Unless otherwise mentioned, all calculations were carried out using SPSS software V.15 (SPSS Inc., Chicago, IL) with 2-sided significant tests. Independence of categorical variables was tested using the χ2 distribution. For small cell counts, a Fisher's exact test (2-tailed) was used. AAO and disease duration were tested for association with expansion using independent t-test. Mann-Whitney U-test was used to determine if the distribution of wild-type alleles is the same across categories of ethnicity and risk or nonrisk haplotype. Survival curve was generated using Kaplan-Meier test.
Spss software v15
Manufactured by IBM
Sourced in United States
SPSS software v15.0 is a comprehensive data analysis software package developed by IBM. It provides a range of statistical and analytical capabilities for researchers, analysts, and decision-makers. The core function of SPSS is to enable users to manage, analyze, and visualize data effectively.
Automatically generated - may contain errors
32 protocols using spss software v15
1
Statistical Analysis of Genetic Factors
2
Efficacy of Novel Intervention Protocol
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Data are presented as the mean and SD. Significance was calculated using Student’s t-test and a one-way analysis of variance (ANOVA) by SPSS software v.15 (SPSS, Chicago, IL, USA).
3
Immune Parameters and CD4 Counts
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Different characteristics of the different groups of subjects and immune parameters analyzed are given as median [interquartile range]. Non-parametric Kruskall-Wallis test (for multiple comparisons) and Mann-Whitney U-test (for two groups comparisons) was used to test differences between groups. Associations were explored using Spearman´s rho or Pearson correlation coefficients. Linear regression analyzes were performed to ascertain which immune parameters were significantly associated with change in CD4 counts. All analyzes were done with SPSS software v15 (SPSS Inc., Chicago, IL, USA) and statistical significance was considered only when two-tailed p-values were lower than 0.05.
4
Statistical Analysis of Variables
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Differences between variables were evaluated by the chi-square test and t test for categorical and continuous variables, respectively. SPSS software v. 15 was used for statistical analysis. All P values were two sided and values less than 0.05 considered to be significant.
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Differences between variables were evaluated by the chi-square test and t test for categorical and continuous variables, respectively. SPSS software v. 15 was used for statistical analysis. All P values were two sided and values less than 0.05 considered to be significant.
5
Analyzing miRNA Expression Patterns
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Data was analyzed using SPSS software v-15 (SPSS, USA) and GraphPad Prism software V5 (GraphPad, California, USA). Data are represented as mean ± SEM. Analysis of variance (one way ANOVA), Tukey. Chi square and post hoc tests were utilized for comparison with P value ≤0.05 considered to be significant. Since miRNA fold change values were not normally distributed as computed by Shapiro-Wilk test, we performed Mann Whitney and Kruskal Wallis as non-parametric tests and data was presented using median and quantiles. Analysis of correlation was carried out to investigate correlation between selected miRNAs in each category using Spearman correlation. Receiver operator characteristic (ROC) curves were plotted for evaluation of accuracy.
6
Analyzing Microbial Community Composition
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A Wilcoxon Rank Sum test corrected for multiple testing was used to compare relative abundances of OPUs between Antarctic and Subantarctic metagenomes, which was implemented in the R-script ANCOM (https://github.com/FrederickHuangLin/ANCOM ). Spearman correlation, Mann-Whitney tests, as well as a Wilcoxon signed rank test to analyze differences in relative abundance of WS/DGAT homolog sequences between free‐living and particle-attached communities in deep sea, were performed in SPSS software (v. 15, SPSS Inc., Chicago, IL, USA).
7
Correlating Molecular and Clinical Findings
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The SPSS software v.15 was used. Correlations between molecular findings and clinical parameters were assessed by the Mann-Whitney or by the chi-square test. Pictorial representation of survival curves was done by the Kaplan-Mayer method and their comparison by the log-rank test.
8
Statistical Analysis of Study Data
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All the statistical analyses were performed using SPSS software, v. 15 (SPSS, Chicago, IL, USA). The results were expressed as crude frequencies and percentages where appropriate. Descriptive results for numeric variables were presented as the mean value ± standard deviation (SD). Chi-square test and Mann-Whitney U test were used to compare the variables between the study groups. Besides, P value < 0.05 was considered as statistically significant.
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All the statistical analyses were performed using SPSS software, v. 15 (SPSS, Chicago, IL, USA). The results were expressed as crude frequencies and percentages where appropriate. Descriptive results for numeric variables were presented as the mean value ± standard deviation (SD). Chi-square test and Mann-Whitney U test were used to compare the variables between the study groups. Besides, P value < 0.05 was considered as statistically significant
9
Epidemiology and Mortality Factors in CAP
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We performed a descriptive analysis of demographics and predisposing conditions for CAP; data were expressed as percentages for categorical variables and as median (IQR) for continuous variables. Incidence rates of CAP were expressed as cases per 1000 person-years and were calculated by dividing the number of CAP cases during the 3-year period by the person-years of disease-free exposure time, which was obtained from population of the last census and assuming that CAP episodes were developed at a half-way point between follow-ups. A multivariate analysis of factors predicting 14-day mortality was performed by applying a binary logistic regression model (p values, OR and 95% CI). P values were two tailed and values less than 0.05 were considered statistically significant. Statistical analyses were conducted using SPSS software V.15.0 (SPSS).
10
Statistical Analysis of Experimental Data
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Statistical analysis was conducted using SPSS software v15.0 (SPSS Inc., Chicago, IL). Descriptive statistics of the variables measured in the study were obtained. Normality of data distribution was assessed with Kolmogorov-Smirnov test. Changes in different parameters from baseline to subsequent visits were compared using ANOVA test with Bonferroni correction. Correlations between different parameters were performed using Pearson correlation. Statistical significance criterion was established at p < 0.05.
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