A basic descriptive statistical analysis was followed by an analysis of variance for mean comparisons. Fisherʼs least significant difference (LSD) procedure at a 95.0% confidence level was used to discriminate among the means (multiple range test). Principal component analysis (PCA) was performed. All statistical analyses were carried out using Statistica, version 6.0 (StatSoft, Inc., Tulsa, OK, USA).
Statistica version 6
Manufactured by StatSoft
Sourced in United States, Poland, Belgium
Statistica version 6.0 is a comprehensive statistical analysis software package. It provides a range of statistical and data mining tools for data analysis, visualization, and modeling. The software is designed to handle a variety of data types and can be used for tasks such as regression analysis, cluster analysis, and time series analysis.
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Lab products found in correlation
Prism 5, by GraphPad (3 mentions)
Version 11, by MedCalc (2 mentions)
Stata se 17, by StataCorp (1 mentions)
Spss statistics version 19, by IBM (1 mentions)
Origin 7, by Malvern Panalytical (1 mentions)
Centurion, by Statgraphics (1 mentions)
Version, by MedCalc (1 mentions)
Kbf720 ich, by Binder (1 mentions)
Drosophila vials, by Genesee Scientific (1 mentions)
Sigmaplot, by IBM (1 mentions)
Drosophila population monitor, by Trikinetics (1 mentions)
Spss version 20, by IBM (1 mentions)
Spss statistics version 17, by IBM (1 mentions)
Version 15, by MedCalc (1 mentions)
Spss 27, by IBM (1 mentions)
60 protocols using statistica version 6
1
Comprehensive Statistical Analysis of Data
2
Multivariate Analysis of Retinal Imaging
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The means of the experimental groups were reported as arithmetic mean (standard deviation) and median (range) for continuous variables in the text and tables. Differences in the means of the dependent variables (red-R, green-G, intensity, and emission wavelengths) were studied with analysis of variance (ANOVA) methods.
In the first analysis, a one-way ANOVA was used to assess the impact of the different types of lesions (SRF, fibrosis, and atrophy) on the dependent variables.
A two-way ANOVA with principal effects was employed in the second analysis. The first two-level factor was MNV type. The second three-level factor was the status (active or inactive) of MNV. Active MNVs were further evaluated based on the presence of SRF versus IRF. When a principal effect was found, a post hoc Scheffé test was used to identify the sources of variability.
Analysis was performed with Statistica version 6.0 (StatSoft, Tulsa, OK, USA) using a two-sided type I error rate of P = 0.05.
In the first analysis, a one-way ANOVA was used to assess the impact of the different types of lesions (SRF, fibrosis, and atrophy) on the dependent variables.
A two-way ANOVA with principal effects was employed in the second analysis. The first two-level factor was MNV type. The second three-level factor was the status (active or inactive) of MNV. Active MNVs were further evaluated based on the presence of SRF versus IRF. When a principal effect was found, a post hoc Scheffé test was used to identify the sources of variability.
Analysis was performed with Statistica version 6.0 (StatSoft, Tulsa, OK, USA) using a two-sided type I error rate of P = 0.05.
3
Comparative Analysis of Assay Replicates
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The assays were carried out in five replicates and results are expressed as mean ± standard error. One-way analysis of variance (ANOVA) and Tukey`s HSD post-hoc test were performed to test any significant differences among means. Statistical significance was declared at P < 0.01. All statistical analyses were done using software STATISTICA, version 6.0 (StatSoft, Inc., Tulsa, USA).
4
Statistical Analysis of Clinical and MRI Data
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Statistical analysis was performed with STATISTICA Version 6.0 (http://www.statsoft.com/ ). Assumptions for normality were tested for all continuous variables by using the Kolmogorov-Smirnov test. All variables were normally distributed, except for educational level. Then, Unpaired t-test and Mann-Whitney U test were applied appropriately to assess potential differences between groups for all demographic clinical and MRI variables. All statistical analyses had a 2-tailed alpha level of <0.05 for defining significance.
5
Polyphenol and Caffeine in Coffee
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The obtained analytical results underwent evaluation, including Dixon’s and Grubbs’s tests to eliminate outliers (with coarse errors). Subsequently, the data were subjected to comprehensive statistical analysis using the following software tools: Statistica version 6.0 (Statsoft, Inc., Tulsa, OK, USA) and Stata/SE 17.0. The results for polyphenol and caffeine content in coffee were expressed in two ways: as mg/100 mL of coffee brew and as mg per coffee serving. These values were presented as means, along with minimum and maximum values.
To evaluate the significance of differences between various coffee types, a one-way analysis of variance (ANOVA) was conducted. Subsequently, multiple comparisons were performed using Tukey’s test to determine significant differences between coffee types. Pearson’s linear correlation coefficient was use to evaluate the association between polyphenol and caffeine content. In all conducted statistical tests, a significance level of p ≤ 0.05 was applied to determine the presence of meaningful differences and relationships among the variables under examination.
To evaluate the significance of differences between various coffee types, a one-way analysis of variance (ANOVA) was conducted. Subsequently, multiple comparisons were performed using Tukey’s test to determine significant differences between coffee types. Pearson’s linear correlation coefficient was use to evaluate the association between polyphenol and caffeine content. In all conducted statistical tests, a significance level of p ≤ 0.05 was applied to determine the presence of meaningful differences and relationships among the variables under examination.
6
Chemerin Concentration Analysis Protocols
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Statistical analyses were performed by STATISTICA (version 6.0) (Statsoft Inc., Tulsa, OK, USA) and IBM Statistical Package for the Social Sciences (SPSS) Statistics (version 19) (IBM Corp., Armonk, NY, USA) computer softwares. Normality of distribution was tested by Kolmogorov-Smirnov test and data were analyzed with paired t test. Data were expressed as means ± standard deviation (SD) or median (upper quartile-lower quartile). A value of P < 0.05 was considered to be statistically significant. Friedman-ANOVA and Kendall Coeff. of concordance test was used to compare eluted chemerin concentrations using solution buffers of various pH.
7
Cognitive Function and BDNF Levels
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Data are shown as mean ± standard deviation, except for sex, which are shown as n (%). The normality of the distributions was assessed using the Shapiro–Wilk test. All data were normally distributed. Baseline values between groups were compared using Student’s t-test. Differences between groups and periods were assessed via two-way (group × time) ANOVA. Tukey post-hoc tests were carried out when necessary. The relationship between cognitive functions and BDNF levels was evaluated using Pearson correlation. The effect size of the results was calculated using Cohen’s d. The level of significance was set at 5% (p < 0.05). All analyses were performed using STATISTICA version 6.0 (StatSoft Inc).
8
Cognitive and Emotional Processing in Parkinson's Disease
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Statistical analysis was performed using Statistica®, Version 6.0 (StatSoft, Inc., Tulsa, OK, USA). Results of the Stroop task were analyzed as follows: the mean reaction times and percentage of correct responses (accuracy) for each stimulus (congruent and incongruent, respectively) was computed; then, three different two-tailed t-tests were computed for each group for the T0 and T1 to assess the effect of add-on therapy.
Results for EST Task were analyzed, computing mean reaction times and accuracy for positive and negative words. Two tailed t-tests were computed for each PD group at T0 and T1.
Results for the monetary reward/loss task were analyzed by computing the percentage of risky and non-risky choices. Three different two-tailed t-tests were performed to assess the effect of add-on therapy.
Between-group comparison was performed for T0 and T1 separately for each task. Where possible, Bonferroni correction was applied to t-test results.
Results for EST Task were analyzed, computing mean reaction times and accuracy for positive and negative words. Two tailed t-tests were computed for each PD group at T0 and T1.
Results for the monetary reward/loss task were analyzed by computing the percentage of risky and non-risky choices. Three different two-tailed t-tests were performed to assess the effect of add-on therapy.
Between-group comparison was performed for T0 and T1 separately for each task. Where possible, Bonferroni correction was applied to t-test results.
9
Microbial Growth Kinetics Analysis
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All the experiments were done in three replicates and the results were expressed as mean ± standard error. One-way analysis of variance (ANOVA) and Tukey's test were performed using STATISTICA, version 6.0 (StatSoft, Inc., Tulsa, USA) to test any significant differences between the means. Statistical significance was declared at p < 0.05.
10
Vessel Diameter and Pigmentation Analysis
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Statistical analysis was performed using Statistica version 6.0 (StatSoft, Tulsa, OK, USA). Following normality testing with the Shapiro–Wilks test, we conducted a series of analysis of variance (anova ) to establish whether the three repeated measures (as obtained per image, per condition) were comparable; following this, for each condition we obtained averaged values for ODR, SO2, pigmentation and vessel diameter for further analyses. Stepwise forward regression analyses were employed to evaluate the influence of the vessel diameter and pigmentary values upon vessel saturation and ODRs and their respective standard deviations.
Across condition testing was performed by one‐wayanova , while examining the impact of individual vessel diameter was performed by a factorial anova (with factor one the measurement condition and factor two the vessel diameter). For this analysis, we arbitrary classified each artery and vein according to their size in three distinct groups: S, M and L (Arteries: S = up to 80 μm; M = 80–110 μm; L = over 110 μm; Veins: S = up to 95 μm; M = 95–130 μm; L = over 130 μm). Due to the fact that most arteries and veins measured in the concentric annulus were of the same morphological type and at a similar branching level, we observed the vessel distributions to select the cut‐off value so to ensure a comparable number of vessels in each group was selected.
Across condition testing was performed by one‐way
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