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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_ > 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 { > FONT-SIZE: 10pt; FONT-FAMILY: Tahoma > } > </style> > <meta content=3D"MSHTML 6.00.6000.17037" name=3D"GENERATOR"> > <style title=3D"owaParaStyle"><!--P { > MARGIN-TOP: 0px; MARGIN-BOTTOM: 0px > } > --></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>&nbsp;</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 &quot;validity&quot; question, for the same reasons Gene outlined.</font>= > </div> > <div dir=3D"ltr"><font face=3D"arial"></font>&nbsp;</div> > <div dir=3D"ltr"><font face=3D"arial"></font>&nbsp;</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>&nbsp;</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&nbsp;to > show that your results are valid.&nbsp;I want to make two comments. One&nb= > sp;comment is&nbsp;about the power computation specifically.&nbsp;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,&nbsp;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>&nbsp; > </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>&nbsp;</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 &quot;<font c= > olor=3D"#000000">As I can estimate the statistical > power to conclude that my results are valid.&quot; 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>&nbsp;</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>&nbsp;</div> > <div dir=3D"ltr" align=3D"left"><font face=3D"Arial" color=3D"#0000ff"></fo= > nt>&nbsp;</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>&nbsp;<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>&nbsp;<br> > <font face=3D"Arial" size=3D"3">Maga</font><br> > </div> > </body> > </html> > > --_000_5F28CD1102E6274BA7BE4796B8EA90F50A46047431TCSTCSESORG_-- > > ===================== > To manage your subscription to SPSSX-L, send a message to > LISTSERV@LISTSERV.UGA.EDU (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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