Sas graph

Manufactured by SAS Institute

Sourced in United States

SAS/GRAPH is a software component within the SAS suite of products. It provides capabilities for creating and customizing a wide range of graphical displays and visualizations from data. SAS/GRAPH offers features for generating high-quality charts, plots, and maps to support data analysis and reporting.

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Lab products found in correlation

Sas stat, by SAS Institute (10 mentions) Sas for windows, by SAS Institute (1 mentions)

Close spelling variants of this product

SAS/GRAPH software (2 citations)

5 protocols using sas graph

Optimizing Conditions via SAS Regression

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Data were analyzed using SAS software. SAS/STAT (2013) procedures were used for regression modeling. Optimum conditions were found through SAS data-step programming. Plots were generated using SAS/GRAPH (2013) .

Rheem S., Rheem I, & Oh S. (2017). Response Surface Methodology Using a Fullest Balanced Model: A Re-Analysis of a Dataset in the Korean Journal for Food Science of Animal Resources. Korean Journal for Food Science of Animal Resources, 37(1), 139-146.

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Adiponectin, Visfatin, and Physical Function

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Descriptive data are presented as mean and standard deviation (S.D.) for continuous variables and frequencies and percentages for categorical variables. Group comparison was performed using the Chi-square test in categorical variables, and two-sample Student’s t-test incontinuous variables. All of the variables underwent a normal assumption check. For those variables with non-normality, a log transformation was applied, and the results were presented in the original scales. Linear regression models with variable selection examined the association of functional limitations with all the potential predictors, and the model fitting results suggested that age, gender, adiponectin and visfatin were significant to the functional outcomes. Then we investigated the effect of adiponectin and visfatin on physical function measures, controlling for age, gender and metabolic comorbidities such as hypertension, diabetes and hyperlipidemia.
The data analysis for this paper was generated using SAS/STAT and SAS/GRAPH software, Version 9.3 of the SAS System for Windows. Copyright © 2002–2010, SAS Institute Inc. SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc., Cary, NC, USA.

SHAH K.N., MAJEED Z., YANG H., GUIDO J.J., HILTON T.N., POLESSKAYA O., HALL W.J, & LUQUE A.E. (2015). FUNCTIONAL LIMITATIONS AND ADIPOKINES IN HIV-INFECTED OLDER ADULTS. The Journal of frailty & aging, 4(1), 41-46.

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Statistical Modeling and Visualization Protocol

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Data were analyzed by the use of SAS software. SAS/STAT (2013) was employed for
the statistical modeling of data. Graphs were produced by SAS/GRAPH (2013).

Rheem S., Rheem I, & Oh S. (2019). Improving the Quality of Response Surface Analysis of an Experiment for Coffee-supplemented Milk Beverage: II. Heterogeneous Third-order Models and Multi-response Optimization. Food Science of Animal Resources, 39(2), 222-228.

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Efficacy of MCO Dialyzer Prototypes

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Analyses were performed using SAS statistical analysis software [SAS, SAS/GRAPH, SAS/STAT; version 9.2 of SAS for Windows (SAS Institute Inc, Cary, NC, USA)]. Treatment effects were evaluated using a two-sided significance level of 0.050.
The intent-to-treat (ITT) population included all patients who received at least one study treatment. The ITT full analysis set included all patients who received at least one MCO HD treatment and one treatment with either high-flux dialyzer. Analyses of the primary and secondary efficacy end points used the ITT full analysis set.
When a laboratory value for any of the efficacy end points or for the safety analysis of the M_D of albumin was below the lower limit of detection (LLOD), an imputed value of LLOD/√2 was used.
For the primary analysis of the λFLC K_ovr, the mean within-patient difference in K_ovr of λFLC between HD with each MCO dialyzer prototype and either HD or HDF was analyzed using a mixed model that included fixed effects of period, study dialyzer type and the random effect of subject.
The null hypothesis was that there was no difference in the λFLC K_ovr between HD with any MCO dialyzer and treatment with either high-flux dialyzer. The corresponding alternative hypothesis was that there was a difference in the K_ovr.
The secondary efficacy end points were analyzed using the same mixed model.

Kirsch A.H., Lyko R., Nilsson L.G., Beck W., Amdahl M., Lechner P., Schneider A., Wanner C., Rosenkranz A.R, & Krieter D.H. (2016). Performance of hemodialysis with novel medium cut-off dialyzers. Nephrology Dialysis Transplantation, 32(1), 165-172.

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Statistical Modeling of Research Data

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Data were analyzed using SAS software. SAS/STAT [16 ] was employed for the statistical modeling of the data. Graphs
were produced using SAS/GRAPH [16 ].

Dang T.D., Yong C.C., Rheem S, & Oh S. (2021). Optimizing the composition of the medium for the viable cells of Bifidobacterium animalis subsp. lactis JNU306 using response surface methodology. Journal of Animal Science and Technology, 63(3), 603-613.

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