Dear SAS Community,   I would like to see if there is a significant difference between the two avocado varieties (I55B and Hass) for each texture attribute. The data was obtained from at least 20 panelists that tested the avocado varieties during 3 days. To make the graph, I used the relative percent I obtained from freq tables for each variety and attribute (from all days) to make the radar graph. The table below only contains part of this data. Since each attribute can only take values of 0 and 1, I guess I should use a Chi-square test to see if there are differences between the two varieties for each attribute when taking the value 1 (e.g. watery). But if I need to compare several varieties for each attribute, I was wondering if I could instead calculate the total frequency of an attribute per day for each variety and then use these frequencies (using day as a rep) to run an ANOVA to compare the varieties for each attribute.  I hope it makes sense. I would really appreciate it your feedback. Thank you very much   palolix_1-1788546434010.png   Rep_Day Variety Panelist Overall Creamy Mushy Smooth Stringy Dry Watery None 1 I55B 1 5 0 0 0 0 0 1 0 1 I55B 2 4 0 0 1 0 1 0 0 1 I55B 3 6 1 0 0 0 0 0 0 1 I55B 4 4 0 0 0 0 0 1 0 1 I55B 5 8 1 0 0 0 0 0 0 1 I55B 6 5 0 0 0 0 0 1 0 1 I55B 7 8 0 0 1 0 0 1 0 1 I55B 8 5 0 0 0 0 0 0 1 1 I55B 9 5 0 0 0 0 0 1 0 1 I55B 10 5 0 0 0 0 1 0 0 1 I55B 11 7 0 0 1 0 0 1 0 1 I55B 12 7 0 0 0 0 0 0 1 1 I55B 13 6 0 0 0 0 0 0 1 1 I55B 14 7 0 1 1 0 0 1 0 1 I55B 15 4 0 0 0 0 0 1 0 1 I55B 17 5 0 1 0 0 0 1 0 1 I55B 18 3 0 1 0 0 0 1 0 1 I55B 19 9 1 0 1 0 0 0 0 1 I55B 20 4 0 0 0 0 0 1 0 1 I55B 21 8 0 0 1 0 0 0 0 1 I55B 22 6 1 1 0 0 0 1 0 1 I55B 23 6 0 0 0 0 0 1 0 1 I55B 25 2 0 1 0 1 0 1 0 1 I55B 26 5 0 1 1 0 0 1 0 2 I55B 1 8 1 0 0 0 0 0 0 2 I55B 2 5 0 0 0 1 0 1 0 2 I55B 3 6 1 0 0 0 0 1 0 2 I55B 4 7 0 0 0 0 0 1 0 2 I55B 5 2 0 0 0 0 0 1 0 2 I55B 6 5 0 0 0 0 0 1 0 2 I55B 7 8 1 0 1 0 0 0 0 2 I55B 8 3 0 1 0 0 0 0 0 2 I55B 9 5 0 0 0 0 0 0 1 2 I55B 10 6 0 0 0 0 1 1 0 2 I55B 11 6 0 0 0 1 0 1 0 2 I55B 12 7 0 0 0 0 0 1 0 2 I55B 13 8 1 0 1 0 0 0 0 2 I55B 14 4 0 0 1 0 0 0 0 2 I55B 15 2 0 0 0 0 0 0 1 2 I55B 16 6 0 0 0 0 0 0 1 2 I55B 17 7 0 0 0 0 1 0 0 2 I55B 18 5 0 1 0 0 0 1 0 2 I55B 19 6 0 0 1 0 0 1 0 2 I55B 20 7 1 0 0 0 0 0 0 3 I55B 1 6 1 0 1 0 0 0 0 3 I55B 2 5 0 0 0 0 1 0 0 3 I55B 3 3 0 0 0 0 0 1 0 3 I55B 4 6 0 0 1 0 0 0 0 3 I55B 5 4 0 1 0 0 0 1 0 3 I55B 6 7 0 0 1 0 0 1 0 3 I55B 7 8 0 0 0 0 0 0 1 3 I55B 8 5 0 0 0 0 0 0 1 3 I55B 9 5 0 0 0 0 0 1 0 3 I55B 10 6 0 0 0 0 0 1 0 3 I55B 11 6 0 0 0 0 1 0 0 3 I55B 12 7 0 1 0 0 0 1 0 3 I55B 13 4 0 1 0 0 0 1 0 3 I55B 14 4 1 1 1 0 0 1 0 3 I55B 15 4 0 0 0 0 0 1 0 3 I55B 16 7 0 0 0 0 0 1 0 3 I55B 17 7 1 0 0 0 0 0 0 3 I55B 18 6 0 1 0 0 0 1 0 3 I55B 19 5 0 0 1 0 1 0 0 3 I55B 20 5 0 0 0 0 0 1 0 3 I55B 21 3 0 0 0 1 0 0 0 3 I55B 22 7 0 0 1 0 0 0 0 3 I55B 23 7 0 0 1 0 0 1 0 3 I55B 25 5 0 1 1 0 0 1 0 3 I55B 26 3 1 0 1 0 0 1 0 1 Hass 1 6 0 0 0 0 0 1 0 1 Hass 2 3 1 0 0 0 0 0 0 1 Hass 3 7 0 0 1 0 0 0 0 1 Hass 4 8 1 0 0 0 0 0 0 1 Hass 5 6 0 0 0 0 0 1 0 1 Hass 6 4 0 0 0 0 0 1 0 1 Hass 7 5 0 0 0 0 0 1 0 1 Hass 8 4 0 0 0 0 0 1 0 1 Hass 9 8 1 0 1 0 0 0 0 1 Hass 10 8 1 0 0 0 0 0 0 1 Hass 11 7 0 0 1 0 0 0 0 1 Hass 12 6 0 1 0 0 0 0 0 1 Hass 13 8 1 0 0 0 0 0 0 1 Hass 14 6 0 0 0 1 0 0 0 1 Hass 15 9 1 0 0 0 0 0 0 1 Hass 17 7 1 0 1 0 0 1 0 1 Hass 18 6 0 0 0 1 1 0 0 1 Hass 19 7 1 1 1 0 0 0 0 1 Hass 20 5 0 0 0 0 1 1 0 1 Hass 21 8 0 0 1 0 0 0 0 1 Hass 22 7 1 1 1 0 0 0 0 1 Hass 23 8 1 0 0 0 0 1 0 1 Hass 25 5 1 1 0 0 0 1 0 1 Hass 26 4 1 0 1 0 0 0 0 2 Hass 1 7 0 0 1 0 0 0 0 2 Hass 2 3 0 1 0 0 0 1 0 2 Hass 3 8 1 1 1 0 0 0 0 2 Hass 4 8 1 1 1 0 0 0 0 2 Hass 5 6 0 0 1 1 0 0 0 2 Hass 6 4 0 0 1 0 0 1 0 2 Hass 7 9 1 1 1 0 0 0 0 2 Hass 8 7 0 0 1 0 0 0 0 2 Hass 9 7 0 0 1 0 0 0 0 2 Hass 10 6 1 0 0 0 0 1 0 2 Hass 11 7 0 0 1 0 0 1 0 2 Hass 12 9 1 1 0 0 0 0 0 2 Hass 13 6 1 1 0 0 1 0 0 2 Hass 14 7 1 0 0 0 0 0 0 2 Hass 15 5 0 0 0 0 0 1 0 2 Hass 16 7 0 0 1 0 0 0 0 2 Hass 17 9 1 0 1 0 0 0 0 2 Hass 18 4 0 0 1 0 0 1 0 2 Hass 19 6 0 0 1 0 0 0 0 2 Hass 20 5 0 1 0 0 0 1 0 3 Hass 1 4 0 0 0 0 0 1 0 3 Hass 2 6 1 0 1 0 0 0 0 3 Hass 3 7 0 0 0 0 0 0 1 3 Hass 4 4 0 1 0 0 0 0 0 3 Hass 5 4 0 1 0 0 0 1 0 3 Hass 6 6 0 0 1 1 0 0 0 3 Hass 7 6 1 0 0 0 0 0 0 3 Hass 8 6 1 0 1 0 0 0 0 3 Hass 9 6 0 0 0 0 0 1 0 3 Hass 10 5 0 0 0 0 0 1 0 3 Hass 11 5 0 0 0 0 0 1 0 3 Hass 12 8 0 1 0 0 0 1 0 3 Hass 13 7 1 1 0 0 0 1 0 3 Hass 14 9 1 1 1 0 0 0 0 3 Hass 15 5 0 0 0 0 0 1 0 3 Hass 16 7 0 0 0 0 0 1 0 3 Hass 17 5 0 0 0 0 0 1 0 3 Hass 18 6 0 0 1 0 0 1 0 3 Hass 19 4 0 0 0 1 1 0 0 3 Hass 20 5 0 0 0 0 0 1 0 3 Hass 21 4 0 0 1 0 0 0 0 3 Hass 22 7 0 0 1 0 1 0 0 3 Hass 23 6 0 0 0 0 1 1 0 3 Hass 25 2 0 0 1 0 0 1 0 3 Hass 26 2 0 0 0 0 0 1 0       ... View more

SAS V9.4. I'm stumped. I have a small file containing error messages from an IBM z/OS utility. I am reading a file that is the SYSPRINT messages from an IDCAMS DCOLLECT run. I have multiple types of records, and delete what I consider trash - for example, the first line.   The records I want all begin with 'IDC11808I' but the record is spread across two lines. One field on the first line is a dataset name(Bad_VVR_DSN) and can be up to 44 characters long. After each dataset name is ' ON ' followed by a 6-character volser.  I read the dataset name (Bad_VVR_DSN) and use an '@' to hold the record. I then do on_ix = index(Full_Rec,' ON ');  I then have VOL_START = on_ix + 4.  Followed by INPUT @(VOL_START) volser $char6.;    But I'm not getting the value for volser off most of the records. I also only see half my records (that is, I know there are 8 problems and only see 4 of them). For example, in the file Lloyd_C_DCOLLECT_SYSPRINT.txt there is a pair of records for Bad_VVR_DSN = LLOYD.CWC.GLOBAL.CSI.BKUP.DATA and it shows in the SASPRINT. There is also a pair of lines for LLOYDC.CWC.GLOBAL.CSI.BKUP.INDEX but that is not in the output. The SAS code is in Lloyd_C_DCOLLECT_BADVVR.txt.  I output the full record in the SASLOG.   Why is the INPUT @VOL_START not resulting in a value for most of the records? Why am I only seeing half of my input records?   ... View more

Imagine two organizations managing hundreds of models.   The first organization relies on emails, spreadsheets, and manual reminders to move models through development, validation, approval, and production.   The second organization uses structured workflows that automatically guide users through every step of the model lifecycle.   Which organization is more likely to maintain consistent governance, meet regulatory requirements, and reduce operational risk?   For most organizations, the answer is obvious.   Workflows are the backbone of model governance. They define how work moves through your organization, who performs each activity, and what conditions must be met before the next step can begin.   In SAS Model Risk Management (MRM), workflows help ensure that every model follows an approved governance process from initial registration through retirement.   Before administrators begin building or modifying workflows, it's important to understand the architecture that makes workflow-driven governance possible.   In this post, we'll explore the key components that power workflow-driven governance in SAS Model Risk Management and build the foundation you'll need for designing, managing, and troubleshooting workflows. ... View more

I am trying to create the equivalent of the below using sas-viya CLI and I am not sure how to achieve it (if it is possible at all):   EyalGonen_0-1788328546040.png   Specifically how to set the conopts parameter within the datasource option   Thanks! ... View more

Was playing around over the weekend and knocked together a SAS platformer game You can run it standalone, without SAS:  https://dash.sasjs.io Or you can hook it up to Viya and compete against each other for high scores: %let apploc=/Public/app/macro-dash; /* SAS Content location */ filename md url "https://github.com/sasjs/macro-dash/releases/latest/download/macro-dash-viya.sas"; %inc md; Source:   https://github.com/sasjs/macro-dash   More info:  https://sasapps.io/macro-dash macro-dash.png ... View more