Spss statistics v21

The independent sample Kruskal-Wallis test (multiple groups) were used to compare proportions of the resistances to antimicrobials for ESBL-producing strains between species, regions, and food types groups by SPSS Statistics V21.0; the independent sample Kruskal-Wallis test (multiple groups) were also used to compare proportions of ESBL-positive Enterobacteriaceae between food type and regions groups by SPSS Statistics V21.0.

Results for all variables are given as mean (SD) [minimum‐maximum], unless stated otherwise.
A one‐way analysis of variance (ANOVA) for repeated measurements was used to evaluate the null hypothesis that there is no difference among patients' mean values for hemodynamic physiological variables obtained at the three measuring points t0, t1 and t2. ANOVA used Greenhouse‐Geisser correction for non‐sphericity if needed. If the ANOVA revealed a difference between the values, post hoc analysis using Bonferroni multiple comparisons test was done. Student's t‐test for paired data was used to compare CVP measurements.
A two‐sample t‐test for groups with unequal variances (Welch's test) was used to compare intraoperative fluids given to our last 10 patients with those reported in two recent papers on intraoperative management in pediatric kidney transplantation.5, 6Data were analyzed using GraphPad Prism V7.0d (GraphPad Software) and IBM SPSS Statistics V21.0. P < .05 was considered statistically significant.

X-tile analysis was performed to dichotomize all 416 patients into galectin-7 low and high groups based on the intensity of immunohistochemistry straining. Fisher's exact test, chi-square test and independent samples t-test were conducted to appraise the correlation of galectin-7 expression and clinic-pathologic factors as appropriate. Kaplan-Meier method was used to plot survival curves. Multivariate Cox regression analyses was conducted to explore independent predictive factors. The concordance index (C-index) and Akaike's Information Criteria (AIC) were used to evaluate the predictive power of different models [37 (link)]. Statistical analyses were conducted with X-tile 3.6.1 (Yale University, New Haven), MedCalc 11.4.2.0 (MedCalc, Mariakerke), IBM SPSS Statistics v21.0 (IBM Corp, Armonk), R 3.2.3 (R Foundation for Statistical Computing, Vienna) and Stata SE 12.0 (Stata, College Station, TX).

In order to simulate leaf length and half-leaf width distribution of C. lanceolata, we fitted leaf tapering function with parabolic models. The best 108 leaves were used to construct the leaf tapering models to calculate the average model in each age group trees and the remaining leaves were used to test the robust of the model and all leaves (308 leaves per age groups and 1848 leaves in total) are used in analysis. Means, standard deviation, 95% confidential interval, median, minimum and maximum value were used to describe leaf width and tipping length ratio. We have checked normality of all data (Shapiro-Wilk normality test), and the tipping leaf length ratio was log10-transformed to test differences between each age groups. The differences between leaf width and tipping length ratio in each leaf among tree age groups were tested using a One-Way ANOVA test (Fisher LSD test) of significance. The model fitting, statistical description and ANOVA test were performed in software IBM SPSS Statistics v 21.0 (IBM Corp., Armonk, NY, USA). The charts were plotted in software OriginPro v 8.0 (OriginLab Co., Northampton, MA, USA) and R software version 3.6.1 (R Core Team 2019) [76 ].

Sample sizes were determined using Altman’s nomogram based upon a 5% significance level and 80% statistical power, with the unit of analysis being number of litters. Fetal weight was the primary outcome and studies were powered according to data from similar studies by our group (Dilworth et al., 2013 (link)). All data were normally distributed following a D’Agostino and Pearson normality test and are shown as mean ± SEM. A Generalized Linear Mixed Models approach, with each litter (dam) used as a random effect, was used to assess whether there was a significant effect of genotype and/or treatment for fetal/placental weights and biometric measures. A Sequential Sidak multiple comparisons test was then used to test for differences between groups. For uterine and umbilical artery wire myography, a two-way ANOVA was used to assess the effects of genotype and treatment, followed by Bonferroni’s post-test to compare differences between individual groups. P < 0.05 was deemed statistically significant. Statistical analyses were performed using either IBM SPSS Statistics v21.0 (IBM, New York, NY, United States) or Graphpad prism v6.0 (Graphpad, La Jolla, CA, United States).