Spss statistics for windows version 25

Data are presented as median (range). In calculations, hormone concentrations below LOD were assigned the value LOD/2. The Mann-Whitney U test was used for comparisons between groups. The Wilcoxon matched-pairs signed-rank test was used for 2 dependent samples. Correlation analyses were performed using Spearman (rho) nonparametric rank correlation and R². A P value < 0.05 was considered significant. The software IBM SPSS Statistics for Windows, version 25.0 (IBM Corp, Armonk, NY, USA) was used for statistical analyses. Figures were drawn using SPSS or Origin version 9.0 (OriginLab Corporation, Northampton, MA, USA).

A ten-question survey was designed and delivered to FY2 doctors who graduated in 2017
and completed their two-year postgraduate foundation training in 2019. The details
of the survey are shown in Table 1. The
survey focused on: a) student exposure to CTS within their undergraduate curriculum,
b) student exposure to CTS outside their undergraduate curriculum, c) exposure to
CTS as a doctor within their postgraduate foundation training, d) foundation doctor
exposure to CTS outside of postgraduate foundation training, and e) their
self-reported interests in CTS.
The survey was delivered online to junior doctors in 2019. The study was conducted
using the SurveyMonkey® platform and was distributed through junior doctor
social media groups and university societies. Medical schools with no graduates in
2017 and 2018 were excluded from our study. IBM Corp. Released 2017, IBM SPSS
Statistics for Windows, Version 25.0, Armonk, NY: IBM Corp. and Microsoft Excel
365® were used for data collection and Student’s t-test statistical analysis.
A P-value < 0.05 is deemed statistically significant.

Statistical significance between groups was determined using Mann–Whitney U‐test of Student’s t‐test. Statistical analysis on growth curves was assessed using two‐way repeated measures ANOVA. Z‐scores of MRI and Mercox parameters were determined by normalization of each experimental mouse to the average and standard deviation of control mice. Pearson’s correlation coefficients were calculated to determine P‐values in gene expression data. Bar graphs and dot plots with error bars represent mean and ±SD, respectively. Box plots represent minimum, first quartile, median, third quartile, and maximum. Statistical analyses were performed using graphpad prism 6 (San Diego, CA, USA) and ibm spss statistics for Windows, version 25.0 (IBM Corp, Armonk, NY, USA). Tests were performed two‐tailed, and a P‐value < 0.05 was considered statistically significant.

Statistical analysis was performed with IBM^®SPSS^® statistics for Windows, version 25.0 (IBM Corp, Armonk, NY, USA). Data are reported as mean ± standard deviation. Differences on archery performance (total score) were detected with a paired-samples t-test. The normality of data was assessed by the Kolmogorov–Smirnov test. All data were normally distributed, and comparisons on subjective feelings between trials and over time (baseline vs. end of archery competition) were made with a two-way Repeated Measures ANOVA (time point × trial). Heart rate response at rest and after arrow throw was also analyzed with two-way Repeated Measures ANOVA (time point × trial). Bonferroni post-hoc analysis was performed where necessary. Effect sizes were calculated using partial eta squared (η²) interpreted as 0.01 for small, 0.06 for moderate and 0.14 for large. Statistical significance was set at p < 0.05. Statistical power analysis was performed using the G*Power 3.1 power analysis software. Post hoc power analysis revealed that the sample size of the present study was adequate to provide statistical power of both heart rate and other main parameters of the study such as fatigue, concentration and thirst) with >90% power and with a significance level, α = 0.05.

Study participants were categorized according to the baseline eGFR. The baseline characteristics, angiographic characteristics and procedural details, intraprocedural and in-hospital complications were shown in Tables 1–3. Continuous variables are presented as the mean ± standard deviation or the median and interquartile range, whereas categorical variables are presented as percentages. Continuous variables were compared with the ANOVA test (normal distribution) or Kruskal–Wallis H test (abnormal distribution). Categorical variables were compared with the chi-square test or Kruskal–Wallis H test (NYHA functional class). The changes of symptoms and QOL (EQ-5D) were showed in Tables 5, 7. The comparison between two groups was used the student t-test while the comparison among four groups was used ANOVA test. Univariable and multivariable binary logistic regression analysis were performed to identify the risk factors of in-hospital complications and 1-year symptoms and QOL improvement in patients with low eGFR (<90 mL/min/1.73 m²) after successful CTO-PCI (Tables 4, 6, 8). A two-sided probability (p) value of <0.05 was considered significant. All calculations were performed with IBM-SPSS Statistics for Windows, version 25.0 (IBM Corporation, Armonk, NY, USA) and STATA 14 software (https://www.stata.com/stata14/).