aov_ss | R Documentation |
Calculates sex specific one way ANOVA from summary statistics.
aov_ss(
x,
Pop = 1,
pairwise = TRUE,
letters = FALSE,
es_anova = "none",
digits = 4,
CI = 0.95
)
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-Kramer'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 "f2" for f squared,"eta2" for eta squared, "omega2" for omega 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.
#For the femur head diameter data
F. Curate, C. Umbelino, A. Perinha, C. Nogueira, A.M. Silva, E. Cunha, Sex determination from the femur in Portuguese populations with classical and machinelearning classifiers, J. Forensic Leg. Med. (2017) , doi:http://dx.doi.org/10.1016/j. jflm.2017.08.011.
O. Gulhan, Skeletal Sexing Standards of Human Remains in Turkey (PhD thesis), Cranfield University, 2017 [Dataset].
P. Timonov, A. Fasova, D. Radoinova, A.Alexandrov, D. Delev, A study of sexual dimorphism in the femur among contemporary Bulgarian population, Euras. J. Anthropol. 5 (2014) 46–53.
E.F. Kranioti, N. Vorniotakis, C. Galiatsou, M.Y. Iscan , M. Michalodimitrakis, Sex identification and software development using digital femoral head radiographs, Forensic Sci. Int. 189 (2009) 113.e1–7.
# Comparisons of femur head diameter in four populations
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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