Sas software v9.4 for windows

Manufactured by SAS Institute

Sourced in United States

SAS software v9.4 for Windows is a comprehensive data analysis and reporting tool. It provides a suite of applications for data management, statistical analysis, and visualization. The software is designed to work on the Windows operating system.

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Jmp pro 13, by SAS Institute (1 mentions) Jmp pro 16, by SAS Institute (1 mentions)

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SAS for Window v9.4 SAS for Windows v9.4 SAS software for Windows SAS software v9.4 SAS for Windows SAS v9.4 SAS software

6 protocols using sas software v9.4 for windows

Systematic Review of MERS-CoV Epidemiology

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Detailed review of current literature was conducted using the five-step model of Khan et al. [24 (link)]. The literature searches on PubMed used following keywords: “Middle East Respiratory Syndrome”, “MERS” and “MERS CoV”. The article’s potential relevance to our topic was examined initially by article title then by abstract content. Included papers were case reports and articles on phylogenetics, healthcare related outbreaks and epidemiology, and we excluded papers on viral structure and model organism research. Relevant publications from national and international public health agencies were reviewed as well. WHO’s Disease Outbreak News and MERS risk assessments spanning September 2012 to June 2016 were used as primary sources to create a map of global transmissions [1 ]. The data were supplemented with the European Centre for Disease Prevention and Control (ECDC)’s Communicable Disease Threats Reports and Korean Center for Disease Control and Prevention (KCDC) and KMoH reports published online [25 , 26 ]. Number of cases in hospital settings and non-hospital settings were compared using Mann-Whitney U test in SAS software v9.4 for Windows [27 ]. Following the literature review, forest plots of basic reproduction numbers were created using DistillerSR Forest Plot Generator [28 ].

Min J., Cella E., Ciccozzi M., Pelosi A., Salemi M, & Prosperi M. (2016). The global spread of Middle East respiratory syndrome: an analysis fusing traditional epidemiological tracing and molecular phylodynamics. Global Health Research and Policy, 1, 14.

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Cytokine Profiles in Eosinophilic Granulomatosis

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The numbers of enrolled patients and controls were based on study feasibility, with a recruitment period running from March 2012 to March 2015. Laboratory values are given as median [interquartile range (IQR)]. Cytokine/chemokine levels, according to groups (active EGPA vs. asthma, HES or controls), were compared using SAS PROC LIFEREG, which allowed for the analysis of normal and log-normal censored cytokine data. Cytokine/chemokine levels were also compared in the 10 patients with EGPA who had serum samples collected at the times of active disease and in remission, using paired Mann-Whitney tests. The Bonferroni correction was used for adjustment to p-values for multiple comparisons, with only p-values ≤0.00093 considered significant (16 (link)). Analyses were performed using SAS Software v. 9.4 for Windows (SAS Institute Inc., Cary, NC, USA).

Pagnoux C., Nair P., Xi Y., Khalidi N.A., Carette S., Cuthberston D., Grayson P.C., Koening C.L., Langford C.A., McAlear C.A., Moreland L.W., Monach P.A., Seo P., Specks U., Sreih A.G., Ytterberg S.R., Tyrrell P.N, & Merkel P.A. (2019). Serum cytokine and chemokine levels in patients with eosinophilic granulomatosis with polyangiitis, hypereosinophilic syndrome, or eosinophilic asthma. Clinical and experimental rheumatology, 37(Suppl 117), 40-44.

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Examining Education and Relationship Status

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A logistic regression model was used to examine the associations between the study groups and level of education and relationship status. The analysis of covariance (ANCOVA) with pairwise comparison with Dunnett’s adjustment was used to determine differences between study groups.
Statistical analyses were conducted with the SAS® software v.9.4 for Windows (SAS Institute Inc., Cary, NC, USA). The level of statistical significance was α = 0.05.

Salakari M., Nurminen R., Sillanmäki L., Pylkkänen L, & Suominen S. (2019). The importance of and satisfaction with sex life among breast cancer survivors in comparison with healthy female controls and women with mental depression or arterial hypertension: results from the Finnish nationwide HeSSup cohort study. Supportive Care in Cancer, 28(8), 3847-3854.

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Factors Affecting BALF Recovery Rate

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The mean or median of continuous data (depending on their distribution) and range were calculated. Counts and percentages were determined for categorical data. The Mann–Whitney U test or one‐way analysis of variance was used to compare the means (or medians). The cut‐off value for good recovery was determined by the average recovery rate. A receiver operating characteristic (ROC) curve analysis was performed to obtain the parameters that affected the recovery rate of BALF. Univariate and multivariate logistic regression analyses were used to identify factors independently affecting the recovery rate of BALF. The independent variables included in the analysis were age, sex, smoking status, disease, use of the bronchus for the procedure and pulmonary function. The same analysis was performed on patients with CFIP. Discrimination through the multivariate logistic regression was assessed using C‐statistics. Two‐sided p‐values of <0.05 were considered statistically significant, and all analyses were performed with SAS software v.9.4 for Windows (SAS Institute Inc., Cary, NC, USA) and JMP Pro 13.2.0 software (SAS Institute Inc. Cary, NC, USA).

Shikano K., Abe M., Shiko Y., Tsushima K., Yoshioka K., Ishiwata T., Kawasaki T., Ikari J., Terada J., Kawasaki Y, & Tatsumi K. (2021). What are the factors affecting the recovery rate of bronchoalveolar lavage fluid?. The Clinical Respiratory Journal, 16(2), 142-151.

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Statistical Analysis of Continuous and Categorical Data

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The median and range of continuous data were calculated. Counts and percentages were determined for categorical data. Continuous data were analyzed using the Wilcoxon rank‐sum test and categorical data were analyzed using the Fisher's exact test. Two‐sided p values of <0.05 were considered statistically significant. All analyses were performed using SAS software v.9.4 for Windows (SAS Institute Inc., Cary, NC, USA) and JMP pro 16.0.0 software (SAS Institute Inc. Cary, NC, USA).

Shikano K., Abe M., Hirama R., Kitahara S., Maruyama K., Horiuchi D., Sakuma N., Ishii D., Kawasaki T., Nakamura H, & Suzuki T. (2023). A retrospective comparison between digital to conventional drainage systems for secondary spontaneous pneumothorax related to diffuse interstitial lung disease. The Clinical Respiratory Journal, 17(8), 733-739.

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Vascular Risk Profile in Cancer-Associated Ischemic Stroke

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Demographic and clinical variables were compared using χ² or Fisher’s exact test for categorical variables and two-sided two-sample t test for continuous variables as appropriate. Cancer incidence rate was determined using the same direct age-standardization method with Segi’s world population as the 2015 SCR report [19 ]. Complete case multivariable logistic regression was performed to identify differences in the vascular risk profile of cancer-IS and non-cancer-IS patients. The inclusion criteria for multivariable analysis were p < 0.1 on univariate analysis and no missing data. Statistical significance was set at p ≤ 0.05. Analyses were performed using SAS software v9.4 for Windows (SAS, Inc, Cary, NC, USA).

Tang K.J., Saffari S.E., Narasimhalu K., Queck K.K, & De Silva D.A. (2023). Non-Hypertensives and Those with Normal Cholesterol Are More Likely to Have Concomitant Cancer amongst Patients with Ischemic Stroke: A Retrospective Cross-Sectional Registry-Based Study. Cerebrovascular Diseases Extra, 13(1), 75-82.

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