psycho (version 0.4.91)

analyze.aov: Analyze aov and anova objects

Description

Analyze aov and anova objects.

Usage

# S3 method for aov
analyze(x, effsize_rules = "field2013", ...)

Arguments

x

aov object.

effsize_rules

Grid for effect size interpretation. See interpret_omega_sq.

...

Arguments passed to or from other methods.

Value

output

References

• Levine, T. R., & Hullett, C. R. (2002). Eta squared, partial eta squared, and misreporting of effect size in communication research. Human Communication Research, 28(4), 612-625.

• Pierce, C. A., Block, R. A., & Aguinis, H. (2004). Cautionary note on reporting eta-squared values from multifactor ANOVA designs. Educational and psychological measurement, 64(6), 916-924.

See Also

http://imaging.mrc-cbu.cam.ac.uk/statswiki/FAQ/os2

Examples

# NOT RUN {
library(psycho)

df <- psycho::affective

x <- aov(df$Tolerating ~ df$Salary)
x <- aov(df$Tolerating ~ df$Salary * df$Sex)

x <- anova(lm(df$Tolerating ~ df$Salary * df$Sex))


summary(analyze(x))
print(analyze(x))

df <- psycho::emotion %>%
  mutate(Recall = ifelse(Recall == TRUE, 1, 0)) %>%
  group_by(Participant_ID, Emotion_Condition) %>%
  summarise(Recall = sum(Recall) / n())

x <- aov(Recall ~ Emotion_Condition + Error(Participant_ID), data = df)
x <- anova(lmerTest::lmer(Recall ~ Emotion_Condition + (1 | Participant_ID), data = df))
analyze(x)
summary(x)
# }
# NOT RUN {
# }