TOSTER (version 0.3.4)

TOSTtwo.raw: TOST function for an independent t-test (raw scores)

Description

TOST function for an independent t-test (raw scores)

Usage

TOSTtwo.raw(m1, m2, sd1, sd2, n1, n2, low_eqbound, high_eqbound, alpha,
  var.equal, plot = TRUE, verbose = TRUE)

Arguments

m1

mean of group 1

m2

mean of group 2

sd1

standard deviation of group 1

sd2

standard deviation of group 2

n1

sample size in group 1

n2

sample size in group 2

low_eqbound

lower equivalence bounds (e.g., -0.5) expressed in raw scale units (e.g., scalepoints)

high_eqbound

upper equivalence bounds (e.g., 0.5) expressed in raw scale units (e.g., scalepoints)

alpha

alpha level (default = 0.05)

var.equal

logical variable indicating whether equal variances assumption is assumed to be TRUE or FALSE. Defaults to FALSE.

plot

set whether results should be plotted (plot = TRUE) or not (plot = FALSE) - defaults to TRUE

verbose

logical variable indicating whether text output should be generated (verbose = TRUE) or not (verbose = FALSE) - default to TRUE

Value

Returns TOST t-value 1, TOST p-value 1, TOST t-value 2, TOST p-value 2, degrees of freedom, low equivalence bound, high equivalence bound, Lower limit confidence interval TOST, Upper limit confidence interval TOST

References

Berger, R. L., & Hsu, J. C. (1996). Bioequivalence Trials, Intersection-Union Tests and Equivalence Confidence Sets. Statistical Science, 11(4), 283-302.

Gruman, J. A., Cribbie, R. A., & Arpin-Cribbie, C. A. (2007). The effects of heteroscedasticity on tests of equivalence. Journal of Modern Applied Statistical Methods, 6(1), 133-140, formula for Welch's t-test on page 135

Examples

# NOT RUN {
## Eskine (2013) showed that participants who had been exposed to organic
## food were substantially harsher in their moral judgments relative to
## those exposed to control (d = 0.81, 95% CI: [0.19, 1.45]). A
## replication by Moery & Calin-Jageman (2016, Study 2) did not observe
## a significant effect (Control: n = 95, M = 5.25, SD = 0.95, Organic
## Food: n = 89, M = 5.22, SD = 0.83). Following Simonsohn's (2015)
## recommendation the equivalence bound was set to the effect size the
## original study had 33% power to detect (with n = 21 in each condition,
## this means the equivalence bound is d = 0.48, which equals a
## difference of 0.384 on a 7-point scale given the sample sizes and a
## pooled standard deviation of 0.894). Using a TOST equivalence test
## with alpha = 0.05, assuming equal variances, and equivalence
## bounds of d = -0.43 and d = 0.43 is significant, t(182) = -2.69,
## p = 0.004. We can reject effects larger than d = 0.43.

TOSTtwo.raw(m1=5.25,m2=5.22,sd1=0.95,sd2=0.83,n1=95,n2=89,low_eqbound=-0.384,high_eqbound=0.384)
# }