I would like to convert a list to dataframe (picture as below)
I did use do.call(rbind.data.frame, contrast), however, I got this Error in xi[[j]] : this S4 class is not subsettable. I still can read them separately. Anyone know about this thing?
This list I got when running the ART anova test by using the package ARTool
Update
This my orignial code to calculate and get the model done.
Organism_df_posthoc <- bird_metrics_long_new %>%
rbind(plant_metrics_long_new) %>%
mutate(Type = factor(Type, levels = c("Forest", "Jungle rubber", "Rubber", "Oil palm"))) %>%
mutate(Category = factor(Category)) %>%
group_by(Category) %>%
mutate_at(c("PD"), ~(scale(.) %>% as.vector())) %>%
ungroup() %>%
nest_by(n1) %>%
mutate(fit = list(art.con(art(PD ~ Category Type Category:Type, data = data),
"Category:Type",adjust = "tukey", interaction = T)))
And the output of fit is that I showed already.
CodePudding user response：
With rbind, instead of rbind.data.frame, there is a specific method for 'emmGrid' object and it can directly use the correct method by matching the class if we specify just rbind
do.call(rbind, contrast)
-output
wool tension emmean SE df lower.CL upper.CL
A L 44.6 3.65 48 33.6 55.5
A M 24.0 3.65 48 13.0 35.0
A H 24.6 3.65 48 13.6 35.5
B L 28.2 3.65 48 17.2 39.2
B M 28.8 3.65 48 17.8 39.8
B H 18.8 3.65 48 7.8 29.8
A L 44.6 3.65 48 33.6 55.5
A M 24.0 3.65 48 13.0 35.0
A H 24.6 3.65 48 13.6 35.5
B L 28.2 3.65 48 17.2 39.2
B M 28.8 3.65 48 17.8 39.8
B H 18.8 3.65 48 7.8 29.8
Confidence level used: 0.95
Conf-level adjustment: bonferroni method for 12 estimates
The reason is that there is a specific method for rbind when we load the emmeans
> methods('rbind')
[1] rbind.data.frame rbind.data.table* rbind.emm_list* rbind.emmGrid* rbind.grouped_df* rbind.zoo*
The structure in the example created matches the OP's structure showed
By using rbind.data.frame, it doesn't match because the class is already emmGrid
data
library(multcomp)
library(emmeans)
warp.lm <- lm(breaks ~ wool*tension, data = warpbreaks)
warp.emmGrid <- emmeans(warp.lm, ~ tension | wool)
contrast <- list(warp.emmGrid, warp.emmGrid)
If the OP used 'ARTool' and if the columns are different, the above solution may not work because rbind requires all objects to have the same column names. We could convert to tibble by looping over the list with map (from purrr) and bind them
library(ARTool)
library(purrr)
library(tibble)
map_dfr(contrast, as_tibble)
-output
# A tibble: 42 × 8
contrast estimate SE df t.ratio p.value Moisture_pairwise Fertilizer_pairwise
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <fct> <fct>
1 m1 - m2 -23.1 4.12 8.00 -5.61 0.00226 NA NA
2 m1 - m3 -33.8 4.12 8.00 -8.20 0.000169 NA NA
3 m1 - m4 -15.2 4.12 8.00 -3.68 0.0256 NA NA
4 m2 - m3 -10.7 4.12 8 -2.59 0.118 NA NA
5 m2 - m4 7.92 4.12 8 1.92 0.291 NA NA
6 m3 - m4 18.6 4.12 8 4.51 0.00849 NA NA
7 NA 6.83 10.9 24 0.625 0.538 m1 - m2 f1 - f2
8 NA 15.3 10.9 24 1.40 0.174 m1 - m3 f1 - f2
9 NA -5.83 10.9 24 -0.533 0.599 m1 - m4 f1 - f2
10 NA 8.50 10.9 24 0.777 0.445 m2 - m3 f1 - f2
# … with 32 more rows
data
data(Higgins1990Table5, package = "ARTool")
m <- art(DryMatter ~ Moisture*Fertilizer (1|Tray), data=Higgins1990Table5)
a1 <- art.con(m, ~ Moisture)
a2 <- art.con(m, "Moisture:Fertilizer", interaction = TRUE)
contrast <- list(a1, a2)