Description Usage Arguments Details Value Examples
Calculates sex specific one way ANOVA from summary statistics.
1 2 3 4 5 6 7 8 9 |
x |
A data frame containing summary statistics. |
Pop |
Number of the column containing populations' names, Default: 1 |
pairwise |
Logical; if TRUE runs multiple pairwise comparisons on different populations using Tukey's post hoc test, Default: TRUE |
letters |
Logical; if TRUE returns letters for pairwise comparisons where significantly different populations are given different letters, Default: FALSE' |
es_anova |
Type of effect size either "f" for f squared,"eta" for eta squared or "none", Default:"none". |
digits |
Number of significant digits, Default: 4 |
CI |
confidence interval coverage takes value from 0 to 1, Default: 0.95. |
Data is entered as a data frame of summary statistics where the column containing population names is chosen by position (first by default), other columns of summary data should have specific names (case sensitive) similar to baboon.parms_df
Sex specific ANOVA tables and pairwise comparisons in tidy format.
1 2 3 4 5 6 7 8 9 10 11 12 | # Comparisons of femur head diameter in four populations
library(TestDimorph)
df <- data.frame(
Pop = c("Turkish", "Bulgarian", "Greek", "Portuguese "),
m = c(150.00, 82.00, 36.00, 34.00),
f = c(150.00, 58.00, 34.00, 24.00),
M.mu = c(49.39, 48.33, 46.99, 45.20),
F.mu = c(42.91, 42.89, 42.44, 40.90),
M.sdev = c(3.01, 2.53, 2.47, 2.00),
F.sdev = c(2.90, 2.84, 2.26, 2.90)
)
aov_ss(x = df)
|
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