topic Re: Restricted Cubic Splines with Multinomial Outcome in Graphics Programming

topic Re: Restricted Cubic Splines with Multinomial Outcome in Graphics Programming https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/424924#M14647 <P>First, <A href="https://blogs.sas.com/content/iml/2016/06/22/sas-effectplot-statement.html" target="_self">you can create this plot by using the EFFECTPLOT statement</A>. Add the statement</P> <P>   EFFECTPLOT FIT;</P> <P>to your PROC LOGISTIC call.</P> <P> </P> <P>Second, in your problem, the FIT, L, and U variables are the predicted values from a regression procedure. To plot them, it is not appropriate to use LOESS or PBSPLINE statements to smooth the predicted values. Use the SERIES statement for the FIT curve and use the BAND statement for the L and U confidence limits:</P> <P> </P> <PRE><CODE class=" language-sas">ods select ModelANOVA ParameterEstimates SplineKnots; proc logistic data=Sashelp.cars(where=(Origin in ('Asia' 'USA') & Type ^="Hybrid")); effect spl = spline(mpg_city / details naturalcubic basis=tpf(noint) knotmethod=percentiles(5) ); model Origin(event ='USA')= spl / selection=none; /* fit model by using spline effects */ output out=SplineOut predicted=Fit lower = l upper = u; /* output predicted values for graphing */ effectplot fit; /* produce fit plot automatically */ run; /* or produce fit plot manually by using predicted values in output data set */ proc sort data=SplineOut; by mpg_city; run; proc sgplot data = splineout; band x = mpg_city lower=L upper=U; series x = mpg_city y = fit / curvelabel = "Predicted value"; /* optional, uncomment if you want to overlay the upper/lower limits */ /* series x = mpg_city y = U / curvelabel = "Upper CL"; series x = mpg_city y = L / curvelabel = "Lower CL"; */ run;</CODE></PRE> <P> </P> <P> </P> Thu, 04 Jan 2018 14:47:06 GMT Rick_SAS 2018-01-04T14:47:06Z Restricted Cubic Splines with Multinomial Outcome https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/423823#M14618 <P>I had been generating spline curves for a dichotomous outcome, but now I am looking at a 3 level outcome, although then ordinal scale is not proportional. Mainly concerned with generating curves for 2 vs 0, and 1 vs 0.</P><P> </P><P>This is the code I had been using:</P><P> </P><PRE>ods select ModelANOVA ParameterEstimates SplineKnots;<BR />proc logistic data=HEERDT.VPICU;<BR /> effect spl = spline(Ind_DBP1 / details naturalcubic basis=tpf(noint) <BR /> knotmethod=percentiles(5) );<BR /> model Vent24 (event ='0')= spl / selection=none; /* fit model by using spline effects */<BR /> output out=SplineOut predicted=Fit lower = l upper = u; /* output predicted values for graphing */<BR /> where CPB=1;<BR /> Title 'Probability of Failed Extubation by 24h: Spline Adjusted Model';<BR />run;<BR /><BR />proc sgplot data = splineout;<BR />loess x = ind_dbp1 y = fit/nomarkers curvelabel = "Predicted value" nolegclm nolegfit;<BR />loess x = ind_dbp1 y = u/nomarkers curvelabel = "Upper CI" nolegclm nolegfit ;<BR />loess x = ind_dbp1 y = l/nomarkers curvelabel = "Lower CI" nolegclm nolegfit;<BR />run;</PRE><P> This is fine for binary outcomes and I have been able to generate curves of quadratic functions of the continuous  exposure </P><PRE>Ind_DBP1</PRE><P>I have tried entering " link=glogit" within the model statement and stated that the outcome has a reference value if 0  rather than stating a particulate value for the event.<BR />p values come out as highly significant for the knot placements but I get the following error message when I try too plot a graph:</P><P> </P><P> </P><DIV><DIV class="sasNote">NOTE: PROCEDURE SGPLOT used (Total process time):</DIV><DIV class="sasNote">real time 0.20 seconds</DIV><DIV class="sasNote">cpu time 0.14 seconds</DIV><DIV class="sasNote"> </DIV><DIV class="sasNote">NOTE: The number of observations of the LOESS plot (5313) exceeds the limit of 5000. Specify the LOESSMAXOBS option of the ODS</DIV><DIV class="sasNote">GRAPHICS statement to override the limit.</DIV><DIV class="sasNote">NOTE: The number of observations of the LOESS plot (5313) exceeds the limit of 5000. Specify the LOESSMAXOBS option of the ODS</DIV><DIV class="sasNote">GRAPHICS statement to override the limit.</DIV><DIV class="sasNote">NOTE: The number of observations of the LOESS plot (5313) exceeds the limit of 5000. Specify the LOESSMAXOBS option of the ODS</DIV><DIV class="sasNote">GRAPHICS statement to override the limit.</DIV><DIV class="sasWarning">WARNING: The LoessPlot statement named 'LOESS' will not be drawn because one or more of the required arguments were not supplied.</DIV><DIV class="sasWarning">WARNING: The LoessPlot statement named 'LOESS1' will not be drawn because one or more of the required arguments were not supplied.</DIV><DIV class="sasWarning">WARNING: The LoessPlot statement named 'LOESS2' will not be drawn because one or more of the required arguments were not supplied.</DIV><DIV class="sasWarning">WARNING: A blank graph is produced. For possible causes, see the graphics template language documentation.</DIV><DIV class="sasWarning">WARNING: The LoessPlot statement named 'LOESS' will not be drawn because one or more of the required arguments were not supplied.</DIV><DIV class="sasWarning">WARNING: The LoessPlot statement named 'LOESS1' will not be drawn because one or more of the required arguments were not supplied.</DIV><DIV class="sasWarning">WARNING: The LoessPlot statement named 'LOESS2' will not be drawn because one or more of the required arguments were not supplied.</DIV><DIV class="sasWarning">WARNING: A blank graph is produced. For possible causes, see the graphics template language documentation.</DIV><DIV class="sasWarning">WARNING: The LoessPlot statement named 'LOESS' will not be drawn because one or more of the required arguments were not supplied.</DIV><DIV class="sasWarning">WARNING: The LoessPlot statement named 'LOESS1' will not be drawn because one or more of the required arguments were not supplied.</DIV><DIV class="sasWarning">WARNING: The LoessPlot statement named 'LOESS2' will not be drawn because one or more of the required arguments were not supplied.</DIV><DIV class="sasWarning">WARNING: A blank graph is produced. For possible causes, see the graphics template language documentation.</DIV><DIV class="sasNote">NOTE: There were 5313 observations read from the data set WORK.SPLINEOUT.</DIV></DIV><DIV><DIV class="sasNote"> </DIV><DIV class="sasSource">81</DIV><DIV class="sasSource">82 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK;</DIV><DIV class="sasSource">95</DIV><DIV class="sasSource"> </DIV><DIV class="sasSource"> </DIV><DIV class="sasSource"> </DIV></DIV><P>Any ideas?</P><P> </P><P>Cheers,</P><P> </P><P>Christos </P> Thu, 28 Dec 2017 02:37:57 GMT https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/423823#M14618 ChristosK 2017-12-28T02:37:57Z Re: Restricted Cubic Splines with Multinomial Outcome https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/423829#M14619 <H5 class="xis-optionNoCategory">Loess is expensive, and there are default limits on the number of observations for loess fit.  Either specify the option below in the ODS GRAPHICS statement or use PBSPLINE instead of LOESS.</H5> <H5 class="xis-optionNoCategory"> </H5> <H5 class="xis-optionNoCategory"><A class="ng-scope" tabindex="0" href="http://documentation.sas.com/?docsetId=odsug&docsetTarget=p0kroq43yu0lspn16hk1u4c65lti.htm&docsetVersion=9.4&locale=en#p0kssk9r8oz909n1o1xjki7c2a5t" rel="nofollow" data-docset-id="odsug" data-docset-version="9.4" data-original-href="#p0kssk9r8oz909n1o1xjki7c2a5t">LOESSOBSMAX=<SPAN class="xis-userSuppliedValue">n</SPAN></A></H5> <P class="xis-shortDescriptionNoCategory">specifies an upper limit for the number of observations that can be used with a loess plot.</P> Thu, 28 Dec 2017 03:53:46 GMT https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/423829#M14619 WarrenKuhfeld 2017-12-28T03:53:46Z Re: Restricted Cubic Splines with Multinomial Outcome https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/423891#M14620 <P>I changed it to this:</P><P> </P><P>proc logistic data=HEERDT.VPICU;<BR />effect spl = spline(Ind_DBP1 / details naturalcubic basis=tpf(noint) knotmethod=percentiles(5) );<BR />model VP24_VasoNE_012(event ='2')= spl / link=glogit ct covb clodds=wald selection=none; /* fit model by using spline effects */<BR />output out=SplineOut predicted=Fit lower = l upper = u; /* output predicted values for graphing */<BR />where CPB=1;<BR />Title '';<BR />run;<BR />proc sgplot data = splineout;<BR />PBSPLINE x = ind_dbp1 y = fit/nomarkers;<BR />PBSPLINE x = ind_dbp1 y = u/nomarkers;<BR />PBSPLINE = ind_dbp1 y = l/nomarkers;<BR />run;</P><P> </P><P> </P><P>The screenshot accompanying it seems meaningless.</P><P> </P><P>I'm certain that there is an effect, because a quadratic works very well at outcome level 3.<BR /><BR /></P><P>Enclosed is an additional screenshot showing the covariate matrix when reference level for the outcome is specified as '0'.</P> Thu, 28 Dec 2017 13:29:17 GMT https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/423891#M14620 ChristosK 2017-12-28T13:29:17Z Re: Restricted Cubic Splines with Multinomial Outcome https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/423894#M14621 <P>Not sure if any of this screenshots went through, trying again, but using the "add photo" option.<span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Screen Shot 2017-12-28 at 8.16.52 AM.png"><img src="https://communities.sas.com/skins/images/70F8802BAA6255D55FBEC62A8226FB10/responsive_peak/images/image_not_found.png" alt="Screen Shot 2017-12-28 at 8.16.52 AM.png" /></span><span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Screen Shot 2017-12-28 at 8.22.32 AM.png"><img src="https://communities.sas.com/skins/images/70F8802BAA6255D55FBEC62A8226FB10/responsive_peak/images/image_not_found.png" alt="Screen Shot 2017-12-28 at 8.22.32 AM.png" /></span></P> Thu, 28 Dec 2017 13:31:20 GMT https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/423894#M14621 ChristosK 2017-12-28T13:31:20Z Re: Restricted Cubic Splines with Multinomial Outcome https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/423895#M14622 <P>Not sure if any of this screenshots went through, trying again, but using the "add photo" option.<span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Screen Shot 2017-12-28 at 8.16.52 AM.png"><img src="https://communities.sas.com/skins/images/70F8802BAA6255D55FBEC62A8226FB10/responsive_peak/images/image_not_found.png" alt="Screen Shot 2017-12-28 at 8.16.52 AM.png" /></span><span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Screen Shot 2017-12-28 at 8.22.32 AM.png"><img src="https://communities.sas.com/skins/images/70F8802BAA6255D55FBEC62A8226FB10/responsive_peak/images/image_not_found.png" alt="Screen Shot 2017-12-28 at 8.22.32 AM.png" /></span></P> Thu, 28 Dec 2017 13:31:21 GMT https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/423895#M14622 ChristosK 2017-12-28T13:31:21Z Re: Restricted Cubic Splines with Multinomial Outcome https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/423899#M14624 <P>When I remove the link =glogit statement, the output looks more like a spline, but I cant tell from this what level of the outcome is specified as without link=glogit  I don't see how SAS knows what levels we are comparing to what?<span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Screen Shot 2017-12-28 at 8.33.06 AM.png"><img src="https://communities.sas.com/skins/images/70F8802BAA6255D55FBEC62A8226FB10/responsive_peak/images/image_not_found.png" alt="Screen Shot 2017-12-28 at 8.33.06 AM.png" /></span><span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Screen Shot 2017-12-28 at 8.33.15 AM.png"><img src="https://communities.sas.com/skins/images/70F8802BAA6255D55FBEC62A8226FB10/responsive_peak/images/image_not_found.png" alt="Screen Shot 2017-12-28 at 8.33.15 AM.png" /></span></P> Thu, 28 Dec 2017 13:37:30 GMT https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/423899#M14624 ChristosK 2017-12-28T13:37:30Z Re: Restricted Cubic Splines with Multinomial Outcome https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/424924#M14647 <P>First, <A href="https://blogs.sas.com/content/iml/2016/06/22/sas-effectplot-statement.html" target="_self">you can create this plot by using the EFFECTPLOT statement</A>. Add the statement</P> <P>   EFFECTPLOT FIT;</P> <P>to your PROC LOGISTIC call.</P> <P> </P> <P>Second, in your problem, the FIT, L, and U variables are the predicted values from a regression procedure. To plot them, it is not appropriate to use LOESS or PBSPLINE statements to smooth the predicted values. Use the SERIES statement for the FIT curve and use the BAND statement for the L and U confidence limits:</P> <P> </P> <PRE><CODE class=" language-sas">ods select ModelANOVA ParameterEstimates SplineKnots; proc logistic data=Sashelp.cars(where=(Origin in ('Asia' 'USA') & Type ^="Hybrid")); effect spl = spline(mpg_city / details naturalcubic basis=tpf(noint) knotmethod=percentiles(5) ); model Origin(event ='USA')= spl / selection=none; /* fit model by using spline effects */ output out=SplineOut predicted=Fit lower = l upper = u; /* output predicted values for graphing */ effectplot fit; /* produce fit plot automatically */ run; /* or produce fit plot manually by using predicted values in output data set */ proc sort data=SplineOut; by mpg_city; run; proc sgplot data = splineout; band x = mpg_city lower=L upper=U; series x = mpg_city y = fit / curvelabel = "Predicted value"; /* optional, uncomment if you want to overlay the upper/lower limits */ /* series x = mpg_city y = U / curvelabel = "Upper CL"; series x = mpg_city y = L / curvelabel = "Lower CL"; */ run;</CODE></PRE> <P> </P> <P> </P> Thu, 04 Jan 2018 14:47:06 GMT https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/424924#M14647 Rick_SAS 2018-01-04T14:47:06Z Re: Restricted Cubic Splines with Multinomial Outcome https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/424938#M14648 <P>Thank you Rick:</P><P> </P><P>There seems to be many ways to do this, although I'm not sure how I can tell which is"more correct" (If such a thing exists).</P><P> </P><P>Why do you think this approach is better and what are the pros / cons? Was my previous approach better suited for other applications?</P><P> </P><P>I was particularly interested in finding a way to run restricted cubic splines rather than just splines. Whilst I understand conceptually what this is, I have not found a way to do this in SAS yet.</P><P> </P><P>Thanks,</P><P> </P><P>Christos </P> Thu, 04 Jan 2018 15:13:08 GMT https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/424938#M14648 ChristosK 2018-01-04T15:13:08Z Re: Restricted Cubic Splines with Multinomial Outcome https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/424975#M14649 <P>> <EM>There </EM>seems<EM> to be many ways to do this, although I'm not sure how I can tell which is"more correct" (If such a thing exists).</EM></P> <P> </P> <P>Yes, there are many ways to do this and other tasks. Of the two ways I showed, neither is  "more correct," but the EFFECTPLOT statement is definitely easier and requires less effort.</P> <P> </P> <P>> <EM>Why do you think this approach is better and what are the </EM>pros / cons<EM>? Was my previous approach better suited for other applications?</EM></P> <P> </P> <P>This approach is better because the curves/band represent actually predicted values from a statistical model. If you use a loess or penalized b-spline to smooth the predicted values, you obtain a curve that is not the one predicted by the model. In many cases, a loess or spline curve does not pass through the predicted values.</P> <P> </P> <P> > <EM>I was particularly interested in finding a way to run restricted cubic splines rather than just splines. Whilst I understand conceptually what this is, I have not found a way to do this in SAS yet.</EM></P> <P> </P> <P>I don't know what you mean by "to do this in SAS." What is "this"? You must have used <A href="https://blogs.sas.com/content/iml/2017/04/19/restricted-cubic-splines-sas.html" target="_self">my article on regression splines</A> to write your code. The article contains links to <A href="http://support.sas.com/documentation/cdl/en/statug/68162/HTML/default/viewer.htm#statug_introcom_sect020.htm" target="_self">the SAS documentation on splines.</A> SAS supports many kinds of splines. <A href="http://support.sas.com/documentation/cdl/en/statug/68162/HTML/default/viewer.htm#statug_transreg_details03.htm" target="_self">The documentation for PROC TRANSREG also contains details and examples.</A> If you can specify the spline basis that you want to use, someone on this community can show you how to use that basis in a regression. </P> Thu, 04 Jan 2018 16:37:11 GMT https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/424975#M14649 Rick_SAS 2018-01-04T16:37:11Z Re: Restricted Cubic Splines with Multinomial Outcome https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/425003#M14650 <P>Regarding "doing this":</P><P>Sorry about not being specific.</P><P>I was referring to "Restricted Cubic Splines". I have seen this alot in the literature in my field and am including a paper with an example  where they used Stata. (Venkatesan et al).</P><P> </P><P>It seems as though they were able to:</P><P>1) Partially dismiss the effects of instability (due to fewer entries)  at the extreme ends of the independent variable of interest.</P><P>2) Assign a definitive trough value, and generate OR's in reference to this.</P><P> </P><P> </P><P>I don't remember reading your article. One of my friends suggested using this code a few months ago for a poster I was presenting.</P><P> </P><P>I guess at the end of the day I need to be able to establish a curve that is publication worthy and that I'll be able to defend.</P><P>Will look at your article. </P><P>Much Appreciated,</P><P> </P><P>Christos</P> Thu, 04 Jan 2018 17:45:06 GMT https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/425003#M14650 ChristosK 2018-01-04T17:45:06Z Re: Restricted Cubic Splines with Multinomial Outcome https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/425030#M14651 Loess output and Series output looks the same even though the shading and colours are different . Can only add one file at a time to this message so will send the series output in the next message. Thu, 04 Jan 2018 19:52:39 GMT https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/425030#M14651 ChristosK 2018-01-04T19:52:39Z Re: Restricted Cubic Splines with Multinomial Outcome https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/425036#M14654 <P>This is the second  output where we used series instead of loess in the proc subplot statement .</P><P>Can anyone see whether the curve is different at all?</P> Thu, 04 Jan 2018 19:55:44 GMT https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/425036#M14654 ChristosK 2018-01-04T19:55:44Z Re: Restricted Cubic Splines with Multinomial Outcome https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/425052#M14655 <P>Yes, if the X values are closely spaced and the Y values are not too wild, you will often obtain a loess curve that looks very similar to a series plot. My point, however, is that it is not statistically appropriate to put a smoother through predicted values. </P> <P>For one thing, the loess curve is actually one of a family of curves that are parameterized by a smoothing parameter. The curve that is displayed is chosen to minimize a system of local regression fits, assuming that the points are data with IID errors.</P> <P> </P> <P>The following example shows data for which the "best" loess curve does not pass anywhere near the fitted points.</P> <P> </P> <PRE><CODE class=" language-sas">data Fit; input x y @@; datalines; 0 0 1 5 3 5 4 0 5 5 ; proc sgplot data=Fit; series x=x y=y / lineattrs=(color=red); loess x=x y=y; run; </CODE></PRE> Fri, 05 Jan 2018 21:24:06 GMT https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/425052#M14655 Rick_SAS 2018-01-05T21:24:06Z Re: Restricted Cubic Splines with Multinomial Outcome https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/427587#M14721 <P>Rick:</P><P>Hope you are enjoying the weekend.</P><P>I am struggling with getting figures for the adjusted models. I guess with out smoothing the curves, the edges will be erratic but I can't really  present these.</P><P>What if anything should I consider doing with this adjusted model in order to make it meaningful or presentable as a figure?</P><P> </P><P> </P><P>Christos</P> Mon, 15 Jan 2018 00:25:00 GMT https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/427587#M14721 ChristosK 2018-01-15T00:25:00Z Re: Restricted Cubic Splines with Multinomial Outcome https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/427646#M14724 <P>The parameter estimates indicate that you are including multiple covariates in the model (age, BMI, etc). You need to use the EFFECTPLOT SLICEFIT statement to create a sliced fit plot. See</P> <P><A href="https://blogs.sas.com/content/iml/2017/12/18/visualize-multivariate-regression-models-by-slicing-continuous-variables.html" target="_self">Visualize multivariate regression models by slicing continuous variables</A>  (see the 2nd graph, which looks like yours)</P> <P>If for some reason you can't use the EFFECTPLOT statement, see</P> <P><A href="https://blogs.sas.com/content/iml/2017/12/20/create-sliced-fit-plot-sas.html" target="_self">How to create a sliced fit plot in SAS</A></P> <P> </P> Mon, 15 Jan 2018 14:06:23 GMT https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/427646#M14724 Rick_SAS 2018-01-15T14:06:23Z Re: Restricted Cubic Splines with Multinomial Outcome https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/428210#M14766 <P>Rick:</P><P> </P><P>Thank you for the link and suggestions. I have been doing a logistic regression with only one continuous variable being a spline.</P><P>The Univariate  code is as follows:</P><PRE><CODE class=" language-sas">ods select ModelANOVA ParameterEstimates SplineKnots; proc logistic data=HEERDT.VPICU_label; effect spl = spline(Ind_DBP1 / details naturalcubic basis=tpf(noint) knotmethod=percentiles(5) ); /* fit model by using spline effects */ model Vent__240(reference ='0')= spl / ct covb clodds=wald selection=none; output out=SplineOut predicted=Fit lower = l upper = u; /* output predicted values for graphing */ effectplot fit; run; proc sort data =SplineOut; by Ind_DBP1; run; proc sgplot data = SplineOut; band x=Ind_DBP1 lower=L upper=U; series x = Ind_DBP1 y = fit/ curvelabel = "Predicted value"; series x = Ind_DBP1 y = u/ curvelabel = "Upper CI"; series x = Ind_DBP1 y = l/ curvelabel = "Lower CI"; run;</CODE></PRE><P> I tried some of your suggestions, but since you were using gym, and only had single lines rather than 95% CI's as well, I got a bit confused and was not able to get it to work.</P><P>Initially I just added multiple covariates, ands this worked fine when running loess in proc sgplot, but with series there were alot of jagged lines for all the reasoned you had mentioned.</P><P> </P><P> </P><P>I tried various iterations of slice fit:</P><PRE><CODE class=" language-sas">ods select ModelANOVA ParameterEstimates SplineKnots; proc logistic data=HEERDT.VPICU_label; effect spl = spline(Ind_DBP1 / details naturalcubic basis=tpf(noint) knotmethod=percentiles(5) ); /* fit model by using spline effects */ class Sex(ref="F")Race_d (ref="C")/param=ref; model Vent__240(reference ='0')= spl Sex Age /* Race_d CABG ACEI ARB Statin1 BMI NIDDM1 BB pre_Cr pre_K*/ / ct covb clodds=wald selection=none; output out=Splineout predicted=Fit lower = l upper = u; /* output predicted values for graphing */ effectplot slicefit / at (Sex ='F' Age=50); run; proc sort data =SplineOut; by Ind_DBP1; run; proc sgplot data = SplineOut ; band x=Ind_DBP1 lower=L upper=U; series x = Ind_DBP1 y = fit/ curvelabel = "Predicted value"; series x = Ind_DBP1 y = u/ curvelabel = "Upper CI"; series x = Ind_DBP1 y = l/ curvelabel = "Lower CI"; run;</CODE></PRE><P>The only difference I see between your examples and what I am modeling is that you had a continuous dependent variable and that I was generating predicted probabilities out of a logistic regression. And that I was plotting confidence intervals, Adding anything my univariate model created jagged edges because this was being modeled on the actual values I guess rather than an an estimate of what these should be by the model.</P><P> </P><P>If this was not entertaining enough, I am also trying to get a way to  get odds ratios for pr-specifiued levels of the  continuous exposure that is splined, comparing the odds of that level to the mode. It seems to be easy in Stada and R but not SAS. Any idea ?</P> Tue, 16 Jan 2018 23:04:04 GMT https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/428210#M14766 ChristosK 2018-01-16T23:04:04Z Re: Restricted Cubic Splines with Multinomial Outcome https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/428331#M14773 <P>Here's an example for PROC LOGISTIC to get you started.</P> <P> </P> <P> </P> <PRE><CODE class=" language-sas">data cars; /* create example data */ set sashelp.cars; where type^='Hybrid' & cylinders in (4,6,8); run; ods graphics / attrpriority=none; /* groups determine symbols and line patterns */ proc logistic data=cars; effect spl = spline(mpg_city / details naturalcubic basis=tpf(noint) knotmethod=percentiles(5) ); class cylinders type / param=ref; model origin = spl cylinders type weight engineSize; effectplot slicefit (X=mpg_city) / clm ilink at(cylinders='4' type='Sedan' weight=MEAN engineSize=MEAN); oddsratio cylinders; oddsratio type; quit; </CODE></PRE> <P>This is complicated stuff, so you might need to reread the articles and <A href="http://go.documentation.sas.com/?docsetId=statug&docsetTarget=statug_introcom_sect027.htm&docsetVersion=14.3&locale=en#statug.introcom.efpl_at" target="_self">the documentation of the EFFECTPLOT statement</A> several times. Also, pay attention to the SAS log. I think you are getting notes that tell you that some of your PROC LOGISTIC syntax is not valid. For example, you are currently fitting a cumulative logistic model, which does not support the REF= and CTABLE options.</P> <P> </P> <P>Your remaining questions seem to be statistical, not graphical. I suggest you close out this thread and if you have questions about odds ratios and logistic models, open a new thread in the Statistical Procedures Community. Good luck!</P> Wed, 17 Jan 2018 11:47:38 GMT https://communities.sas.com/t5/Graphics-Programming/Restricted-Cubic-Splines-with-Multinomial-Outcome/m-p/428331#M14773 Rick_SAS 2018-01-17T11:47:38Z