About wateas

wateas

I can't use LSMEANS for a multinomial distribution. The issue is not interpreting the content of the solution table, but rather the odd ratios table. The multinomial model is modeling the probabilities of a lower value of the response variable "weed_rating" (screenshot below). The odds ratio table is easier to interpret when the first level has a lower response score than the second level, as the odds ratio estimate is a measure of the odds that the first level will have a LOWER score than the second level. So if the estimate is 10, then the odds are 10x more likely that the first level will have a lower score than the second. When the odds ratio is less than 1, the interpretation is not as intuitive to me, so it would be advantageous if I can rearrange factor level orders to accommodate that and make my life easier. Here is a good link for reference and further detail. Of course, I can simply manually rename my factor levels so they will have the desired ordering, but I thought I would try for a more sophisticated approach at first. It is easy to reorder factor levels in R, so I thought there might be similarly easy solution in SAS. Thanks for your help.

wateas

I'm conducting ANOVA for a multinomial, ordinal response variable in proc glimmix. I would like to alter the order of factor levels to make interpretation of odd ratios easier, but short of renaming the factor levels, I'm not sure how to do it. The variable is "Trt_CC" and the levels are "CC" and "no_CC". The default ordering is alphabetical, but I would like "no_CC" ordered first as to help me interpret the procedure output. So far, I've only been successful at renaming the factor levels /* Change order of factor levels in factor2 such that no_CC is first. */ proc format; value $trtfmt 'no_CC' = 1 'CC' = 2; run; /* Reponse_Var is an ordered, categorical variable with 5 levels.*/ proc glimmix data=df; class Site Block factor1 factor2; format factor2 $trtfmt.; model Response_Var = factor1 | factor2 | Site / dist=multinomial link=cumlogit oddsratio(diff=all) solution; random Block(Site) / solution; run; The above code successfully renames the levels of "factor2" as numbers and provides to desired ordering, but that has obvious drawbacks with respect to interpretability. Any advice as to how to change the ordering of "factor2" so that "no_CC" is before "CC" would be appreciated. Thanks for reading.

wateas · ‎11-26-2024

Hey now that I'm looking at it again, I appear to have made a error with my strings! So the problem is solved now. Thanks for your help.

wateas · ‎11-26-2024

Edited: There was an error in my factor level strings causing the issue. The code below works otherwise. Thanks. Hey Ksharp - thank you for your response. From running PROC FREQ, I see that I can easily see the level values, but I'm not sure exactly what you mean that I need to use their 'FORMATTED values'. PROC CONTENTS indicates that these factors are all type "char". This code returned the same error, "cannot find control level for effect...": lsmeans Trt_Amend_App * Trt_CC / pdiff=control('Control-Fert-nan' 'no_CC') adjust=dunnett;

wateas · ‎11-25-2024

Using a mixed effects model in PROC GLIMMIX, I would like to determine the differences between lsmeans with a chosen control. I'm trying to mimic the method outlined in the documentation to the best of my ability, but I get an error indicating "cannot find control level". proc glimmix data=df_y1 plots=studentpanel; class Trt_Amend_App Trt_CC ID_S Block; model Yield_Grain_Mg_ha = Trt_Amend_App | Trt_CC | ID_S / ddfm=kr2; random Block(ID_S); lsmeans Trt_Amend_App * Trt_CC / pdiff=control('7' '2') adjust=dunnett; run; The control corresponds to the 7th level of factor Trt_Amend_App and the 2nd level of Trt_CC. Any help clarifying this issue would be much appreciated.

wateas · ‎11-22-2024

Regarding this issue in "Build Models", I see now that variables can be set to have a role of "partition", but that option appears to disappear after the pipeline has been run.

wateas · ‎11-22-2024

Thanks for your response. Regarding your suggest to address the issue in the "Explore and Visualize" module, if I select "new partition" after right-clicking Block I get an error: "Cannot set this item as a partition because it is already in use by a partitionable analytic". So apparently some data item in my project is interfering. Regardless, it's good to know that I have an option to do this in the Explore and Visualize Module. What about the "Build Pipelines" module? From the partition data menu in project settings: "Note: These settings are active only when a partition variable is not set within the data. Using a data source with a pre-defined partition variable or manually selecting a partition variable will override these settings." How might I go about establishing a pre-defined partition variable?

wateas · ‎11-14-2024

I'm working in SAS Visual Analytics version 4.0. I would like to partition data in Build Models, but the corresponding menu in project settings is grayed out (see screenshot below). Additionally, I would like to partition data in a specific way using my blocking variable "block". Based on the options shown above, there does not appear to be a way to do this. However, it does seem that the "Explore and Visualize" module has this capability, however, my blocking variable is not listed as an option for some reason (see screenshot below). Available are a number of categorical variables, and for some reason a single continuous variable. Note that the variable "Block" is visible in the data pane as a categorical variable with 4 levels. Ideally, my data partitions would set training, validation, and test partitions to 50, 25, and 25%, respectively, using any of blocks 1, 2, 3, of 4. Thanks for reading!

wateas · ‎11-05-2024

Thanks for the suggestion, but I don't see any additional output when I add the statement.

wateas · ‎11-04-2024

I am analyzing data from a factorial experiment using PROC GLIMMIX in SAS. In the model, "Trt_Amend_App" is a categorical variable that is one of the experimental treatments and "ID_S" is one of two locations. The model results indicate that there is a significant interaction between Trt_Amend_App and ID_S such that Trt_Amend_App is significant at one location, but not the other. I would like to conduct a post-hoc test to determine which levels of Trt_Amend_App are different from each other, corrected for multiple comparisons using the Tukey adjustment, but only for the significant location "Site 2". How might I code that? I've included the code for my model below. The commented line under the first LSMEANS statement can be thought of a pseudocode indication of what I want to do (it doesn't work 🙂). proc glimmix data=df_y3_t3 plots=studentpanel; class ID_S Block Trt_Amend_App Trt_CC; model Response_Var = Trt_Amend_App | Trt_CC | ID_S ID_S(Block); lsmeans ID_S * Trt_Amend_App / slice=ID_S plot=meanplot(sliceby=Trt_Amend_App join); /*lsmeans Trt_Amend_App / diff adjust=tukey where(ID_S='Site 2');*/ run; I understand that the WHERE statement can be used to achieve the desired test in a separate procedure, but I'm hoping for a more streamlined solution. Thanks for reading.

wateas · ‎06-28-2024

I don't see any unusual characters when examining the applicable data in the source CSV file. Can you provide help with displaying the data in the HEX format? I tried the code below, which only deleted the data set. data df; put Trt_CC $hex10.; run;

wateas · ‎06-27-2024

I'm stumped as to why the concatenate function "cat" is not working for me. data df; set df; Trt_Unique = cats(Trt_Amend, "_", Trt_App, "_", Trt_CC); run; I don't know what to make of the error indicating that argument 5 is "invalid". The string "no_CC" concatenates just fine to other strings in the variable. Notice how "Ctrl-Fert_NA_CC" concatenates just fine, but there is an error for "Ctrl-Fert_NA_no_CC". Printing the data shows that these values are omitted by the operation. The issue doesn't seem to be that the character limit is exceeded. Using a length statement prior to the set statement causes the variable to not be created for some odd reason, without any errors to indicate why. Any ideas regarding this issue would be appreciated. Thanks for reading.

Online Status	Offline
Date Last Visited	a week ago

Re: Change factor level order for ordinal ANOVA

Change factor level order for ordinal ANOVA

Re: PROC GLIMIMIX: Issue specifying control level for pdiff

Re: PROC GLIMIMIX: Issue specifying control level for pdiff

PROC GLIMIMIX: Issue specifying control level for pdiff

Re: Issue with Partitioning Data in SAS Viya / Build Models

Re: Issue with Partitioning Data in SAS Viya / Build Models

Issue with Partitioning Data in SAS Viya / Build Models

Re: Tukey-adjusted comparisons for one location in PROC GLIMMIX

Tukey-adjusted comparisons for one location in PROC GLIMMIX

Re: PROC GLIMIMIX: Issue specifying control level for pdiff

Re: Tukey-adjusted comparisons for one location in PROC GLIMMIX

Re: Error using function concat to create character variable

Issue with Partitioning Data in SAS Viya / Build Models

Re: Change factor level order for ordinal ANOVA

Change factor level order for ordinal ANOVA

Re: PROC GLIMIMIX: Issue specifying control level for pdiff

Re: PROC GLIMIMIX: Issue specifying control level for pdiff

PROC GLIMIMIX: Issue specifying control level for pdiff

Re: Issue with Partitioning Data in SAS Viya / Build Models

Re: Issue with Partitioning Data in SAS Viya / Build Models

Issue with Partitioning Data in SAS Viya / Build Models

Re: Tukey-adjusted comparisons for one location in PROC GLIMMIX

Tukey-adjusted comparisons for one location in PROC GLIMMIX

Re: Error using function concat to create character variable

Error using function concat to create character variable