Statistical analysis was performed with the IBM Statistical Package for the Social Sciences (IBM SPSS Statistic v26.0 Inc., Chicago, IL, USA). The gathered results were inserted into the SPSS database in the implied manner. Correlations between findings of immunohistochemical staining were performed with Spearman’s analysis. The nonparametric Kruskal–Wallis for more than two independent groups or the Mann–Whitney U test was used to test for differences in TIL density regarding the set prognostic markers. OS (in years) and DFS (in years) were compared by Kaplan–Meier graphics, and differences in patient survival times were tested for significance using the chi-square statistics of the log-rank test. For multivariate analyses, the Cox regression model for survival was used, and the following factors were included: age of the patient, pT and pN of the TNM staging system, grading, and histology type. Each parameter considered significant showed a value of p < 0.05. The p-value and the number of patients analyzed in each group are given for each chart.
Spss statistic v 26
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SPSS Statistics v. 26 is a statistical analysis software application developed by IBM. It provides users with a comprehensive set of tools for data analysis, including data manipulation, statistical modeling, and visualization. The software is designed to help researchers, analysts, and professionals gain insights from their data.
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10 protocols using spss statistic v 26
1
Multivariate Analysis of Tumor Immune Profiles
2
Statistical Analysis of Prognostic Markers
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Statistical analysis was performed using IBM Statistical Package for the Social Sciences (IBM SPSS Statistic v26.0 Inc., Chicago, IL, USA). Collected results were inserted into the SPSS database in an implicit manner and constructed a TC. The chi-square test was used to assess the distribution of clinico-pathologic variables. Correlations between immuno-histochemical staining results were determined via Spearman’s analysis. The non-parametric Kruskal–Wallis test was used to test for differences in cytoplasmic and nuclear expression of TRα, TRα1, and TRα2 in respect to the assigned prognostic markers. Life expectancy (in years), 10-year survival (in years), and disease-free survival (DFS) (in years) were compared using the Kaplan–Meier plot, and differences in patient survival times were tested for significance using the chi-square log-rank test statistic. The Cox regression model for survival was used for multivariate analysis, and the following factors were included: age at surgery, histology type, pT and pN from the TNM staging system, grading, and estrogen and progesterone receptor. Each parameter considered to be significant was indicated as p < 0.05. The p-value and the number of patients analyzed in each group were indicated for each graph.
3
Prognostic Factors in Cancer Pathology
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Statistical analysis was performed with the IBM Statistical Package for the Social Sciences (IBM SPSS Statistic v26.0 Inc., Chicago, IL, USA). The gathered results were inserted into the SPSS database in the implied manner, building the TC. The Chi-squared test was used to assess the distribution of clinical-pathological variables. Correlations between findings of immunohistochemical staining were determined with Spearman’s analysis. The nonparametric Kruskal–Wallis test was used to test for differences in cytoplasmic and nuclear RXRα expression regarding the set prognostic markers. OS (in years) and disease-free survival (DFS) (in years) was compared using Kaplan–Meier graphics and differences in patient survival times were tested for significance using the Chi-squared statistics of the log rank test. For multivariate analyses, the Cox regression model for survival was used and the following factors were included: pT and pN of the TNM staging system, grading, histology type, focality, and estrogen and progesterone receptors. Each parameter to be considered showed significance at the level of p < 0.05. The p-value and the number of patients analyzed in each group are given for each chart.
4
Exploring Psychosocial Factors and IAT
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The analysis focused on describing the data along with testing for differences, and on assessing possible relationships. Non-parametric tests of differences were used to assess differences, namely the Mann Whitney U-test for two categories and the Kruskal-Wallis H-test for three or more categories. Multiple negative binomial regression was used to assess the relationships, where the dependent variable was IAT and its subscales and the independent variables were characteristics such as gender, age, residence (urban/rural), family (incomplete/complete), housing during the semester (at home/away from home), form of study (part-time/full-time), PHQ-9, PSS-10, and GAD-7. The reference categories for nominal variables were selected with an emphasis on the frequency of observations in a given category and the logical interpretation of the results.
Statistical processing was performed using SPSS Statistic v. 26 (IBM, Inc., Armonk, NY, US) and programming language R v 4.1.2 (65 ).
Statistical processing was performed using SPSS Statistic v. 26 (IBM, Inc., Armonk, NY, US) and programming language R v 4.1.2 (65 ).
5
Quantitative Analysis of Bacterial Cell Morphology
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Cells were grown until exponential phase. Nile red (Sigma-Aldrich) (5 µg ml−1) and DAPI (Sigma-Aldrich) (1 µg ml−1) were used to stain membranes and DNA, respectively. Cells were spotted on agarose pads (1 %, w/v, in 1x PBS) and imaged using a Nikon Ti-E microscope (Nikon Instruments) equipped with a Hamamatsu Orca Flash4.0 camera. Image analysis was performed using the software packages ImageJ (http://rsb.info.nih.gov/ij/ ), ObjectJ (https://sils.fnwi.uva.nl/bcb/objectj/index.html ), ChainTracer [27 (link)] and Adobe Photoshop (Adobe Systems). Automated image analysis was performed using ChainTracer. Box plots were generated using BoxPlotR (http://shiny.chemgrid.org/boxplotr/ ). All quantitative results were derived from at least two biological replicate experiments. In order to determine whether the cell-length distributions between the strain were statistically different, first a Kolmogorov–Smirnov test was performed, which indicated that the data did not follow a normal distribution. Therefore, the non-parametric Mann–Whitney U‐test (P<0.05) was used to compare the different groups. IBM SPSS Statistic V26 was used to perform the statistical analysis.
6
Radon Exposure Assessment in Buildings
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Statistical analysis was carried by verifying the log-normal distribution of radon values using Kolmogorov–Smirnov test. The comparison of radon activity concentration values was performed for the categories ‘ground’ and ‘underground’ level with the non-parametric Mann–Whitney test. Descriptive statistics (median, mean, standard deviation, range, etc.) have been computed on radon annual averages estimated in the two groups. The measurement uncertainty of radon activity concentrations is expressed as expanded uncertainty with coverage factor k = 2 (95% confidence interval). This is a precautionary approach, as indicated in the ISO 11665-3:2020. The metrological relative uncertainty is equal to 14%. Thus, the rooms that showed an annual average radon activity concentration higher than the reference value were classified ‘critical’. Statistical analyses were performed using the Statistical Package for the Social Sciences (IBM SPSS Statistic v.26).
7
Migraines During Social Distancing
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We adopted absolute numbers and percentages to report categorical variables and medians with interquartile range (IQR) to report distributed continuous variables. We compared patients’ characteristics before social distancing among the three groups of patients reporting increased, decreased, or unchanged headache frequency during social distancing. We compared categorical variables using the Chi-square test and continuous variables through the Mann–Whitney U test. We also performed paired analyses to assess the change in migraine characteristics, physical activity, dietary habits, and sleep quality before and during social distancing. Those paired analyses were performed with chi-square test or Wilcoxon signed rank test as appropriate. Lastly, we assessed correlations between the change in headache frequency and in lifestyle variables during social distancing by means of the Spearman’s correlation coefficient. We performed all tests using SPSS Statistic (v26, https://www.ibm.com/docs/en/spss-statistics/26.0.0 , accessed on 18 April 2021) and established the level of significance at <0.05.
8
Efficacy of Radiotherapy Intervention
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Descriptive statistics will be used to summarise the sociodemographic and clinical metrics. Baseline characteristics will be compared between arms using independent sample (unpaired) t-tests and χ2 tests (or their counterparts), and the efficacy of the intervention (difference between arms over time) will be determined using effect size expressed as Cohen’s d, with calculated 95% CIs. If the data met a normal distribution, the efficacy analysis will be conducted according to the intention-to-treat principle and following an analysis of covariance with corresponding post hoc analysis with Bonferroni adjustment for multiple comparisons. The analysis will be adjusted for the effects of the following covariates: type of RT, RT dose, time since the end of RT, glandular dissection, age, cancer stage and xerostomia drug/device/product. To reduce adherence bias, a minimum of 75% attendance (≥18 sessions) will be required for a patient’s data to be included in the analyses. All analyses will be performed using IBM SPSS Statistic V.26.
9
Circular RNA Regulation in Breast Cancer
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Statistical analysis was done by GraphPad Prism 8.4.3 and IBM SPSS statistic v.26 software. Relative expression of circ_0009910, miR-145-5p, and MUC1 were compared between breast tumors and adjacent normal tissues using the paired sample t-test. The correlation of expression of these genes was computed via the Spearman correlation coefficient. The relationship between the expression of circ_0009910 and clinicopathological characters of patients was determined by Mann-Whitney and one-way ANOVA assessments (Kruskal-Wallis). Moreover, the charts of the MTT assay, wound healing assay, and receiver operating characteristic (ROC) curve were displayed by the GraphPad Prism v.8.4.3 software. The p-value <0.05 was contemplated to describe the statistical significance in all of the amounts.
10
Comparative Analysis of Joint Scores, Body Composition, and Serum Lipids
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Mann-Whitney U tests and Kruskal-Wallis with Bonferroni correction were used to compare knee joint scores, body composition, and serum lipid profiles across experimental groups. Comparisons were made using IBM SPSS statistic V26 (IBM SPSS, Armonk, NY). Significance was accepted for P < 0.05, 2-tailed test.
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