TOSTER (version 0.3.4)

TOSTmeta: TOST function for meta-analysis

Description

TOST function for meta-analysis

Usage

TOSTmeta(ES, var, se, low_eqbound_d, high_eqbound_d, alpha, plot = TRUE,
  verbose = TRUE)

Arguments

ES

meta-analytic effect size

var

meta-analytic variance

se

standard error

low_eqbound_d

lower equivalence bounds (e.g., -0.5) expressed in standardized mean difference (Cohen's d)

high_eqbound_d

upper equivalence bounds (e.g., 0.5) expressed in standardized mean difference (Cohen's d)

alpha

alpha level (default = 0.05)

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 Z-value 1, TOST p-value 1, TOST Z-value 2, TOST p-value 2, alpha, low equivalence bound d, high equivalence bound d, Lower limit confidence interval TOST, Upper limit confidence interval TOST

References

Rogers, J. L., Howard, K. I., & Vessey, J. T. (1993). Using significance tests to evaluate equivalence between two experimental groups. Psychological Bulletin, 113(3), 553, formula page 557.

Examples

# NOT RUN {
## Run TOSTmeta by specifying the standard error
TOSTmeta(ES=0.12, se=0.09, low_eqbound_d=-0.2, high_eqbound_d=0.2, alpha=0.05)
## Run TOSTmeta by specifying the variance
TOSTmeta(ES=0.12, var=0.0081, low_eqbound_d=-0.2, high_eqbound_d=0.2, alpha=0.05)
## If both variance and se are specified, TOSTmeta will use standard error and ignore variance
TOSTmeta(ES=0.12, var=9999, se = 0.09, low_eqbound_d=-0.2, high_eqbound_d=0.2, alpha=0.05)
# }