esc_t {esc} | R Documentation |
Compute effect size from Student's t-test
Description
Compute effect size from Student's t-test for independent samples.
Usage
esc_t(
t,
p,
totaln,
grp1n,
grp2n,
es.type = c("d", "g", "or", "logit", "r", "f", "eta", "cox.or", "cox.log"),
study = NULL,
...
)
Arguments
t |
The t-value of the t-test. One of |
p |
The p-value of the t-test. One of |
totaln |
Total sample size. Either |
grp1n |
Treatment group sample size. |
grp2n |
Control group sample size. |
es.type |
Type of effect size that should be returned.
|
study |
Optional string with the study name. Using |
... |
Other parameters, passed down to further functions. For internal use only, can be ignored. |
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
This function only applies to independent sample t-tests, either
equal or unequal sample sizes. It can't be used for t-values from
dependent or paired t-tests, or t-values from other statistical procedures
(like regressions).
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 Unpublished manuscript: George Mason University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
# unequal sample size
esc_t(t = 3.3, grp1n = 100, grp2n = 150)
# equal sample size
esc_t(t = 3.3, totaln = 200)
# unequal sample size, with p-value
esc_t(p = 0.03, grp1n = 100, grp2n = 150)
# equal sample size, with p-value
esc_t(p = 0.03, totaln = 200)