onefacaov_fac2 | R Documentation |
The function performs a one-way ANOVA and Tukey post-hoc test over grouping variable 2 (Factor2). The function takes each control + treatment combination of grouping variable 2 and perfoms a one-way ANOVA iterating over grouping Variable 1 (Factor1). The p-values are adjusted using Benjamini-Hochberg correction.
onefacaov_fac2(
root_norm,
col_grouping1 = "Factor1",
col_grouping2 = "Factor2",
col_value = "LengthMM",
control = "20",
draw_out = F,
file_base = "1fac_ANOVA_factor2",
axis_label_size = 0.7,
p_value_size = 0.8
)
root_norm |
data.frame; normalized Rootdetection data set |
col_grouping1 |
string; name of the column that should be used as grouping variable 1 (Factor1) |
col_grouping2 |
string; name of the column that should be used as grouping variable 2 (Factor2) |
col_value |
string; name of the column containing values (dependent variable) (LengthMM) |
control |
string; name of the grouping variable 2 (Factor2) control condition |
draw_out |
logical; If TRUE a matrix containing p-values is plotted in a pdf file |
file_base |
string; file base name of the pdf output (is needed if draw_out = TRUE) |
axis_label_size |
numeric; font size of axis labels in pdf file (if draw_out = TRUE) |
p_value_size |
numeric; font size of p-values in pdf file (if draw_out = TRUE) |
list; data.frames containing p-values for one-way ANOVA and Tukey post-hoc
# get data.frame containg p-values for one-way ANOVA and Tukey post-hoc over grouping variable 2
root_norm <- norm_10mm_standard(root_output)
onefacaov_fac2(root_norm, control = "20", draw_out = FALSE)
# plot p-value matrix as pdf output
onefacaov_fac2(root_norm, control = "20", draw_out = TRUE, file_base = "1fac_ANOVA_factor2")
# function creates a pdf file 1fac_ANOVA_factor2_28.pdf
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