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Spss statistics v 26.0 for windows

Manufactured by IBM
Sourced in United States

SPSS Statistics V.26.0 for Windows is a software application that provides statistical analysis and data management capabilities. It is designed to help users analyze and interpret data, generate reports, and visualize findings. The software offers a range of statistical techniques, including regression analysis, correlation, and hypothesis testing, among others. SPSS Statistics V.26.0 for Windows is compatible with the Windows operating system.

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Lab products found in correlation

4 protocols using spss statistics v 26.0 for windows

1

Assessing Kidney Transplant Outcomes

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A descriptive analysis of the results was undertaken, expressing the quantitative variables as the mean ± standard deviation for parametric data or median and interquartile range (IQR) for non-parametric data. Categorical variables were expressed as numbers and percentages. For univariate comparisons of numerical variables, the t-test and chi-square test were used. Correlations between biochemical parameters (s-Kl, FGF-23 and GFR) were performed by univariate regression. We performed multivariate linear regression analysis of factors associated with s-Kl at three months post-transplant. A repeated-measures ANOVA model was used to evaluate pre- and post-KT differences in the s-Kl levels and FGF-23 levels over time.
Statistical analysis was performed with SPSS Statistics V26.0 for Windows (IBM Corp., Armonk, NY, USA) and the significance was set at p < 0.05.
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2

Discriminant Analysis of 18F-FDG and MRI

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Descriptive statistics were performed with GraphPad Prism 9.1 (GraphPad Software, La Jolla, CA, USA). Significance was accepted at the 95% probability level.
Discriminant analysis was performed using SPSS Statistics v26.0 for Windows (IBM Armonk, NY, USA) with general discriminant modeling. The independent variables (predictor variables) used to predict the grouping variable (CON vs. VSS) were regional relative VOI uptake data for 18F-FDG and MR GMV values. VOI data were entered independently into the discriminant function at once. For all analyses, a leave-one-out post-hoc classification was performed, only these data are reported. Receiver operating characteristic (ROC) analysis was performed for the significant discriminant 18F-FDG and MR GM VOIs to assess the diagnostic accuracy in discriminating between the VSS and CON groups.
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3

Analysis of 30-day Diary Data

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Data were tabulated in Excel (Office 365 for Windows V.64). Descriptive statistics, χ² analysis for comparisons of categorical variables, regression analysis, Friedman test for comparisons between groups of ordinal variables with repeated measures and Wilcoxon signed-rank test were performed with SPSS Statistics V.26.0 for Windows (IBM, Armonk, New York: IBM). Violin plots and stacked column graphs were performed in GraphPad Prism V.8.0.0 for Windows V.64 (GraphPad Software, San Diego, California USA, www.graphpad.com) and used to visually represent the 30-day diary and treatment questionnaire data, respectively. p<0.05 was considered significant.
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4

Comorbidity Risk Factor Analysis

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We calculated numbers and percentages for categorical variables and means and SDs for normally distributed continuous variables. We used simple logistic regression method to investigate the association between the different variables and the comorbidities. We developed a multiple logistic regression model to identify any independent associations. For this, we used backward stepwise regression analysis and included all the variables. Additionally, we performed a sensitivity analysis—in the multiple logistic regression model, we included only those variables that had a p value≤0.20 in simple logistic regressions. We calculated ORs and 95% CIs. We used IBM SPSS Statistics V.26.0 for Windows for statistical analyses.
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