Statistical analyses were performed using Microsoft Excel for Office 365, SAS Software Package for Windows V9.4 (SAS Institute GmbH, Heidelberg, Germany) and STATISTICA 10.0 (StatSoft, Inc., Tulsa, U.S.). All statistical tests were two‐sided at significance level alpha = 0.05.
Sas software package for windows v9
Manufactured by SAS Institute
Sourced in United States
The SAS Software Package for Windows V9.4 is a comprehensive data analysis and statistical software suite. It provides a range of tools and functionalities for data management, statistical modeling, and advanced analytics. The software package is designed to run on the Windows operating system.
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Lab products found in correlation
4 protocols using sas software package for windows v9
1
Statistical Analysis of Research Data
2
Statistical Analyses of Experimental Data
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Statistical analyses were performed using Microsoft Excel for Office 365 (Microsoft Corporation, Redmond, Washington, United States), SAS Software Package for Windows V9.4 (SAS Institute GmbH, Heidelberg, Germany) and GraphPad Prism V8 (GraphPad Software, San Diego, California, United States).
The normal distribution of data was assessed using a Shapiro–Wilk's test. If normal distribution was confirmed, a repeated measure analysis of variance (RM‐ANOVA) with post‐hoc pairwise comparison was performed. If the normality hypothesis was rejected, Blom‐transformed ranks of the original data were assessed using a RM‐ANOVA with post‐hoc pairwise comparison or original data were assessed by using a Wilcoxon sign rank test. All statistical tests were two‐sided at significance level alpha = 0.05.
The normal distribution of data was assessed using a Shapiro–Wilk's test. If normal distribution was confirmed, a repeated measure analysis of variance (RM‐ANOVA) with post‐hoc pairwise comparison was performed. If the normality hypothesis was rejected, Blom‐transformed ranks of the original data were assessed using a RM‐ANOVA with post‐hoc pairwise comparison or original data were assessed by using a Wilcoxon sign rank test. All statistical tests were two‐sided at significance level alpha = 0.05.
3
Statistical Analysis of Skinly Data
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For the statistical analysis of Skinly data, we worked with SciPy as the main Python package. To check the data distributions, we used the Shapiro Wilk's test for all parameters. We chose corresponding statistical tests to check significance, depending on the type of data that we wanted to analyze. All statistical tests were two‐sided at a significance level α = 0.05.
By cause of validating the Skinly parameters with the standard measurement devices, we used time series techniques such as moving averages smoothing, since the measuring principle of Skinly was tracking the skin every day. We have generally used the moving rolling average of the last 14 measurements as the single value of the parameter.
All other data were analyzed for statistical analyses with Microsoft Excel (Microsoft, USA) for Office 365, the SAS Software Package for Windows V9.4 (SAS Institute GmbH, Heidelberg, Germany) and STATISTICA 10.0 (StatSoft, Inc., Tulsa, USA).
By cause of validating the Skinly parameters with the standard measurement devices, we used time series techniques such as moving averages smoothing, since the measuring principle of Skinly was tracking the skin every day. We have generally used the moving rolling average of the last 14 measurements as the single value of the parameter.
All other data were analyzed for statistical analyses with Microsoft Excel (Microsoft, USA) for Office 365, the SAS Software Package for Windows V9.4 (SAS Institute GmbH, Heidelberg, Germany) and STATISTICA 10.0 (StatSoft, Inc., Tulsa, USA).
4
Skin Barrier Assessment: Comprehensive Statistical Analyses
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Statistical analyses were performed using Microsoft Excel 2010 and the Microsoft Excel 2013 (XP; Microsoft Corp., Redmond, WA, USA), the SAS Software Package for Windows V9.4 (SAS Institute GmbH, Heidelberg, Germany), and STATISTICA 12.0 (StatSoft, Inc., Tulsa, OK, USA). All statistical tests were two-sided at significance level alpha = 0.05.
For study I, the less pronounced effect could be expected for TEWL measurements (c.f. delta = 0.75, SD = 1.73). To achieve a power of at least 80% with a paired t-test, a sample of n = 44 was necessary. For corneometry, a higher effect was expected, thus n = 44 was considered sufficient here.
For study II, based on our experience with gene expression analyses in suction blisters of subjects with dry skin in a similar study design [21] , we derived empirically the minimum number of subjects needed. Significance (adjusted p value ≤0.05; experimentwise error rate is controlled) is tested by applying Wilcoxon's signed rank test with p value adjustment according to Benjamini and Hochberg; in order to control, the false discovery rate was used.
For study I, the less pronounced effect could be expected for TEWL measurements (c.f. delta = 0.75, SD = 1.73). To achieve a power of at least 80% with a paired t-test, a sample of n = 44 was necessary. For corneometry, a higher effect was expected, thus n = 44 was considered sufficient here.
For study II, based on our experience with gene expression analyses in suction blisters of subjects with dry skin in a similar study design [21] , we derived empirically the minimum number of subjects needed. Significance (adjusted p value ≤0.05; experimentwise error rate is controlled) is tested by applying Wilcoxon's signed rank test with p value adjustment according to Benjamini and Hochberg; in order to control, the false discovery rate was used.
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