Differences between DLBCL‐type and CHL‐type MTX‐LPD were determined using Student's t and χ2 tests. A P < 0.05 was considered statistically significant. Overall survival was defined as the time from the date of diagnosis of a MTX‐LPD to the date of death or last follow‐up. Progression‐free survival was defined as the time from the date of diagnosis of a MTX‐LPD to the date of commencing chemotherapy or the date of death or last follow‐up. The follow‐up duration was calculated as the time from the date of diagnosis of a MTX‐LPD to the date of death from any cause or last follow‐up. The duration from the date of diagnosis of a MTX‐LPD to the date of commencing chemotherapy was determined. Survival curves were generated using the Kaplan‐Meier method. All statistical analyses were conducted using SPSS for Windows software version 14.0 (SPSS Inc., Chicago, IL, USA).
Spss software for windows version 14
Manufactured by IBM
Sourced in United States
SPSS software for Windows, version 14.0, is a statistical analysis software package. It provides tools for data management, analysis, and presentation. The software is designed to work on the Windows operating system.
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Lab products found in correlation
10 protocols using spss software for windows version 14
1
Statistical Analysis of MTX-LPD Subtypes
2
Comparing EBV-associated DLBCL Subtypes
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Statistical differences between EBVMCU, EBV-positive DLBDL and EBV-negative DLBCL were determined using the Mann-Whitney test and the Chi-squared (χ 2 ) test. P < 0.05 was considered statistically significant. All statistical analyses were performed using SPSS for Windows software version 14.0 (SPSS Inc., Chicago, IL, USA).
3
Grain Yield Analysis of Genotypes
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The results were statistically analyzed using s two-way factorial RCBD analysis of variance (ANOVA) and presented as mean ± standard deviation (SD). For each trait, the coefficient of variation (CV) was determined. Significant differences between the genotype means were determined using the Fisher’s least significant difference (LSD) test at the 0.05 probability level, and differences with p ≤ 0.05 were considered as significant. SPSS software for Windows, version 14.0 (SPSS Inc., Chicago, IL, USA), was used for the statistical analyses. Pearson’s correlation coefficient was used to determine the relationship between the measured metabolites and the obtained grain yield.
4
Phytochemical Profiling of Microwave-Popped Popcorn
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To analyse the data on the evaluated phytochemical parameters, two-factorial analysis of variance (ANOVA) set up according to the randomized complete block design (RCBD) was applied using the SPSS software for Windows, version 14.0 (SPSS Inc., Chicago, IL, USA). To determine the differences between the hybrids (H) and the popping treatment (T), as well as the hybrid–popping treatment interaction (H × T), Fisher’s least significant difference (LSD) test at a 0.95 confidence level (p ≤ 0.05) was conducted. Furthermore, to determine the relationship between the content of the evaluated phytochemical parameters in the popcorn kernels and flakes in response to microwave popping, principal component analysis (PCA) and agglomerative hierarchical cluster analysis (HCA) were carried out using MATLAB (R2011a) with the PLS Toolbox software package (v.6.2.1). For analysis, the obtained data were mean-centred, auto-scaled, and the singular value decomposition (SVD) algorithm was employed (95% confidence level) for Hotelling T2 limits. A percent change (% change) was used to determine the trend of the evaluated phytochemical content in response to popping treatment.
5
Statistical Analysis of Experimental Results
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The statistical study and analysis of the results were performed using SPSS software for Windows, version 14.0 (SPSS, Chicago, Illinois). The χ2 method was used in the statistical analysis of discrete variables, whereas the Student t test was used to analyze continuous variables. In addition, univariate and multivariate analyses were conducted including the aforementioned variables.
6
Genetic Polymorphism and Colorectal Cancer
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The differences in the frequencies of the CCL4 gene polymorphism between CRC patients and controls and between clinical characteristics within the CRC subgroups were analyzed using the chi-squared test. The Hardy-Weinberg equilibrium was assessed for the genotypes. Survival analysis was performed through Kaplan-Meier analysis with log-rank test. The Wilcoxon’s signed-rank test and the Mann-Whitney U-test were used for the analysis of the related and independent parameters and the Kruskal-Wallis test was used for comparing three or more classes. Correlations between parameters were analyzed using Spearman’s rank correlation test. Statistical analyses were performed using Stata Statistical Software Release 15 (Stata Corp., College Station, TX, United States) and SPSS software for Windows, version 14.0 (SPSS Inc., Chicago, IL, United States). Results were considered statistically significant at P < 0.05. The statistical methods of this study were reviewed by Roland E Andersson from Region Jönköping County, Sweden.
7
CXCL10 Genetic Polymorphism in CRC
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The differences in the frequencies of the CXCL10 gene polymorphism between CRC patients and control subjects and between clinical data within the CRC subgroup were analyzed using the Chi-square test. The Hardy-Weinberg equilibrium was assessed for the genotypes. The comparisons between groups regarding tissue and plasma levels of CXCL10 were performed with non-parametric tests. The Wilcoxon’s signed-rank test and the Mann-Whitney U test were used for the analysis of the related and independent parameters. The correlations between parameters were analyzed according to the Spearman’s rank correlation test. Statistical analyses were performed using SPSS software for Windows, version 14.0 (SPSS, Inc., Chicago, IL, USA). P<0.05 was considered to indicate a statistically significant difference.
8
Comparative Analysis of Treatment Groups
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One-way analysis of variance test was used for comparison between different groups followed by Dunnett’s t-test (two- sided) multiple comparisons to detect significant differences among individual mean values of all groups. Results are expressed as the mean ± standard deviation. The level of significance was set at P≤0.05. Statistical analysis was generated using SPSS software for windows, version 14.0 (SPSS Inc., Chicago, IL, USA).
9
Phenolic Compounds and Seedling Performance
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SPSS software for Windows, version 14 .0 (SPSS Inc ., Chicago, IL, USA), was used for the statistical analyses . Pearson's correlation coefficient is used to determine the relationship between the measured phenolic compounds content and the obtained seedlings performances .
10
Cumulus Cell Gene Expression Analysis
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Statistical significance was determined using SPSS software for Windows, version 14.0 (SPSS, Chicago, IL, USA). Cumulus cell gene expression results were analysed using oneway analysis of variance followed by least-significant difference (LSD) post-hoc test.
Statistical analysis was performed following normalisation to the reference gene. The data are presented as the mean ± SEM. Significance was accepted at a P value of < 0.05.
Statistical analysis was performed following normalisation to the reference gene. The data are presented as the mean ± SEM. Significance was accepted at a P value of < 0.05.
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