Really Easy Question about Mediation (HELP!!)

[toph_bei_fong]

Hi everyone,

I am very, very new to mediation and could use some help. I know the steps to Baron and Kenny's method but am unsure of how to actually do them in SPSS.

I have two categorical IVs (which I have dummy coded), the interaction term of these categorical variables and three continuous mediators.

So, here are my questions:

1) If I'm wanting to look at mediation of one of my IV effects, would I enter that variable in by itself in Step 1 as a predictor and leave the other IV out? Or can I assess both at the same time by entering both as my IVs? Or should I just enter the full model (IV1, IV2, IV1*IV2)?

2) If I'm wanting to look at mediation at it pertains to my interaction term, do it enter the interaction term as the sole predictor in Step 1 or do I also enter IV1 and IV2 as covariates?

I just really need someone to walk me through these steps, but after that I'm golden.

Thank you!

tbf

[Maguin, Eugene]

TBF,

Baron and Kenny's (B&K) work has been superceded by more recent work. A key
name among others is David MacKinnon who is (or was) at Arizona State
University. His website lists his articles. One of the key contributions of
MacKinnon is computing the standard error for the mediated effect. Kris
Preacher is another key name. He has a useful website also.

Given that X is the IV, M is the mediator, and Y is the DV, the B&K
formulation requires, in part, that X->Y, X->M, and M->Y all be significant,
where -> means 'predicts'. And, given X,M->Y, that X->Y=0.

>>1) If I'm wanting to look at mediation of one of my IV effects, would I
enter that variable in by itself in Step 1 as a predictor and leave the
other IV out?

Is step 1 X->Y or X->M? If you leave IV2 out then you should be interested
in testing whether M mediates the relationship between IV1 and the DV.

>>Or can I assess both at the same time by entering both as my
IVs? Or should I just enter the full model (IV1, IV2, IV1*IV2)?

This is testing a different question.


2) If I'm wanting to look at mediation at it pertains to my interaction
term, do it enter the interaction term as the sole predictor in Step 1 or do
I also enter IV1 and IV2 as covariates?

This question has nothing to do with mediation. Entering an interaction term
but leaving out the main effects gives an incorrect estimate for the
interaction term.

What you are wanting to do is not easy because your model is, I think, very
complex. You have two IVs plus their interaction and three possible
mediators. I don't know whether or not you are analyzing each mediator
separately. If you are not analyzing the mediators separately, then you are
talking about 9 possible pathways. You have to use a structural equation
modeling program for something like this. If you are, then an analysis
structured as a multiple regression implies that the effects of IV1, IV2 and
IV1_IV2 all flow through the mediator. Is this what you want? However, this
is also complicated because you have three mediation pathways to test. This
not something that I have done but I'd guess that this also would be better
done in a strucural equation modeling program.

I assume your DV is continuous. If not, that is another issue to contend
with.


Citations (from Cam MacIntosh on Semnet) to look at would include

MacKinnon, D. P., & Fairchild, A. J. (2009). Current directions in mediation
analysis. Current Directions in Psychological Science, 18, 16-20.

MacKinnon, D.P. (2008). Introduction to statistical mediation analysis.
Mahwah, NJ: Erlbaum.

MacKinnon, D. P., Fairchild, A. J., & Fritz, M. S. (2007). Mediation
analysis. Annual Review of Psychology, 58, 593-614.

MacKinnon, D. P., Lockwood, C. M., Hoffman, J. M., West, S. G., & Sheets, V.
(2002). A comparison of methods to test mediation and other intervening
variable effects. Psychological Methods, 7(1), 83-104.


Gene Maguin


-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of
toph_bei_fong
Sent: Wednesday, May 18, 2011 2:13 AM
To: [hidden email]
Subject: Really Easy Question about Mediation (HELP!!)

Hi everyone,

I am very, very new to mediation and could use some help. I know the steps
to Baron and Kenny's method but am unsure of how to actually do them in
SPSS.

I have two categorical IVs (which I have dummy coded), the interaction term
of these categorical variables and three continuous mediators.

So, here are my questions:

1) If I'm wanting to look at mediation of one of my IV effects, would I
enter that variable in by itself in Step 1 as a predictor and leave the
other IV out? Or can I assess both at the same time by entering both as my
IVs? Or should I just enter the full model (IV1, IV2, IV1*IV2)?

2) If I'm wanting to look at mediation at it pertains to my interaction
term, do it enter the interaction term as the sole predictor in Step 1 or do
I also enter IV1 and IV2 as covariates?

I just really need someone to walk me through these steps, but after that
I'm golden.

Thank you!

tbf

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[Bruce Weaver]

Gene M. has responded with some comments.  Here are some more from a slightly different perspective.  My training was in psychology, but that was in the days before mediation became the rage.  By that time, I was working in the area of health-related research & biostatistics.  One thing I find interesting is that the definitions of confounding and mediation are nearly identical, the difference being that the mediator is on a presumed causal chain between X and Y.  For some good discussion of this, see Mike Babyak's short article available here:

   http://ebmh.bmj.com/content/12/3/68.full

Given this similarity between confounding and mediation, I find it very interesting that the standard advice in the world of biostatistics is (or at least was a few years ago) that one should NOT perform a statistical test for confounding, whereas the mediation folks are going whole hog down the road of testing (e.g., developing standard errors).  

Here's an example of the biostats view from Bob Wolfe's (from University of Michigan) "classic lecture" series.  (Unfortunately, these lectures no longer seem to be available online.  Fortunately, I saved copies of some of them.)

--- start of excerpt ---

C. Testing for confounding (don't do it):

    When attempting to document the effect of a specific risk
    factor on an outcome, confounding factors should be
    controlled for even if they are not significantly related to
    the outcome in the analysis.  In this case, the objective of
    the analysis is to estimate the strength of the relationship
    between the risk factor and the outcome not explainable by
    confounding factors, and the strength of the relationship
    between the confounding factors and the outcome is not as
    important.

    When searching for a parsimonious model for predicting the
    outcome, it is useful to exclude unimportant factors from
    the model.  Some data analysts use statistical significance
    as a criterion for importance.  This approach may miss confounders.

--- end of excerpt ---

Finally, I should mention that the next section in that same lecture has the title, "D. Confounders and intervening variables:  Often a quandary."  Intervening variable is another name for mediator, of course.

HTH.

toph_bei_fong wrote

Hi everyone,

I am very, very new to mediation and could use some help. I know the steps to Baron and Kenny's method but am unsure of how to actually do them in SPSS.

I have two categorical IVs (which I have dummy coded), the interaction term of these categorical variables and three continuous mediators.

So, here are my questions:

1) If I'm wanting to look at mediation of one of my IV effects, would I enter that variable in by itself in Step 1 as a predictor and leave the other IV out? Or can I assess both at the same time by entering both as my IVs? Or should I just enter the full model (IV1, IV2, IV1*IV2)?

2) If I'm wanting to look at mediation at it pertains to my interaction term, do it enter the interaction term as the sole predictor in Step 1 or do I also enter IV1 and IV2 as covariates?

I just really need someone to walk me through these steps, but after that I'm golden.

Thank you!

tbf

[Art Kendall]

Different individuals use the same words in different ways.
some words that sometimes mean the same things and sometimes mean different things are:
covariate, confounder, mediator, suppressor, moderator.  Sometimes people say any of those words for any continuous independent (predictor, right-hand-side) variable.

What are your variables? What substantive questions are you using the data to answer?
What values can the categorical variables have?

Is this an experiment (one or more of the IV's represents random assignment)? 

Art Kendall
Social Research Consultants


On 5/18/2011 2:12 AM, toph_bei_fong wrote:

Hi everyone,

I am very, very new to mediation and could use some help. I know the steps
to Baron and Kenny's method but am unsure of how to actually do them in
SPSS.

I have two categorical IVs (which I have dummy coded), the interaction term
of these categorical variables and three continuous mediators.

So, here are my questions:

1) If I'm wanting to look at mediation of one of my IV effects, would I
enter that variable in by itself in Step 1 as a predictor and leave the
other IV out? Or can I assess both at the same time by entering both as my
IVs? Or should I just enter the full model (IV1, IV2, IV1*IV2)?

2) If I'm wanting to look at mediation at it pertains to my interaction
term, do it enter the interaction term as the sole predictor in Step 1 or do
I also enter IV1 and IV2 as covariates?

I just really need someone to walk me through these steps, but after that
I'm golden.

Thank you!

tbf

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[Salbod]

Bruce is there any way to get the Babyak's article without paying for it? --Steve

-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Bruce Weaver
Sent: Wednesday, May 18, 2011 5:08 PM
To: [hidden email]
Subject: Re: Really Easy Question about Mediation (HELP!!)

Gene M. has responded with some comments.  Here are some more from a slightly different perspective.  My training was in psychology, but that was in the days before mediation became the rage.  By that time, I was working in the area of health-related research & biostatistics.  One thing I find interesting is that the definitions of confounding and mediation are nearly identical, the difference being that the mediator is on a presumed causal chain between X and Y.  For some good discussion of this, see Mike Babyak's short article available here:

   http://ebmh.bmj.com/content/12/3/68.full

Given this similarity between confounding and mediation, I find it very interesting that the standard advice in the world of biostatistics is (or at least was a few years ago) that one should NOT perform a statistical test for confounding, whereas the mediation folks are going whole hog down the road of testing (e.g., developing standard errors).

Here's an example of the biostats view from Bob Wolfe's (from University of
Michigan) "classic lecture" series.  (Unfortunately, these lectures no longer seem to be available online.  Fortunately, I saved copies of some of
them.)

--- start of excerpt ---

C. Testing for confounding (don't do it):

    When attempting to document the effect of a specific risk
    factor on an outcome, confounding factors should be
    controlled for even if they are not significantly related to
    the outcome in the analysis.  In this case, the objective of
    the analysis is to estimate the strength of the relationship
    between the risk factor and the outcome not explainable by
    confounding factors, and the strength of the relationship
    between the confounding factors and the outcome is not as
    important.

    When searching for a parsimonious model for predicting the
    outcome, it is useful to exclude unimportant factors from
    the model.  Some data analysts use statistical significance
    as a criterion for importance.  This approach may miss confounders.

--- end of excerpt ---

Finally, I should mention that the next section in that same lecture has the title, "D. Confounders and intervening variables:  Often a quandary."
Intervening variable is another name for mediator, of course.

HTH.



toph_bei_fong wrote:

>
> Hi everyone,
>
> I am very, very new to mediation and could use some help. I know the
> steps to Baron and Kenny's method but am unsure of how to actually do
> them in SPSS.
>
> I have two categorical IVs (which I have dummy coded), the interaction
> term of these categorical variables and three continuous mediators.
>
> So, here are my questions:
>
> 1) If I'm wanting to look at mediation of one of my IV effects, would
> I enter that variable in by itself in Step 1 as a predictor and leave
> the other IV out? Or can I assess both at the same time by entering
> both as my IVs? Or should I just enter the full model (IV1, IV2, IV1*IV2)?
>
> 2) If I'm wanting to look at mediation at it pertains to my
> interaction term, do it enter the interaction term as the sole
> predictor in Step 1 or do I also enter IV1 and IV2 as covariates?
>
> I just really need someone to walk me through these steps, but after
> that I'm golden.
>
> Thank you!
>
> tbf
>

-----
--
Bruce Weaver
[hidden email]
http://sites.google.com/a/lakeheadu.ca/bweaver/

"When all else fails, RTFM."

NOTE: My Hotmail account is not monitored regularly.
To send me an e-mail, please use the address shown above.

--
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[Bruce Weaver]

Hi Steve.  Drop me a line off-list (to the @lakeheadu.ca address in my sig file), and I'll send you a copy.

Cheers,
Bruce

Salbod, Mr. Stephen wrote

Bruce is there any way to get the Babyak's article without paying for it? --Steve

-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Bruce Weaver
Sent: Wednesday, May 18, 2011 5:08 PM
To: [hidden email]
Subject: Re: Really Easy Question about Mediation (HELP!!)

Gene M. has responded with some comments.  Here are some more from a slightly different perspective.  My training was in psychology, but that was in the days before mediation became the rage.  By that time, I was working in the area of health-related research & biostatistics.  One thing I find interesting is that the definitions of confounding and mediation are nearly identical, the difference being that the mediator is on a presumed causal chain between X and Y.  For some good discussion of this, see Mike Babyak's short article available here:

   http://ebmh.bmj.com/content/12/3/68.full

Given this similarity between confounding and mediation, I find it very interesting that the standard advice in the world of biostatistics is (or at least was a few years ago) that one should NOT perform a statistical test for confounding, whereas the mediation folks are going whole hog down the road of testing (e.g., developing standard errors).

Here's an example of the biostats view from Bob Wolfe's (from University of
Michigan) "classic lecture" series.  (Unfortunately, these lectures no longer seem to be available online.  Fortunately, I saved copies of some of
them.)

--- start of excerpt ---

C. Testing for confounding (don't do it):

    When attempting to document the effect of a specific risk
    factor on an outcome, confounding factors should be
    controlled for even if they are not significantly related to
    the outcome in the analysis.  In this case, the objective of
    the analysis is to estimate the strength of the relationship
    between the risk factor and the outcome not explainable by
    confounding factors, and the strength of the relationship
    between the confounding factors and the outcome is not as
    important.

    When searching for a parsimonious model for predicting the
    outcome, it is useful to exclude unimportant factors from
    the model.  Some data analysts use statistical significance
    as a criterion for importance.  This approach may miss confounders.

--- end of excerpt ---

Finally, I should mention that the next section in that same lecture has the title, "D. Confounders and intervening variables:  Often a quandary."
Intervening variable is another name for mediator, of course.

HTH.



toph_bei_fong wrote:
>
> Hi everyone,
>
> I am very, very new to mediation and could use some help. I know the
> steps to Baron and Kenny's method but am unsure of how to actually do
> them in SPSS.
>
> I have two categorical IVs (which I have dummy coded), the interaction
> term of these categorical variables and three continuous mediators.
>
> So, here are my questions:
>
> 1) If I'm wanting to look at mediation of one of my IV effects, would
> I enter that variable in by itself in Step 1 as a predictor and leave
> the other IV out? Or can I assess both at the same time by entering
> both as my IVs? Or should I just enter the full model (IV1, IV2, IV1*IV2)?
>
> 2) If I'm wanting to look at mediation at it pertains to my
> interaction term, do it enter the interaction term as the sole
> predictor in Step 1 or do I also enter IV1 and IV2 as covariates?
>
> I just really need someone to walk me through these steps, but after
> that I'm golden.
>
> Thank you!
>
> tbf
>


-----
--
Bruce Weaver
[hidden email]
http://sites.google.com/a/lakeheadu.ca/bweaver/

"When all else fails, RTFM."

NOTE: My Hotmail account is not monitored regularly.
To send me an e-mail, please use the address shown above.

--
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[Ryan]

For those interested, this is a nice tutorial on testing for indirect
effects using the graphical interface in AMOS.

http://amosdevelopment.com/video/indirect/flash/indirect.html

Ryan

On Wed, May 18, 2011 at 2:12 AM, toph_bei_fong <[hidden email]> wrote:

> Hi everyone,
>
> I am very, very new to mediation and could use some help. I know the steps
> to Baron and Kenny's method but am unsure of how to actually do them in
> SPSS.
>
> I have two categorical IVs (which I have dummy coded), the interaction term
> of these categorical variables and three continuous mediators.
>
> So, here are my questions:
>
> 1) If I'm wanting to look at mediation of one of my IV effects, would I
> enter that variable in by itself in Step 1 as a predictor and leave the
> other IV out? Or can I assess both at the same time by entering both as my
> IVs? Or should I just enter the full model (IV1, IV2, IV1*IV2)?
>
> 2) If I'm wanting to look at mediation at it pertains to my interaction
> term, do it enter the interaction term as the sole predictor in Step 1 or do
> I also enter IV1 and IV2 as covariates?
>
> I just really need someone to walk me through these steps, but after that
> I'm golden.
>
> Thank you!
>
> tbf
>
> --
> View this message in context: http://spssx-discussion.1045642.n5.nabble.com/Really-Easy-Question-about-Mediation-HELP-tp4405692p4405692.html
> Sent from the SPSSX Discussion mailing list archive at Nabble.com.
>
> =====================
> To manage your subscription to SPSSX-L, send a message to
> [hidden email] (not to SPSSX-L), with no body text except the
> command. To leave the list, send the command
> SIGNOFF SPSSX-L
> For a list of commands to manage subscriptions, send the command
> INFO REFCARD
>

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[Salbod]

Ryan: Thank you for the video link on Mediation.  --Steve

-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of R B
Sent: Wednesday, May 18, 2011 9:12 PM
To: [hidden email]
Subject: Re: Really Easy Question about Mediation (HELP!!)

For those interested, this is a nice tutorial on testing for indirect effects using the graphical interface in AMOS.

http://amosdevelopment.com/video/indirect/flash/indirect.html

Ryan

On Wed, May 18, 2011 at 2:12 AM, toph_bei_fong <[hidden email]> wrote:

> Hi everyone,
>
> I am very, very new to mediation and could use some help. I know the
> steps to Baron and Kenny's method but am unsure of how to actually do
> them in SPSS.
>
> I have two categorical IVs (which I have dummy coded), the interaction
> term of these categorical variables and three continuous mediators.
>
> So, here are my questions:
>
> 1) If I'm wanting to look at mediation of one of my IV effects, would
> I enter that variable in by itself in Step 1 as a predictor and leave
> the other IV out? Or can I assess both at the same time by entering
> both as my IVs? Or should I just enter the full model (IV1, IV2, IV1*IV2)?
>
> 2) If I'm wanting to look at mediation at it pertains to my
> interaction term, do it enter the interaction term as the sole
> predictor in Step 1 or do I also enter IV1 and IV2 as covariates?
>
> I just really need someone to walk me through these steps, but after
> that I'm golden.
>
> Thank you!
>
> tbf
>
> --
> View this message in context:
> http://spssx-discussion.1045642.n5.nabble.com/Really-Easy-Question-abo
> ut-Mediation-HELP-tp4405692p4405692.html
> Sent from the SPSSX Discussion mailing list archive at Nabble.com.
>
> =====================
> To manage your subscription to SPSSX-L, send a message to
> [hidden email] (not to SPSSX-L), with no body text except
> the command. To leave the list, send the command SIGNOFF SPSSX-L For a
> list of commands to manage subscriptions, send the command INFO
> REFCARD
>

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[John F Hall]

There's a chapter on Causal Explanations in Marsh and Elliott, Exploring Data, followed by a bit on crosstabs with 3 variables (using SPSS 13).  I know the late Cathie Marsh discussed much of the logic of this with Jim Davis (see his Elementary Survey Analysis) and Joe Spaeth when they taught on SST=RC Summer Schools, and there is a fair bit in Rosenberg, The Logic of Survey Analysis.  Graham Kalton always swore by elaboration and there's a bit in Moser and Kalton as well (but no SPSS as it wasn't invented then).  We used the term "intervening variable" T in various relations with X and Y.

 

 

John F Hall

 

[hidden email]  

www.surveyresearch.weebly.com

 

 

 

 

 

 

-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of R B
Sent: 19 May 2011 03:12
To: [hidden email]
Subject: Re: Really Easy Question about Mediation (HELP!!)

 

For those interested, this is a nice tutorial on testing for indirect

effects using the graphical interface in AMOS.

 

http://amosdevelopment.com/video/indirect/flash/indirect.html

 

Ryan

 

On Wed, May 18, 2011 at 2:12 AM, toph_bei_fong <[hidden email]> wrote:

> Hi everyone,

> 

> I am very, very new to mediation and could use some help. I know the steps

> to Baron and Kenny's method but am unsure of how to actually do them in

> SPSS.

> 

> I have two categorical IVs (which I have dummy coded), the interaction term

> of these categorical variables and three continuous mediators.

> 

> So, here are my questions:

> 

> 1) If I'm wanting to look at mediation of one of my IV effects, would I

> enter that variable in by itself in Step 1 as a predictor and leave the

> other IV out? Or can I assess both at the same time by entering both as my

> IVs? Or should I just enter the full model (IV1, IV2, IV1*IV2)?

> 

> 2) If I'm wanting to look at mediation at it pertains to my interaction

> term, do it enter the interaction term as the sole predictor in Step 1 or do

> I also enter IV1 and IV2 as covariates?

> 

> I just really need someone to walk me through these steps, but after that

> I'm golden.

> 

> Thank you!

> 

> tbf

> 

> --

> View this message in context: http://spssx-discussion.1045642.n5.nabble.com/Really-Easy-Question-about-Mediation-HELP-tp4405692p4405692.html

> Sent from the SPSSX Discussion mailing list archive at Nabble.com.

> 

> =====================

> To manage your subscription to SPSSX-L, send a message to

> [hidden email] (not to SPSSX-L), with no body text except the

> command. To leave the list, send the command

> SIGNOFF SPSSX-L

> For a list of commands to manage subscriptions, send the command

> INFO REFCARD

> 

 

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TBF et al.,

I wrote a quick & dirty primer on how to run mediation analyses in SPSS, but when I tried to send it to the listserv as an attachment, it got kicked back to me.  Here's the syntax that creates the coefficients necessary for most/all methods of mediation models.

 

In this case, the DV is DRUGUSEPOST.

The IV is GROUP.

The M is COPINGSKILLSw8.

 

The values of a, b, and c are taken from the standard regression equations, specifically the unstandardized beta weights and associated standard errors.

 

Here is example SPSS syntax for such a process:

Step I: 

 

REGRESSION

  /DESCRIPTIVES MEAN STDDEV CORR SIG N

  /MISSING LISTWISE

  /STATISTICS COEFF OUTS R ANOVA

  /CRITERIA=PIN(.05) POUT(.10)

  /NOORIGIN

  /DEPENDENT drugusepost

  /METHOD=ENTER group.

                   

Step II.

 

REGRESSION

  /DESCRIPTIVES MEAN STDDEV CORR SIG N

  /MISSING LISTWISE

  /STATISTICS COEFF OUTS R ANOVA

  /CRITERIA=PIN(.05) POUT(.10)

  /NOORIGIN

  /DEPENDENT  copingskillsw8

  /METHOD=ENTER group  .

 

Step III.

 

REGRESSION

  /DESCRIPTIVES MEAN STDDEV CORR SIG N

  /MISSING LISTWISE

  /STATISTICS COEFF OUTS R ANOVA

  /CRITERIA=PIN(.05) POUT(.10)

  /NOORIGIN

  /DEPENDENT drugusepost

Step I is used to obtain the value of c

  /METHOD=ENTER copingskillsw8 group.

 

And the statistical output:

 

Step I.

                                                                                Coefficients(a)

 

  

 

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta	B	Std. Error
1	(Constant)	32.895	2.762		11.909	.000
	Treatment Group	1.241	2.762	.066	.449	.655

Step II is used to obtain the value of a

a  Dependent Variable: drugusepost

 

Step II.

                                                                                Coefficients(a)

 

  

 

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta	B	Std. Error
1	(Constant)	4.226	.123		34.280	.000
	Treatment Group	.258	.123	.295	2.096	.042

a  Dependent Variable: copingskillsw8

Step III is used to obtain the value of b and c’

 

Step III.

                                                                                Coefficients(a)

 

  

 

 

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta	B	Std. Error
1	(Constant)	-8.920	12.909		-.691	.493
	Treatment Group	-1.316	2.623	-.070	-.502	.618
	copingskillsw8	9.894	2.996	.461	3.302	.002

a  Dependent Variable: drugusepost

 

HTH

 

-----Original Message-----
From: John F Hall <[hidden email]>
To: [hidden email]
Sent: Thu, May 19, 2011 1:49 pm
Subject: Re: Really Easy Question about Mediation (HELP!!)

There's a chapter on Causal Explanations in Marsh and Elliott, Exploring Data, followed by a bit on crosstabs with 3 variables (using SPSS 13).  I know the late Cathie Marsh discussed much of the logic of this with Jim Davis (see his Elementary Survey Analysis) and Joe Spaeth when they taught on SST=RC Summer Schools, and there is a fair bit in Rosenberg, The Logic of Survey Analysis.  Graham Kalton always swore by elaboration and there's a bit in Moser and Kalton as well (but no SPSS as it wasn't invented then).  We used the term "intervening variable" T in various relations with X and Y.

 

 

John F Hall

 

[hidden email]  

www.surveyresearch.weebly.com

 

 

 

 

 

 

-----Original Message-----
From: SPSSX(r) Discussion [[hidden email]] On Behalf Of R B
Sent: 19 May 2011 03:12
To: [hidden email]
Subject: Re: Really Easy Question about Mediation (HELP!!)

 

For those interested, this is a nice tutorial on testing for indirect

effects using the graphical interface in AMOS.

 

http://amosdevelopment.com/video/indirect/flash/indirect.html

 

Ryan

 

On Wed, May 18, 2011 at 2:12 AM, toph_bei_fong <[hidden email]> wrote:

> Hi everyone,

> 

> I am very, very new to mediation and could use some help. I know the steps

> to Baron and Kenny's method but am unsure of how to actually do them in

> SPSS.

> 

> I have two categorical IVs (which I have dummy coded), the interaction term

> of these categorical variables and three continuous mediators.

> 

> So, here are my questions:

> 

> 1) If I'm wanting to look at mediation of one of my IV effects, would I

> enter that variable in by itself in Step 1 as a predictor and leave the

> other IV out? Or can I assess both at the same time by entering both as my

> IVs? Or should I just enter the full model (IV1, IV2, IV1*IV2)?

> 

> 2) If I'm wanting to look at mediation at it pertains to my interaction

> term, do it enter the interaction term as the sole predictor in Step 1 or do

> I also enter IV1 and IV2 as covariates?

> 

> I just really need someone to walk me through these steps, but after that

> I'm golden.

> 

> Thank you!

> 

> tbf

> 

> --

> View this message in context: http://spssx-discussion.1045642.n5.nabble.com/Really-Easy-Question-about-Mediation-HELP-tp4405692p4405692.html

> Sent from the SPSSX Discussion mailing list archive at Nabble.com.

> 

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