Associations between the clinicopathological features and IGFBP-6 expression were evaluated with the χ2 test and Pearson's index. The overall survival curves and survival differences were analyzed by the Kaplan-Meier method and log-rank test. Multivariate analysis was assessed using the Cox proportional-hazard regression model. The predictive ability of the two models including and excluding IGFBP-6 expression and other prognostic clinicopathological variables were compared based on Akaike information criterion (AIC) and Harrell's concordance index (c-index). The minimum AIC value indicates the optimum predictive prognosis model with the least clinicopathological data loss and inefficiency. Harrell's c-index was an index to evaluate the predictive accuracy, with a value much closer to 1.0 implying higher accuracy. All data were analyzed statistically using the SPSS 18.0 software package (SPSS, Inc., Chicago, IL, USA), and statistical significance was considered to be indicated by P<0.05 in a two-tailed test.
Spss 18.0 software package
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SPSS 18.0 is a software package developed by IBM that provides advanced statistical analysis capabilities. The software is designed to handle a wide range of data types and offers a variety of analytical tools, including regression analysis, data mining, and predictive modeling. The core function of SPSS 18.0 is to assist users in the analysis and interpretation of complex data sets.
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Lab products found in correlation
24 protocols using spss 18.0 software package
1
Prognostic Value of IGFBP-6 Expression
2
Statistical Analysis of Experimental Data
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Statistical analysis was performed using SPSS 18.0 Software Package (SPSS Inc., Chicago, USA). The experimental values were analyzed using paired-samples t test and expressed as mean values ± standard deviation (SD). One-way analysis of variance (ANOVA) was performed to determine the differences between groups for each evaluated parameter at each time point. Non parametrical tests [κ independent samples tests (Kruskal–Wallis test)] were calculated when equal variances were not assumed in one-way ANOVA. The level of significance was defined as P < 0.05.
3
Propensity-Matched Analysis of Antibiotic-Loaded Bone Cement
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Continuous and categorical variables are presented as means (with standard deviation, SD) and counts and percentages, respectively. Continuous data was compared between the groups with the Student's t-Test for independent samples and, over time, with the Paired Student’s t-Test. Categorical variables were compared with the Chi square or Fisher test, when appropriate. A bivariate analysis comparing each parameter with the assigned group was completed using the Chi Square or Fisher test as necessary. P values of < 0.05 were considered statistically significant. A propensity matching score was made to assess the covariates (antibiotic-loaded bone cement).
No power size calculation was needed for the main purpose as it was a descriptive one. For the second purpose, the Chi Square difference test was used to determine the sample size. Assuming a statistically significant difference of KSS greater than or equal to 5 units and a 10% rate of lost to follow-up, 9 subjects were necessary in the first group and 18 in the second group, establishing an α error of 0.05 and a statistical power of 80%.
The statistical analysis was done using SPSS 18.0 software package (SPSS Inc., Chicago, IL).
No power size calculation was needed for the main purpose as it was a descriptive one. For the second purpose, the Chi Square difference test was used to determine the sample size. Assuming a statistically significant difference of KSS greater than or equal to 5 units and a 10% rate of lost to follow-up, 9 subjects were necessary in the first group and 18 in the second group, establishing an α error of 0.05 and a statistical power of 80%.
The statistical analysis was done using SPSS 18.0 software package (SPSS Inc., Chicago, IL).
4
Microbial Community Analysis of Chemical Properties
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All statistical analyses were conducted using the SPSS 18.0 Software package (SPSS Inc., Chicago, IL, United States). Differences in datasets were evaluated by conducting one-way ANOVA tests followed by least significant difference (LSD) tests. Differences were considered significant at p < 0.05. The unweighted pair group method with arithmetic mean analysis (UPGMA) hierarchical clustering was used to assess community compositional similarities based on Bray-Curtis distances with microbial abundance data within the R vegan package v.2.5-7 (Oksanen et al., 2019 ). Correlations among microbial compositional characteristics and chemical properties were estimated by Spearman’s correlation coefficients, and strong correlations were identified by values of | ρ| > 0.7 and a p < 0.05. Heatmap visualization was constructed in the R environment with the “vegan” package.
5
Statistical Analysis of Cell Viability
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In this study, all experiments were repeated at least three times, and data are expressed as the mean ± SEM SPSS 18.0 software package (SPSS, Chicago, IL, United States) was used to perform statistical analysis. The Inhibitory concentration 50 (IC50) values were taken from the minimal experimental concentration showing 50% cell death and calculated using GraphPad Prism 7. Difference between two groups was compared by independent-samples t test. Difference among three or more groups was compared by One-Way ANOVA with post hoc Bonferroni test. The clinical association between MIAT expression and clinicopathological variables in lung cancer patients was evaluated by chi-square test. The P value less than 0.05 were considered statistically significant.
6
Diagnostic Biomarkers in Colorectal Cancer
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Data are shown as mean ± standard deviation for normally-distributed variables and as absolute and relative frequencies for categorical variables. Tumor markers CA 19-9 and CEA deviated from normal distribution and are presented as geometrical mean and 95th confidence interval. For inter-group comparison we have used Student-t test and ANOVA, with distinct post hoc test where appropriate, and chi-square test for frequency data comparison.
We performed receiver operating characteristic (ROC) curves analysis and sensitivity and specificity calculation within a group consisting of the control group and all CRC patients (Group I), and within a group consisting of the control group and patients classified as Dukes A/B (Group II). Additionally, we used ROC analysis to test CEA and CA 19-9 capability to discriminate subjects with and without CRC. The SPSS 18.0 software package (SPSS. Chicago, IL, USA) and Medcalc software, version 13.2 were used for all calculations.
We performed receiver operating characteristic (ROC) curves analysis and sensitivity and specificity calculation within a group consisting of the control group and all CRC patients (Group I), and within a group consisting of the control group and patients classified as Dukes A/B (Group II). Additionally, we used ROC analysis to test CEA and CA 19-9 capability to discriminate subjects with and without CRC. The SPSS 18.0 software package (SPSS. Chicago, IL, USA) and Medcalc software, version 13.2 were used for all calculations.
7
Analyzing Left Atrial Appendage Thrombus Risk
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SPSS 18.0 software package (Chicago, IL, USA) was used for data processing. Data were expressed as mean ± standard deviation (SD). One-way analysis of variance (ANOVA) was employed in the comparison of multiple sets of measurement data. LSD methods were used to compare between two mean values of multiple sets of mean values. Pearson's method was applied to compare LAA-PEV, LAA-V and LAA-EF. Receiver operating characteristic (ROC) curve was used in the prediction of cut-off values of the left atrial appendage thrombus through LAA-EDV and LAA-ESV. P<0.05 was considered statistically significant.
8
Soil Nitrogen Dynamics in Naphthalene-Amended Microcosms
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The net ammonification, nitrification and inorganic N mineralization at the end of the incubation (52 days) was calculated as the differences in the NH4+-N (ammonium), nitrate (NO3--N) and inorganic N (NH4+-N + NO3--N) contents in the microcosms between the start and end of the incubation. Moreover, data for quantifying the effects of naphthalene addition on soil biochemical properties were calculated as the differences in the average values of the measured variables between the naphthalene treatments and the controls during the whole incubation period.
For specific sampling times, Student’s independent-sample t-test was used to compare the effects of naphthalene application. We used repeated measures of analysis of variance (ANOVA) to test the effects of naphthalene application, sampling time, and their interactions on the measured variables. Differences were considered significant at P < 0.05 level for all analyses. All statistical analyses were performed using SPSS 18.0 software package for Windows (SPSS Inc., IL, USA).
For specific sampling times, Student’s independent-sample t-test was used to compare the effects of naphthalene application. We used repeated measures of analysis of variance (ANOVA) to test the effects of naphthalene application, sampling time, and their interactions on the measured variables. Differences were considered significant at P < 0.05 level for all analyses. All statistical analyses were performed using SPSS 18.0 software package for Windows (SPSS Inc., IL, USA).
9
Survival Outcomes and Immune Markers in Breast Cancer
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Disease-free survival (DFS) was defined as the time from the first diagnosis of breast cancer to the initial occurrence of disease relapse (local, regional, or distant). Overall survival (OS) was defined as the time between the date of the primary surgery and the date of death. Patients without any evidence of relapse or death were censored at the last date they were known to be alive. The probability of postoperative DFS and OS was derived from a Kaplan-Meier estimate, and the differences between the survival curves were compared using the log-rank test. MyD88 or TLR4 high-expressing tumors were compared with low-expressing tumors using the two-sided Pearson χ2 test. The effects of MyD88, TLR4, and other possible risk factors on DFS and OS were assessed by a Cox proportional hazards regression using a univariate or multivariate analysis with adjusted hazard ratios (HRs) and associated 95% confidence intervals (95% CI).
Statistical analyses were analyzed using the SPSS 18.0 software package (SPSS, Chicago, IL, USA). All P values were two sided, and p<0.05 was considered significant.
Statistical analyses were analyzed using the SPSS 18.0 software package (SPSS, Chicago, IL, USA). All P values were two sided, and p<0.05 was considered significant.
10
Statistical Analysis Using SPSS
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SPSS 18.0 software package (SPSS Inc., Chicago, IL, USA) was used for analysis. Data are presented as the mean ± standard deviation. The means of multiple groups were compared with one-way analysis of variance (ANOVA), P<0.05 was considered to indicate a statistically significant difference.
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