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Spss statistical analysis software for windows version 23

Manufactured by IBM
Sourced in United States

SPSS Statistical Analysis Software for Windows, version 23.0, is a comprehensive software package for statistical analysis. It provides a wide range of analytical tools and techniques for data manipulation, exploration, and modeling. The software is designed to facilitate the analysis of complex data sets and assist in making informed decisions based on statistical inferences.

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2 protocols using spss statistical analysis software for windows version 23

1

Dietary Intervention for MAFLD Remission

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Sample size calculations were carried out in PASS 15.0.5 software (NCSS, Kaysville, UT, USA) based on the data from Properzi et al. (26 (link)). To find an expected difference of 25% in MAFLD remission between groups after the 12-week intervention, considering a significance level of 5%, power of at least 80%, and allowing for 10% dropout, the study aimed to recruit 60 subjects. At least 27 subjects from each dietary group were required to detect diet-induced differences.
The case report form (CRF) was strictly reviewed by the quality control team and entered into the management system after confirmation. All follow-up data were recorded and time checked before being entered into the system.
At the end of the study, endpoints were analyzed based on the intention-to-treat method. IBM SPSS Statistical Analysis Software for Windows, version 23.0, was used for statistical analysis. After baseline values were adjusted, differences in macronutrient and clinical indicator outcomes between groups were examined using repeated measures analysis of covariance (ANCOVA). The Fisher's permutation test was used to assess the independence of the main outcome of this trial. Paired t-tests or nonparametric Wilcoxon signed-rank tests were used to analyze statistical differences within groups. The significance was determined using a p-value threshold of 0.05.
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2

Statistical Analysis for Adrenalectomy Outcomes

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Continuous variables were expressed as means and standard deviations (SDs) or as medians with interquartile ranges (IQRs). Categorical variables were expressed as numbers and percentages. Comparisons between groups were made by way of analysis of variance or Student's t-test for continuous variables and by the chi-squared test or Fisher's exact test for categorical variables. The Kolmogorov-Smirnov test was performed to determine the normality of distribution of the parameters. If the resulting data did not show a normal distribution, the geometric mean±standard deviation was reported; the Mann-Whitney U test or Kruskal-Wallis test was used for multiple comparisons. Multivariate logistic regression analysis was performed to identify independent predictors of AKI after adrenalectomy. The results of the logistic regression analysis were presented as odds ratios (ORs) and 95% confidence intervals (CIs). Statistical significance was defined as p<0.05. Data were analyzed using IBM SPSS statistical analysis software for Windows version 23.0 (IBM Corporation, Armonk, NY, USA) and SAS software version 9.4 (SAS Institute, Cary, NC, USA).
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