Statistical analyses were performed using GraphPad PRISM v.7.00 for Windows (GraphPad Software, San Diego, CA, United States). All data are presented as mean ± SE. The means were compared using Student’s t-test or one-way ANOVA with Tukey’s multiple comparisons test.
Prism v 7.00 for windows
Manufactured by GraphPad
Sourced in United States
GraphPad Prism V.7.00 for Windows is a scientific data analysis and graphing software. It provides tools for data organization, statistical analysis, and graph creation. The software is designed to work with Windows operating systems.
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Lab products found in correlation
8 protocols using prism v 7.00 for windows
1
Statistical Analysis of Experimental Data
2
Statistical Analysis of Data Normality
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GraphPad Prism V.7.00 for Windows (GraphPad Software, La Jolla, California USA, www.graphpad.com ) was used for statistical analysis and graph creation. Data were checked for normality using the Shapiro-Wilk test. Repeated measures data are presented as mean and range, non-parametric data as median, IQR (box) and range (whiskers). For unpaired data, one-way analysis of variance (ANOVA) was used with post hoc Dunnett’s multiple comparison test for parametric data and the Kruskal-Wallis test with Dunn’s post hoc analysis for non-parametric data. Non-parametric repeated measures data were analysed using the Friedman test with Dunn’s post hoc analysis. To investigate differences between adjacent Trek and Rest days, data were analysed by two-way ANOVA with Sidak’s multiple comparison test. Statistical significance was set at p<0.05.
3
Statistical Analysis of Experimental Data
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GraphPad Prism V.7.00 for Windows (GraphPad Software, San Diego, California, USA) was used for standard statistical analysis of the data. Data were presented as mean±SEM. Simple pairwise comparisons were made using unpaired two-tailed t tests. Multiple comparisons were made using two-way analysis of variance (ANOVA) with Bonferroni post-tests. Comparison of proportion was evaluated by χ2 test. P value <0.05 was considered to be statistically significant.
4
Predicting Long-Term Mortality Risk
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Values are expressed as mean±SD or number of patients (%), as appropriate. Multivariate logistic regression models were used to identify independent predictors of long-term mortality. To minimise selection bias and obtain comparable groups, propensity score matching (PSM) analysis was used to confirm the association between HR and long-term mortality. PSM of 1:1 ratio and 0.20 calliper by the ‘nearest neighbour’ method was performed with the ‘Matching’ package. The area under the receiver operating characteristic curve (AUC) was used to assess the discriminative performance of the logistic regression model. The long-term survival rate was analysed using the Kaplan-Meier analytical method and Cox regression analysis. The predictive models were built using the average of the predicted 5-year risk from the Cox proportional hazard model via the ‘coxph’ function of the ‘survival’ package in the R software package (R Foundation for Statistical Computing, Vienna, Austria). The Kaplan-Meir survival analyses were visualised using ‘survminer’ and ‘ggplot2’ packages in the R software package. The R software package, V.3.5.1 was used to analyse the data, and GraphPad Prism V.7.00 for Windows (GraphPad Software, San Diego, California, USA) was used for data analysis and visualisation. A two-tailed p value <0.05 was considered statistically significant.
5
Statistical Analysis of Experimental Data
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Statistical analysis was performed using GraphPad Prism v7.00 for Windows, GraphPad Software, La Jolla, CA, USA. Data were analyzed for normality using the Shapiro-Wilk normality test. Statistical analyses on normally distributed data sets were performed using One-way ANOVA followed by Sidak´s multiple comparisons test, and where indicated, Two-way ANOVA followed by Sidak´s multiple comparisons test and Tukey’s multiple comparisons test. Data sets with non-normal distributions were analyzed using the nonparametric Friedman´s test followed by Dunn’s multiple comparisons test. Statistical significance was defined as *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001; ns: non-significant.
6
Comparative Statistical Analysis of Groups
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All results are expressed as the mean ± standard error of the mean. The statistical analyses were carried out using independent‐samples t tests for two groups with SPSS version 17.0 (IBM Corporation), and one‐way analysis of variance for multiple groups with GraphPad Prism V.7.00 for Windows (GraphPad Software). Differences were considered to be statistically significant at p < 0.05.
7
Vascular Ischemic Complications in Temporal Arteritis
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Data are expressed as median (ranges) for quantitative variables, and number (%) for categorical variables. Continuous data were compared by Mann Whitney or Kruskal–Wallis test for more than two groups and categorical data by Fisher’s exact test as appropriate considering the value distribution. Event-free survival was defined as the time from the date of TA diagnosis and the date of first vascular complication, death (of any cause), or last follow-up. Survivals were estimated using the Kaplan–Meier method and compared using log-rank test. Factors associated with the time-to-event outcomes (vascular ischemic complications and relapses) were evaluated using Cox models, with estimation of hazards ratios and their 95% confidence interval. All tests were two-tailed and p < 0.05 was considered statistically significant. Statistical analyses involved using GraphPad Prism v7.00 for Windows (GraphPad Software, La Jolla, CA, USA) and R software.
8
Comparative Statistical Analysis of Experimental Data
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Categorical variables are expressed as percentages, and discrete variables as medians with the observed range, or as means ±95% CI. Fisher’s exact tests or Yates correction and ORs with 95% CI were used for comparative analyses. Continuous variables are presented as the arithmetic mean ± SD, and Mann–Whitney U-tests were used for the comparative analysis. The analysis was performed with SPSS v.15.0 software (SPSS, Inc.) and graphs were performed by GraphPad Prism v.7.00 for Windows, GraphPad Software, with values of P ≤ 0.05 considered statistically significant.
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