Patients with missing data for any of the variables being examined were excluded from our final analysis. Continuous normally distributed variables are reported as means and SD, while categorical variables are reported as counts and percentages. Normally distributed data were compared using Analysis of variance (ANOVA), whereas non-parametric and categorical data were compared using Kruskal-Wallis and Χ2 tests, respectively. Standardised adjusted residuals were used for post-hoc analysis of Χ2 tests, with a level of greater than 1.96 (2.0 is used by convention) used to indicate statistical significance.49 Dunn multiple comparison test was used for post-hoc analysis of the Kruskal-Wallis test, while the Bonferroni procedure was used during post-hoc analysis for ANOVA. Statistical analysis was conducted using the SPSS V.25 package.
Spss v25 package
Manufactured by IBM
Sourced in United States
SPSS v25 is a comprehensive statistical analysis software package developed by IBM. It provides a wide range of advanced statistical techniques for data analysis, including regression, correlation, and hypothesis testing. The software is designed to handle large datasets and offers a user-friendly interface for researchers, analysts, and data scientists.
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Lab products found in correlation
3 protocols using spss v25 package
1
Statistical Analysis of Missing Data
2
Genetic Associations of Arylesterase Levels
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The arylesterase levels were sqrt-transformed in order to achieve a normal distribution. The mean values among the samples were compared using one-way ANOVA followed by Tukey honest significance test (HSD) for pairwise comparisons. The alleles, genotype frequencies, Hardy–Weinberg equilibrium, and Fisher’s exact test for samples’ differentiation for SNPs rs705379 and rs662 were estimated using Arlequin 3.5 software using Markov Chain model with 10,000 steps [46 (link)]. Finally, correlation among arylesterase levels (dependent variable) and genotypes for SNPs rs705379 and rs662 (independent variables) were analyzed using a multiple regression model, setting up age and gender as covariates. ANOVA, HSD, and multiple regression analysis were executed using the SPSS v25 package.
3
Multivariate Analysis of Environmental Factors
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A non-parametric Mann-Whitney U test was performed and Spearman's correlation coefficient was calculated for multiple comparisons or to analyze interactive effects between different factors. Principle component analysis (PCA) was conducted on the concentrations of TEs, ABs, and ARGs. Varimax rotation was applied because orthogonal rotation minimizes the number of variables with a high loading on each component and facilitates the interpretation of results. Statistical significance was defined as p?0.05. The data analysis was performed with the SPSS v25 package (Chicago, IL, US).
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