Pasw statistics for windows version 18

Statistical analyses were performed by using statistical software (PASW Statistics for Windows, version 18.0; IBM Co., Armonk, NY, USA). The significance level was set at 0.05.
A pilot study estimated the expected difference in the mean SBS values between the untreated and the treated specimens as 2.3 MPa and the within-group standard deviation as 2.4 MPa. Given the α level of 0.0167 (Bonferroni adjustment for multiple comparisons) with a power of 80%, a minimum number of 24 specimens was required for each group.
The Shapiro-Wilk test showed that the SBS data were consistent with a Gaussian distribution in the control and 0°-angulation groups, but they were not normally distributed in the 45°-angulation group. Therefore, Kruskal-Wallis test was used to evaluate these data. Pairwise comparisons were performed by using the Mann-Whitney U-test with Bonferroni correction (adjusted α level = 0.0167). The Kruskal-Wallis test was also used to assess the significance of the differences in the ARI scores among the groups.

All statistical calculations, except for those of the pyrosequencing data, were conducted using PASW Statistics for Windows, version 18.0 (Released 2009; IBM Corp, Armonk, NY USA). Groups were compared using the Mann-Whitney U test (also known as the Wilcoxon rank-sum test). Correlations between gene expression and species were determined using Spearman’s correlation. Statistical significance was set at P < 0.05.

The intention-to-treat analysis was used with the last-observation-carried-forward (LOCF) method. All values were presented as mean and standard deviation or n (%) unless stated otherwise. An independent t test was used to compare the changes in the scores after performing the Shapiro-Wilk test to confirm the normality of the distribution. All statistical analyses were 2 sided, and statistical significance was set at .05. The resultant data were analyzed using the corresponding 1-way analysis of covariance, considering the baseline scores as covariates. Baseline variables were compared between the groups by using the independent t test, chi-square test, or Fisher’s exact test. All statistical analyses were performed using PASW Statistics for Windows, Version 18.0 (IBM Corp, Armonk, NY, USA) and GraphPad Prism 5 (GraphPad Software Inc, San Diego, CA, USA).

Continuous data that were normally distributed are presented as the
mean ± standard deviation. Data that were not normally distributed are presented
as the median and interquartile range. Fisher’s exact test was performed.
P < 0.05 (two-sided) was considered statistically
significant. Statistical analyses were performed by using PASW Statistics for
Windows, version 18.0 (IBM, Armonk, NY, USA).

The intrareliability of the principal investigator was tested by measuring all of the samples as described previously, with measurements repeated 2 weeks later. The measurements showed high reliability (r > 0.9). The data analysis was performed using the paired-samples t-test. Because the raw data for a few variables were not distributed on a normal curve, as indicated by the Shapiro-Wilk normality test, we performed nonparametric tests. Since similar results were found with the parametric and nonparametric tests, the parametric data were reported for all variables. Statistical significance was set at 0.05. Data analysis was performed using PASW Statistics for Windows, version 18.0 (IBM Corp., Armonk, NY, USA).

The reliability of the ISI and ESS was evaluated by estimating internal consistency using Cronbach's alpha. The factorial validity of the ISI and ESS was assessed using exploratory factor analysis (EFA; principal axis factoring) with promax rotation. The number of factors was determined based on eigenvalues (> 1), which represents the variance explained by each factor, as well as the coherence and interpretability of the factors. The factors that were identified by the EFA were tested using confirmatory factor analysis (CFA). Model fit was evaluated using criteria based on fit indices, such as RMR < 0.05, GFI > 0.90, RMSEA < 0.08, NFI > 0.9 and AGFI > 0.90.25 All analyses were conducted with PASW Statistics for Windows, Version 18.0 and AMOS 18.0 (IBM Co., New York, NY, USA).

The patients were grouped into three age groups. The continuous variables were expressed as means ± SD and categorical variables as numbers (percentage). The data were analyzed using One-way analysis of variance (ANOVA) or Student’s t-tests for continuous variables and Chi-square tests for categorical variables. Stepwise multivariate logistic regression analyses were performed to identify the factors associated with uroseptic shock in UTI and very old patients with UTI, respectively. P values <0.05 were considered statistically significant. All analyses were performed using PASW Statistics for Windows, version 18.0 (IBM Corp.).