Various statistical software programs were used for statistical analysis namely: R Statistics version 3.5.1 (The R Foundation, Vienna, Austria); SPSS v25 statistical software (IBM SPSS, New York, USA), and Graph Pad Prism 5.0 (Graph Pad Software, San Diego California, USA). ANOVA and Bonferroni post-hoc tests were used for comparison of the mean number of oocysts shedded and cytokine levels. Levels of signi cance were set at 95% CI with p<0.05 considered as a signi cant difference. The correlation coe cient (R-values) was used to compare the relationship between the number of oocyst shedding and the lymphocytes being produced during the establishment of an infection. Probit analysis was performed for the prediction of minimum dosage capable of causing an infection using SPSS v25 statistical software (IBM SPSS, New York, USA).
Spss statistical software v25
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Sourced in United States
SPSS Statistical Software v25.0 is a comprehensive data analysis and statistical software package. It provides a wide range of advanced analytical capabilities for processing and analyzing data. The software enables users to perform complex statistical analyses, data management, and data visualization tasks.
Automatically generated - may contain errors
47 protocols using spss statistical software v25
1
Oocyst Shedding and Cytokine Levels
2
Statistical Analysis of Experimental Data
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All the statistical analyses were performed using the SPSS statistical software (v. 25). For all the above methods, the results were expressed as mean ± standard error. Statistical analysis was done using parametric (multiple comparison test) or non-parametric statistics based on the normality test. Then, the data were analyzed using the Mann–Whitney U test. Besides, differences were considered significant at P < 0.05.
3
Statistical Analysis of Research Data
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Statistical analysis was performed using SPSS Statistical Software, V.25 (SPSS, IBM). Continuous variables are expressed as mean±SD and median (range) according to their distributions (Shapiro-Wilk normality test). Categorical variables are described as proportions (%). A p value of less than 0.05 was considered statistically significant.
4
Exploring Heart Dose Reduction in RT
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The study was designed as an exploratory study with reduction of heart dose as the primary endpoint, so no meaningful power calculation was possible. Wilcoxon signed rank test for non-parametric paired data was used to compare differences for the dependent variables in the FB and DIBH RT plans with a two-tailed significance level of 0.05. We tested the two sets of FB data with 1.0 cm (FB 1.0 cm) and 1.5 cm CTV-to-PTV margin cranio-caudally (FB 1.5 cm) with the DIBH data separately. All statistical analyses were performed with the SPSS statistical software v. 25.
5
Postprandial Curcumin and Antioxidant Responses
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We used Statistical Package for the Social Sciences (SPSS) statistical software v.25 (SPSS Inc., Chicago, IL, USA) for the statistical analyses. GraphPad Prism 5.0 (GraphPad Software, Inc., San Diego, CA) was used to create the graphs. Results are presented as mean ± standard deviation. We used the Kolmogorov-Smirnov test to determine the normality of the data normality. We used a two-way analysis of variance test (groups × times) with repeated measurements to analyze plasma curcumin and antioxidant capacity. When a significant interaction was detected, Bonferroni's multiple comparison method was used. We used the trapezoidal method to compare postprandial responses between conditions with the incremental area under the curve (iAUC) [19 (link)]. Effect sizes (ES) were calculated using Cohen's formula, which were then classified as small (d = 0.2), medium (d = 0.5), or large (d = 0.8). A p value of <0.05 was considered statistically significant.
6
Effects of Blood Flow Restriction Training
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All data for measured variables were found to be normally distributed as assessed with a Shapiro-Wilks test (P ≤ 0.05). All dependent variables for muscle strength, body composition, and MTH were analyzed for absolute (kg) as well as normalized percentage change from baseline which was calculated as: (post−pre)/prex 100. Total tonnage (TT) was calculated as a sum of all six resistance exercises 1RM at each testing time point, as a reflection of whole body strength. One outlier was removed from the normalized data for CR as the data was 3SD above the mean. A linear mixed model was used to measure main effects for Group (BFR-T, HL-T, LL-T, CON) and Time (Baseline, week 4, week 8, week 12) while also accounting for the small sample size and missing data points. For any Group x Time interactions, a Bonferroni correction was used to determine differences for each dependent variable while accounting for family-wise error. The linear mixed model was performed using SPSS statistical software (v25). The level of significance was set at P ≤ 0.05 and all data is presented as mean ± standard deviation (SD) unless stated otherwise.
7
Statistical Analysis of CAR-T Cell Toxicity
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Kolmogorov-Simirnov or Shapiro-Wilk normality tests were applied for each continuous variable, depending on the n. Results are expressed as mean±SD for normal continuous variables; as median±IQR for non-parametric continuous variables and as absolute count and percentages for qualitative variables. Statistical analysis was performed with parametric or non-parametric tests, as needed: Student’s t-test and paired Student’s t-test or Mann-Whitney U and Wilcoxon test, respectively. Cross tables and χ2 tests were applied for the evaluation of frequencies among categorical variables. Analyses with receiver operating characteristic (ROC) curves were applied for establishing the diagnostic or predictive potential of each biomarker individually and their cut-off values. Regression curves were calculated for the assessment of the predictive model with the combination of biomarkers with area under the curve (AUC) >0.7 and p<0.05 in the individual ROC analysis. The outcomes for the predictive models determined were ‘presence of any CAR-T cell-related toxicity’, ‘ICU admission’ and diagnosis of ‘sepsis’, and were established and analyzed retrospectively. Statistical analysis was processed with SPSS statistical software (V.25; SPSS, Chicago, Illinois, USA). Results were considered statistically significant when p<0.05.
8
Hearing, Vestibular, and Cognitive Decline
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Data will be analysed using SPSS statistical software V.25. Descriptive analyses will be expressed as mean values with SD or SEM. If the data is not normally distributed, median and median absolute difference will be reported. Cross-sectional results will be studied first using intended parametric or non-parametric tests, to provide insight in the correlation between hearing, vestibular function and cognition. Longitudinal differences will be analysed at 12 and 24 months using variance analyses (repeated measure design). A corresponding non-parametric test will be used to study the effect on conversion to dementia in patients with MCI. A significance level of 0.05 will be applied. The Holm-Bonferroni method will be used for multiple comparison correction.
9
Analysis of Continuous and Categorical Data
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All data were tested for normality and outliers, reaching a value higher or lower than two times the standard deviation of the mean, were excluded.
The association between categorical data was tested by a Pearson’s Chi-squared test with asymptotic significance correction. Continuous data were statically assessed with an independent student’s t-test or with a one-way ANOVA if there were more than two categorical variables involved. Survival times were assessed by means of Kaplan–Meier survival analysis. Differences between groups were tested by means of a log-rank test. For continuous covariates, survival analysis was performed by Cox-regression analysis with backward conditional modeling. A p-value of less than 0.05 was considered statistically significant. Statistical analyses were performed using SPSS statistical software (v.25; SPSS, Chicago, IL). Data are represented as means and standard error of the mean.
The association between categorical data was tested by a Pearson’s Chi-squared test with asymptotic significance correction. Continuous data were statically assessed with an independent student’s t-test or with a one-way ANOVA if there were more than two categorical variables involved. Survival times were assessed by means of Kaplan–Meier survival analysis. Differences between groups were tested by means of a log-rank test. For continuous covariates, survival analysis was performed by Cox-regression analysis with backward conditional modeling. A p-value of less than 0.05 was considered statistically significant. Statistical analyses were performed using SPSS statistical software (v.25; SPSS, Chicago, IL). Data are represented as means and standard error of the mean.
10
Comparative Analysis of Cell Responses
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Descriptive statistics were performed. Normality was tested using Shapiro Wilk test. Attachment, proliferation and cytotoxicity after 3 and 7 days showed normal distribution while cytotoxicity after 24 hours was not normally distributed. Comparisons between groups were done using One Way ANOVA (for normally distributed results) followed by Tukey’s test with Bonferroni adjustment and Kruskal Wallis test (for non-normally distributed results) followed by post hoc comparisons with Bonferroni correction. Comparisons of cytotoxicity between the three-time points for each group were done using Kruskal Wallis test due to independency of specimens at each time point. Differences in proliferation percentage between two time points were compared using independent t test. The level of statistical significance was set at p ≤ 0.05. Data were analyzed with IBM SPSS statistical software V.25, (SPSS Inc).
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