re:[tips] Effects, Affects, Independent and Depentent Variables

[Mike Palij]

A few points:

(1)  I think that there is a conceptual confusion of using the
terms "to effect" as a substitute for "related to", the latter
can be either causal or correlational or both.

(2) One could argue that the fundamental goal of science
is to identify and define causal relationships among
variables (both empirical and latent) -- Humanistic psychologists
and others in that camp might disagree (at least they did
back in the 1960s and 1970s).  Causal relationships
can be observed in two general situations:

(a) Systematic Observational Research:  if we accept
that causal relationships actually exist in the physical world
(and not just in our minds), then systematic observation
can help to locate and identify such causal relationships.
Astronomy is the classical example of how the relationships
in systematic observations can be mathematically modeled
and these model imply explanations and theories.  Similar
situations exist in economics, political science, sociology,
and other areas where general mathematical modeling
and structural equation modeling (SEM) have been used.
Astronomy, however, is boosted by developments in physics,
making it more rigorous and provide guidance on how
choose among competing models of the same phenomenon.
The more "squishy" social and biomedical sciences have
additional difficulties due to problems of construct validity,
measurement model issues, and, the problem of "complexity"
because these phenomena are observed in what has
once been called "open systems", that is, an infinite number
of variable are present in the phenomena being studied but
only a few of them are really relevant.  Deciding which variables
are relevant is an ongoing process between collecting observations,
model testing, and repeat ad infinitum or one has "good enough"
model/theory.

In the case of astronomy, would anyone really quibble if
one asked "What is the effect of large planetary mass on
other nearby planets and objects?"  I grant that one might
have to understand how gravitational forces operate in order
to appreciate the question.

(b) Experimental designs, when conceived and implemented
correctly, represent "closed systems" where variables that might
be  involved in a cause-effect relationship are clearly defined
allow the causal relationship to be detected and measured
while controlling for all other variables that may or may not
be involved in the causal relationship (i.e., situations where
moderation and/or mediation may be operating).  This is
the classic situation of "independent variables" which are
selected and manipulated by the research (though participant
attributes like gender, age, degree of illness, skill, knowledge,
etc., might also be used as "independent variables" though
the mechanisms that are involved may be unclear and it would
be better to refer to these as "quasi-independent variables")
and "dependent variable(s)" which are suppose to manifest
the "effect" of the independent variable -- this is best represented
by the equation "dependent variable" = f("independent variable").

The function f(x) can take a variety of different forms though
there is the old saying that is relevant "causation implies correlation"
but correlation does not necessarily refer to the Pearson r, rather,
it refers to the general mathematical relationship relating the
independent variables to the dependent variable(s).  Note that
in (b) whether or not one is actually detecting a causal relationship
or merely a correlational relationship depends upon the quality
of the research design being used, how well the procedures
were executed, and other factors.  The recent problems with
replications highlight these points.

Experimental designs have been developed to establish causal
relationship and it may be proper to say the "Effect of X on Y"
though this may not apply to quasi-independent variables or
when relevant 3rd variables have not be included (in SEM
terms we have "model misspecification" regardless of whether
we are referring to an ANOVA structural model or a regression
model or an SEM model that uses both empirical and latent
variables to represent that cause-effect relationships.
NOTE:  In SEM modeling, especially of open systems, a
variable in one part of the model might be a "dependent
variable' but may also be an "independent variable" in relationship
to other variables.

So, perhaps one should ask for the mathematical model that
the "effect" embodies to better understand what it means,
as well as the degree that 3rd variables have been controlled.

More below.

Thu, 20 Jul 2017 16:53:19 -0700, Karl Louis Wuensch wrote:
 When using the word "effect," as in "effect-size," I 
sometimes

warn my students that I am using it in the "soft" sense (not causal).


I think that one should probably make clear how "effect sizes"
for causal relationships differ from "effect sizes" in correlational
relationships.  The former directly represents how changes in
the causal variable produce changes 

Re: [tips] Grad level cognition text

[Rick Stevens]

Thanks for the ideas.  Ours is a MS-only program and for almost all of them
this will be their only grad-level cognitive course, some their first
introduction to the topic.  I'll check out your #1 suggestions.  I'm sure
I'll want a book for them. The article repositories could be handy.  My
first course only had readings.

RS

Rick Stevens
School of Behavioral and Social Sciences
University of Louisiana at Monroe


On Fri, Jul 21, 2017 at 12:58 PM, Mike Palij  wrote:

> On Wed, 19 Jul 2017 07:50:44 -0700, Rick Stevens wrote:
>
>> Anyone have suggestions for a graduate level cognition textbook?
>>
>
> I think one would first have to answer a couple of questions:
>
> (1)  Is the textbook being in a course that is open to master's
> students and graduate students in non-experimental areas
> (e.g., clinical, developmental, social, etc.)?
>
> (2) Or is the textbook being used in a course for Ph.D. experimental
> psychology students?
>
> If (1) is the case, then one of the cognitive textbooks used in
> junior/senior level courses (e.g., John Anderson's text, maybe
> the textbook by Solso which is being written mainly by co-authors,
> etc.). might do the trick.  I would, however, supplement the text
> with relevant article from sources like (Sigma Xi's) American
> Scientist, Science mag, American Psychologist (I still like
> Robyn Dawes' "The Robust Beauty of Improper Linear Models"
> which lays out the classic argument between those who think
> they can rationally decide what the best choice is from sources
> like interview or what might be called "qualitative" data sources
> versus explicit decision rules with quantitative variables that
> reflect the most important features to consider -- multiple
> regression equations used, say, to predict Grade Point Average
> at the end of first year in college or grad school typically outperform
> human judgments based on interviews, etc., but in this article
> Dawes shows that arbitrary weights chosen to reflect the importance
> and impact of the variable [i.e., magnitude like using 1, 2, 3,..to
> reflect importance and positive/negative sign to reflect the nature
> of the "effect")., and other articles and chapters written for a
> general scientifically oriented audience.
>
> If (2) is the case, I don't know if there really is a single text
> that does the job though Michael Eysenck & Mark Keane's
> "Cognitive Psychology: A Student's Handbook" might be
> one source to consider but supplemented with articles and
> chapters from the Annual Reviews (of Psychology, Neuroscience,
> Sociology, Medicine, etc.), the series "Psychology of Learning
> and Motivation", and other sources (e.g., comparing and contrasting
> traditional rule and symbol cognitive architectures [Atkinson & Shiffrin,
> Newell's SOAR, etc.) versus neural network/connectionist cognitive
> architectures [the Rumelhart crew, and others who have proposed
> alternatives to traditional models] ).  There is the question of
> how and to what degrees one wants to cover computational models
> of cognition and neuroscience models of cognition -- which may
> limit one to materials published in the last 5-10 years plus some
> classic/historically significant papers.
>
> I hope that the above helps but I understand if one finds what
> I say somewhat vague.  The graduate courses in cognition I
> took did not use a textbook (at Stony Brook Marcia Johnson
> used a list of readings; when I took grad courses at NYU
> Sperling, Glanzer, Braine, and Kaufman used original sources
> though Sperling provided very few sources and he expected
> one follow his lectures which were mostly incomprehensible ;-).
> When I started to teach the Master's level course in cognition
> at NYU I use an textbook like Solso or Matlin and supplemented
> them with "accessible" original sources (though signal detection
> theory  really required me to make my lectures as clear as
> possible).  Some of the master's students had not been psych
> majors or science majors, like English Lit majors, and I had to
> be remind myself that the material was not only novel to them but
> the perspective provided they brought to class could be very
> different from that presented in class (i.e., the scientific study
> of the mind).  Sadly, some psych majors were also in this boat.
>
> -Mike Palij
> New York University
> m...@nyu.edu
>
>
>
>
> ---
> You are currently subscribed to tips as: stevens.r...@gmail.com.
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Re: [tips] Effects, Affects, Independent and Depentent Variables.

[Joan Warmbold]

APS has challenged members and others to read "Degrees of Maybe: How We
Can All Make Better Predictions" on NPR and then to leave a comment.  This
challenge can be found at:

https://www.psychologicalscience.org/news/degrees-of-maybe-how-we-can-all-make-better-predictions.html

The story is at:

http://www.npr.org/2017/06/26/534120962/degrees-of-maybe-how-we-can-all-make-better-predictions

Our concern with being more precise in our use of language ties in with
our concern with general scientific literacy, does it not?  And this story
concerning the type of mindset that enables people to make better
predictions very relevant.  Enjoy I hope.

Joan
jwarm...@oakton.edu


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re: [tips] Grad level cognition text

[Mike Palij]

On Wed, 19 Jul 2017 07:50:44 -0700, Rick Stevens wrote:

Anyone have suggestions for a graduate level cognition textbook?


I think one would first have to answer a couple of questions:

(1)  Is the textbook being in a course that is open to master's
students and graduate students in non-experimental areas
(e.g., clinical, developmental, social, etc.)?

(2) Or is the textbook being used in a course for Ph.D. experimental
psychology students?

If (1) is the case, then one of the cognitive textbooks used in
junior/senior level courses (e.g., John Anderson's text, maybe
the textbook by Solso which is being written mainly by co-authors,
etc.). might do the trick.  I would, however, supplement the text
with relevant article from sources like (Sigma Xi's) American
Scientist, Science mag, American Psychologist (I still like
Robyn Dawes' "The Robust Beauty of Improper Linear Models"
which lays out the classic argument between those who think
they can rationally decide what the best choice is from sources
like interview or what might be called "qualitative" data sources
versus explicit decision rules with quantitative variables that
reflect the most important features to consider -- multiple
regression equations used, say, to predict Grade Point Average
at the end of first year in college or grad school typically outperform
human judgments based on interviews, etc., but in this article
Dawes shows that arbitrary weights chosen to reflect the importance
and impact of the variable [i.e., magnitude like using 1, 2, 3,..to
reflect importance and positive/negative sign to reflect the nature
of the "effect")., and other articles and chapters written for a
general scientifically oriented audience.

If (2) is the case, I don't know if there really is a single text
that does the job though Michael Eysenck & Mark Keane's
"Cognitive Psychology: A Student's Handbook" might be
one source to consider but supplemented with articles and
chapters from the Annual Reviews (of Psychology, Neuroscience,
Sociology, Medicine, etc.), the series "Psychology of Learning
and Motivation", and other sources (e.g., comparing and contrasting
traditional rule and symbol cognitive architectures [Atkinson & 
Shiffrin,

Newell's SOAR, etc.) versus neural network/connectionist cognitive
architectures [the Rumelhart crew, and others who have proposed
alternatives to traditional models] ).  There is the question of
how and to what degrees one wants to cover computational models
of cognition and neuroscience models of cognition -- which may
limit one to materials published in the last 5-10 years plus some
classic/historically significant papers.

I hope that the above helps but I understand if one finds what
I say somewhat vague.  The graduate courses in cognition I
took did not use a textbook (at Stony Brook Marcia Johnson
used a list of readings; when I took grad courses at NYU
Sperling, Glanzer, Braine, and Kaufman used original sources
though Sperling provided very few sources and he expected
one follow his lectures which were mostly incomprehensible ;-).
When I started to teach the Master's level course in cognition
at NYU I use an textbook like Solso or Matlin and supplemented
them with "accessible" original sources (though signal detection
theory  really required me to make my lectures as clear as
possible).  Some of the master's students had not been psych
majors or science majors, like English Lit majors, and I had to
be remind myself that the material was not only novel to them but
the perspective provided they brought to class could be very
different from that presented in class (i.e., the scientific study
of the mind).  Sadly, some psych majors were also in this boat.

-Mike Palij
New York University
m...@nyu.edu




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Re: [tips] Effects, Affects, Independent and Depentent Variables.

[Michael Scoles]

I'll tell ya, I don't see it happening.


On Fri, Jul 21, 2017 at 9:23 AM, Christopher Green  wrote:

>
> Perhaps (he said wearily), we should end the long-futile effort to enforce
> conceptual distinctions by legislating the use of mere words and, instead,
> educate people rigorously enough that they are capable and, indeed,
> desirous, of respecting and expressing important conceptual distinctions in
> the flexible vocabulary of the true sophisticate.
>
> Chris
> …..
> Christopher D Green
> Department of Psychology
> York University
> Toronto, ON M3J 1P3
> Canada
> 43.773895°, -79.503670°
>
> chri...@yorku.ca
> http://www.yorku.ca/christo
> orcid.org/-0002-6027-6709
> ...
>
> On Jul 20, 2017, at 8:42 PM, Stuart McKelvie  wrote:
>
>
>
>
>
>
>
> I agree with Karl.
>
>
>
> Here are some incomplete thoughts.
>
>
>
> When teaching methods, I would devote time to nomenclature. I suggested
> that the terms “independent variable” and “dependent variable” be reserved
> for experimental designs.
>
>
>
> How, then, do we refer to variables in non-experimental designs? If it is
> correlational, I suggested “predictor variable” and “predicted variable”
> (if the argument was framed in that manner). In some cases, the predictor
> variable might be categorical (perhaps a subject variable) and in others
> it might be continuous. If only a relationship was being examined, without
> any thought of predicting one from the other, we might say that each one is
> simply an associated variable or a correlated variable.
>
>
>
> Trickier is the situation where one variable is manipulated, but
> randomization has not occurred, as in a quasi-experimental design. Perhaps
> the manipulated variable could still be termed “independent”, but it would
> be inappropriate to call the other variable “dependent”. I suggested that
> “predicted variable” is a safer bet.
>
>
>
>
>
>
>
> 
> ___
>
>"*F**loreat* *L**abore*"
>
>
>
>
>
> "*Recti cultus pectora roborant*"
>
>
>
> *Stuart J. McKelvie, Ph.D.*, *Phone*: 819 822 9600 x 2402
> <(819)%20822-9600>
>
> Department of Psychology, *Fax*: 819 822 9661 <(819)%20822-9661>
>
> Bishop's University,
>
> 2600 rue College,
>
> Sherbrooke,
>
> Québec J1M 1Z7,
>
> Canada.
>
>
>
> E-mail: stuart.mckel...@ubishops.ca (or smcke...@ubishops.ca)
>
>
>
> Bishop's University Psychology Department Web Page:
>
> http://www.ubishops.ca/ccc/div/soc/psy
>
>
>
>  *F**loreat* *L**abore*"
>
>
>
>  
>
>
>
> 
>
> 
> ___
>
>
>
>
>
>
>
>
>
> *From:* Wuensch, Karl Louis [mailto:wuens...@ecu.edu ]
> *Sent:* July-20-17 7:52 PM
> *To:* Teaching in the Psychological Sciences (TIPS)
> *Subject:* [tips] Effects, Affects, Independent and Depentent Variables.
>
>
>
>
>
>   When using the word “effect,” as in “effect-size,” I sometimes
> warn my students that I am using it in the “soft” sense (not causal).  A
> related concern of mine is the use of the terms “independent variable” and
> “dependent variable” in research that is not experimental – that is, when
> no variable is manipulated.  There is a tendency to use “independent
> variable” whenever the variable is categorical and “dependent variable”
> when it is continuous.  Once I helped a previous student with his
> dissertation.  No variables were manipulated, but several were
> categorical.  I help him dummy code the categorical variables and use them
> in a multiple correlation analysis, with continuous covariates, to predict
> the focal continuous outcome variable.  His dissertation advisor told him
> no, do an ANOVA instead, because then we have independent and dependent
> variables and thus can make causal inferences.
>
>
>
> Cheers,
>
>  
>
> *From:* Annette Taylor [mailto:tay...@sandiego.edu ]
> *Sent:* Wednesday, July 19, 2017 10:08 AM
> *To:* Teaching in the Psychological Sciences (TIPS)
> *Subject:* [tips] Opinions needed
>
>
>
>
>
> Back in the good old dayswhen I was in graduate school...I
> specifically being told by my advisor that "effect" could not be used in a
> title unless it was a clearly causal effect. So this does err on the side
> of emphasizing causal. Nevertheless, I also heard somewhere from someone
> (???) that the reason that the APA guidelines reduced the maximum number of
> words for a title in APA style was to focus on the actual variables in the
> title and eliminate any suggestion of "effect" in the title to reduce the
> abuse of the term "effect"
>
>
>
> Now, it makes for splashier headlines when your study gets published and
> people can talk about something BY INFERENCE "causing" something else
> simply because 

Re: [tips] Effects, Affects, Independent and Depentent Variables.

[Christopher Green]

Perhaps (he said wearily), we should end the long-futile effort to enforce 
conceptual distinctions by legislating the use of mere words and, instead, 
educate people rigorously enough that they are capable and, indeed, desirous, 
of respecting and expressing important conceptual distinctions in the flexible 
vocabulary of the true sophisticate. 

Chris
…..
Christopher D Green
Department of Psychology
York University
Toronto, ON M3J 1P3
Canada
43.773895°, -79.503670°

chri...@yorku.ca
http://www.yorku.ca/christo
orcid.org/-0002-6027-6709
...

On Jul 20, 2017, at 8:42 PM, Stuart McKelvie  wrote:

> 
> 
> 
> 
>  
> I agree with Karl.
>  
> Here are some incomplete thoughts.
>  
> When teaching methods, I would devote time to nomenclature. I suggested that 
> the terms “independent variable” and “dependent variable” be reserved for 
> experimental designs.
>  
> How, then, do we refer to variables in non-experimental designs? If it is 
> correlational, I suggested “predictor variable” and “predicted variable” (if 
> the argument was framed in that manner). In some cases, the predictor 
> variable might be categorical (perhaps a subject variable) and in others  it 
> might be continuous. If only a relationship was being examined, without any 
> thought of predicting one from the other, we might say that each one is 
> simply an associated variable or a correlated variable.
>  
> Trickier is the situation where one variable is manipulated, but 
> randomization has not occurred, as in a quasi-experimental design. Perhaps 
> the manipulated variable could still be termed “independent”, but it would be 
> inappropriate to call the other variable “dependent”. I suggested that 
> “predicted variable” is a safer bet.
>  
>  
>  
> ___
>"Floreat Labore"
>  
>   
> "Recti cultus pectora roborant"
>  
> Stuart J. McKelvie, Ph.D., Phone: 819 822 9600 x 2402
> Department of Psychology, Fax: 819 822 9661
> Bishop's University,
> 2600 rue College,
> Sherbrooke,
> Québec J1M 1Z7,
> Canada.
>  
> E-mail: stuart.mckel...@ubishops.ca (or smcke...@ubishops.ca)
>  
> Bishop's University Psychology Department Web Page:
> http://www.ubishops.ca/ccc/div/soc/psy   
>  
>  Floreat Labore"
>  
>  
>  
> 
> ___
>  
>  
>  
>  
> From: Wuensch, Karl Louis [mailto:wuens...@ecu.edu] 
> Sent: July-20-17 7:52 PM
> To: Teaching in the Psychological Sciences (TIPS)
> Subject: [tips] Effects, Affects, Independent and Depentent Variables.
>  
>  
> 
>   When using the word “effect,” as in “effect-size,” I sometimes warn 
> my students that I am using it in the “soft” sense (not causal).  A related 
> concern of mine is the use  of the terms “independent variable” and 
> “dependent variable” in research that is not experimental – that is, when no 
> variable is manipulated.  There is a tendency to use “independent variable” 
> whenever the variable is categorical and “dependent variable” when it is 
> continuous.  Once I helped a previous student with his dissertation.  No 
> variables were manipulated, but several were categorical.  I help him dummy 
> code the categorical variables and use them in a multiple correlation 
> analysis, with continuous covariates, to predict the focal continuous outcome 
> variable.  His dissertation advisor told him no, do an ANOVA instead, because 
> then we have independent and dependent variables and thus can make causal 
> inferences.
>  
> Cheers,
> 
> From: Annette Taylor [mailto:tay...@sandiego.edu] 
> Sent: Wednesday, July 19, 2017 10:08 AM
> To: Teaching in the Psychological Sciences (TIPS)
> Subject: [tips] Opinions needed
>  
>  
> 
> Back in the good old dayswhen I was in graduate school...I specifically 
> being told by my advisor that "effect" could not be used in a title unless it 
> was a clearly causal effect. So this does err on the side of emphasizing 
> causal. Nevertheless, I also heard somewhere from someone (???) that the 
> reason that the APA guidelines reduced the maximum number of words for a 
> title in APA style was to focus on the actual variables in the title and 
> eliminate any suggestion of "effect" in the title to reduce the abuse of the 
> term "effect"
>  
> Now, it makes for splashier headlines when your study gets published and 
> people can talk about something BY INFERENCE "causing" something else simply 
> because it is systematically linked with it. 
>  
> Finally, on a similar topic, I woke up this morning to a news story about 
> "risk factors" for Alzheimer's and my immediate thought was, how are these 
> things "risk factors?" Specifically it mentioned hearing loss and sleep 
>