# effect_size_t

##### Simple Effect Size Calculation for t-Tests

Calculates Cohen's d for two sample comparisons.

##### Usage

```
effect_size_t(data, response, group, absolute = FALSE, paired = FALSE,
na.rm = TRUE)
```

##### Arguments

- data
A

`data.frame`

.- response
The response variable (dependent).

- group
The group variable, usually a

`factor`

.- absolute
If set to

`TRUE`

, the absolute effect size is returned.- paired
Whether the effect should be calculated for a paired t-test, default is

`FALSE`

.- na.rm
If

`TRUE`

(default), missing values are dropped.

##### Details

The effect size here is Cohen's d as calculated by \(d = \frac{m_{diff}}{S_p}\), where \(m_{diff} = \bar{x}_1 - \bar{x}_2\) and \(S_p = \sqrt{ \frac{n_1 - 1 \cdot {s_{x_1}}^2 + n_2 - 1 \cdot {s_{x_2}}^2} {n_1 + n_2 - 2} } \).

For `paired = TRUE`

, \(S_p\) is substituted by \(S_D = S_{x_1 - x_2}\)
via `sd(x1 - x2)`

.

##### Value

`numeric`

of length 1.

##### Examples

```
# NOT RUN {
set.seed(42)
df <- data.frame(x = runif(100), group = sample(c("A", "B"), 100, TRUE))
effect_size_t(df, "x", "group")
# }
```

*Documentation reproduced from package tadaatoolbox, version 0.16.0, License: MIT + file LICENSE*