According to this usage note, there's an old defect for CONNECT USING together with OLEDB access: 48877 - A pass-through connection invokes the Data Link Properties dialog box even though an assigned OLEDB libref is also present (sas.com) CONNECT USING was imoplemnted because it's conventient to avoid keeping connection information in many places. Also, this especially nice when you want to generete the connections dynamically in PROC SQL. ... View more

Request: Please can SAS include the option to calculate test statistics for the unadjusted and stratified MN method.   Background: Miettinen-Nurminen (MN) methods are increasingly being requested by regulatory agencies. This is particularly relevant for non-inferiority trials where it's appropriate for the variance to be estimated under the null hypothesis. Within the PROC FREQ procedure, it's currently possible to calculate the treatment differences (and CIs) for both the unadjusted MN and the stratified MN methods as well as other MN tests such as the Summary Score method (also referred to as Agresti Score). However, whilst for the Summary Score method SAS allows the option to calculate the test statistics this is not yet available for the unadjusted MN method or the stratified MN method.   These methods are important as they estimate variance under the null hypothesis, specifically the test statistics are of particular useful for: testing superiority and presenting a p-value studies with interim analyses, particularly when multiplicity is controlled via a group sequential design i.e. with alpha boundaries less than the typical 1-sided 2.5%/2-sided 5% alpha Example SAS code (for reference): Note: data not supplied due to proprietary nature, however code shared to illustrate current options/limitations.  The unadjusted MN treatment difference can be calculated using: proc freq data=DATA; tables TRT*AVAL / riskdiff(CL=(MN) noninferiority margin=0.1);  run; Note: whilst the (unadjusted) Wald test statistics are calculated, it would be helpful if the unadjusted MN test statistics could also be provided. The stratified MN Score treatment difference can be calculated using: proc freq data=DATA; tables STRATA*TRT*AVAL / riskdiff(CL=(MN) noninferiority margin=0.1) COMMONRISKDIFF(CL=(MN score) test=(score)); run; Note: whilst the (adjusted) Summary Score (also referred to as Agresti Score) test statistics are calculated, it would be helpful if the stratified MN test statistics could also be provided. Specifically, if MN could also be an option within COMMONRISKDIFF(TEST=( )) ... View more

As I understand the situation, a "spike and slab" prior in PROC MCMC cannot now be specified because this distribution requires a combination of a DGENERAL and GENERAL distribution. [Regarding "spike and slab", see the reference:  https://www.mv.helsinki.fi/home/mjxpirin/HDS_course/material/HDS8_variable_selection.html] The "spike and slab" prior for a predictor X would support "variable selection" when using PROC MCMC.  To fully implement the approach given in the reference above, the functionality of the R package called BoomSpikeSlab would be needed. See https://cran.r-project.org/web/packages/BoomSpikeSlab/index.html ... View more

Perhaps due to my ignorance, but I had a use case where WHICHC function was ideal. The problem was that the array I had was multidimensional, so I had to resort to DO i=1 TO...looping. Just allowing a multidimensional array to be specified, but with 2nd dimension specified with a constant would be an improvement: do i=1 to x; pos = whichc('#',of space[*,i]); end; ... View more

Sample code, based on SAS Usage note 22883 http://support.sas.com/kb/22/883.html   data a; do Rater1=1 to 2; do Rater2=1 to 2; input Wt @@; output; end; end; datalines; 0 3 0 3 ; run; proc freq data=a; weight Wt / zeros; tables Rater1*Rater2 / agree nocol norow nopercent plots=none; run;   This code generates a 2x2 table to estimate Cohen's Kappa with standard error and confidence interval. One of the margins has a sum of zero, but it is forced to fit a 2x2 table using the weight statement and zeros option. The results are that the estimated Kappa is zero, the standard error is zero and the Confidence Interval is (0 to 0).   I've convinced myself that the standard error result is numerically correct, having checked the result using equations in the documentation and the cited reference. I think it is a special case for 2x2 tables, since the usage note above gives an example for 4x4 tables, and the resulting standard error is strictly positive. That said, an estimated statistic having no variability might not appear correct to a reader.   I suggest that 1) PROC FREQ provides a warning/note in the log/output to draw attention to this anomaly. 2) Ideally, if there are suitable improved formulae that don't have this defect, could they be implemented as an alternative option? (I admit, I don't have a better suggestion in mind).   Reference: Fleiss JL, Cohen J, Everitt B. (1969) Large sample standard errors of kappa and weighted kappa. Psychological Bulletin. 72 (5) 323-327. https://api.semanticscholar.org/CorpusID:85541244, https://doi.org/10.1037/H0028106 ... View more

To view how well the model discriminates those with and those without the event, the user needs the area under the receiver operating characteristic curve (AUC). However, the options for the users are limited when the INMODEL= option is specified in the PROC LOGISTIC statement, with AUC only available when the user specifies both the SCORE statement and the FITSTAT option. But a big deficit in the process is the lack of confidence interval of AUC, which is automatically computed and displayed in the ROC statement but is not available when the INMODEL= option is specified in the PROC LOGISTIC statement. Therefore, when the user is validating a model, he/she cannot obtain it directly. What is more, the formula of the standard error of the AUC is not reported in anywhere of SAS Help, so the user is unable to calculate the confidence interval on his/her own. Therefore, I suggest that SAS (1) automatically compute the standard error and confidence interval of the AUC when the INMODEL= option is specified in the PROC LOGISTIC statement; (2) include the formula of the standard error of AUC in SAS Help. ... View more

The OUTSTATS dataset created by PROC COMPARE includes summary statistics for only numeric columns, eg. N, MEAN, STD, NDIF.  While the MEAN, MIN, MAX, STD, STDERR etc values are not applicable to character columns, N and NDIF are.   The OUTSTATS data is very helpful to very quickly get a sense of the magnitude of differences between the BASE and COMPARE datasets.  e.g.   outstats = column_diffs ( where = ( _type_ = 'NDIF' and _base_ ne 0 )). The ODS table output produced by "ods table comparesummary = blah" is just the printed output that must be parsed, an untenable solution.   Please add N and NDIF to the OUTSTATS data for character columns. ... View more

Currently, PROC MIXED can implement just one type of heteroscedasticity consistent estimator of the variance, namely the Huber-White / empirical / sandwich / HC0 estimator; this is accomplished with the EMPIRICAL option on the PROC MIXED statement in conjunction with the SUBJECT= option on either the RANDOM or REPEATED statement:  https://documentation.sas.com/doc/en/pgmsascdc/9.4_3.4/statug/statug_mixed_syntax01.htm#statug.mixed.procstmt_empirical   PROC REG, on the other hand, can implement 4 types of heteroscedasticity consistent estimators: HC0, HC1, HC2, and HC3 using the HCC option in the MODEL statement: https://documentation.sas.com/doc/en/pgmsascdc/9.4_3.4/statug/statug_reg_syntax08.htm#statug.reg.modelhcc   Long and Ervin (2000) argue that HC3 is superior to HC0.   Additional methods such as HC4, HC4m, and HC5 have been proposed in the literature and implemented in the vcovHC function of R package sandwich.    Please consider adding these additional heteroscedasticity consistent estimators to PROC MIXED.   Relevant references:  Long J. S., Ervin L. H. (2000). “Using Heteroscedasticity Consistent Standard Errors in the Linear Regression Model.” The American Statistician, 54, 217–224. Cribari-Neto F. (2004). “Asymptotic Inference under Heteroskedasticity of Unknown Form.” Comuputational Statistics & Data Analysis 45, 215–233. Cribari-Neto F., Souza T.C., Vasconcellos, K.L.P. (2007). “Inference under Heteroskedasticity and Leveraged Data.” Communications in Statistics – Theory and Methods, 36, 1877–1888. Errata: 37, 3329–3330, 2008. Cribari-Neto F., Da Silva W.B. (2011). “A New Heteroskedasticity-Consistent Covariance Matrix Estimator for the Linear Regression Model.” Advances in Statistical Analysis, 95(2), 129–146. ... View more

For debugger we can sort based on variable and based on value, but there is no way to sort for WATCH variable. an there be a functionality added that will allow us to filter on the WATCH variables so they appear together versus where they appear in the PDV? ... View more

Hi,   I'm suggesting if you could let the user add two legends to the Line-Bar chart as below screenshot: to show more details to the info based on two measures and two categories    ... View more

While many welcome the availability of SAS EG for connecting to SAS Viya 4 as they see it as a continuity from the past (and carry the historical baggage along with), the availability of multiple interfaces to connect to SAS Viya 4 (SAS EG, SAS Studio, VS Code ) is  chaotic and an avoidable irritant for admins.  In my experience VS Code has proved it's mettle . When it works for   Java, C#, go, python and, C++,   Oracle etc.,  it can work for SAS too as efficiently. It is my humble suggestion that SAS promote VS Code as the official Code editor for SAS/CAS programming and deprecate SAS Studio and SAS EG over a reasonable period of time. This would simplify managing the environment (and make business sense to SAS too!). SAS would only need to focus on extensions. ... View more

It would be highly appreciated if an option is given in the bar graph to resize the Y-axis labels area so that labels are never hidden and replaced by "...". So far it seems that the space allocated for labels and the space allocated for bars is automatically defined by SAS and it happens that labels are hidden when too long (in these cases we would like just to reduce the space for the bars). We provide an example in the picture on how we would like it work. We didn't find any option to avoid this behaviour without having to just reduce the size of the labels. We would like to have this on SAS Viya 4.0. Thank you.     ... View more

It is not possible to cancel a program that has been submitted using the Background Submit feature in SAS Viya. There is no Cancel button for individual programs that are submitted using Background Submit. Only an admin can cancel the jobs using workload orchestrator.  ... View more

When processing character in a data step, SAS silently truncates the result when assigning it to a variable with length shorter than the result. I know this is standard, documented behavior and that SAS programmers are generally aware of it. However in even mildly complex data steps, a small oversight can lead to truncations that are difficult to detect at all, let alone quickly find the source problem. So the idea is to add an option to report errors or warnings whenever a DATA step assignment statement truncates the value.   I'd guess that in 99% of these cases, the truncation is clearly undesired behavior, like in this example:     /* definition of shortvar; in practice, this may be imported or heavily processed data, so it isn't obvious what length it has */ data example1; shortvar = "short"; run; data example2; set example1; shortvar = shortvar || ' long'; /* silently truncates */ run; proc print data=example2; run; /* output: obs shortvar 1 short */     This type of truncation is obviously not desired because it happens when we try to add more characters. The result is that the variable appears unchanged and it isn't obvious why. ... View more

Recently, our cloud security team started enforcing the Kubernetes ‘pod security standards’ with the Kyverno tools.  See standard details: https://kubernetes.io/docs/concepts/security/pod-security-standards/#restricted  Most of the SAS VIYA pods are running with ‘no-root’ user security setting, but do not have the explicit restriction on "runAsNonRoot" security context. Kyverno flags and blocks all these pods and breaks down the SAS VIYA application.  The temporary work-around is to write kyverno exception. See below. Since this is the Kubernetes security standard, it is strongly suggested to SAS VIYA platform to consider this and reconfigure the pod security standard.   ... View more

SAS Mirror Manager can upload/push SAS images to some container registries like AWS ECR. I suggest to add an option to allow to delete/remove SAS images in order to be able to cleanup the container registry. For example, if I use SAS Mirror Manager to upload three SAS releases to AWS ECR: Stable 2024.04, 2024.05 and 2024.06. Now I want to delete all SAS images that belong to release Stable 2024.04 to cleanup my AWS ECR but there is no option in SAS Mirror Manager to do it. ... View more

Investigators using Procurement Integrity Visual Investigator Solutions (CMPI) on Viya4 need the ability to manage, assign, and route alerts at the scenario-fired event or incident level, not just at the entity level (e.g., vendor or employee).   Currently, Visual Investigator treats alerts as entities, meaning investigators must handle all scenario-fired events/incidents linked to an entity before closing an alert.   Disposition: Management has difficulty tracking progress because investigators need to address all events linked to an entity before an alert can be closed. Although investigators can manage a subset of events, they cannot disposition of individual scenario-fired events/incidents directly, only assess them.   Assign/Route: Investigators might need to review all incidents related to a specific scenario, such as multiple vendors sharing the same VAT number. Typically, investigator groups need to focus on specific scenarios, but the system currently routes all events associated with an alert together, making it hard to focus on individual scenarios.   Rollup: Incidents cannot be categorised under multiple alert types or strategies, which complicates the disposition and assignment processes.   Bulk Disposition: Users would need to export alerts to Excel, update disposition reasons and productivity ratings, and then upload the results back to Visual Investigator. This process is often faster than using the Visual Investigator interface directly, especially for repetitive tasks. For instance, an auditor reviewing instances where a vendor and an employee share a phone number would find it more efficient to use Excel than navigating through each alert individually.   ROI: Calculating ROI is challenging due to the lengthy implementation process (averaging 6 months) and the time required for system stabilisation and user training. The current process for capturing disposition at the alert level delays ROI reporting, which the sales teams need for end-of-year assessments and contract renewal. In some cases, solution rollouts have been delayed because clients cannot provide ROI figures on time.   These issues have been consistently encountered in all Viya/Visual Investigator implementations. Many of these features were available in the previous SAS Fraud Framework UI, and existing migrations cannot proceed until these issues are resolved, extending support for the older SAS Fraud Framework.   How does R&D receive client feedback and determine what is working or not working with the product? As SAS Partners, we do not have access to internal SAS systems and cannot log feature requests directly. ... View more

Hi,    Context:   Viya implemented in Azure using https://github.com/sassoftware/viya4-iac-azure. SAS admin team stated that Viya 4 does not support the use or configuration of a proxy.   Request:   To improve security posture, it will be beneficial for Viya4 to support the use of a proxy to inspect SSL traffic.   Note: Microsoft has a new feature available  (In Preview) for their Azure Kubernetes Services  which will allow to use custom CA. More information here:  Custom certificate authority (CA) in Azure Kubernetes Service (AKS) (preview) - Azure Kubernetes Service | Microsoft Learn| https://learn.microsoft.com/en-us/azure/aks/custom-certificate-authority     ... View more

There are time series animation available for Bar/Line/Geo-maps on SAS-Viya. This function (Animation) should be made available to any kind of graphs/plots and even Tables too. Particularly, I was looking to make a Custom graph using Butterfly plot adding this animation. I have managed to use bar-graph with animation instead of Butterfly plots but one-side of that graph shows negative values. Thank you in advance.   ... View more