Flow cytometry data was analyzed in FlowJo v.9.8.2 (Treestar; Ashland, OR, USA). Expression of surface markers was compared between Th subsets using the Friedman chi-square test; with post-hoc pairwise comparisons made using the Wilcoxon related samples rank test; Bonferroni adjusted p-values are reported. T cell populations were compared between S. mansoni-infected and uninfected men by Mann-Whitney U test. Analysis of Th17 cell polyfunctionality was performed using Boolean gating in FlowJo software, and polyfunctionality compared between S. mansoni-infected and uninfected men with a chi-squared distribution (1000 permutations of pies) using SPICE v5.35 software (Exon, National Institute of Allergy & Infectious Diseases)[63 (link)]. Post-hoc comparisons between functional Th17 subsets were made using related samples Wilcoxon rank test. Excel v.14.4.8 (Microsoft; Redmond, WA, USA) was used prior to statistical testing, and statistical tests were run using SPSS v.20.0 for Mac (IBM; New York, NY, USA). Based on previous foreskin T cell studies [26 (link), 62 (link), 64 (link)], a sample size of 34 men provided 80% power to detect a difference of one standard deviation in the proportion of either foreskin or blood CD4 T cells that were Th17 cells (α = 0.05).
Spss v 20.0 for mac
Manufactured by IBM
Sourced in United States
SPSS v.20.0 for Mac is a statistical software package developed by IBM. It provides data analysis, data management, and data visualization capabilities for researchers and analysts. The software is available for the macOS operating system.
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Lab products found in correlation
4 protocols using spss v 20.0 for mac
1
Th17 Cell Polyfunctionality in Schistosomiasis
2
Statistical Analysis of Experimental Data
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All of the statistical analyses were performed using SPSS V.20.0 for Mac (IBM Corp.). Quantitative data are presented as the mean ± standard error of mean (mean ± SEM) and differences between groups were assessed using the Student's t-test (unpaired, two-tailed). Multi-group comparisons were conducted using one-way analysis of variance followed by Tukey's honestly significant difference post-hoc test. The Chi-squared test (two-tailed) and Fisher's exact test were used for the comparison of categorical variables in the IHC data. P<0.05 was considered to indicate a statistically significant difference. Prism 8.0 software (GraphPad Software, Inc.) was used to prepare the graphs.
3
Predicting Barbell Velocity from Perceived Exertion
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All data were expressed as mean ± SD for the mean velocity variables and OMNI–RES scale responses. Normality distributions of variables was assessed using the Kolmogorov–Smirnov test. Pearson correlations were analysed to establish a relation between Velmean of the bar and OMNI-RES scale. Finally, linear regression analyses were conducted to create a model for predicting bar velocities using RPE derived from the OMNI–RES scale. Pearson correlation analysis was performed to establish a relation between PotEst and PotReal. To solve the problem of non-independence of data when performing a linear correlation analysis, subjects were required to participate in one load category only. This ensured each subject in the sample was used only once. All analyses were conducted using SPSS v 20.0 for Mac (Chicago, IL). The alpha level was set at p < 0.05.
4
Survival Analysis of Chronic Kidney Disease
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Continuous variables were expressed as mean ± standard deviation (SD) or the median [interquartile range (IQR)] as appropriate, and they were analyzed with Student’s t-test or U Mann–Whitney test, as proceeded. Qualitative variables were showed as absolute and relative frequencies and they were compared with the chi-square test. Patient survival was drawn by the Kaplan–Meier method and different groups were compared with the Log Rank test. Patients were censured from analysis if they received a RT, transferred to peritoneal dialysis or other facilities. When we analyzed factors associated with CV death, we censured for other causes of death. We performed a multivariate analysis using Cox regression model (backward conditional selection). We defined an explicative model. Interaction between variables was explored. We included in multivariate analysis all variable with p value < 0.10 in univariate analysis and clinical relevance. Results shown as hazard ratios (HR) and the corresponding 95% confidence intervals (CI). We consider as statistical significance a p value < 0.05. The statistical analysis was performed with the program SPSS v. 20.0 for Mac (SPSS, Chicago, IL, USA).
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