| LSDTest | R Documentation |
Performs unadjusted pairwise t-tests following a significant ANOVA.
LSDTest(modelo, comparar = NULL, alpha = 0.05)
modelo |
An |
comparar |
Character vector with the name(s) of the factor(s) to compare:
- One name: main effect (e.g., "treatment" or "A")
- Several names: interaction (e.g., |
alpha |
Significance level (default 0.05). |
Advantages: - Very powerful when assumptions are met. - Simple and easy to interpret.
Disadvantages: - High risk of Type I error without correction. - Not recommended if many comparisons are made.
An object of class "lsd" and "comparaciones" containing:
Resultados: a data.frame with columns Comparacion, Diferencia, SE, t_value,
p_value (unadjusted), p_ajustada (LSD), Valor_Critico (critical difference), and Significancia.
Promedios: a named vector of group means as defined by comparar.
Orden_Medias: group names ordered from highest to lowest mean.
Metodo: "LSD t-test".
Termino: the term being compared (e.g., "A", "B", or "A:B").
MSerror, df_error, N: useful for plots with error bars.
Fisher, R. A. (1935). The Design of Experiments. Oliver & Boyd.
data(d_e, package = "Analitica")
mod <- aov(Sueldo_actual ~ as.factor(labor), data = d_e)
resultado <- LSDTest(mod)
summary(resultado)
plot(resultado)
# RCBD
mod <- aov(Sueldo_actual ~ as.factor(labor) + Sexo, data = d_e)
res <- LSDTest(mod, comparar = "as.factor(labor)")
summary(res); plot(res) # plot usara p_value
# Factorial
mod2 <- aov(Sueldo_actual ~ as.factor(labor) * Sexo, data = d_e)
resAB <- LSDTest(mod2, comparar = c("as.factor(labor)","Sexo"))
summary(resAB, n = Inf); plot(resAB, horizontal = TRUE)
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