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Can someone please help me. Last month I passed my PhD viva (yay!) with minor revisions and one of the revisions is providing effect sizes for me separate studies. For one of my studies I used the PRocess macro for SPSS. I know that process provides effect sizes, because you can click on it, and the r-squared is given for the a path and b path. For the direct and indirect effect, however, all that's added for the direct/indirect effect is the partially standardized, and completely standardized effect. I have no idea what that means, or how I'm supposed to use that.

Any advice would be greatly appreciated on how to interpret this, and how to add this to my thesis in a way that would satisfy a reviewer. See below for my output!

Thanks!!

 
**************** PROCESS Procedure for SPSS Version 3.5.3 **************** 
 
          Written by Andrew F. Hayes, Ph.D.       www.afhayes.com 
    Documentation available in Hayes (2018). www.guilford.com/p/hayes3 
 
************************************************************************** 
Model  : 4 
    Y  : MAV 
    X  : AVOT 
    M  : GFF 
 
Sample 
Size:  247 
 
************************************************************************** 
OUTCOME VARIABLE: 
 GFF 
 
Model Summary 
          R       R-sq        MSE          F        df1        df2          p 
      .4694      .2203      .3082    69.2330     1.0000   245.0000      .0000 
 
Model 
              coeff         se          t          p       LLCI       ULCI 
constant    -1.1462      .1280    -8.9539      .0000    -1.3983     -.8940 
AVOT          .2619      .0315     8.3206      .0000      .1999      .3238 
 
************************************************************************** 
OUTCOME VARIABLE: 
 MAV 
 
Model Summary 
          R       R-sq        MSE          F        df1        df2          p 
      .4372      .1911     1.3149    28.8235     2.0000   244.0000      .0000 
 
Model 
              coeff         se          t          p       LLCI       ULCI 
constant     4.4883      .3046    14.7340      .0000     3.8883     5.0883 
AVOT          .2018      .0736     2.7410      .0066      .0568      .3468 
GFF           .6553      .1320     4.9655      .0000      .3954      .9152 
 
****************** DIRECT AND INDIRECT EFFECTS OF X ON Y ***************** 
 
Direct effect of X on Y 
     Effect         se          t          p       LLCI       ULCI      c'_ps      c'_cs 
      .2018      .0736     2.7410      .0066      .0568      .3468      .1589      .1787 
 
Indirect effect(s) of X on Y: 
        Effect     BootSE   BootLLCI   BootULCI 
GFF      .1716      .0447      .0889      .2667 
 
Partially standardized indirect effect(s) of X on Y: 
        Effect     BootSE   BootLLCI   BootULCI 
GFF      .1351      .0330      .0729      .2023 
 
Completely standardized indirect effect(s) of X on Y: 
        Effect     BootSE   BootLLCI   BootULCI 
GFF      .1520      .0374      .0811      .2287 
 
*********************** ANALYSIS NOTES AND ERRORS ************************ 
 
Level of confidence for all confidence intervals in output: 
  95.0000 
 
Number of bootstrap samples for percentile bootstrap confidence intervals: 
  5000 
 
------ END MATRIX -----```
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  • $\begingroup$ Are you sure that beta-square is interchangeable with eta-square?? $\endgroup$ Oct 26, 2023 at 16:42

1 Answer 1

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firstly, with the beta (coefficient value), we can find Cohen's f-square by: beta-square /( 1 - beta-square ).

After that, you can just convert it to any effect size indicator(s) that you want.

Hope it helps.

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