es.fsq.partial {powertools} | R Documentation |
Cohen f-squared effect size for partial F test in multiple linear regression
Description
Computes the f-squared (f^2) effect size for a partial F test in a multiple linear regression model using either model R^2 (Rsq) values or a partial correlation. Based on Cohen (1988). (EDIT THIS)
Usage
es.fsq.partial(Rsq.red = NULL, Rsq.full = NULL, Rsq.diff = NULL, pc = NULL)
Arguments
Rsq.red |
The squared population multiple correlation coefficient for the reduced model. Either 2 out of 3 Rsq terms OR pc must be specified. |
Rsq.full |
The squared population multiple correlation coefficient for the full model. Either 2 out of 3 Rsq terms OR pc must be specified. |
Rsq.diff |
The difference between the squared population multiple correlation coefficient for the full model and the reduced model. Either 2 out of 3 Rsq terms OR pc must be specified. |
pc |
The partial correlation coefficient. Either 2 out of 3 Rsq terms OR pc must be specified. |
Details
Cohen J (1988) Statistical Power Analysis for the Behavioral Sciences, 2nd edition. Lawrence Erlbaum Associates, Hillsdale, New Jersey
Value
A list of the arguments and the f^2 effect size.
Examples
es.fsq.partial(pc = 0.2)
es.fsq.partial(Rsq.red = 0.25, Rsq.full = 0.35)
es.fsq.partial(Rsq.red = 0.25, Rsq.diff = 0.1)
es.fsq.partial(Rsq.full = 0.35, Rsq.diff = 0.1)