# stand_result: Convert different statistical reports into a standardized... In setgree/PrejMetaFunctions: Some functions John-Henry Pezzuto and I wrote for a forthcoming meta-analysis

 stand_result R Documentation

## Convert different statistical reports into a standardized framework (Cohen's D and Variance/Standard Error of Cohen's D)

### Description

Convert different statistical reports into a standardized framework (Cohen's D and Variance/Standard Error of Cohen's D)

### Usage

```stand_result(eff_type, raw_effect_size, sd, n_t, n_c)
```

### Arguments

 `eff_type` The effect type to convert. Currently accepted options are "d_i_d" (difference in differences), "d_i_m" (difference in means), 'd' (For Cohen's D – this won't recalculate Cohen's D but will estimate its variance and standard error), "unspecified null" (for when authors report that they found null effects but don't give a more precise recording of what those were), "eta_squared" (for eta squared), "reg_coef" (for a regression coefficient), "t_test" (for a T statistic), and "f_test" (for an F test). `raw_effect_size` the reported test statistic, in terms of the reported statistical information. So, if the eff_type = "t_test", raw_effect_size will equal the T statistic. `sd` the standard deviation by which you are standardizing the given test statistic. This is needed for some but not all of the equations – F test and T ' statistics already contain information about samplng distribution and thus can be converted directly and this parameter can be left blank. `n_t` sample size in the treatment group. `n_c` sample size in the control group.

### Examples

```stand_result(eff_type = 'd_i_m', raw_effect_size = 2.43,  sd = 6.3, n_t = 100, n_c = 100)
```

setgree/PrejMetaFunctions documentation built on March 13, 2023, 9:27 a.m.