> 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:
[hidden email]
>> Subject: Re: help me
>> To:
[hidden email]
>>
>> --_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 [
[hidden email]] On Behalf Of Gene
>> Magu=
>> in [
[hidden email]]
>> Sent: Wednesday, June 15, 2011 9:22 AM
>> To:
[hidden email]
>> 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:
[hidden email]] On Behalf Of
>> MA=
>> RGOT mh
>> Sent: Tuesday, June 14, 2011 4:41 PM
>> To:
[hidden email]
>> 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_
>> Content-Type: text/html; charset="iso-8859-1"
>> Content-Transfer-Encoding: quoted-printable
>>
>> <html dir=3D"ltr"><head>
>> <meta http-equiv=3D"Content-Type" content=3D"text/html;
>> charset=3Diso-8859-=
>> 1">
>> <style>.hmmessage P {
>> PADDING-RIGHT: 0px; PADDING-LEFT: 0px; PADDING-BOTTOM: 0px; MARGIN: 0px;
>> P=
>> ADDING-TOP: 0px
>> }
>> BODY.hmmessage {
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>> }
>> </style>
>> <meta content=3D"MSHTML 6.00.6000.17037" name=3D"GENERATOR">
>> <style title=3D"owaParaStyle"><!--P {
>> MARGIN-TOP: 0px; MARGIN-BOTTOM: 0px
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>> --></style>
>> </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 [
[hidden email]]<br>
>> <b>Sent:</b> Wednesday, June 15, 2011 9:22 AM<br>
>> <b>To:</b>
[hidden email]<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>
[hidden email]<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>
>>
>> --_000_5F28CD1102E6274BA7BE4796B8EA90F50A46047431TCSTCSESORG_--
>>
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