Sentence examples for medium effects and from inspiring English sources

By this metric, values about.5 indicate medium effects, and values above.8 suggest large effects [27].

According to effect size conventions "effect size" was chosen 0.1 for small effects, 0.25 for medium effects and 0.4 for large effects.

Following Cohen [ 54], η values from.010 to < .059 are interpreted as small effects, from.059 to < .138 as medium effects, and from.138 as large effects.

Additionally, the classification of effect sizes (f) was determined by calculating partial η 2 p. According to Cohen [ 27], 0.00 ≤  f ≤ 0.24 indicate small effects, 0.25 ≤  f ≤ 0.39 indicate medium effects, and f ≥ 0.4 indicate large effects.

Correlation coefficients (r) or partial eta-squared (η p 2 ) are reported indicating the effect sizes (r < .10 and η p 2 <.05 representing small effects, r < .30 and η p 2 around.10 representing medium effects, and r > .50 and η > .20 representing large effects; Cohen, 1973, 1988).

For Cohen's d, an effect size of 0.2 to 0.3 might be a "small" effect; around 0.5, a "medium" effect; and 0.8 to infinity, a "large" effect.

Changes in depression are also highlighted by nearly a one-point improvement on the CGI-Depression Scale corresponding with a medium effect and robust change.

Instead, Fuzzy Logic Theory allows us to summarize opinions via linguistic terms (e.g., a mechanism may have a "weak" or "medium" effect) and consider that each term is associated to a range of values.

We interpreted effect size using Cohen's [21] general guidelines, whereby d = 0.2 is a small effect, d = 0.5 is a medium effect, and d = 0.8 is a large effect.

Cohen's d is a standardized measure of effect size in which values between 0.2 to 0.3 are taken to indicate "small" effect, values around 0.5 indicate a "medium" effect and values >0.8 indicate a "large" effect.

Effect size index is interpreted as 0.10 small effect, 0.30 medium effect and 0.50 large effect (Cohen 1988).