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Statview j version 5

Manufactured by SAS Institute
Sourced in United States

StatView J version 5.0 is a data analysis and presentation software. It provides standard statistical analysis tools and options for creating graphs and charts from data.

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9 protocols using statview j version 5

1

Statistical Analysis Protocol

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The level of significance was set at p < 0.05 for all analyses. Statistical analyses were performed using the StatView J version 5.0 software package (SAS Institute) and SPSS version 22 (IBM Corp.).
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2

Correlation Analysis of ELISA Biomarkers

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Data are presented as the median (range). Correlation was assessed using Pearson's product-moment correlation coefficient. The degree of correlation was determined according to the absolute value of the correlation coefficient R as follows: No correlation, 0≤R<0.2; weak correlation, 0.2≤R<0.4; moderate correlation, 0.4≤R<0.7 and strong correlation, 0.7≤R<1.0. The Kruskal-Wallis test followed by a Games-Howel post hoc test was used to detect significant differences between the ELISA results. The Kaplan-Meier method was used to estimate overall survival and survival differences were analyzed by the log-rank test. P<0.05 was considered to indicate a statistically significant difference. All statistical analyses were performed using StatView J version 5.0 (SAS Institute, Inc., Cary, NC, USA) and Microsoft Excel 2011 (Microsoft Corporation, Redmond, WA, USA).
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3

Multivariate Analysis of Remission Predictors

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Data are expressed as the mean ± standard deviation. Statistical analyses were performed using a one-way analysis of variance (ANOVA) followed by Tukey’s post hoc test. Chi-squared tests were used for comparisons between categorical variables. Remission curves were evaluated by Kaplan–Meier method. A possible predictor of the LOS after the treatment, durations of remission, and major adverse effects were tested by multivariate analysis. Statistical analyses were performed using SPSS statistics 19 (IBM) or Stat-View J version 5.0 (SAS institute Inc). Values of P < 0.05 were considered significant.
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4

Statistical Analysis of Differential Factors

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Differences between two groups were analyzed using Student’s t test or Mann-Whitney U test. Differences among multiple groups were analyzed using post hoc test. The chi-squared test was used to analyze clinicopathological features. The level of significance was set at P<0.05 for all analyses. Based on TCR, receiver-operator characteristic (ROC) analyses were performed, and the area under the curve (AUC) value was determined. Statistical analyses were performed using the StatView J version 5.0 software package (SAS Institute, Inc., Cary, NC, USA) and XLSTAT (Addinsoft, New York, NY, USA).
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5

Statistical Analysis of Quantitative Data

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All quantitative data are presented as mean ± standard error of the mean (SEM). Data were compared using a one‐way ANOVA, and P‐values <0.05 were considered statistically significant. Analyses were performed using StatView J version 5.0 (SAS Institute, Inc., Cary, NC, USA).
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6

FGFR-2 Expression in Cancer Prognosis

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Results are shown as mean ± SE, and the data between different groups were compared using the Student's t-test. The χ2 and Fisher's exact tests were used to analyze the correlation between FGFR-2 expression and clinicopathological features. Cumulative survival rates were calculated using the Kaplan–Meier method, and the significance of differences in survival rate was analyzed by the log–rank test. The data between multiple groups were compared using one-way anova. < 0.05 was considered significant in all analyses. Computations were carried out using the StatView J version 5.0 software package (SAS Institute, Cary, NC, USA).
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7

Survival Analysis of Grading Systems

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Concordance between the two observers was assessed using Cohen's kappa coefficient. Receiver operating characteristics (ROC) were analyzed to determine the best cut-off value for each grading system. OS and RFS were analyzed based on Kaplan–Meier survival estimates. Significant survival-related factors according to univariate analysis (P < 0.05) were entered in a multivariate Cox proportional-hazards model. Clinicopathological characteristics were analyzed using chi-square test. P < 0.05 was considered to indicate significance in all analyses. Statistical analyses were performed using the StatView J version 5.0 software package (SAS Institute, Inc., Cary, NC, USA) and SPSS version 22 (IBM Corp., New York, NY, USA).
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8

Clinicopathological Factors and Survival

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Data are presented as the median (range). The Mann-Whitney U test was used to determine the statistically significant differences between the mean values. Chi-square and Fisher’s exact tests were used to analyze clinicopathological features. Kaplan-Meier analysis was performed to analyze the relationship to overall survival and clinicopathological features. Overall survival was defined as period from surgery to death or censor. Statistical analysis was performed using the Stat View J version 5.0 software package (SAS Institute, Inc., Cary, NC, USA). A P value of <0.05 was considered statistically significant.
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9

Plasma TSG-6 Level Predictors

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Results are expressed as mean ± SEM for continuous variables and as percentages for categorical variables. Normal distribution of continuous variables was assessed using the Kolmogorov-Smirnov test. On the basis of the normality of the variables, the parametric or the nonparametric test was chosen as appropriate. Comparisons between 2 groups were made using the unpaired Student t test or the Mann-Whitney U test. Multiple comparisons were made among ≥3 groups using 1-way analysis of variance or the Kruskal-Wallis test followed by the Bonferroni post-hoc test. The categorical variables were analyzed using the chi-square test. Multiple linear regression analysis was performed to evaluate the predictor variables for plasma TSG-6 levels. Pearson's correlation coefficient was used to evaluate the linear relationship between plasma TSG-6 levels and other variables. Statistical analyses were performed using Statview-J version 5.0 (SAS Institute, Cary, North Carolina) and SPSS version 22.0 (SPSS Inc., Chicago, Illinois). A value of p < 0.05 was considered to indicate statistical significance.
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