ROC curves for ULBPs in order to predict NSCLC recurrence were generated to determine the expected cut-off value that yielded optimal sensitivity and specificity. Chi-square tests or Fischer exact tests were performed to evaluate the relationship between ULBP expression levels and patient characteristics. Kaplan-Meier survival analysis was used to determine the association between ULBP expression and RFS or OS until death or last follow-up; the significance of the differences in RFS or OS between groups was assessed by log-rank test using GraphPad Prism 6.01 (GraphPad Software, La Jolla, CA). Cluster analysis used for the classification of our patients into subgroups based on the expression pattern of NKG2D ligands including MICA/B was performed using SPSS statistical package 17.0 (SPSS, Chicago, IL). Univariate and multivariate analyses were performed using the Cox proportional hazards model in order to identify independent prognostic factors. Statistical analyses were also performed using the SPSS statistical package 17.0. In all cases, p < 0.05 was considered significant. The follow up period was set to a maximum of 5 years (1825 days). The median length of follow up was 1522 days (range, 37 to 1825 days) for all patients and the last follow-up date was October 6, 2017.
Spss statistical package 17
Manufactured by IBM
Sourced in United States
SPSS Statistical Package 17.0 is a comprehensive software suite for statistical analysis. It provides a wide range of statistical techniques and tools for data management, analysis, and reporting. The package offers features such as data import, data transformation, descriptive statistics, regression analysis, and advanced statistical modeling. SPSS 17.0 is designed to help users analyze and interpret data effectively.
Automatically generated - may contain errors
31 protocols using spss statistical package 17
1
Predicting NSCLC Recurrence via ULBP
2
Efficacy of Novel Therapeutic Intervention
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All the data were presented with mean ± standard (x ± s) error. Differences between the groups were analyzed using Student’s t test. Differences in the distribution of nominal parameters were analyzed with χ2 test. All the statistical analyses were performed with SPSS statistical package 17.0 (SPSS Inc., Chicago, USA), and P < 0.05 was considered to be statistically significant.
3
Gamma Irradiation Effect on Highland Barley Stress Response
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All data were obtained from three independent replicate experiments (n = 3). The values from all experiments were expresses as the mean ± standard deviation (SD). Statistical analysis was performed using SPSS statistical package 17.0 (SPSS Inc., USA). An analysis of variance (ANOVA) was conducted to compare the effects of gamma irradiation on highland barley growth as well as H2O2, MDA, and proline levels and antioxidant enzyme activity (SOD, CAT and POD) in highland barley under Pb/Cd stress. The significant differences among treatments were identified by least significant difference (LSD) test with a confidence level at p < 0.05, which is a sensitive two-step testing method for pairwise comparisons among all groups. Moreover, the paired-sample t-test was applied to evaluate the significant difference of gene expression between the non-irradiated and irradiated highland barley under Pb/Cd stress. The difference is expressed as * at p < 0.05, ** at p < 0.01, and *** at p < 0.001.
4
Circulating SETDB1 Predicts Survival
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Data were presented as mean ± standard error of the mean (SEM). The differences between the groups were analyzed by Student’s t-test when two groups were compared. Receiver operating characteristic (ROC) curves and area under the curve (AUC) were constructed to determine the optimal values of circSETDB1, which provided high sensitivity and specificity. Analyses were performed with Graph-Pad Prism, version 6.0 (GraphPad Software, Inc., San Diego, CA, USA). Kaplan–Meier curves were constructed to determine patient progression-free survival rates using SPSS statistical package 17.0 (SPSS, Inc., Chicago, IL, USA). Patients who were lost to the follow-up or who died from causes unrelated to SOC were treated as censored events. The statistical differences in survival among subgroups were compared using the log-rank test. P-values of <0.05 were considered statistically significant.
5
Evaluating Probiotic Characteristics in Sows and Piglets
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Data were obtained from at least 3 replicate experiments. Microsoft Excel 2019 software was used to process the data, and values from all experiments were expressed as mean ± standard deviation (SD). Statistical analysis was performed using SPSS statistical package 17.0 (SPSS Inc., Chicago, IL, USA) by one-way analysis of variance (ANOVA) to compare the effects of different LAB on EPS production capacity, cell surface hydrophobicity, auto-aggregation ability, survival after simulated GIT exposure, reproductive performance of sows, and immune indexes of serum in sows and weaned piglets, and Tukey’s test was used for comparisons at the 5% significance level. In addition, paired-sample t-tests were employed to compare the growth performance of weaned piglets, as well as the antioxidant capacity of serum in sows and weaned piglets; 0.01 < p < 0.05 indicated significant difference and p < 0.01 extremely significant difference, marked with * and **, respectively.
6
Uncertainty Analysis of Disease Risk
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The statistical analyses were performed by using SPSS statistical package 17.0 (SPSS Inc., Chicago, IL, USA) with a significant level of 5% of probability. The model was developed by using a Microsoft® Excel 2010 spreadsheet (Microsoft Corporation, Redmond, WA, USA). All simulations were run by using the Monte Carlo sampling method of input variables and combining the values properly in order to generate the output variables. The simulations were implemented by using the @Risk software. The distribution of uncertainty for the probability of disease was determined by running 10,000 iterations.
7
Statistical Analysis of Cadmium-Induced Kidney Dysfunction
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The SPSS statistical package 17.0 (SPSS Inc., Chicago, IL, USA) was used to analyze data. We used the Mann-Whitney U-test to compare two groups of subjects. The distribution of the variables was examined for skewness and those showing right skewing were subjected to logarithmic transformation before analysis, where required. One sample Kolmogorov-Smirnov test was used to detect a departure from normal distribution of variables. We used the logistic regression analysis to estimate Prevalence Odds Ratio (POR) for CKD, attributable to Cd exposure and kidney tubular pathologies. The univariate analysis was used to estimate effect size of Cd exposure levels with adjustment for covariates and urinary Cd quartiles × smoking × gender interactions. In addition, we used a multilinear regression analysis to evaluate the strength of associations between eGFR and its predictors in subjects stratified by gender, smoking status and Cd exposure levels. p values ≤ 0.05 for a two-tailed test was considered to indicate statistical significance.
8
Survival Analysis of Treatment Outcomes
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Data analyses were performed using SPSS statistical package 17.0 (SPSS Inc., Chicago, IL, USA). Statistical values are presented as the mean ± standard deviation. The Student t-test was used to assess differences between groups. A univariate analysis was performed using the Kaplan-Meier estimator method and a log-rank test. The median survival time was calculated using SPSS. p < 0.05 was considered to indicate a statistically significant difference.
9
Comparative Analysis of Treatment Outcomes
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All values were expresses as the mean ± standard deviation (SD). Statistical analysis was performed by using SPSS statistical package 17.0 (SPSS Inc., Chicago, USA). One way analysis of variance was conducted to compare the effects under different conditions. The least significant difference (LSD) test was used to determine differences at α = 0.05.
10
Multivariate Analysis of Experimental Data
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A pie chart and a three-dimensional histogram model were plotted using Microsoft Office Excel 2003 (Microsoft Corp., Redmond, WA, USA). Statistical analysis was performed using SPSS statistical package 17.0 (SPSS Inc., Chicago, IL, USA). One-way analysis of variance (ANOVA) was performed to determine the significance of the main factors and their interactions. p < 0.05 was considered statistically significant. Multivariate analysis was used to perform principal component analysis (PCA) by SIMCA-P software 11.0 (Umetrics, Umea, Sweden).
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