All data are expressed as the mean ± SD. SPSS17.0 software package (IBM, Armonk, NY, United States) was used for statistical analyses. Homogeneity of variance test was performed. Then, the data were analyzed using a one-way ANOVA test or Welch test and a post hoc test. P < 0.05 was considered statistically significant.
Spss 17.0 software package
Manufactured by IBM
Sourced in United States
SPSS 17.0 is a software package developed by IBM for statistical analysis. It provides a range of statistical techniques, data management, and visualization tools to help users analyze and interpret data. The core function of SPSS 17.0 is to enable users to perform various statistical analyses, such as regression, correlation, and hypothesis testing, on their data.
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49 protocols using spss 17.0 software package
1
Statistical Analysis of Experimental Data
2
Nonparametric Statistical Analysis Protocol
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Non-parametric tests were applied for the statistical analysis. Comparisons within different groups in general were analyzed with the Kruskal-Wallis H test. P < 0.05 was considered statistically significant. Differences between each of two groups were analyzed with the Mann-Whitney U-test. P < α′ was considered statistically significant; α′ was calculated for multiple testing correction. α′ = α/0.5p (p – 1) (α = 0.05, p represents the number of groups). The statistical analysis for microarray and proteomic assays was as described above. SPSS 17.0 software package (IBM, Armonk, NY, USA) was used.
3
Statistical Analysis of OSAHS Risk Factors
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The data were encoded and the authors that performed the statistical analysis were therefore also blind to grouping. The normal distribution of the continuous data was tested by the Kolmogorov-Smirnov test. Continuous data that followed normal distribution were represented by means ± SD, whereas in any other case the median (range) was used. The continuous data between the two groups that followed normal distribution were represented by the student t test. The categorical data and/or grade data were expressed as n (%). Statistical analysis was carried out by the Chi-square and/or the rank sum tests. Moreover, univariable and multivariable logistic regression analyses were conducted. The parameters that were significantly different as determined by univariable analyses were included in the multivariable logistic regression analysis. The process of parameter inclusion was set to forward (the dependent parameter y was the presence of OSAHS, and the independent parameters were various potential risk factors). Correlation analysis was conducted by Pearson and/or Spearman correlation analysis. SPSS 17.0 software package was used (IBM, Armonk, NY, USA). A P value of lower than 0.05 (P<0.05) was considered statistically significant.
4
Nasal Symptom Improvement with Novel Treatment
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The randomization was provided centrally in a block of 4. Analysis was performed on all of the randomized patients who had both Visit0 and Visit1 follow-up data and had continued the study medication. A sample size of 28 patients (the treatment arm) was expected to have an 80% power to detect a difference of 9.4 between the NCP and placebo treatments in the mean total symptom scores from the nasal challenge,12 (link) with a standard deviation (SD) of 12.2 and a 2-sided alpha error of 0.05. All statistical analyses were conducted using the SPSS 17.0 Software Package (IBM, Chicago, IL, USA). Nonparametric tests were used as follows: the χ2 test for the differences in the distributions of the actual frequencies of the scores; the Mann-Whitney U test for the medians and the correlations between the groups; and the Wilcoxon signed-rank test for the medians and the correlations within each group. A P value of <0.05 was considered to indicate statistical significance.
5
Statistical analysis
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Statistical analysis was performed with the SPSS17.0 software package for Windows by using the two-sided Student’s t-test for independent groups. Statistical significance was based on a value of P < 0.05. Data are expressed as mean±s.d.
6
Statistical Analysis of Research Data
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SPSS17.0 software package (SPSS, Inc) was utilized to conduct all statistical analyses. All data were presented as the mean ± SD (standard deviation). ANOVA (one‑way analysis of variance) was performed to compare between two groups. Three‑way ANOVA was performed to compare the differences among three groups. The P value of less than .05 was considered significant.
7
Statistical Analysis of Experimental Data
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Data were expressed as mean ± standard deviation. All statistical analysis was performed with SPSS 17.0 software package (SPSS Inc., Chicago, USA). Statistically significant differences between groups were determined by ANOVA followed by Tukey's test. The results were considered statistically significant if P values were <0.05.
8
Statistical Analysis of Research Data
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SPSS 17.0 software package (SPSS Inc.) was used for statistical analysis. Data were presented as the median (range) or mean ± standard deviation in intergroup comparisons. Student's t‐test or a nonparametric Mann–Whitney U test were used to determine differences between two groups, whereas one‐way analysis of variance was used to compare differences among multiple groups. Repeated measures analysis of variance was used to evaluate the continuous data. Statistical significance was defined as p < .05.
9
Differentiating Neoplastic and Bland Portal Vein Thrombosis
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Regions of interest (ROI) were drawn directly to delineate the entire HCC and PVT, avoiding any vessels and hemorrhages (Figure 1 ). The mean and standard deviation (SD) of the Siemens Phase Unit (SPU) were obtained from the entire ROIs and converted into radians using the following equation: (SPU-2048) x π /2048 [15 (link)]. The phase values of the tumors in the neoplastic and bland cohorts were compared using the Mann–Whitney test. The phase values of the tumors and thrombi were compared in each group using the Wilcoxon matched pairs signed rank test. The phase values of the thrombi of the two cohorts were compared using the Mann–Whitney test. P values <0.05 were considered statistically significant. Receiver operator characteristics (ROC) analysis was conducted to evaluate the diagnostic ability of phase values for neoplastic and bland thrombi discrimination. The areas under the ROC curve (AUC) and the confidence intervals (CIs) were assessed. The cut-off values that maximized the sum of the sensitivity and specificity were determined and set as the point in the most upper left hand corner. All statistical analyses were performed with the SPSS 17.0 software package (SPSS Inc., Chicago, IL, USA).![]()
10
Music Intervention for Anxiety and Depression
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Data are presented with means±standard deviations for continuous variables or with numbers and percentages for categorical variables. Normality of distribution was confirmed through Kolmogorov-Smirnov testing. The unpaired t test or Mann-Whitney U test (for non-normal distributions) was used for between-group comparisons. Categorical variables were compared through chi-squared testing.
Repeated-measures analysis of variance (repeated-measure ANOVA) was performed to compare the differences in HAMA and GDS scores between the intervention and control groups over time. There were 3 time-points (baseline, week 6, and week 12) throughout the trial. Time-dependent effects of the music intervention on HAMA or GDS between intervention and control groups were assessed by fitting a “time x group” interaction term. If the “time x group” interaction effect on GDS or HAMA was statistically significant, a post hoc t test was used to compare the mean difference of GDS or HAMA at each assessment time point. Within the intervention group, we further compared the differences in clinical symptoms over time between low and high musical aptitude subgroups using the same repeated-measures ANOVA followed by post hoc t tests. The SPSS 17.0 software package (SPSS, Inc., Chicago, IL, USA) was used for statistical analysis. A P value of less than 0.05 was considered statistically significant.
Repeated-measures analysis of variance (repeated-measure ANOVA) was performed to compare the differences in HAMA and GDS scores between the intervention and control groups over time. There were 3 time-points (baseline, week 6, and week 12) throughout the trial. Time-dependent effects of the music intervention on HAMA or GDS between intervention and control groups were assessed by fitting a “time x group” interaction term. If the “time x group” interaction effect on GDS or HAMA was statistically significant, a post hoc t test was used to compare the mean difference of GDS or HAMA at each assessment time point. Within the intervention group, we further compared the differences in clinical symptoms over time between low and high musical aptitude subgroups using the same repeated-measures ANOVA followed by post hoc t tests. The SPSS 17.0 software package (SPSS, Inc., Chicago, IL, USA) was used for statistical analysis. A P value of less than 0.05 was considered statistically significant.
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