Compute effect size from Student's ttest for independent samples.
esc_t( t, p, totaln, grp1n, grp2n, es.type = c("d", "g", "or", "logit", "r", "f", "eta", "cox.or", "cox.log"), study = NULL, ... )
t  The tvalue of the ttest. One of 

p  The pvalue of the ttest. 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. 
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
.
This function only applies to independent sample ttests, either
equal or unequal sample sizes. It can't be used for tvalues from
dependent or paired ttests, or tvalues 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.
Lipsey MW, Wilson DB. 2001. Practical metaanalysis. Thousand Oaks, Calif: Sage Publications
Wilson DB. 2016. Formulas Used by the "Practical MetaAnalysis Effect Size Calculator". Unpublished manuscript: George Mason University
# unequal sample size esc_t(t = 3.3, grp1n = 100, grp2n = 150)#> #> Effect Size Calculation for Meta Analysis #> #> Conversion: tvalue to effect size d #> Effect Size: 0.4260 #> Standard Error: 0.1305 #> Variance: 0.0170 #> Lower CI: 0.1703 #> Upper CI: 0.6818 #> Weight: 58.7211# equal sample size esc_t(t = 3.3, totaln = 200)#> #> Effect Size Calculation for Meta Analysis #> #> Conversion: tvalue to effect size d #> Effect Size: 0.4667 #> Standard Error: 0.1433 #> Variance: 0.0205 #> Lower CI: 0.1858 #> Upper CI: 0.7476 #> Weight: 48.6748# unequal sample size, with pvalue esc_t(p = 0.03, grp1n = 100, grp2n = 150)#> #> Effect Size Calculation for Meta Analysis #> #> Conversion: tvalue to effect size d #> Effect Size: 0.2818 #> Standard Error: 0.1297 #> Variance: 0.0168 #> Lower CI: 0.0275 #> Upper CI: 0.5360 #> Weight: 59.4337# equal sample size, with pvalue esc_t(p = 0.03, totaln = 200)#> #> Effect Size Calculation for Meta Analysis #> #> Conversion: tvalue to effect size d #> Effect Size: 0.3091 #> Standard Error: 0.1423 #> Variance: 0.0202 #> Lower CI: 0.0303 #> Upper CI: 0.5880 #> Weight: 49.4098