All the analyses were conducted independently for at least three times in cells of different passages and the data were analysed based on ANOVA and Duncan’s multiple range test to compare means for significant difference (P < 0.05) by employing a SPSS software system (IBM, New York, NY, USA).
Spss software system
Manufactured by IBM
Sourced in United States
SPSS is a comprehensive statistical software system developed by IBM for analyzing data. It provides a wide range of statistical and analytical tools for data management, data analysis, and reporting. The core function of SPSS is to enable users to perform advanced statistical analysis on various types of data, allowing for the identification of significant patterns, trends, and relationships within the data.
Automatically generated - may contain errors
Lab products found in correlation
29 protocols using spss software system
1
Statistical Analysis of Cell Data
2
Statistical Analysis of Sepsis Factors
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Chi-square tests or Fisher exact tests, where appropriate, were used for the statistical analysis of categorical variables. Continuous variables are presented as the mean (standard deviation) and compared using the independent sample t test because a normal distribution was noted. The forward selection multiple logistic regression model was used to identify factors that might be associated with sepsis in these patients. Clinical variables and spectral powers of HRV with a univariate comparison of P < .2 between the 2 groups were eligible for inclusion in the model. The receiver operating characteristic (ROC) curve for statistically independent HRV variables associated with sepsis was also drawn. A P < .05 was considered statistically significant. Bonferroni correction was performed, and P < .007 was considered statistically significant for HRV measure comparisons. Statistical analyses were performed using SPSS software system, version 23.0 (IBM, Armonk, NY, USA).
3
Relationship between E-cadherin, β-catenin and Clinicopathology
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The relationship between E-cadherin and β-catenin expression and clinicopathologic parameters were analyzed using a two- tailed Chi-square test or Fisher's exact test. The correlation between E-cadherin and β-catenin expression status was analyzed with the Spearman's rank test. Survival estimation was performed with the Kaplan-Meier method and log rank test. Univariate or multivariate analysis of prognostic factors was analyzed with Cox proportional hazards regression models. All statistical analyses were performed using the SPSS software system (version 19.0; SPSS, Inc., Chicago, IL, USA). P < 0.05 was considered to be statistically significant.
4
Evaluating EZH2 and Ki67 Expression
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Measures of continuous parameters, such as age, were summarized using mean, standard deviation, median, and range. Relationship between EZH2 and Ki67 expression was evaluated with Spearman correlation using SPSS software system (version 26.0; SPSS, Inc., Chicago, IL, USA). p value of <0.05 was considered statistically significant.
5
Statistical Analysis of Categorical and Continuous Variables
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The numbers of cases (n) and frequencies (percentages) were calculated for categorical variables, and the means ± standard deviations (SDs) or medians were calculated for continuous variables. Student’s t-test and chi-square test were used to analyze the differences between two groups in continuous variables and categorical variables, respectively. We defined a P value < 0.05 as statistically significant. All statistical analyses were performed using SPSS software system (version 20.0, SPSS, Inc., Chicago, IL).
6
Periparturient Micronutrient Feeding Analysis
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The data was analyzed by using the SPSS software system (version 22). All the data obtained from the study were expressed as mean ± standard error and were analyzed by two-way ANOVA. Tukey"s multiple comparison test was used to find significance at the 5 percent level. The effect of treatment group (Gr), days (D) of the periparturient period, and their interactions (Gr×D) were estimated using the statistical model shown below
where, Yijk is a dependent variable, μ is the overall mean of the population, Gri is the effect of micronutrients feeding (i = 4), Dj is the effect due to the measurement days (j = 4 - 7 based on parameters studied), and (GrD)ij is the effect due to treatment group by measurement days’ interactions, and eijk is the residual error.
where, Yijk is a dependent variable, μ is the overall mean of the population, Gri is the effect of micronutrients feeding (i = 4), Dj is the effect due to the measurement days (j = 4 - 7 based on parameters studied), and (GrD)ij is the effect due to treatment group by measurement days’ interactions, and eijk is the residual error.
7
Diagnostic Biomarkers for Urinary Tract Infection
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Median, range, and interquartile range (IQR) were reported when appropriate. Comparisons between groups were made using the nonparametric tests: Mann-Whitney U test, χ2 test, and Fisher's exact test. The level of statistical significance was defined as a 2-tailed P value of 0.05. Correlations between variables were assessed using the Spearman's rank coefficient. Receiver operating characteristic curves were constructed, and areas under curves (AUC) were calculated to illustrate the diagnostic power of U-HBP, U-IL-6, U-WBC, and U-nitrite. Sensitivity, specificity, positive predictive values (PPVs), and negative predictive values (NPVs) were calculated. The SPSS software system, version 20.0, was used for statistical calculations. Figures were made using GraphPad Prism 6 software.
8
Improving Donation Willingness: Evaluating Publicity Methods
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Quantities and percentages were calculated from all data. To explore whether all the three methods increase participants' willingness to donate, McNemar's test was used to compare the donation rate of the same groups before and after publicity. A Chi-square test was used to compare data between groups, to determine the effect of the three methods in improving participants' willingness to donate, and to identify the most effective method. A Chi-square test was also used to analyze whether gender, residence, education, profession, or health condition influenced the effectiveness of text-based material, picture-based material, or a lecture in raising participants' willingness to donate. Fisher's exact test was applied to cases in which the expected frequencies were <5. All statistical analyses were conducted using SPSS software system (SPSS version 22).
9
Biomarker Correlation and Survival Analysis
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The correlation between biomarkers was determined using Fisher's exact test. Relationships between clinical-pathological parameters were assessed using contingency tables with a Fisher's exact test. Survival curves were estimated using the Kaplan-Meier method and compared using the log rank test. Overall survival (OS) was calculated from the day of surgery to the day of death or to the end of follow-up. Disease-free survival (DFS) was calculated from the day of surgery to the documented day of disease progression (relapse or metastasis) or to the end of follow-up. Univariate and multivariate survival analyses with calculation of hazard ratios (HR) were performed using Cox's proportional-hazards model. All statistical analyses were performed using the SPSS software system (version 17.0; SPSS. Inc., Chicago, IL, USA). A p-value ≤ 0.05 was considered to be statistically significant.
10
PD-L1 Expression in Histological Analysis
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Statistical analyses were performed using the SPSS software system (version 24.0, Chicago, IL, USA). Chi-square or Fisher’s exact tests and logistic regression analysis were used to determine if any association was evident between PD-L1 expression and histological characteristics. Kappa tests were used to analyse the concordance between paired specimens, and the strength of concordance was categorized as follows: kappa value >0.75, good agreement; 0.4 to 0.75, moderate agreement; <0.4, poor agreement. All statistical values were determined using two-tailed statistical analyses, and a P value <0.05 was considered to indicate a statistically significant difference.
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