esc_B {esc} R Documentation

## Compute effect size from Unstandardized Regression Coefficient

### Description

Compute effect size from Unstandardized Regression Coefficient.

### Usage

```esc_B(
b,
sdy,
grp1n,
grp2n,
es.type = c("d", "g", "or", "logit", "r", "f", "eta", "cox.or", "cox.log"),
study = NULL
)
```

### Arguments

 `b` The unstandardized coefficient B. `sdy` The standard deviation of the dependent variable. `grp1n` Treatment group sample size. `grp2n` Control group sample size. `es.type` Type of effect size that should be returned. `"d"`returns standardized mean difference effect size `d` `"f"`returns effect size Cohen's `f` `"g"`returns adjusted standardized mean difference effect size Hedges' `g` `"or"`returns effect size as odds ratio `"cox.or"`returns effect size as Cox-odds ratio (see `convert_d2or` for details) `"logit"`returns effect size as log odds `"cox.log"`returns effect size as Cox-log odds (see `convert_d2logit` for details) `"r"`returns correlation effect size `r` `"eta"`returns effect size eta squared `study` Optional string with the study name. Using `combine_esc` or `as.data.frame` on `esc`-objects will add this as column in the returned data frame.

### Value

The effect size `es`, the standard error `se`, the variance of the effect size `var`, the lower and upper confidence limits `ci.lo` and `ci.hi`, the weight factor `w` and the total sample size `totaln`.

### Note

If `es.type = "r"`, Fisher's transformation for the effect size `r` and their confidence intervals are also returned.

### References

Lipsey MW, Wilson DB. 2001. Practical meta-analysis. Thousand Oaks, Calif: Sage Publications

Wilson DB. 2016. Formulas Used by the "Practical Meta-Analysis Effect Size Calculator". Unpublished manuscript: George Mason University

### Examples

```esc_B(3.3, 5, 100, 150)

```

[Package esc version 0.5.1 Index]