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Interpreting Mediation results

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psy_vm

Interpreting Mediation results

Hello,

I have a few questions regarding interpretation of my results for Mediation using Hayes' Process macro. The key point for finding significance is to see that the Class Interval does not include zero. However, in my mediation model, although the indirect effect CI doesn't include zero, the initial Models's CI (for bcope_ma, under Duration) includes zero. Should I still count my indirect effects as significant even though initial model for mediation is not significant?

Results pasted below. Please Help! Thanks in advance!

Model = 4
Y = qoltot
X = duration
M = bcope_ma

Sample size
70

**************************************************************************
Outcome: bcope_ma

Model Summary
R R-sq F df1 df2 p
.1830 .0335 2.3550 1.0000 68.0000 .1295

Model
coeff se t p LLCI ULCI
constant 22.5169 1.3151 17.1223 .0000 19.8927 25.1411
duration -.0388 .0253 -1.5346 .1295 -.0893 .0117

**************************************************************************
Outcome: qoltot

Model Summary
R R-sq F df1 df2 p
.3234 .1046 3.9140 2.0000 67.0000 .0247

Model
coeff se t p LLCI ULCI
constant 91.2951 9.5536 9.5560 .0000 72.2258 110.3643
bcope_ma -1.0460 .3823 -2.7364 .0079 -1.8091 -.2830
duration .0059 .0811 .0725 .9425 -.1559 .1677

************************** TOTAL EFFECT MODEL ****************************
Outcome: qoltot

Model Summary
R R-sq F df1 df2 p
.0674 .0045 .3102 1.0000 68.0000 .5794

Model
coeff se t p LLCI ULCI
constant 67.7413 4.3387 15.6134 .0000 59.0836 76.3990
duration .0465 .0834 .5570 .5794 -.1200 .2129

***************** TOTAL, DIRECT, AND INDIRECT EFFECTS ********************

Total effect of X on Y
Effect SE t p LLCI ULCI
.0465 .0834 .5570 .5794 -.1200 .2129

Direct effect of X on Y
Effect SE t p LLCI ULCI
.0059 .0811 .0725 .9425 -.1559 .1677

Indirect effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma .0406 .0311 .0009 .1240

Partially standardized indirect effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma .0022 .0016 .0000 .0068

Completely standardized indirect effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma .0589 .0411 .0017 .1650

Ratio of indirect to total effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma .8736 149.0933 .1603 53.5001

Ratio of indirect to direct effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma 6.9093 17.9156 3.4423 275.8767

R-squared mediation effect size (R-sq_med)
Effect Boot SE BootLLCI BootULCI
bcope_ma .0045 .0173 -.0184 .0543

Preacher and Kelley (2011) Kappa-squared
Effect Boot SE BootLLCI BootULCI
bcope_ma .0601 .0401 .0066 .1692

Normal theory tests for indirect effect
Effect se Z p
.0406 .0318 1.2753 .2022

******************** ANALYSIS NOTES AND WARNINGS *************************

Number of bootstrap samples for bias corrected bootstrap confidence intervals: 1000

Level of confidence for all confidence intervals in output: 95.00

NOTE: Some cases were deleted due to missing data. The number of such cases was: 33

peter link

Re: Interpreting Mediation results

The short answer is that if you are using a method such as bootstrapping to
test the Indirect Effect, then you need to only find a significant ab-path.
If you are using a method like The Test of Joint Significance (TJS), then
you would look to see if both a and b are different from 0.

In your example - The test of the indirect effect is under "Total, Direct,
and Indirect Effects". The CI for the Indirect Effect is [.0009,.1240]
which doesn't include zero, so you would conclude that it is statistically
significant (using bootstrapping criterion). So, you could have an "a" or
"b" path that is non-significant, but the "ab" path is significant.

However, the Total Effect is non-significant, indicating that there isn't an
effect to mediate, to begin with. Do you expect a Total Effect (should X
predict Y)? The Direct and Indirect Effects have the same sign, so you
aren't dealing with "Inconsistent Mediation" (a suppression effect). So,
you could talk about having an Indirect Effect but not Mediation. Also, you
should look at the size of the Indirect Effect. It seems small - is this an
important effect or is it trivial?

pl

-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of
psy_vm
Sent: Thursday, July 24, 2014 12:17 AM
To: [hidden email]
Subject: [SPSSX-L] Interpreting Mediation results

Hello,

I have a few questions regarding interpretation of my results for Mediation
using Hayes' Process macro. The key point for finding significance is to see
that the Class Interval does not include zero. However, in my mediation
model, although the indirect effect CI doesn't include zero, the initial
Models's CI (for bcope_ma, under Duration) includes zero. Should I still
count my indirect effects as significant even though initial model for
mediation is not significant?

Results pasted below. Please Help! Thanks in advance!

Model = 4
Y = qoltot
X = duration
M = bcope_ma

Sample size
70

**************************************************************************
Outcome: bcope_ma

Model Summary
R R-sq F df1 df2 p
.1830 .0335 2.3550 1.0000 68.0000 .1295

Model
coeff se t p LLCI

ULCI
constant 22.5169 1.3151 17.1223 .0000 19.8927 25.1411
duration -.0388 .0253 -1.5346 .1295 -.0893 .0117

**************************************************************************
Outcome: qoltot

Model Summary
R R-sq F df1 df2 p
.3234 .1046 3.9140 2.0000 67.0000 .0247

Model
coeff se t p LLCI

ULCI
constant 91.2951 9.5536 9.5560 .0000 72.2258 110.3643
bcope_ma -1.0460 .3823 -2.7364 .0079 -1.8091 -.2830
duration .0059 .0811 .0725 .9425 -.1559
.1677

************************** TOTAL EFFECT MODEL ****************************
Outcome: qoltot

Model Summary
R R-sq F df1 df2 p
.0674 .0045 .3102 1.0000 68.0000 .5794

Model
coeff se t p LLCI

ULCI
constant 67.7413 4.3387 15.6134 .0000 59.0836 76.3990
duration .0465 .0834 .5570 .5794 -.1200 .2129

***************** TOTAL, DIRECT, AND INDIRECT EFFECTS ********************

Total effect of X on Y
Effect SE t p LLCI ULCI
.0465 .0834 .5570 .5794 -.1200 .2129

Direct effect of X on Y
Effect SE t p LLCI ULCI
.0059 .0811 .0725 .9425 -.1559 .1677

Indirect effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma .0406 .0311 .0009 .1240

Partially standardized indirect effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma .0022 .0016 .0000 .0068

Completely standardized indirect effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma .0589 .0411 .0017 .1650

Ratio of indirect to total effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma .8736 149.0933 .1603 53.5001

Ratio of indirect to direct effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma 6.9093 17.9156 3.4423 275.8767

R-squared mediation effect size (R-sq_med)
Effect Boot SE BootLLCI BootULCI
bcope_ma .0045 .0173 -.0184 .0543

Preacher and Kelley (2011) Kappa-squared
Effect Boot SE BootLLCI BootULCI
bcope_ma .0601 .0401 .0066 .1692

Normal theory tests for indirect effect
Effect se Z p
.0406 .0318 1.2753 .2022

******************** ANALYSIS NOTES AND WARNINGS *************************

Number of bootstrap samples for bias corrected bootstrap confidence
intervals: 1000

Level of confidence for all confidence intervals in output: 95.00

NOTE: Some cases were deleted due to missing data. The number of such cases
was: 33

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Muir Houston-3

Re: Interpreting Mediation results

In reply to this post by psy_vm

Have you checked out Hayes website?
http://www.afhayes.com/spss-sas-and-mplus-macros-and-code.html

and also perhaps
http://www.afhayes.com/macrofaq.html

Muir Houston, HNC, BA (Hons), M.Phil., PhD, FHEA
College of Social Sciences Ethics Officer
Social Justice, Place and Lifelong Education Research
School of Education
University of Glasgow
0044+141-330-4699

Silver bullet or red herring? New evidence on the place of aspirations in education
R3L+ Project - Adult education in the light of the European Quality Strategy
http://www.learning-regions.net/

GINCO Project - Grundtvig International Network of Course Organisers
http://www.ginconet.eu/

THEMP - Tertiary Higher Education for People in Mid Life
http://themp.eu/

-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of psy_vm
Sent: 24 July 2014 08:17
To: [hidden email]
Subject: Interpreting Mediation results

Hello,

I have a few questions regarding interpretation of my results for Mediation using Hayes' Process macro. The key point for finding significance is to see that the Class Interval does not include zero. However, in my mediation model, although the indirect effect CI doesn't include zero, the initial Models's CI (for bcope_ma, under Duration) includes zero. Should I still count my indirect effects as significant even though initial model for mediation is not significant?

Results pasted below. Please Help! Thanks in advance!

Model = 4
Y = qoltot
X = duration
M = bcope_ma

Sample size
70

**************************************************************************
Outcome: bcope_ma

Model Summary
R R-sq F df1 df2 p
.1830 .0335 2.3550 1.0000 68.0000 .1295

Model
coeff se t p LLCI
ULCI
constant 22.5169 1.3151 17.1223 .0000 19.8927 25.1411
duration -.0388 .0253 -1.5346 .1295 -.0893 .0117

**************************************************************************
Outcome: qoltot

Model Summary
R R-sq F df1 df2 p
.3234 .1046 3.9140 2.0000 67.0000 .0247

Model
coeff se t p LLCI
ULCI
constant 91.2951 9.5536 9.5560 .0000 72.2258 110.3643
bcope_ma -1.0460 .3823 -2.7364 .0079 -1.8091 -.2830
duration .0059 .0811 .0725 .9425 -.1559
.1677

************************** TOTAL EFFECT MODEL ****************************
Outcome: qoltot

Model Summary
R R-sq F df1 df2 p
.0674 .0045 .3102 1.0000 68.0000 .5794

Model
coeff se t p LLCI
ULCI
constant 67.7413 4.3387 15.6134 .0000 59.0836 76.3990
duration .0465 .0834 .5570 .5794 -.1200 .2129

***************** TOTAL, DIRECT, AND INDIRECT EFFECTS ********************

Total effect of X on Y
Effect SE t p LLCI ULCI
.0465 .0834 .5570 .5794 -.1200 .2129

Direct effect of X on Y
Effect SE t p LLCI ULCI
.0059 .0811 .0725 .9425 -.1559 .1677

Indirect effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma .0406 .0311 .0009 .1240

Partially standardized indirect effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma .0022 .0016 .0000 .0068

Completely standardized indirect effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma .0589 .0411 .0017 .1650

Ratio of indirect to total effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma .8736 149.0933 .1603 53.5001

Ratio of indirect to direct effect of X on Y
Effect Boot SE BootLLCI BootULCI
bcope_ma 6.9093 17.9156 3.4423 275.8767

R-squared mediation effect size (R-sq_med)
Effect Boot SE BootLLCI BootULCI
bcope_ma .0045 .0173 -.0184 .0543

Preacher and Kelley (2011) Kappa-squared
Effect Boot SE BootLLCI BootULCI
bcope_ma .0601 .0401 .0066 .1692

Normal theory tests for indirect effect
Effect se Z p
.0406 .0318 1.2753 .2022

******************** ANALYSIS NOTES AND WARNINGS *************************

Number of bootstrap samples for bias corrected bootstrap confidence
intervals: 1000

Level of confidence for all confidence intervals in output: 95.00

NOTE: Some cases were deleted due to missing data. The number of such cases
was: 33

--
View this message in context: http://spssx-discussion.1045642.n5.nabble.com/Interpreting-Mediation-results-tp5726809.html
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psy_vm

Re: Interpreting Mediation results

In reply to this post by peter link

Thank you for your response. I have used bootstrapping method in my mediation. I will discuss the small effect size that you pointed out with my professor.

Thanks once again!
Vijaita

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From: peter link [via SPSSX Discussion] <[hidden email]>;
To: psy_vm <[hidden email]>;
Subject: Re: Interpreting Mediation results
Sent: Thu, Jul 24, 2014 5:12:02 PM

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psy_vm

Re: Interpreting Mediation results

In reply to this post by peter link

Hello,

Please may you help me with an additional question?

Do you know what effect size has Hayes used in his process? I've been through his book where he talks about the 6 different effect sizes that process gives in the result section:
Partial, complete, r_square, kappa, etc. But which one has he used in the total, direct, indirect effects, etc.

Would appreciate your help.
Thanks,
Vijaita

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Subject: Re: Interpreting Mediation results
Sent: Thu, Jul 24, 2014 5:12:02 PM

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peter link

Re: Interpreting Mediation results

I’m not familiar with PROCESS but from the output it looks like an R-sq and Kappa-sq is provided. This is towards the bottom of the output. Is this different than what you are asking about?

By the way, Andrew Hayes has an email address listed on his website. Perhaps, go to his website and contact him directly.

Peter

From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of psy_vm
Sent: Friday, August 15, 2014 3:48 PM
To: [hidden email]
Subject: Re: [SPSSX-L] Interpreting Mediation results

Hello,

Please may you help me with an additional question?

Would appreciate your help.
Thanks,
Vijaita

Sent from Yahoo Mail on Android

From: peter link [via SPSSX Discussion] <[hidden email]>;
To: psy_vm <[hidden email]>;
Subject: Re: Interpreting Mediation results
Sent: Thu, Jul 24, 2014 5:12:02 PM

If you reply to this email, your message will be added to the discussion below:

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View this message in context: Re: Interpreting Mediation results
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psy_vm

Re: Interpreting Mediation results

I meant the sizes of the total, direct and indirect effects (.0465, .0059 and .0406 respectively). Are they Cohen's d or some other ones?

I did mail him with this and the previous questions and he suggested I buy the book, which I just did. I read about the 6 different effects process gives at the bottom but I wanted to know about these other 3 ones. Makes sense?

Vijaita

Sent from Yahoo Mail on Android

From: peter link [via SPSSX Discussion] <[hidden email]>;
To: psy_vm <[hidden email]>;
Subject: Re: Interpreting Mediation results
Sent: Fri, Aug 15, 2014 11:26:51 PM

I’m not familiar with PROCESS but from the output it looks like an R-sq and Kappa-sq is provided. This is towards the bottom of the output. Is this different than what you are asking about?

By the way, Andrew Hayes has an email address listed on his website. Perhaps, go to his website and contact him directly.

Peter

Hello,

Please may you help me with an additional question?

Would appreciate your help.
Thanks,
Vijaita

Sent from Yahoo Mail on Android

From: peter link [via SPSSX Discussion] <[hidden email]>;
To: psy_vm <[hidden email]>;
Subject: Re: Interpreting Mediation results
Sent: Thu, Jul 24, 2014 5:12:02 PM

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peter link

Re: Interpreting Mediation results

Hi - Those are regression/path coefficients or products thereof and not effect sizes.

The Total Effect: The effect of X on Y. Often this is labeled as the c path.

The Direct Effect: The effect of X on Y adjusting for M. Often this is labeled as the c’ path.

The Indirect Effect: The product of the effects of X on M (a path) and M on Y (b path). Often this product is labeled as the ab path.

Hope this helps.

peter

From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of psy_vm
Sent: Friday, August 15, 2014 11:56 PM
To: [hidden email]
Subject: Re: [SPSSX-L] Interpreting Mediation results

I meant the sizes of the total, direct and indirect effects (.0465, .0059 and .0406 respectively). Are they Cohen's d or some other ones?

Vijaita

Sent from Yahoo Mail on Android

From: peter link [via SPSSX Discussion] <[hidden email]>;
To: psy_vm <[hidden email]>;
Subject: Re: Interpreting Mediation results
Sent: Fri, Aug 15, 2014 11:26:51 PM

Iâ€™m not familiar with PROCESS but from the output it looks like an R-sq and Kappa-sq is provided. This is towards the bottom of the output. Is this different than what you are asking about?

By the way, Andrew Hayes has an email address listed on his website. Perhaps, go to his website and contact him directly.

Peter

Hello,

Please may you help me with an additional question?

Would appreciate your help.
Thanks,
Vijaita

Sent from Yahoo Mail on Android

From: peter link [via SPSSX Discussion] <[hidden email]>;
To: psy_vm <[hidden email]>;
Subject: Re: Interpreting Mediation results
Sent: Thu, Jul 24, 2014 5:12:02 PM

The short answer is that if you are using a method such as bootstrapping to
test the Indirect Effect, then you need to only find a significant ab-path.
If you are using a method like The Test of Joint Significance (TJS), then
you would look to see if both a and b are different from 0.

In your example - The test of the indirect effect is under "Total, Direct,
and Indirect Effects". Â The CI for the Indirect Effect is [.0009,.1240]
which doesn't include zero, so you would conclude that it is statistically
significant (using bootstrapping criterion). Â So, you could have an "a" or
"b" path that is non-significant, but the "ab" path is significant.

However, the Total Effect is non-significant, indicating that there isn't an
effect to mediate, to begin with. Do you expect a Total Effect (should X
predict Y)? The Direct and Indirect Effects have the same sign, so you
aren't dealing with "Inconsistent Mediation" (a suppression effect). Â So,
you could talk about having an Indirect Effect but not Mediation. Â Also, you
should look at the size of the Indirect Effect. Â It seems small - is this an
important effect or is it trivial?

pl

-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of
psy_vm
Sent: Thursday, July 24, 2014 12:17 AM
To: [hidden email]
Subject: [SPSSX-L] Interpreting Mediation results

Hello,

I have a few questions regarding interpretation of my results for Mediation
using Hayes' Process macro. The key point for finding significance is to see
that the Class Interval does not include zero. However, in my mediation
model, although the indirect effect CI doesn't include zero, the initial
Models's CI (for bcope_ma, under Duration) includes zero. Should I still
count my indirect effects as significant even though initial model for
mediation is not significant?

Results pasted below. Please Help! Thanks in advance!

Model = 4
Â Â Y = qoltot
Â Â X = duration
Â Â M = bcope_ma

Sample size
Â Â Â Â Â 70

**************************************************************************
Outcome: bcope_ma

Model Summary
Â Â Â Â Â R Â Â Â Â R-sq Â Â Â Â Â F Â Â Â Â Â Â df1 Â Â Â Â df2 Â Â Â Â Â p
Â Â Â .1830 Â Â Â .0335 Â Â 2.3550 Â Â 1.0000 Â Â 68.0000 Â Â Â .1295

Model
Â Â Â Â Â Â Â Â Â Â coeff Â Â Â Â Â se Â Â Â Â Â Â Â t Â Â Â Â Â p Â Â Â LLCI

ULCI
constant Â Â 22.5169 Â Â 1.3151 Â Â 17.1223 Â Â Â .0000 Â Â 19.8927 Â Â 25.1411
duration Â Â -.0388 Â Â Â .0253 Â Â -1.5346 Â Â Â .1295 Â Â -.0893 Â Â Â .0117

**************************************************************************
Outcome: qoltot

Model Summary
Â Â Â Â Â R Â Â Â Â Â R-sq Â Â Â Â Â F Â Â Â Â Â df1 Â Â Â Â df2 Â Â Â Â Â p
Â Â Â .3234 Â Â Â .1046 Â Â 3.9140 Â Â 2.0000 Â Â 67.0000 Â Â Â .0247

Model
Â Â Â Â Â Â Â Â Â Â coeff Â Â Â Â se Â Â Â Â Â t Â Â Â Â Â Â Â p Â Â Â LLCI

ULCI
constant Â Â Â 91.2951 Â Â 9.5536 Â Â 9.5560 Â Â Â .0000 Â Â 72.2258 Â 110.3643
bcope_ma Â Â -1.0460 Â Â Â .3823 Â Â -2.7364 Â Â Â .0079 Â Â -1.8091 Â Â -.2830
duration Â Â Â .0059 Â Â Â Â Â .0811 Â Â Â .0725 Â Â Â .9425 Â Â -.1559 Â Â
.1677

************************** TOTAL EFFECT MODEL ****************************
Outcome: qoltot

Model Summary
Â Â Â Â Â R Â Â Â Â R-sq Â Â Â Â Â F Â Â Â Â Â df1 Â Â Â Â df2 Â Â Â Â Â p
Â Â Â .0674 Â Â Â .0045 Â Â Â .3102 Â Â 1.0000 Â Â 68.0000 Â Â Â .5794

Model
Â Â Â Â Â Â Â Â Â coeff Â Â Â Â se Â Â Â Â Â Â t Â Â Â Â Â Â Â p Â Â Â LLCI

ULCI
constant Â Â 67.7413 Â Â 4.3387 Â Â 15.6134 Â Â Â .0000 Â Â 59.0836 Â Â 76.3990
duration Â Â Â .0465 Â Â Â .0834 Â Â Â .5570 Â Â Â .5794 Â Â -.1200 Â Â Â .2129

***************** TOTAL, DIRECT, AND INDIRECT EFFECTS ********************

Total effect of X on Y
Â Â Â Effect Â Â Â Â SE Â Â Â Â Â Â t Â Â Â Â Â p Â Â Â Â Â LLCI Â Â Â ULCI
Â Â Â .0465 Â Â Â .0834 Â Â Â .5570 Â Â Â .5794 Â Â -.1200 Â Â Â .2129

Direct effect of X on Y
Â Â Â Effect Â Â Â Â SE Â Â Â Â Â t Â Â Â Â Â Â p Â Â Â Â LLCI Â Â Â ULCI
Â Â Â .0059 Â Â Â .0811 Â Â Â .0725 Â Â Â .9425 Â Â -.1559 Â Â Â .1677

Indirect effect of X on Y
Â Â Â Â Â Â Â Â Â Â Effect Â Â Boot SE Â BootLLCI Â BootULCI
bcope_ma Â Â Â .0406 Â Â Â .0311 Â Â Â .0009 Â Â Â .1240

Partially standardized indirect effect of X on Y
Â Â Â Â Â Â Â Â Â Â Effect Â Â Boot SE Â BootLLCI Â BootULCI
bcope_ma Â Â Â .0022 Â Â Â .0016 Â Â Â .0000 Â Â Â .0068

Completely standardized indirect effect of X on Y
Â Â Â Â Â Â Â Â Â Â Effect Â Â Boot SE Â BootLLCI Â BootULCI
bcope_ma Â Â Â .0589 Â Â Â .0411 Â Â Â .0017 Â Â Â .1650

Ratio of indirect to total effect of X on Y
Â Â Â Â Â Â Â Â Â Effect Â Â Boot SE Â BootLLCI Â BootULCI
bcope_ma Â Â Â .8736 Â 149.0933 Â Â Â .1603 Â Â 53.5001

Ratio of indirect to direct effect of X on Y
Â Â Â Â Â Â Â Â Â Effect Â Â Boot SE Â BootLLCI Â BootULCI
bcope_ma Â Â 6.9093 Â Â 17.9156 Â Â 3.4423 Â 275.8767

R-squared mediation effect size (R-sq_med)
Â Â Â Â Â Â Â Â Â Effect Â Â Boot SE Â BootLLCI Â BootULCI
bcope_ma Â Â Â .0045 Â Â Â .0173 Â Â -.0184 Â Â Â .0543

Preacher and Kelley (2011) Kappa-squared
Â Â Â Â Â Â Â Effect Â Â Boot SE Â BootLLCI Â BootULCI
bcope_ma Â Â Â .0601 Â Â Â .0401 Â Â Â .0066 Â Â Â .1692

Normal theory tests for indirect effect
Â Â Â Effect Â Â Â Â se Â Â Â Â Â Z Â Â Â Â Â p
Â Â Â .0406 Â Â Â .0318 Â Â 1.2753 Â Â Â .2022

******************** ANALYSIS NOTES AND WARNINGS *************************

Number of bootstrap samples for bias corrected bootstrap confidence
intervals: Â Â 1000

Level of confidence for all confidence intervals in output: Â Â 95.00

NOTE: Some cases were deleted due to missing data. Â The number of such cases
was: Â 33

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psy_vm

Re: Interpreting Mediation results

Thank you so much for this clarification! Very helpful.
Bests,
Vijaita

Sent from Yahoo Mail on Android

From: peter link [via SPSSX Discussion] <[hidden email]>;
To: psy_vm <[hidden email]>;
Subject: Re: Interpreting Mediation results
Sent: Mon, Aug 18, 2014 3:09:31 PM

Hi - Those are regression/path coefficients or products thereof and not effect sizes.

The Total Effect: The effect of X on Y. Often this is labeled as the c path.

The Direct Effect: The effect of X on Y adjusting for M. Often this is labeled as the c’ path.

The Indirect Effect: The product of the effects of X on M (a path) and M on Y (b path). Often this product is labeled as the ab path.

Hope this helps.

peter

I meant the sizes of the total, direct and indirect effects (.0465, .0059 and .0406 respectively). Are they Cohen's d or some other ones?

Vijaita

Sent from Yahoo Mail on Android

From: peter link [via SPSSX Discussion] <[hidden email]>;
To: psy_vm <[hidden email]>;
Subject: Re: Interpreting Mediation results
Sent: Fri, Aug 15, 2014 11:26:51 PM

Iâ€™m not familiar with PROCESS but from the output it looks like an R-sq and Kappa-sq is provided. This is towards the bottom of the output. Is this different than what you are asking about?

By the way, Andrew Hayes has an email address listed on his website. Perhaps, go to his website and contact him directly.

Peter

Hello,

Please may you help me with an additional question?

Would appreciate your help.
Thanks,
Vijaita

Sent from Yahoo Mail on Android

From: peter link [via SPSSX Discussion] <[hidden email]>;
To: psy_vm <[hidden email]>;
Subject: Re: Interpreting Mediation results
Sent: Thu, Jul 24, 2014 5:12:02 PM

The short answer is that if you are using a method such as bootstrapping to
test the Indirect Effect, then you need to only find a significant ab-path.
If you are using a method like The Test of Joint Significance (TJS), then
you would look to see if both a and b are different from 0.

In your example - The test of the indirect effect is under "Total, Direct,
and Indirect Effects". Â The CI for the Indirect Effect is [.0009,.1240]
which doesn't include zero, so you would conclude that it is statistically
significant (using bootstrapping criterion). Â So, you could have an "a" or
"b" path that is non-significant, but the "ab" path is significant.

However, the Total Effect is non-significant, indicating that there isn't an
effect to mediate, to begin with. Do you expect a Total Effect (should X
predict Y)? The Direct and Indirect Effects have the same sign, so you
aren't dealing with "Inconsistent Mediation" (a suppression effect). Â So,
you could talk about having an Indirect Effect but not Mediation. Â Also, you
should look at the size of the Indirect Effect. Â It seems small - is this an
important effect or is it trivial?

pl

-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of
psy_vm
Sent: Thursday, July 24, 2014 12:17 AM
To: [hidden email]
Subject: [SPSSX-L] Interpreting Mediation results

Hello,

I have a few questions regarding interpretation of my results for Mediation
using Hayes' Process macro. The key point for finding significance is to see
that the Class Interval does not include zero. However, in my mediation
model, although the indirect effect CI doesn't include zero, the initial
Models's CI (for bcope_ma, under Duration) includes zero. Should I still
count my indirect effects as significant even though initial model for
mediation is not significant?

Results pasted below. Please Help! Thanks in advance!

Model = 4
Â Â Y = qoltot
Â Â X = duration
Â Â M = bcope_ma

Sample size
Â Â Â Â Â 70

**************************************************************************
Outcome: bcope_ma

Model Summary
Â Â Â Â Â R Â Â Â Â R-sq Â Â Â Â Â F Â Â Â Â Â Â df1 Â Â Â Â df2 Â Â Â Â Â p
Â Â Â .1830 Â Â Â .0335 Â Â 2.3550 Â Â 1.0000 Â Â 68.0000 Â Â Â .1295

Model
Â Â Â Â Â Â Â Â Â Â coeff Â Â Â Â Â se Â Â Â Â Â Â Â t Â Â Â Â Â p Â Â Â LLCI

ULCI
constant Â Â 22.5169 Â Â 1.3151 Â Â 17.1223 Â Â Â .0000 Â Â 19.8927 Â Â 25.1411
duration Â Â -.0388 Â Â Â .0253 Â Â -1.5346 Â Â Â .1295 Â Â -.0893 Â Â Â .0117

**************************************************************************
Outcome: qoltot

Model Summary
Â Â Â Â Â R Â Â Â Â Â R-sq Â Â Â Â Â F Â Â Â Â Â df1 Â Â Â Â df2 Â Â Â Â Â p
Â Â Â .3234 Â Â Â .1046 Â Â 3.9140 Â Â 2.0000 Â Â 67.0000 Â Â Â .0247

Model
Â Â Â Â Â Â Â Â Â Â coeff Â Â Â Â se Â Â Â Â Â t Â Â Â Â Â Â Â p Â Â Â LLCI

ULCI
constant Â Â Â 91.2951 Â Â 9.5536 Â Â 9.5560 Â Â Â .0000 Â Â 72.2258 Â 110.3643
bcope_ma Â Â -1.0460 Â Â Â .3823 Â Â -2.7364 Â Â Â .0079 Â Â -1.8091 Â Â -.2830
duration Â Â Â .0059 Â Â Â Â Â .0811 Â Â Â .0725 Â Â Â .9425 Â Â -.1559 Â Â
.1677

************************** TOTAL EFFECT MODEL ****************************
Outcome: qoltot

Model Summary
Â Â Â Â Â R Â Â Â Â R-sq Â Â Â Â Â F Â Â Â Â Â df1 Â Â Â Â df2 Â Â Â Â Â p
Â Â Â .0674 Â Â Â .0045 Â Â Â .3102 Â Â 1.0000 Â Â 68.0000 Â Â Â .5794

Model
Â Â Â Â Â Â Â Â Â coeff Â Â Â Â se Â Â Â Â Â Â t Â Â Â Â Â Â Â p Â Â Â LLCI

ULCI
constant Â Â 67.7413 Â Â 4.3387 Â Â 15.6134 Â Â Â .0000 Â Â 59.0836 Â Â 76.3990
duration Â Â Â .0465 Â Â Â .0834 Â Â Â .5570 Â Â Â .5794 Â Â -.1200 Â Â Â .2129

***************** TOTAL, DIRECT, AND INDIRECT EFFECTS ********************

Total effect of X on Y
Â Â Â Effect Â Â Â Â SE Â Â Â Â Â Â t Â Â Â Â Â p Â Â Â Â Â LLCI Â Â Â ULCI
Â Â Â .0465 Â Â Â .0834 Â Â Â .5570 Â Â Â .5794 Â Â -.1200 Â Â Â .2129

Direct effect of X on Y
Â Â Â Effect Â Â Â Â SE Â Â Â Â Â t Â Â Â Â Â Â p Â Â Â Â LLCI Â Â Â ULCI
Â Â Â .0059 Â Â Â .0811 Â Â Â .0725 Â Â Â .9425 Â Â -.1559 Â Â Â .1677

Indirect effect of X on Y
Â Â Â Â Â Â Â Â Â Â Effect Â Â Boot SE Â BootLLCI Â BootULCI
bcope_ma Â Â Â .0406 Â Â Â .0311 Â Â Â .0009 Â Â Â .1240

Partially standardized indirect effect of X on Y
Â Â Â Â Â Â Â Â Â Â Effect Â Â Boot SE Â BootLLCI Â BootULCI
bcope_ma Â Â Â .0022 Â Â Â .0016 Â Â Â .0000 Â Â Â .0068

Completely standardized indirect effect of X on Y
Â Â Â Â Â Â Â Â Â Â Effect Â Â Boot SE Â BootLLCI Â BootULCI
bcope_ma Â Â Â .0589 Â Â Â .0411 Â Â Â .0017 Â Â Â .1650

Ratio of indirect to total effect of X on Y
Â Â Â Â Â Â Â Â Â Effect Â Â Boot SE Â BootLLCI Â BootULCI
bcope_ma Â Â Â .8736 Â 149.0933 Â Â Â .1603 Â Â 53.5001

Ratio of indirect to direct effect of X on Y
Â Â Â Â Â Â Â Â Â Effect Â Â Boot SE Â BootLLCI Â BootULCI
bcope_ma Â Â 6.9093 Â Â 17.9156 Â Â 3.4423 Â 275.8767

R-squared mediation effect size (R-sq_med)
Â Â Â Â Â Â Â Â Â Effect Â Â Boot SE Â BootLLCI Â BootULCI
bcope_ma Â Â Â .0045 Â Â Â .0173 Â Â -.0184 Â Â Â .0543

Preacher and Kelley (2011) Kappa-squared
Â Â Â Â Â Â Â Effect Â Â Boot SE Â BootLLCI Â BootULCI
bcope_ma Â Â Â .0601 Â Â Â .0401 Â Â Â .0066 Â Â Â .1692

Normal theory tests for indirect effect
Â Â Â Effect Â Â Â Â se Â Â Â Â Â Z Â Â Â Â Â p
Â Â Â .0406 Â Â Â .0318 Â Â 1.2753 Â Â Â .2022

******************** ANALYSIS NOTES AND WARNINGS *************************

Number of bootstrap samples for bias corrected bootstrap confidence
intervals: Â Â 1000

Level of confidence for all confidence intervals in output: Â Â 95.00

NOTE: Some cases were deleted due to missing data. Â The number of such cases
was: Â 33

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-tp5726809.html
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