  List of 13  $ coefficients : Named num [1:2] 0.2862 0.0973   ..- attr(*, "names")= chr [1:2] "(Intercept)" "asq[, 187]"  $ residuals    : Named num [1:1337] 0.519 0.519 -0.481 -0.481 -0.481 ...   ..- attr(*, "names")= chr [1:1337] "1" "2" "3" "4" ...  $ effects      : Named num [1:1337] -16.19 -1.738 -0.505 -0.505 -0.505 ...   ..- attr(*, "names")= chr [1:1337] "(Intercept)" "asq[, 187]" "" "" ...  $ rank         : int 2  $ fitted.values: Named num [1:1337] 0.481 0.481 0.481 0.481 0.481 ...   ..- attr(*, "names")= chr [1:1337] "1" "2" "3" "4" ...  $ assign       : int [1:2] 0 1  $ qr           :List of 5   ..$ qr   : num [1:1337, 1:2] -36.565 0.0273 0.0273 0.0273 0.0273 ...   .. ..- attr(*, "dimnames")=List of 2   .. .. ..$ : chr [1:1337] "1" "2" "3" "4" ...   .. .. ..$ : chr [1:2] "(Intercept)" "asq[, 187]"   .. ..- attr(*, "assign")= int [1:2] 0 1   ..$ qraux: num [1:2] 1.03 1.02   ..$ pivot: int [1:2] 1 2   ..$ tol  : num 1e-07   ..$ rank : int 2   ..- attr(*, "class")= chr "qr"  $ df.residual  : int 1335  $ na.action    :Class 'omit'  Named int [1:12] 26 257 352 458 508 624 820 874 1046 1082 ...   .. ..- attr(*, "names")= chr [1:12] "26" "257" "352" "458" ...  $ xlevels      : list()  $ call         : language aov(formula = asq[, 9] ~ asq[, 187])  $ terms        :Classes 'terms', 'formula' length 3 asq[, 9] ~ asq[, 187]   .. ..- attr(*, "variables")= language list(asq[, 9], asq[, 187])   .. ..- attr(*, "factors")= int [1:2, 1] 0 1   .. .. ..- attr(*, "dimnames")=List of 2   .. .. .. ..$ : chr [1:2] "asq[, 9]" "asq[, 187]"   .. .. .. ..$ : chr "asq[, 187]"   .. ..- attr(*, "term.labels")= chr "asq[, 187]"   .. ..- attr(*, "order")= int 1   .. ..- attr(*, "intercept")= int 1   .. ..- attr(*, "response")= int 1   .. ..- attr(*, ".Environment")=<environment: R_GlobalEnv>    .. ..- attr(*, "predvars")= language list(asq[, 9], asq[, 187])   .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"   .. .. ..- attr(*, "names")= chr [1:2] "asq[, 9]" "asq[, 187]"  $ model        :'data.frame':  1337 obs. of  2 variables:   ..$ asq[, 9]  : int [1:1337] 1 1 0 0 0 1 1 1 0 0 ...   ..$ asq[, 187]: int [1:1337] 2 2 2 2 2 2 2 2 2 2 ...   ..- attr(*, "terms")=Classes 'terms', 'formula' length 3 asq[, 9] ~ asq[, 187]   .. .. ..- attr(*, "variables")= language list(asq[, 9], asq[, 187])   .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1   .. .. .. ..- attr(*, "dimnames")=List of 2   .. .. .. .. ..$ : chr [1:2] "asq[, 9]" "asq[, 187]"   .. .. .. .. ..$ : chr "asq[, 187]"   .. .. ..- attr(*, "term.labels")= chr "asq[, 187]"   .. .. ..- attr(*, "order")= int 1   .. .. ..- attr(*, "intercept")= int 1   .. .. ..- attr(*, "response")= int 1   .. .. ..- attr(*, ".Environment")=<environment: R_GlobalEnv>    .. .. ..- attr(*, "predvars")= language list(asq[, 9], asq[, 187])   .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"   .. .. .. ..- attr(*, "names")= chr [1:2] "asq[, 9]" "asq[, 187]"   ..- attr(*, "na.action")=Class 'omit'  Named int [1:12] 26 257 352 458 508 624 820 874 1046 1082 ...   .. .. ..- attr(*, "names")= chr [1:12] "26" "257" "352" "458" ...  - attr(*, "class")= chr [1:2] "aov" "lm" 

Answer 1

Here:

summary(test)[[1]][["Pr(>F)"]][1] 

Answer 2

since the suggest above didn't work for me this is how i managed to solve it:

sum_test = unlist(summary(test)) 

then looking at the names with

names(sum_test) 

i have"Pr(>F)1" and "Pr(>F)2", when the first it the requested value, so

sum_test["Pr(>F)1"] 

will give the requested value