The data was analyzed using binomial and multinomial regression models. Bivariate and multivariate logistic regression, and chi-squared tests were used to assess the association between dependent and independent variables. During analysis P-value <0.05 was considered as statistically significant. The analysis was performed using SPSS® Statistics program, version 25 (IBM Corporation, Armonk, NY, USA).
Spss statistics program version 25
Manufactured by IBM
Sourced in United States
SPSS Statistics is a software program for statistical analysis. Version 25 provides data management, analysis, and presentation capabilities. The program allows users to import and analyze data, generate reports, and perform advanced statistical procedures.
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Lab products found in correlation
15 protocols using spss statistics program version 25
1
Statistical Analysis of Experimental Data
2
Readmission Factors in Breast Cancer
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Univariate and bivariate descriptive analyzes were performed comparing women’s and tumoral characteristics, complications, and the treatments received between women with and without readmission. We differentiated between early, late and long-term readmissions throughout the study. Statistical significance was estimated using the chi-squared test. For those variables showing statistically significant differences, two-sided equality tests for column proportions were calculated to assess which categories were statistically different.
To evaluate factors associated with early, late and long-term readmissions, we fitted 3 logistic regression models adjusted by age, Charlson Index, detection mode, TNM stage, focality, tumor grade, tumor phenotype, surgical and adjuvant treatment, general complications, surgical complications, medical complications, and screening program. Finally, additional analyses were performed, excluding complications from the final model.
Data management and statistical analyses were performed using the IBM SPSS Statistics program, version 25. Statistical significance was set at p < 0.05.
To evaluate factors associated with early, late and long-term readmissions, we fitted 3 logistic regression models adjusted by age, Charlson Index, detection mode, TNM stage, focality, tumor grade, tumor phenotype, surgical and adjuvant treatment, general complications, surgical complications, medical complications, and screening program. Finally, additional analyses were performed, excluding complications from the final model.
Data management and statistical analyses were performed using the IBM SPSS Statistics program, version 25. Statistical significance was set at p < 0.05.
3
Spatiotemporal and Kinematic Analysis
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A descriptive analysis of all the study variables was conducted to find the mean and standard deviation. After this, the Shapiro–Wilk test was performed to check if the variables corresponded to a normal distribution. Inferential statistics were performed to examine the relationship between spatiotemporal, kinematic, and kinetic variables. Correlations were performed using the bivariate analysis of Rho’s Spearman, considering very weak (0–0.19), weak (0.2–0.39), moderate (0.4–0.59), strong (0.6–0.79), and very strong (≥0.8) [49 (link)]. In addition, multivariate linear regression models were performed and adjusted by BMI. A one-factor ANOVA analysis was performed, and subsequently, a Bonferroni posthoc test was performed to specify the differences between variables in the three groups of 30 s, 30 steps and 1 step (Supplementary Data S4 ). Statistical analysis was performed using the IBM SPSS Statistics program Version 25 (Armonk, NY, USA), with an alpha level of significance of p < 0.05.
4
Cellular Uptake Investigation and Analysis
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Data were generated out of at least three independent replicates and are presented as mean ± SD. IBM SPSS statistics program, version 25 (SPSS Inc., Chicago, IL, USA) was used for statistical analysis. Means were compared using unpaired Student’s t-tests (for cellular uptake investigation) and one-way analysis of variance (ANOVA), followed by Tukey as a post-hoc test, unless otherwise indicated. A result of p < 0.05 was considered significant.
5
Analysis of Biomarker Response
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All experiments were done with groups of n ≥ 4 and repeated with at least 3 independent patient samples. Statistical analyses were performed using SPSS Statistics program version 25 (IBM Corp., Armonk, NY, USA). Graphical presentations were created using OriginPro 2020b (OriginLab Corporation, Norhampton, USA). The normality of the response variables was tested with Kolmogorov–Smirnov or Shapiro–Wilk test (for experiments with n < 50) and histogram visualization. Statistical differences between the test groups were evaluated using Kruskal–Wallis test, and comparison between groups was done with Mann–Whitney U test. p < 0.05 was considered significant. Benjamini–Hochberg procedure was performed for comparisons of n > 20 p-values. Data are shown as means ± SEM.
6
Bilberry Anthocyanin Quantification and Analysis
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The quantitative results of gene expression and measurements of anthocyanins in bilberry fruits were analysed either with Student’s t-Test or one-way analysis of variance (ANOVA) followed by Tukey’s HSD test by using SPSS Statistics program, version 25 (IBM, New York, NY, United States).
7
Sentiment Analysis of User Comments
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The IBM SPSS Statistics program, version 25, was used to evaluate the differences in the probabilities that sentiments (positive, negative, and hopefulness) were reflected in the user comments, depending on the developmental phase, intended therapeutic effect, and the presence of language intensifiers in the text. Crude and mutually adjusted binary logistic regression models were used to calculate odds ratios (ORs) and 95% CIs. Furthermore, it was assessed whether Facebook pages ID, commenter ID, and gender data contributed to the logistic regression models.
8
Comprehensive Statistical Analysis of Data
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The normal distribution of the data was tested. In the case of a normal distribution, the mean and standard deviation were delineated. If data were non-normally distributed, the median and interquartile range (IQR) were reported. The Mann-Whitney U test was performed to determine significant differences between groups on continuous variables. X 2 -tests and Fisher exact tests were utilized to compare categorical variables. All data analyses were performed with IBM SPSS Statistics Program version 25.
9
Comparative Analysis of Microbial Identification
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The data in this study were analyzed with IBM SPSS Statistics program version 25. Spearman correlation was done to measure the strength and direction of monotonic association between the methods of identification i.e. phenotypic, multiplex PCR and RFLP assay. P-value < 0.05 was considered statistically significant.
10
Statistical Analysis of Experimental Data
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The data generated in this study are presented as the mean ± standard deviation. For statistical analysis, one-way analysis of variance and Duncan’s multiple range test were performed using the SPSS statistics program, version 25.0 (IBM, Inc., Armonk, NY, USA).
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