Data analysis was conducted in SAS 9.4 version (SAS Institute, Cary, NC, USA) using data from the electronic database created from observations. The average of the variable was used as the unit of analysis; variables were summed and divided by the number of games. Univariate analysis was conducted for all nutrition categories (total calories offered, calories for beverages only, calories for snacks only, total sugar, sugar for beverages and snacks only, sodium, carbohydrates, fat, saturated fat, fiber, protein, and cholesterol). Shapiro−Wilk normality tests were conducted on all continuous variables; data were normally distributed and met assumptions. Independent t-tests were used to test differences between baseline and comparison groups to determine similarity; additional paired t-tests were conducted to test for differences between the baseline and intervention group for caloric intake and macro/micronutrients (alpha level was set at p < 0.05). Each macro/micronutrient was averaged for a summation of the amount offered at each game. Because a number of games did not offer snacks or beverages, a separate analysis for these games occurred.
Sas 9.4 version
Manufactured by SAS Institute
Sourced in United States
SAS 9.4 is a software application developed by SAS Institute. It provides a comprehensive suite of tools for data management, analysis, and reporting. SAS 9.4 offers a wide range of functionalities, including data manipulation, statistical modeling, advanced analytics, and business intelligence capabilities. The software is designed to help organizations make data-driven decisions and gain insights from their data.
Automatically generated - may contain errors
Lab products found in correlation
46 protocols using sas 9.4 version
1
Nutritional Analysis of Game-Day Offerings
2
Welch's t-test Statistical Analysis
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
All data were analyzed by a two tailed, Welch’s t test. A p-value of 0.05 or less was considered statistically significant (SAS 9.4 version; SAS Institute Inc., Cary, NC, USA).
3
Assessing Nicotine Exposure and Quit Intention
4
Cataract and Blepharoptosis Association
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The data were expressed as numbers and percentage (categorical) or mean ± standard error (continuous). Differences in the distribution of continuous and categorical variables by cataract were evaluated using t-tests or the χ2 test, respectively. Multivariable adjusted logistic regression analysis was conducted to examine the odds ratio (OR) and 95% confidence interval (CI) for association of each specific type of cataract with presence of blepharoptosis. Model 1 was unadjusted, model 2 was only adjusted by age and sex, and model 3 was additionally adjusted by smoking, drinking, regular exercise, BMI, general income, education level, vitamin D (Vit D), and sun exposure, in addition to age and sex. Subgroup analysis was adjusted for age, sex, smoking, drinking, regular exercise, BMI, general income, education level, and Vit D level. Statistical analyses were performed using SAS 9.4 version software (SAS Institute, Cary, NC, USA) to account for the complex sampling design and provide national prevalence estimates. A p-value less than 0.05 was considered statistically significant.
5
Thalassemia and Gout Arthritis Risk
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
We conducted an absolute standardized difference (ASD) to assess the balance of baseline variables in the age and sex matched cohorts and PSM cohorts. In general, ASD < 0.10 indicates that the variable is balanced between the two groups. The Poisson regression model was used in estimating the incidence rate (per 100 patients-year) of gout arthritis and crude relative risk (and its 95%CI). We draw a Kaplan–Meier curve to observe the cumulative incidence of gouty arthritis since the index date. The log-rank test showed that the difference in the cumulative incidence of gouty arthritis between the thalassemia group and the controls when p < 0.05. Two models, the univariate model, and multivariate Cox proportional hazard regression were used to estimate the hazard ratio (HR) and 95% CI of gout arthritis for thalassemia exposure and covariates. Our data were analyzed using SAS 9.4 version software and p < 0.05 (2-sided) was considered statistically significant.
6
Sleepiness in Shift Bus Drivers
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
We used Chi-square tests and t-tests to identify differences in demographic and other variables between Daily two shift and Alternating day shift bus drivers. We conducted log-binomial regression analyses and produced prevalence ratios (PRs) for severe sleepiness (KSS ≥ 7) while driving with 95% confidence intervals (95% CI) to identify the difference in sleepiness for the five working time periods between groups. To evaluate the effect of the variables, we used univariate and multivariate models with adjustment for covariates. Statistical analyses were performed using SAS 9.4 version (SAS institute Inc., Cary, NC, US). The level of statistical significance was set at p < 0.05.
7
Impact of COVID-19 Pandemic on Prenatal Care
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Counts and percentages were calculated for categorical variables, mean and standard deviation were calculated for numeric variables. For bivariate analyses, Chi square tests were performed to assess the association between the pandemic or covariates and initiation or adequacy of prenatal care. Regarding multivariable analyses, first an unadjusted logistic regression model was performed to test the association between the pandemic and adequacy of prenatal care, and between the pandemic and early initiation of prenatal care. Second, the model was adjusted for the above-mentioned covariates. Finally, the pandemic*race was added to the adjusted model. A separate statistical model was computed for each stratum of race if the interaction term was significant. A p-value < 0.05 was considered statistically significant. SAS 9.4 version (SAS institute, Cary, NC) was utilized for data cleaning and data analysis.
8
Incidence of Iron Deficiency Anemia and Subsequent Risk of Immune-Mediated Rheumatic Diseases
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The incidence of IDA was calculated by dividing the number of newly diagnosed IDA cases by the total number of Korean women per year. The age-specific incidence rate of IDA was calculated by dividing the number of newly diagnosed IDA cases observed in a certain age group by the total number of same-aged Korean women per year. The χ2 test was performed for the descriptive statistics. Time from the initial diagnosis of IDA to the initial diagnosis of IRDs was calculated using the Kaplan–Meier estimator for the 10-year-follow-up period. The Cox proportional hazard model was implemented to estimate the RR of IRDs and 95% confidence intervals (CIs). All statistical analyses were performed using SAS 9.4 version (SAS Institute Inc., Cary, NC, USA) and the R version 2.13.
9
COVID-19 Severity and TG/HDL Ratio
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
We performed chi-square tests to evaluate the difference in categorical variables between groups. Independent t-tests were done to compare continuous variables between two groups. To evaluate the association between TG/HDL ratio and prognosis after COVID-19 infection, we used logistic regression analysis for the development of severe complications within 2 months. To better describe the relationship between TG/HDL ratio and severe complications of COVID-19, we illustrated smoothing spline plot based on the generalized additive regression model. In the multivariable analysis, age, gender, body mass index, alcohol consumption, smoking, physical activity, household income, hypertension, diabetes mellitus, chronic kidney disease, ischemic heart disease, stroke, asthma, malignancy, and level of total cholesterol were adjusted. Data manipulation and statistical analyses were performed using SAS 9.4 version (SAS Inc., Cary, NC, USA) and R 3.3.3 version (R Foundation for Statistical Computing, Vienna, Austria). A two-tailed p-value of less than 0.05 was considered statistically significant.
10
COVID-19 Serum Vitamin Levels in Critically Ill Patients
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
This pilot study included all 21 critically ill COVID-19 patients hospitalized in May 2020 in the ICU of North Suburban Medical Center, Thornton, Colorado, in whose care the principal investigator (C.A.) was involved. Their demographics are shown in the Tables below. All patients had consented to standard of care investigation and treatment. Collection of lab samples, including serum vitamin C and vitamin D levels, were part of the routine immunologic assessment of their severe infectious disease. All variables in this study were described using descriptive statistics. To compare serum level for survivors and non-survivors we used t-test for independent samples. For all statistical tests, an alpha level of 0.05 or less was considered statistically significant. All statistical analysis was done using SAS 9.4 version, SAS Institute, Cary, NC.
About PubCompare
Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.
We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.
However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.
Ready to get started?
Sign up for free.
Registration takes 20 seconds.
Available from any computer
No download required
Revolutionizing how scientists
search and build protocols!