Date: Wed, 15 Jun 2011 17:16:25 -0400
Reply-To: Gene Maguin <emaguin@buffalo.edu>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Gene Maguin <emaguin@buffalo.edu>
Subject: Re: help me
In-Reply-To: <SNT106-W63A3F9F5257E1001E3A48CB46B0@phx.gbl>
Content-Type: multipart/alternative;
Maga,
Why are you using GEE? What is there about your analysis or dataset that
requires you to use GEE?
If you really have to use GEE, then the little program i mentioned won't
work and i don't know what type of software would be required to compute
power.
Gene Maguin
_____
From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of
MARGOT mh
Sent: Wednesday, June 15, 2011 5:01 PM
To: SPSSX-L@LISTSERV.UGA.EDU
Subject: Re: help me
Dear Gene and Evan,
Thank very much for your help me.
I got a model (GEE) with 5 independent variables (2 and 3 were categories
were continuous covariates), these are all significant. Not consider
covariates did not influence my model. As this analysis is an analysis of a
secondary database, I have requested that I submit the statistical power. My
English is not very good, I hope I could make myself understood.
My understanding is that the sample is large gives a high statistical power,
so I do not understand is referred to the effect size.
Thanks in advance.
Maga
> Date: Wed, 15 Jun 2011 11:45:37 -0500
> From: EHarrington@thechicagoschool.edu
> Subject: Re: help me
> To: SPSSX-L@LISTSERV.UGA.EDU
>
> --_000_5F28CD1102E6274BA7BE4796B8EA90F50A46047431TCSTCSESORG_
> Content-Type: text/plain; charset="iso-8859-1"
> Content-Transfer-Encoding: quoted-printable
>
> I might add to Gene's comments that large sample sizes yield high power
(de=
> pending on the effect size in question). Assuming that the real population
=
> effect size values of your predictors are moderate in magnitude (or
larger)=
> then you should have high power with that sample size.
>
> Your question seems to be closer in meaning to a computation of the
confide=
> nce intervals around your estimates. Large samples yield narrow confidence
=
> intervals, which one could think as having greater precision in the
estimat=
> e of the where the population parameters are. Again, this does not answer
t=
> he "validity" question, for the same reasons Gene outlined.
>
>
> Evan Harrington, Ph.D.
> Department of Forensic Psychology
> The Chicago School of Professional Psychology
> 325 N. Wells Street
> Chicago, IL 60654
> ________________________________
> From: SPSSX(r) Discussion [SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of Gene
Magu=
> in [emaguin@buffalo.edu]
> Sent: Wednesday, June 15, 2011 9:22 AM
> To: SPSSX-L@LISTSERV.UGA.EDU
> Subject: Re: help me
>
> Maga,
>
> It sounds like you did a logistic regression with 5 predictors
(independent=
> variables) using data from a sample with an N of 600. You now want to
comp=
> ute power to show that your results are valid. I want to make two
comments.=
> One comment is about the power computation specifically. First of all,
you=
> can not do what you want using spss. You have to find something else. Do
a=
> search on 'statistical power logistic regression' or a set of search
terms=
> like that. One link is to a program called G*Power 3. I've never used
this=
> program, which seems to be free, but i think it could be a good option
for=
> you. The site is:
http://www.psycho.uni-duesseldorf.de/abteilungen/aap/gpo=
> wer3/
>
> That may get you through the power computation question itself. My second
c=
> omment is about this statement "As I can estimate the statistical power to
=
> conclude that my results are valid." I'm guessing that English is not your
=
> first language so there may be word choice issues. A high power number is
n=
> ot going to establish 'validity'. A high power number will show the degree
=
> of confidence that you can have
> that you would have found a relationship of the specified size it it were
r=
> eally present. 'Validity' depends on the correctness of your experimental
d=
> esign and statistical analysis logic.
>
> Gene Maguin
>
>
>
> ________________________________
> From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of
MA=
> RGOT mh
> Sent: Tuesday, June 14, 2011 4:41 PM
> To: SPSSX-L@LISTSERV.UGA.EDU
> Subject: help me
>
> Dear all,
>
> I have a database with 600 subjects who carried out, a secondary
statistica=
> l analysis with logistic regression with 5 independent variables. As I can
=
> estimate the statistical power to conclude that my results are valid.
>
> Thank you very much for your answers
>
> Maga
>
> --_000_5F28CD1102E6274BA7BE4796B8EA90F50A46047431TCSTCSESORG_
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> Content-Transfer-Encoding: quoted-printable
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charset=3Diso-8859-=
> 1">
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> </head>
> <body class=3D"hmmessage" ocsi=3D"x">
> <div dir=3D"ltr"><font face=3D"Arial" color=3D"#000000" size=3D"2">I might
=
> add to Gene's comments that large sample sizes yield high power (depending
=
> on the effect size in question). Assuming that the real population effect
s=
> ize values of your predictors are moderate
> in magnitude (or larger) then you should have high power with that sample
=
> size.</font></div>
> <div dir=3D"ltr"><font face=3D"arial"></font> </div>
> <div dir=3D"ltr"><font face=3D"arial">Your question seems to be closer in
m=
> eaning to a computation of the confidence intervals around your estimates.
=
> Large samples yield narrow confidence intervals, which one could think as
h=
> aving greater precision in the estimate
> of the where the population parameters are. Again, this does not answer
th=
> e "validity" question, for the same reasons Gene
outlined.</font>=
> </div>
> <div dir=3D"ltr"><font face=3D"arial"></font> </div>
> <div dir=3D"ltr"><font face=3D"arial"></font> </div>
> <div>
> <div><font face=3D"Arial" size=3D"2">Evan Harrington, Ph.D.</font></div>
> <div><font face=3D"arial" size=3D"2">Department of Forensic
Psychology</fon=
> t></div>
> <div><font face=3D"arial" size=3D"2">The Chicago School of Professional
Psy=
> chology</font></div>
> <div><font face=3D"arial" size=3D"2">325 N. Wells Street</font></div>
> <div><font face=3D"arial" size=3D"2">Chicago, IL 60654</font></div>
> </div>
> <div id=3D"divRpF171723" style=3D"DIRECTION: ltr">
> <hr tabindex=3D"-1">
> <font face=3D"Tahoma" size=3D"2"><b>From:</b> SPSSX(r) Discussion
[SPSSX-L@=
> LISTSERV.UGA.EDU] On Behalf Of Gene Maguin [emaguin@buffalo.edu]<br>
> <b>Sent:</b> Wednesday, June 15, 2011 9:22 AM<br>
> <b>To:</b> SPSSX-L@LISTSERV.UGA.EDU<br>
> <b>Subject:</b> Re: help me<br>
> </font><br>
> </div>
> <div></div>
> <div>
> <div dir=3D"ltr" align=3D"left"><font face=3D"Arial"
color=3D"#0000ff"><spa=
> n class=3D"314294013-15062011">Maga,
> </span></font></div>
> <div dir=3D"ltr" align=3D"left"><font face=3D"Arial"
color=3D"#0000ff"><spa=
> n class=3D"314294013-15062011"></span></font> </div>
> <div dir=3D"ltr" align=3D"left"><font face=3D"Arial"
color=3D"#0000ff"><spa=
> n class=3D"314294013-15062011">It sounds like you did a logistic
regression=
> with 5 predictors (independent variables) using data from a sample with
an=
> N of 600. You now want to compute power to
> show that your results are valid. I want to make two comments.
One&nb=
> sp;comment is about the power computation specifically. First of
=
> all, you can not do what you want using spss. You have to find something
el=
> se.
> </span></font><font face=3D"Arial" color=3D"#0000ff"><span
class=3D"3142940=
> 13-15062011">Do a search on 'statistical power logistic regression' or a
se=
> t of search terms like that. One link is to a program called G*Power 3.
> </span></font><font face=3D"Arial" color=3D"#0000ff"><span
class=3D"3142940=
> 13-15062011">I've never used this program, which seems to be
free, but=
> i think it could be a good option for you. The site is:
> </span></font><font face=3D"Arial" color=3D"#0000ff"><span
class=3D"3142940=
> 13-15062011"><a
href=3D"http://www.psycho.uni-duesseldorf.de/abteilungen/aa=
> p/gpower3/"
target=3D"_blank">http://www.psycho.uni-duesseldorf.de/abteilun=
> gen/aap/gpower3/</a>
> </span></font></div>
> <div dir=3D"ltr" align=3D"left"><font face=3D"Arial"
color=3D"#0000ff"><spa=
> n class=3D"314294013-15062011"></span></font> </div>
> <div dir=3D"ltr" align=3D"left"><font face=3D"Arial"
color=3D"#0000ff"><spa=
> n class=3D"314294013-15062011">That may get you through the power
computati=
> on question itself. My second comment is about this statement "<font
c=
> olor=3D"#000000">As I can estimate the statistical
> power to conclude that my results are valid." I'm guessing that
Engli=
> sh is not your first language so there may be word choice issues. A high
po=
> wer number is not going to establish 'validity'. A high power number will
s=
> how the degree of confidence that you
> can have</font></span></font></div>
> <div dir=3D"ltr" align=3D"left"><font face=3D"Arial"
color=3D"#0000ff"><spa=
> n class=3D"314294013-15062011"><font color=3D"#000000">that you would have
=
> found a relationship of the specified size it it were really present.
'Vali=
> dity' depends on the correctness of your experimental
> design and statistical analysis logic. </font></span></font></div>
> <div dir=3D"ltr" align=3D"left"><font face=3D"Arial"
color=3D"#0000ff"><spa=
> n class=3D"314294013-15062011"></span></font> </div>
> <div dir=3D"ltr" align=3D"left"><font face=3D"Arial"
color=3D"#0000ff"><spa=
> n class=3D"314294013-15062011">Gene Maguin</span></font></div>
> <div dir=3D"ltr" align=3D"left"><font face=3D"Arial"
color=3D"#0000ff"></fo=
> nt> </div>
> <div dir=3D"ltr" align=3D"left"><font face=3D"Arial"
color=3D"#0000ff"></fo=
> nt> </div>
> <font face=3D"Arial" color=3D"#0000ff"></font><br>
> <div class=3D"OutlookMessageHeader" lang=3D"en-us" dir=3D"ltr"
align=3D"lef=
> t">
> <hr tabindex=3D"-1">
> <font face=3D"Tahoma"><b>From:</b> SPSSX(r) Discussion
[mailto:SPSSX-L@LIST=
> SERV.UGA.EDU]
> <b>On Behalf Of </b>MARGOT mh<br>
> <b>Sent:</b> Tuesday, June 14, 2011 4:41 PM<br>
> <b>To:</b> SPSSX-L@LISTSERV.UGA.EDU<br>
> <b>Subject:</b> help me<br>
> </font><br>
> </div>
> <div></div>
> <font face=3D"Arial" size=3D"3">Dear all,</font><br>
> <font face=3D"Arial" size=3D"3"></font> <br>
> <p class=3D"MsoNormal" style=3D"MARGIN: 0cm 0cm 0pt; VERTICAL-ALIGN: top;
L=
> INE-HEIGHT: normal">
> <span lang=3D"EN" style=3D"COLOR: black; FONT-FAMILY:
'Arial','sans-serif'"=
> ><font size=3D"3">I have a database with 600 subjects who carried out, a
se=
> condary statistical analysis with logistic regression with 5 independent
va=
> riables. As I can estimate the statistical
> power to conclude that my results are valid.</font></span></p>
> <p class=3D"MsoNormal" style=3D"MARGIN: 0cm 0cm 0pt; VERTICAL-ALIGN: top;
L=
> INE-HEIGHT: normal">
> <span lang=3D"EN" style=3D"COLOR: black; FONT-FAMILY:
'Arial','sans-serif'"=
> ><br>
> <font size=3D"3">Thank you very much for your answers</font></span><span
la=
> ng=3D"EN-GB" style=3D"FONT-SIZE: 9pt; COLOR: #888888; FONT-FAMILY:
'Arial',=
> 'sans-serif'"></span></p>
> <font face=3D"Arial" size=3D"3"></font> <br>
> <font face=3D"Arial" size=3D"3">Maga</font><br>
> </div>
> </body>
> </html>
>
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>
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