`TOSTone.Rd`

Development on this function is complete, and for new code we recommend switching to tsum_TOST, which is easier to use, more featureful, and still under active development.

```
TOSTone(
m,
mu,
sd,
n,
low_eqbound_d,
high_eqbound_d,
alpha,
plot = TRUE,
verbose = TRUE
)
TOSTone.raw(
m,
mu,
sd,
n,
low_eqbound,
high_eqbound,
alpha,
plot = TRUE,
verbose = TRUE
)
```

- m
mean

- mu
value to compare against

- sd
standard deviation

- n
sample size

- 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

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

- high_eqbound
upper equivalence bounds (e.g., 0.5) expressed in raw units

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

```
## Test observed mean of 0.54 and standard deviation of 1.2 in sample of 100 participants
## against 0.5 given equivalence bounds of Cohen's d = -0.3 and 0.3, with an alpha = 0.05.
TOSTone(m=0.54,mu=0.5,sd=1.2,n=100,low_eqbound_d=-0.3, high_eqbound_d=0.3, alpha=0.05)
#> Warning: `TOSTone()` was deprecated in TOSTER 0.4.0.
#> ℹ Please use `tsum_TOST()` instead.
#> TOST results:
#> t-value lower bound: 3.33 p-value lower bound: 0.0006
#> t-value upper bound: -2.67 p-value upper bound: 0.004
#> degrees of freedom : 99
#>
#> Equivalence bounds (Cohen's d):
#> low eqbound: -0.3
#> high eqbound: 0.3
#>
#> Equivalence bounds (raw scores):
#> low eqbound: -0.36
#> high eqbound: 0.36
#>
#> TOST confidence interval:
#> lower bound 90% CI: -0.159
#> upper bound 90% CI: 0.239
#>
#> NHST confidence interval:
#> lower bound 95% CI: -0.198
#> upper bound 95% CI: 0.278
#>
#> Equivalence Test Result:
#> The equivalence test was significant, t(99) = -2.667, p = 0.00447, given equivalence bounds of -0.360 and 0.360 (on a raw scale) and an alpha of 0.05.
#>
#>
#> Null Hypothesis Test Result:
#> The null hypothesis test was non-significant, t(99) = 0.333, p = 0.740, given an alpha of 0.05.
#>
#>
#> NHST: don't reject null significance hypothesis that the effect is equal to 0
#> TOST: reject null equivalence hypothesis
```