Sas package

Manufactured by SAS Institute

Sourced in United States

The SAS package is a comprehensive software suite designed for data analysis, statistical modeling, and business intelligence. It provides a wide range of tools and functionalities for managing, analyzing, and visualizing data from various sources. The core function of the SAS package is to enable users to perform advanced statistical analysis, predictive modeling, and business reporting, facilitating data-driven decision-making.

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Lab products found in correlation

Spss v13.0 for windows, by IBM (1 mentions)

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SAS) version 9.1 statistical package SAS statistical software package, version SAS statistical software package version 6.12 Sas software package version 8.2 SAS statistical package, version SAS package 8.2 SAS 8.2 statistical package SAS 9.3 statistical package SAS/STAT statistical package SAS statistical package for Windows

54 protocols using sas package

Cardiovascular Risk Factors and Arterial Calcification

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Continuous data are presented as the mean ( ± standard deviation). Categorical variables are presented as counts (proportions). T-tests were performed to test for significant differences in continuous parameters between two or more groups. The χ2 or Fisher exact test (based on expected frequency) was used to compare categorical variables between groups. The Bonferroni method was used for post hoc tests. We adjusted the p level according to the number of hypotheses tested. Logistic regression analysis [with odds ratios (OR) and confidence intervals (CI)] was used to evaluate the association between CVRF and calcification. From univariate analysis, we selected variables with p < 0.10 (statistical criterion). Variables were eliminated from highest to lowest p in the multivariate model, but remained in the final model if p was less than 0.05 or seemed to be confounding (more than 10% change in estimate). All two-way interactions between pairs of predictors in the model were tested one at a time. p < 0.05 was considered statistically significant when no Bonferroni correction was applied. Data were analyzed with SAS packages (SAS Institute Inc. version 9.4, Cary, NC).
CVRF and calcifications were analyzed by comparing the arterial territories (CA, FA and IPA) in pathological arteries.

Steenman M., Espitia O., Maurel B., Guyomarch B., Heymann M.F., Pistorius M.A., Ory B., Heymann D., Houlgatte R., Gouëffic Y, & Quillard T. (2018). Identification of genomic differences among peripheral arterial beds in atherosclerotic and healthy arteries. Scientific Reports, 8, 3940.

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Statistical Analysis of Categorical and Continuous Data

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Data were analysed with SAS packages (SAS Institute Inc., Cary, NC). Chi2 or Fisher's exact tests were used to compare categorical variables. The t-test, Mann-Whitney, Kruskall-Wallis tests were performed to test for differences in continuous parameters. Means with standard deviations or medians with quartile data are presented as appropriate. A two-sided P-value<0.05 was considered as statistically significant in all tests.

Andorin A., Gourraud J.B., Mansourati J., Fouchard S., le Marec H., Maury P., Mabo P., Hermida J.S., Deharo J.C., Delasalle B., Esnault S., Sadoul N., Davy J.M., Leenhardt A., Klug D., Defaye P., Babuty D., Sacher F, & Probst V. (2017). The QUIDAM study: Hydroquinidine therapy for the management of Brugada syndrome patients at high arrhythmic risk. Heart rhythm, 14(8).

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Statistical Analysis of Clinical Data

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Data were analyzed with SAS packages (SAS Institute Inc., Cary, NC). The Chi2 or Fisher exact tests were used to compare categorical variables. The t-test, Mann-Whitney, Kruskall Wallis tests were performed to test for differences in continuous parameters. ECG baseline data were corrected for age using linear regression model. Mean data were presented with standard deviation. Time data were presented with median [1 st -3 rd quartile]. Time from diagnosis to the first event was analyzed with Cox proportional hazards model. Hazards ratios (HR), confidence intervals (CI) and p-values were calculated in univariate analysis. Log-rank p-value was used if Cox model was not relevant. Multivariate analysis was adjusted on variable with p-value<0.15 in univariate analysis using Cox model. Survival curves were plotted by the Kaplan Meier method. A p-value <0.05 was considered statistically significant.
The authors had full access to and take full responsibility for the integrity of the data.
All authors have read and agree to the manuscript as written.

Andorin A., Behr E.R., Denjoy I., Crotti L., Dagradi F., Jesel L., Sacher F., Petit B., Mabo P., Maltret A., Wong L.C., Degand B., Bertaux G., Maury P., Dulac Y., Delasalle B., Gourraud J.B., Babuty D., Blom N.A., Schwartz P.J., Wilde A.A, & Probst V. (2016). Impact of clinical and genetic findings on the management of young patients with Brugada syndrome. Heart rhythm, 13(6).

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Statistical Analysis of Sow Experiment

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Data generated in the present study was subjected to statistical analysis using the general linear model procedure of SAS package [19 ] (SAS Inst. Inc., Cary, NC, USA) in a complete block design. When significant difference were identified among treatment means, they were separated using Tukey’s honestly significant difference test. Individual sow was used as experimental unit for analysis of all variables. Probability values of ≤0.05 were considered significant in both experiments.

Choi Y., Hosseindoust A., Shim Y., Kim M., Kumar A., Oh S., Kim Y, & Chae B.J. (2017). Evaluation of high nutrient diets on litter performance of heat-stressed lactating sows. Asian-Australasian Journal of Animal Sciences, 30(11), 1598-1604.

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Mammary Tumor Analysis in Mice

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Statistical analysis was performed using the SAS package (release 9.1, SAS Institute Inc., NC, USA). Data are expressed as the mean ± SD. One-way analysis of variance (ANOVA) and Duncan's multiple test were used to determine statistical differences between the treatment groups. Interactions between two variables were examined using two-way ANOVA. P-values less than 0.05 were considered significant. Only two mice developed mammary tumors in the OVX+ND group; therefore, statistical analyses on tumor tissue were performed for animals in the SHAM+ND, SHAM+HD, and OVX+HD groups using one-way ANOVA.

Kim J., Lee Y.H., Park J.H, & Sung M.K. (2015). Estrogen deprivation and excess energy supply accelerate 7,12-dimethylbenz(a)anthracene-induced mammary tumor growth in C3H/HeN mice. Nutrition Research and Practice, 9(6), 628-636.

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Statistical Analysis of Outcome Data

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All outcome data were analyzed by the SAS package (Version 9.3; SAS Institute Inc.) with intention-to-treat approach. t-test or Mann–Whitney rank test was used to analyze the continuous data. Pearson's Chi-square test or Fisher's exact test was used to analyze the categorical data. P < .05 was set as the statistical significance level.

Xue X.C., Qi X.X, & Wan X.Y. (2017). Randomized controlled study of efficacy and safety of drotaverine hydrochloride in patients with irritable bowel syndrome. Medicine, 96(51), e9235.

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Analyzing CPRS Effects Using SAS

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Data were analyzed using the MIXED procedure of the SAS package program (SAS Inst. Inc., Cary, NC, USA) as a completely randomized software. The model was,
where μ is the average value, T_i is the treatment value, B_j is a random value, and E_ij(t) is the error value. The model included CPRS as the fixed effect and season as the random effect. Pairwise comparisons were performed to determine the CPRS effect using the TTEST option. Orthogonal contrasts were used to determine the CPRS effect, location effect, and interaction between the CPRS and location effect using the CONTRAST option. Least squares mean values were assessed using a pairwise comparison method and the orthogonal contrast method. Treatment effects were considered significant at p<0.05, and trends were considered at 0.05≤p<0.10.

Choi Y., Ha D.M., Lee S, & Kim D.H. (2021). Effect of aerobically treated manure on odorous material emissions from a swine finishing barn equipped with a continuous pit recirculation system. Animal Bioscience, 35(2), 308-316.

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Statistical Analysis of Outcome Measurements

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In this study, all outcome measurements were analyzed by the SAS package (Version 9.1; SAS Institute Inc., Cary, NC). Continuous values were analyzed by the t test or Mann–Whitney rank test, whereas the categorical values were performed by Pearson χ² test or Fisher exact test. The level of statistical significance was defined as P < .05.

Wang J.K, & Liu J. (2018). Neuromuscular electrical stimulation as an adjunctive therapy to drotaverine hydrochloride for treating patients with diarrhea-predominant irritable bowel syndrome: A retrospective study. Medicine, 97(29), e11478.

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Observational Study of Alirocumab Safety

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Due to the non-interventional observational study design, no formal sample size was determined. Quantitative data (eg, age) were analysed using means and SD or medians with IQRs, as appropriate. Qualitative data (eg, gender) were presented as proportions. 95% CIs were provided, if appropriate, for qualitative and quantitative data. Safety was analysed among all patients receiving at least one alirocumab dose (safety analysis set, SAS). Descriptive and efficacy variables were analysed in the full analysis set (FAS), which included all patients in SAS who met the selection criteria and had sufficient data for the primary analysis (at least one LDL-C value at baseline and on treatment). All statistical analyses were carried out using the SAS package (V.9.4, Cary, North Carolina, USA).

Steffens D., Bramlage P., Müller J., Dorn C., Paar W.D., Scheeff C., Kasner M, & Rauch-Kröhnert U. (2021). Intensified lipid-lowering treatment with alirocumab in patients with coronary heart disease. Open Heart, 8(1), e001572.

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Determinants of Cerebral Infarction in Warfarin Therapy

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Statistical analysis was performed using the Windows SPSS package (version 18.0, SPSS Inc., Chicago, IL, USA) and the SAS package (version 9.1.3, SAS Inc., Cary, NC, USA). Fisher's exact chi-square test was used for categorical variables and independent t-test or Kruskal-Wallis test for continuous variables, as appropriate. In the investigation of determinants for cerebral infarction or TIA on therapeutic warfarin treatment between the case and control group, categorical variables were compared with McNemar test or exact McNemar test and continuous variables with paired t-tests or Wilcoxon signed-rank test, as appropriate. To find independent factors that were associated with development of cerebral infarction or TIA while on optimal warfarin therapy, a conditional logistic regression analysis was performed using variables with p<0.05 on univariate analysis. Statistical significance was set at p<0.05.

Kim Y.D., Lee K.Y., Nam H.S., Han S.W., Lee J.Y., Cho H.J., Kim G.S., Kim S.H., Cha M.J., Ahn S.H., Oh S.H., Lee K.O., Jung Y.H., Choi H.Y., Han S.D., Lee H.S., Nam C.M., Kim E.H., Lee K.J., Song D., Park H.N, & Heo J.H. (2015). Factors Associated with Ischemic Stroke on Therapeutic Anticoagulation in Patients with Nonvalvular Atrial Fibrillation. Yonsei Medical Journal, 56(2), 410-417.

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