Spss statistic version 23

The statistical analyses were performed with IBM SPSS Statistic Version 23.0 (IBM Corp., Armonk, New York, USA). Quantitative data are expressed as medians with interquartile ranges (IQR). Pairwise comparisons for quantitative variables were performed with an unpaired t-test or Mann–Whitney U-Test. Categorical variables are given as frequencies and percentages, respectively, and for the comparisons of two or more patients groups a chi-square test was applied. Regarding the endpoint of death/need for liver transplantation (mortality), survival curves were analyzed using Kaplan–Meier curves and a log-rank test. The correlation of clinical und epidemiological factors with vitamin A was assessed by means of univariate analyses. Variables with a P < 0.1 in the univariable analysis were subsequently considered in a multivariate linear regression model for each score. To reliably identify factors associated with vitamin A deficiency, final forward multivariate model was built based on a stepwise variable selection procedure for each score. Our complete data analysis is exploratory. Hence, no adjustments for multiple testing were performed. For all tests, we used a 0.05 level to define statistically relevant deviations from the respective null hypothesis.

In order to determine whether there are significant differences between the probability distributions of the results for both campuses, a statistical analysis of the data obtained in the measurement campaigns was carried out. For this purpose, the probability distribution of the data was evaluated using the Kolmogorov–Smirnov test. Nonparametric test (the Mann–Whitney U test or the Kruskal–Wallis test) was applied to the non‐normally distributed means of data in order to examine the statistical significance of the possible difference between both campuses. Furthermore, the Spearman correlation test was determined between: (1) the satisfaction and the interference on the learning performance for each IEQ factor; (2) the satisfaction of IEQ factor and the overall satisfaction; and (3) interference of each IEQ factor and the overall interference.
In addition, a tendency analysis was carried out on the obtained datasets. Linear and polynomial fits were used to assess the relationship between the values of the subjective and objective IEQ factors. IBM SPSS statistic (version 23.0) was used to perform all the statistical analyses.

Descriptive and categorical variables are presented as median values with interquartile ranges (IQR 25th; 75th) or mean values with SD and frequencies with percentages. For the comparison of differences between groups of categorical variables, an unpaired t test or the Mann‐Whitney U test was used. The chi‐squared test was applied for the comparison of two or more patient‐groups. All tests were two‐tailed; statistically significant values were defined as p < 0.05. Univariable linear regression was used to examine correlations between demographic and clinical variables with the UI‐value of the EQ‐5D‐5L. All variables with a p value of < 0.05 in the univariable analysis were then analyzed in a multivariable linear regression model based on a stepwise variable selection process. For all data analyses and statistical tests, IBM SPSS Statistic Version 23.0 (IBM Corp.) was used. For all figures, Microsoft Excel 2016 (Microsoft Corp.) was used.

Descriptive analysis of data is expressed as median values with interquartile ranges (IQR 25th–75th). The Mann–Whitney U rank test was used to compare groups and to calculate differences between two groups with continuous variables. Categorical variables are presented as frequencies and percentages. For the comparison of two or more patient-groups, a chi-squared test was applied. All tests were two-tailed, statistically significant values were defined as P less than 0.05. All variables with P less than 0.05 and the clinical parameters age, sex and alcohol intake were then included into a multivariable logistic regression model to examine associations with NAFLD, fibrosis (LSM ≥8.2 kPa) and a FAST score greater than 0.35. Due to the large number of tests, P values should be interpreted with caution and in connection with effect estimates. For all data analysis and statistical tests, IBM SPSS Statistic Version 23.0 (IBM Corp., Armonk, New York, USA) was used. For all figures, Microsoft Excel 2016 (Microsoft Corp., Redmond, Washington, USA) was used.