Statistical package for social science spss version 23

Continuous and categorical variables were described as medians (interquartile ranges - IQRs) and frequencies (percentages - %), respectively. The univariate analysis of 28-day mortality rate risk associations was performed using Mann-Whitney and Chi-square tests, where appropriate, for day 0 and day 3 variables. The multivariate backward stepwise logistic regression included day 0 and day 3 variables with p < 0.10 on univariate analysis and excluded variables with p > 0,10 from the final model. Survival analysis used the Kaplan-Meier method. Statistical significance was defined as p ≤ 0.05. Statistical analysis was performed using IBM Statistical Package for Social Science (SPSS), version 23 (IBM Corp, North Castle, NY, US).

Data were collected, coded, and entered into IBM Statistical Package for Social Science (SPSS) version 23. Parametric numerical data were described by mean and standard deviation, while nonparametric numerical data was described by median and interquartile range (IQR). Non-numerical variables were presented as frequency and percentage. Analyses of qualitative variables were performed by chi-square. Parametric variables were analyzed by independent t-test, and nonparametric variables were analyzed by Mann–Whitney U test. Using receiver operating characteristic curves (ROC), we determined the prediction utility of brachial artery FMD% for no-reflow. The margin of error accepted was set to 5% by setting the confidence interval to 95%, so the p-value was considered significant if p < 0.05.

Data were analysed using the IBM Statistical Package for Social Science (SPSS) version 23 (SPSS Inc., Chicago, IL, USA). Descriptive analyses were conducted to identify the frequencies for the categorical variables, and the mean and standard deviation for the continuous variables. One-way analysis of variance and the independent-sample t-test were used to assess the differences in IIFAS scores between particular groups. Simple logistic regression was used to determine the significance of the variables, with a p-value < 0.25 being the threshold for inclusion in the multiple logistic regression [7 ]. Further analysis, using multiple logistic regression, was conducted to calculate the odds ratio and associated 95% confidence interval for predictors of breastfeeding attitude among mothers with premature infants in NICUs in Selangor. A p-value of 0.05 was considered statistically significant.

Data were documented and described using Microsoft Excel (Microsoft Corporation, Redmond, USA). Further analyses were performed using the IBM Statistical Package for Social Science (SPSS) version 23 (IBM Corporation, Armonk, USA). Categorical variables were presented as numbers and percent, and continuous variables as median with range. Cases were grouped for T-RAMIE or H-RAMIE. Comparisons between groups were performed with Fisher’s exact test, Chi-squared test, or Mann–Whitney U test. For postoperative complications, the risk ratio (RR) was calculated, comparing the chance to experience complications for the analyzed groups treated with H-RAMIE (= exposed group) and T-RAMIE. 95% confidence intervals (CI) for RR and p-values resulting from Fisher’s exact test were calculated. Statistical significance was considered with p-values of less than 0.05.

Statistical analysis described discrete variables through count and percentage and continuous variables using mean (SD) or median (Q1, Q3), where appropriate. The Pearson coefficient was used to test correlations between continuous variables. Univariate analysis of continuous variables was performed using the t-test or the Mann-Whitney U test as a non-parametric alternative where appropriate. Chi-square and Fisher’s exact tests were used for categorical variables. Multivariable analysis in backward stepwise logistic regression was performed using variables with p value ≤0.10 in univariable analysis. For multivariate statistical analysis the etiology of liver cirrhosis was dichotomized to compare between “alcohol alone or combined” versus “all other causes” and, similarly, precipitant events of clinical decompensation were categorized into “infection”, “bleeding” and “other”. Statistical significance was defined as p-value ≤0.05. Statistical analysis was performed using IBM Statistical Package for Social Science (SPSS), version 23 (IBM Corp, North Castle, NY, US).

For data entry and analysis, IBM’s Statistical Package for Social Science (SPSS) version 23 (Chicago, IL, USA) was used. For the quantitative data analysis, basic frequencies and percentages and the means and standard deviations were used to describe and compare responses among individuals. Paired t-tests and chi-square tests were used to compare the means at baseline and in the weeks before and after. Repeated analysis of variance measurements was used to investigate the effects of the KD on changes in the anthropometric measurements over time. p < 0.05 was chosen as the statistical significance level [25 (link)].