Sas eg version 7

Manufactured by SAS Institute

Sourced in United States

SAS EG version 7.1 is a software product designed for data management, analysis, and reporting. It provides a graphical user interface (GUI) for accessing and utilizing the SAS programming language. The core function of SAS EG is to facilitate data-driven decision-making through intuitive data exploration, transformation, and statistical analysis.

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SAS version (194 citations) SAS version 7.1 (32 citations) SAS 7.1 (22 citations) SAS EG 7.1 (16 citations) SAS EG statistical software version 7.1 (2 citations)

3 protocols using sas eg version 7

Pairwise Food-Phthalate Associations

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We examined associations between pairwise combinations of food groups and individual ln-transformed urinary phthalate metabolites using linear regression, accounting for multiple comparisons using a Benjamini-Hochberg false discovery rate correction of 0.1 for each set of 242 analyses per individual urinary phthalate metabolite [30 ].
We conducted RRR using SAS EG, version 7.1 (SAS Institute, Inc.); all other analyses were performed in R (Core Team. 2018. R: A language and environment for statistical computing. Vienna Austria:R Foundation for Statistical Computing).

Carwile J.L., Seshasayee S.M., Ahrens K.A., Hauser R., Chavarro J.E, & Fleisch A.F. (2021). Dietary Correlates of Urinary Phthalate Metabolite Concentrations in 6-19 Year Old Children and Adolescents. Environmental research, 204(Pt B), 112083.

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Trends in Canadian Emergency Department Hospitalizations

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Results of total and first-time ED hospitalizations were presented as rates, proportions, means and medians, by sex, age group, province/territory, discharge disposition, hospital length of stay and ED diagnosis. Age and sex-specific rates per 100,000 population were calculated, using Statistics Canada national population estimates (excl. QC), over the 13-year period (2010/11 to 2022/23). Age-standardized rates per 100,000 population were standardized to the 2011 Canadian population (excl. QC) by direct standardization. Annual trends were quantified using average annual percent change (AAPC). Age-standardized rates that have significantly changed over the study period, were identified by an AAPC that is significantly different from zero at the alpha = 0.05 level [28 ]. Linear regression was used to calculate the mean change in length of hospital stay and age at hospitalization during the study period.
SAS EG version 7.1 (SAS Institute Inc., Cary, NC, USA) was used to conduct all descriptive analyses. Joinpoint Regression Program version 5.0.2 (SEERStat, NCI, Bethesda, MD, USA) was used to conduct trend analyses. Cells with small counts between one and four as well as rates that would allow for calculation of small cells have been presented as a range, to reduce potential identification of individuals and comply with CIHI’s data sharing agreements.

Toigo S., Katzman D.K., Vyver E., McFaull S.R., Iynkkaran I, & Thompson W. (2024). Eating disorder hospitalizations among children and youth in Canada from 2010 to 2022: a population-based surveillance study using administrative data. Journal of Eating Disorders, 12, 3.

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Predictors of Postoperative Opioid Use

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Logistic regression was used to explore potential predictors of opioid use at 3 and 9 months after surgery. Covariates investigated include patient age and sex, neighbourhood income quintile, rural residence, procedure type (hernia vs cholecystectomy), institution teaching status, surgeons' years of experience and calendar year. In addition, further regression modelling for predictors of opioid use at 9 months was performed in three specific age categories (18-45, 46-64 and 65 and above). Ages 18-45 are the highest risk age group for opioid dependence, and the greater than 65 age group have been the most studied in the persistent opioid use paradigm. For all models, a generalized estimating equation (GEE) approach was used to account for the clustering of patients within physicians and institutions. A priori, a subgroup analysis assessing differences in the proportion of patients aged >65 years versus those aged 65 years or below with opioid prescriptions at 3 and 9 months after surgery was planned and completed using a chi-square test of association. For all analyses, reported p-values are from two-tailed tests where a value less than 0.05 was considered statistically significant. All analyses were performed using SAS EG version 7.1 (SAS Institute, Cary, NC, USA).

Clarke C., McClure A., Allen L., Hartford L., Van Koughnett J.A., Gray D., Murphy P.B., Vinden C., Leslie K, & Vogt K.N. (2022). Opioid use after outpatient elective general surgery: quantifying the burden of persistent use. British journal of pain, 16(4).

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