Code
res
Output
$effect_size
[1] -0.8528028
$LL
[1] -2.121155
$UL
[1] 0.4482578
$numerator
[1] -2
$denominator
[1] 2.345208
$SE
[1] 0.6554747
$df
[1] 12
$d_biased
[1] -0.8528028
$properties
$properties$effect_size_name
[1] "d_s"
$properties$effect_size_name_html
[1] "<i>d</i><sub>s.biased</sub>"
$properties$denominator_name
[1] "s_p"
$properties$denominator_name_html
[1] "<i>s</i><sub>p</sub>"
$properties$bias_corrected
[1] FALSE
$properties$effect_size_category
[1] "difference"
$properties$effect_size_precision
[1] "magnitude"
$properties$conf_level
[1] 0.95
$properties$assume_equal_variance
[1] TRUE
$properties$error_distribution
[1] "t_dist"
$properties$message
This standardized mean difference is called d_s because the standardizer used was s_p. d_s has *not* been corrected for bias. Correction for bias can be important when df < 50.
$properties$message_html
This standardized mean difference is called <i>d</i><sub>s.biased</sub>
because the standardizer used was <i>s</i><sub>p</sub>.<br>
<i>d</i><sub>s.biased</sub> has *not*
been corrected for bias.
Correction for bias can be important when <i>df</i> < 50. <br>
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