Median value and ranges are reported for continuous variables and proportions for categorical variables. The ratio of CD4/CD8 introduced to display the distribution of T-cell subsets was brought into calculation. The Kolmogorov–Smirnov test was used to estimate the normality of variables, and variables consistent with a normal distribution were analyzed using Student's t-test. To analyze the association of cellular compositions and outcomes, Mann–Whitney U nonparametric tests were conducted for patient age, sex, weight, HLA mismatched loci, ABO-matched status, patient ABO blood type, donor-recipient sex match, donor-recipient relationship, and each graft component. Multivariate analysis was performed using logistic regression with a forward selection procedure to determine independent influence factors involving dichotomous variables selected from the univariate analysis. Ninety-five percent confidence intervals (CIs) were calculated with log transformation. P < 0.1 was defined as significant in the univariate analysis, while the P < 0.05 was defined as significant in the multivariate analysis. Calculations were performed using the SPSS 16.0 statistical package (SPSS Inc., Chicago, IL, USA).
Spss 16.0 statistical package
Manufactured by IBM
Sourced in United States
SPSS 16.0 is a statistical software package developed by IBM. It provides a comprehensive set of tools for data analysis, including data management, statistical modeling, and reporting. The core function of SPSS 16.0 is to enable users to analyze and interpret data, as well as to create visualizations and reports.
Automatically generated - may contain errors
Lab products found in correlation
32 protocols using spss 16.0 statistical package
1
Cellular Composition Analysis in Transplantation
2
Statistical Analysis of Procedural Outcomes
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Descriptive statistics are reported as mean ± standard deviation (SD; or median and range for skewed distributions) for continuous variables, and as absolute frequencies and percentages for categorical variables. Between-group comparisons were performed with the unpaired Student t test, the Mann–Whitney U-test, or Fisher exact test, as appropriate. VT-free survival after the procedure was evaluated by means of Kaplan–Meier estimation (differences between strata were assessed by the log-rank test). All tests were 2-sided, and P < 0.05 was considered statistically significant. Statistical analyses were done using the SPSS 16.0 statistical package (SPSS Inc., Chicago, IL).
3
DGGE Profile Analysis for Microbial Communities
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The relative position and intensity of DNA bands on DGGE profiles were used for principal component analysis (PCA) by SPSS 16.0 statistical package (SPSS Inc. IL, USA). Statistical analyses were performed using a two-tailed Student t-test, with the assistance from GraphPad Prism Program (version 5.01, GraphPad Software Inc., USA). All values were expressed as means ± standard deviation (SD) and the sample sizes. Significance was accepted at p < 0.05. If not otherwise specified, statistical significance was indicated as follows: *p < 0.05; **p < 0.01; ***p < 0.001.
4
Statistical Analysis of Research Outcomes
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Data are presented as mean ± SD or median (range). Statistical analysis was performed with SPSS 16.0 statistical package (SPSS Inc., Chicago, IL, USA).
5
Statistical Analysis of CGF Effects
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All statistical analyses were performed using the SPSS 16.0 statistical package (SPSS Inc., Chicago, IL, USA) for Windows. The results were expressed as the mean ± SD. Both control and CGF intra- and inter-groups were statistically compared. The data were analyzed using Student’s t test and one-way ANOVA followed by post-hoc Scheffe test and multiple comparisons Dunnet t test. A level of p < 0.05 was considered to be statistically significant.
6
Genetic Variants and Metabolic Syndrome
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Chi-square test was performed to compare the genotypic distribution between cases and controls. Differences in the mean values of quantitative traits among case and control groups were evaluated using Student's t-test. All the genotypes of the 282–283 ins AG in the APOA5 gene were categorized as AAGG insertion, GG insertion and no insertion genotypes, and in 285–286 ins A as AA insertion and no insertion. One-way analysis of variance was used to compare the features of MetS between all genotypes of two variants. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated by simple and multivariate logistic regression analyses, respectively, to estimate the associations between the genotypes and MetS risk. The multivariate regression analysis models were adjusted for age. Statistical analyses were conducted with the SPSS 16.0 statistical package (SPSS, Inc., Chicago, IL, USA). Values were expressed as mean ± standard error of mean and P < 0.05 was considered statistically significant.
7
Assessing Pain Intensity and Satisfaction
8
Statistical Analysis of Biological Data
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SPSS 16.0 statistical package (SPSS, Inc., Chicago, IL, USA) or GraphPad Software was used to analyze the data. All results are presented as the mean ± S.D. Two-group comparisons were analyzed using the two-tailed Student's t test. Comparisons of three or more groups were analyzed using one-way ANOVA. Statistical significance was defined as *P < 0.05 and **P < 0.01.
9
Statistical Analysis of Five Samples
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The statistical analysis was performed with the SPSS 16.0 statistical package (SPSS Inc., Chicago, IL, USA). The data are expressed as the mean ± standard deviation values. The single factor analysis of variance (ANOVA) and q test were applied to evaluate five independent samples. Statistical significance was assumed at p < 0.05.
10
Comparative Grading Scores Analysis
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Data were expressed as mean ± standard deviation (SD). SPSS 16.0 statistical package was used to conduct the statistic analysis. One way ANOVA was used for comparing the grading scores of different groups, and Fisher’s exact test was used for rate comparison. A P value of less than 0.05 (two-tailed) was considered statistically significant.
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