The statistical analysis was made by the IBM SPSS statistical program version 22 (SPSS-Inc., Chicago, IL, USA). The data were analyzed through one-way analysis of variance (ANOVA) and general linear method followed by Tukey’s test at p > 0.05 post hoc test for observation of the significance of differences between different treatments.
Spss statistical program version 22
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SPSS Statistics is a software package used for statistical analysis. Version 22 provides a comprehensive set of tools for data management, data analysis, and reporting. The software offers a wide range of statistical procedures, including regression, descriptive statistics, and multivariate analysis, among others. SPSS Statistics is a widely used tool for researchers, analysts, and data professionals across various industries.
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Lab products found in correlation
13 protocols using spss statistical program version 22
1
Statistical Analysis of Treatments
2
Analyzing Trends in Organ Transplantation Criteria
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Quantitative variables were described by medians and quartiles, given the distance between mean and median and asymmetry observed in the variables through histograms and normality tests. Categorical variables were described by absolute frequencies and percentages. Simple logistic regression models assessed the relationship between the occurrence and the number of ET-ECD criteria over the years. In addition, the simple Poisson regression adjustment was used to assess the year. The relationship between organ refusal for transplantation, the occurrence, and the number of ET-ECD criteria was also evaluated by simple and multiple logistic regression adjustment. Depending on the expected frequency per category, other associations between qualitative variables were assessed using Fisher's exact or Chi-squared tests. Finally, the nonparametric Mann-Whitney test was used to compare quantitative measures between groups, depending on the distribution of numerical measures. The SPSS statistical program version 22 (IBM Corp, Armonk, NY, United States) was used for analyses, and the significance level adopted was 5%.
3
Comparing Ultrasonography Devices for Alveolar Evaluation
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The evaluation was carried out with IBM SPSS statistical program version 22. Kappa statistics were used to evaluate the consistency between the devices in the evaluation of alveolar syndrome and pleura. Bland–Altman analysis was used to assess presence of agreement or presence of any significant proportional bias between two ultrasonography devices and to calculate maximum acceptable difference. Upper and lower limits of agreement and the limits of maximum acceptable differences were also calculated. Medcalc statistical analysis programme was used to plot Fig. 1 . Interobserver reliability was assessed using the intraclass correlation test. Intraclass correlation coefficient (ICC) greater than 0.7 was taken to indicate a strong correlation.![]()
Blant Altman test chart comparing standart ultrasonography device and pocked sized ultrasonography device in terms of total aeration score and count of total B2 lines. MAD Maximum accepted difference
4
Gaze Behavior and Decision-Making in Sports
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A series of one-way ANOVAs with post hoc LSD t-tests were used to examine between-group differences in experience, decisionmaking accuracy, search rate, and entropy. Percentage viewing time for the fixation locations was analysed using a two-way ANOVA with group (elite vs. trainee vs. player) as the betweensubjects factor and fixation location (central-vs. outer-vs. nonpack) as the within-subjects factor. Significant main and interaction effects were followed up with post-hoc one-way ANOVAs and LSD t-tests. In all ANOVAs in which the sphericity assumption was violated, the degrees of freedom were corrected using the Greenhouse-Geisser correction procedure. Effect sizes were calculated as partial eta-squared (η p 2 ), with values of 0.01, 0.06, and 0.14 interpreted as small, medium, and large effects, respectively. Finally, a series of bivariate regression analyses were conducted to examine if search rate, percentage viewing time to central-, outer-, and non-pack locations, or entropy, predicted a significant amount of variance in decision-making accuracy. These regression analyses were based on mean values for each participant's decision-making accuracy and gaze behaviour metrics. A p-value of less than .05 was considered statistically significant (Field, 2013) , and all analyses were conducted using IBM SPSS statistical program version 22.
5
Statistical Analysis of Experimental Replicates
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All experiments were repeated thrice independently with technical replicates. The significant differences between experimental groups were statistically determined using the Student’s t- test or one-way ANOVA and multiple comparisons with post hoc tests. Results are presented as mean ± standard error of the mean (S.E.M). When the p-value was less than 0.05, we rejected the null hypothesis of no difference between experimental groups. SPSS Statistical program version 22.0 (SPSS, Inc., Chicago, IL, USA) and GraphPad Prism software ver. 5 (GraphPad Software Inc., San Diego, CA) were utilized for all statistical analyses in the present study.
6
Aromatase Activity and Tumor Characteristics
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All calculations were performed using SPSS Statistical Program version 22.0 (SPSS Inc. Chicago, IL, USA).
The correlation between aromatase activity and patient characteristics was analyzed using the Goodman and Kruskal's gamma test (G). The significance of differences in activity levels between tissue groups was determined by the Wilcoxon signed-rank test (WSR) or Mannwhitney U test (MU) as needed. ANOVA was performed for evaluation of the aromatase activity alterations together with the stage, grade and receptor status of the tumor. Two-sided tests were used to obtain all reported p-values and the results below 0.05 were considered as statistically significant.
The correlation between aromatase activity and patient characteristics was analyzed using the Goodman and Kruskal's gamma test (G). The significance of differences in activity levels between tissue groups was determined by the Wilcoxon signed-rank test (WSR) or Mannwhitney U test (MU) as needed. ANOVA was performed for evaluation of the aromatase activity alterations together with the stage, grade and receptor status of the tumor. Two-sided tests were used to obtain all reported p-values and the results below 0.05 were considered as statistically significant.
7
Aromatase Activity and Tumor Characteristics
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All calculations were performed using SPSS Statistical Program version 22.0 (SPSS Inc. Chicago, IL, USA).
The correlation between aromatase activity and patient characteristics was analyzed using the Goodman and Kruskal's gamma test (G). The significance of differences in activity levels between tissue groups was determined by the Wilcoxon signed-rank test (WSR) or Mannwhitney U test (MU) as needed. ANOVA was performed for evaluation of the aromatase activity alterations together with the stage, grade and receptor status of the tumor. Two-sided tests were used to obtain all reported p-values and the results below 0.05 were considered as statistically significant.
The correlation between aromatase activity and patient characteristics was analyzed using the Goodman and Kruskal's gamma test (G). The significance of differences in activity levels between tissue groups was determined by the Wilcoxon signed-rank test (WSR) or Mannwhitney U test (MU) as needed. ANOVA was performed for evaluation of the aromatase activity alterations together with the stage, grade and receptor status of the tumor. Two-sided tests were used to obtain all reported p-values and the results below 0.05 were considered as statistically significant.
8
Quantitative Analysis of Steroidogenic Enzymes
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The samples size required for statistical significance and proper interpretation of the results was calculated according to the experimental methodologies used in the study as we previously described24 (link). mRNA levels of the target genes used in the qRT-PCR assay (steroidogenic enzymes, LH and FSH receptor) and hormone levels are continuous variables therefore, expressed as the mean ± SD. ANOVA/ Bonferroni or Kruskal–Wallis/Dunn post-hoc tests were applied to compare the groups if data is parametric or nonparametric, respectively. The percentages of viable and apoptotic cells were compared between the groups using Fisher’ exact test. Significance level was set at 5% (P < 0.05). SPSS statistical program (version 22) was used to analyze the data.
9
Statistical Analysis of Experimental Data
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Statistical analysis was performed with SPSS statistical program version 22 (SPSS Inc., Chicago, IL, USA). To test the normality, we performed the Kolmogorov–Smirnov test, which showed that the data were normally distributed (p > 0.05). Furthermore, Levene’s tests were determined for each dependent variable. The effects of the experimental treatment were analyzed using a two-way analysis of variance (ANOVA) in which the main and interaction effects (group × time) were calculated. Moreover, we used the Cohen’s d effect size (ES) with the use of the following criteria: trivial 0.0–0.2; small 0.2–0.6; moderate 0.6–1.2; large 1.2–2.0; and very large > 2.0 [17 (link)]. In addition to the statistical significance, which was set at p < 0.05, a partial eta squared (η2) was used for the differences between groups using 0.01, 0.06, and 0.14, determined as a small effect, medium effect, and a large effect [18 ].
10
Factors Associated with Anemia in Schoolchildren
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The sample size was estimated on the basis of the expected additional impact on anemia of the intervention arm versus the comparator [23] . Data were entered and stored in Epi info7. Frequencies were used to assess the prevalence of asymptomatic malaria and anaemia in school children. Differences in mean values for continuous variables (e.g., HAZ, WAZ, BAZ, Hb, parasite densities) were assessed using the student t-test analysis. One-way ANOVA was used to analyze differences in Hb concentration mean of the study population by intestinal infection status and by infection intensity (negative, light and moderate-to-heavy) of each parasite species. Odds ratios (ORs), 95% confidence intervals (CIs) were calculated and p<0.05 values were considered to be statistically significant. Multivariate logistic regression models were constructed to identify factors associated with anemia in schoolchildren. Statistical analyses were done using SPSS statistical program, version 22 (SPSS, Chicago, IL, USA).
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