Spss statistic version 25

Quantitative data are expressed as medians with interquartile ranges (IQR). Categorical variables are given as frequencies and percentages, respectively. First, the correlation of demographic and clinical variables with the raw scores of the sub-scales of the HLQ were assessed by means of univariable analyses. Correlation analyses were conducted using Spearman’s rank correlation and point-biserial correlation. Variables with p <0.1 in the univariable analysis were subsequently considered in a multivariable linear regression model for each sub-scale. To reliably identify factors being associated with poorer health literacy, the final multivariable models were built based on a stepwise variable selection procedure for each scale. Only patients with complete datasets were included into the respective analyses.
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. However, due to the large number of tests, p-values should be interpreted with caution. Data were analysed using IBM SPSS Statistic Version 25.0 (Armonk, NY: IBM Corp.). Figure was drawn with GraphPad Prism Version 8.0.2 (GraphPad Software, California, US).

Statistical analysis was performed with SPSS Statistic version 25.0 (IBM Company, Armonk, NY; USA). Some variables in this study did not follow a normal distribution. Since the sample size was small (21 infants), we considered it more appropriate to use nonparametric methods. Therefore, quantitative variables were expressed as medians and interquartile ranges (IQRs), and qualitative variables were expressed as a relative frequency and sample size (n). The U Mann–Whitney test was used to analyze differences in the variables according to diet supplementation, and Spearman’s rho correlations (r) were used to determine the association between variables. Statistical significance was defined as p < 0.05.

Percentages were used for categorical data. The mean and standard deviation were used for continuous data after the normality assumption was validated, and a paired t-test was used in the analysis. Characteristics of the data between groups were analyzed by analysis of variance (ANOVA). The correlation of the data was measured using Pearson correlation coefficients. An r value of more than 0.3 or less than −0.3 confirmed a statistical correlation [20 (link)], and a p value of less than 0.05 indicated statistical significance. Interobserver reliability testing was performed using the Intraclass Correlation Coefficient (ICC). All statistical calculations were performed on IBM SPSS Statistic version 25.0 (IBM Corporation, Armonk, NY, USA).