eta.full.SS: Eta for ANOVA from F and Sum of Squares
In MOTE: Effect Size and Confidence Interval Calculator

Description Usage Arguments Details Value Examples

This function displays eta squared from ANOVA analyses and its non-central confidence interval based on the F distribution. This formula works for one way and multi way designs with careful focus on the sum of squares total.

1	eta.full.SS(dfm, dfe, ssm, sst, Fvalue, a = 0.05)

`dfm`	degrees of freedom for the model/IV/between
`dfe`	degrees of freedom for the error/residual/within
`ssm`	sum of squares for the model/IV/between
`sst`	sum of squares total
`Fvalue`	F statistic
`a`	significance level

Eta squared is calculated by dividing the sum of squares for the model by the sum of squares total.

eta^2 = ssm / sst

Learn more on our example page.

Provides eta with associated confidence intervals and relevant statistics.

`eta`	effect size
`etalow`	lower level confidence interval of eta
`etahigh`	upper level confidence interval of eta
`dfm`	degrees of freedom for the model/IV/between
`dfe`	degrees of freedom for the error/resisual/within
`F`	F-statistic
`p`	p-value
`estimate`	the eta squared statistic and confidence interval in APA style for markdown printing
`statistic`	the F-statistic in APA style for markdown printing

#The following example is derived from the "bn1_data" dataset, included
#in the MOTE library.

#A health psychologist recorded the number of close inter-personal
#attachments of 45-year-olds who were in excellent, fair, or poor
#health. People in the Excellent Health group had 4, 3, 2, and 3
#close attachments; people in the Fair Health group had 3, 5,
#and 8 close attachments; and people in the Poor Health group
#had 3, 1, 0, and 2 close attachments.

anova_model = lm(formula = friends ~ group, data = bn1_data)
summary.aov(anova_model)

eta.full.SS(dfm = 2, dfe = 8, ssm = 25.24,
            sst = (25.24+19.67), Fvalue = 5.134, a = .05)