Data were analyzed using SPSS 18.0 statistical software. Each variable was assessed for a normal distribution. Continuous variables were expressed as the mean ± standard deviation (SD) or median (inter-quartile range[25-75%]) and were compared using the one-way ANOVA or KruskaleWallis H test. Categorical variables were presented as numbers and proportions and were compared using the chi-square test. Multivariate logistic regression analyses were used to analyze the significance of variables in arterial stiffness and the 10-year CVD risk after adjusting for other confounding risk factors. The metabolic status interaction between BMI and baPWV was assessed using generalized linear models (GLMs). Significance tests were two-tailed, and a p value < 0.05 was considered significant.
Spss 18.0 statistical
Manufactured by IBM
Sourced in United States
SPSS 18.0 is a statistical software package developed by IBM. It provides a range of tools for data analysis, including data manipulation, statistical modeling, and reporting. The software supports a variety of data types and offers a user-friendly interface for analyzing and interpreting data.
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Lab products found in correlation
142 protocols using spss 18.0 statistical
1
Arterial Stiffness and CVD Risk
2
Statistical Analysis of Experimental Data
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Statistical analysis was performed using SPSS 18.0 statistical software. The data are expressed as means ± SEM and one-way analysis of variance (ANOVA) was used to compare the differences among groups. The comparison between two different groups was performed by t test and differences were considered statistically significant if P<0.05.
3
Comparative Analysis of Soil Microbiomes
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Standard errors are indicated and Student’s two-tailed t-test was used for experimental comparisons. A single asterisk (∗) indicates that the difference is statistically significant at P < 0.05 while double asterisks (∗∗) indicate that the difference is statistically significant at P < 0.01. Treatments with different letters are significantly different at the 0.05 probability level, with the statistical analysis performed by comparing means in the SPSS 18.0 statistical package.
4
ANOVA Analysis of Experimental Data
5
Coronary Restenosis Genetic Risk Factors
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The SPSS 18.0 statistical package was used for statistical analyses. Gene linkage disequilibrium was analyzed by SHEsis software (http://analysis.bio-x.cn/myAnalysis.php ). Gene frequency was calculated for all genotypes or alleles, and the difference among groups was performed using multiple group comparison. Data for continuous variables were presented as mean value±standard deviation (SD). Depending on data types, non-parametric Mann-Whitney test or chi-square test were used for testing the differences among the groups. In addition to univariate analysis, multivariate Logistic regression analysis was performed to evaluate the correlation of coronary restenosis with geographic factors (gender and age), comorbidity (hypertension and diabetes), lifestyle (smoking and alcohol drinking), lipid profiling, renal function (creatinine) and RAS gene polymorphisms. For multivariate logistic regression analysis, odds ratio (OR) and its 95% confidence interval (CI) were calculated. In all analyses, p<0.05 was considered statistically significant.
6
Statistical Analysis of Experimental Data
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SPSS18.0 statistical software was used to process the data. The measurement data are expressed by the mean standard deviation (±s), which all conform to the normality test, and two independent samples are used for t-test. The inter-group count data were expressed by (%), and Pearson χ2 test was used. and the Mann-Whitney U test was used for rank data between groups. P < 0.05 was considered a statistically significant difference.
7
Statistical Analysis of Ophthalmic Outcomes
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Statistical analysis of all the variables including visual acuity, IOP, corneal endothelium, and hexagonal cell ratios before surgery, 1 week, 1 month, 3 months, and 6 months after surgery, was performed using SPSS 18.0 statistical software. Both the Quantile-Quantile plot and Kolmogorov-Smirnov test (P > .05) showed a normal distribution for parameters such as visual acuity, corneal endothelial cells, and intraocular pressure. Statistical analysis of the preoperative and postoperative data was performed using the paired t test. Statistical analysis among multiple groups was performed using analysis of variance. P < .05 was considered statistically significant.
Vision was converted to the logarithm of the minimum angle of resolution (logMAR) vision to facilitate statistical analysis. The standard logMAR visual acuity with hand motion and finger count is 2.4 and 2.1, respectively.[10 (link)]
Vision was converted to the logarithm of the minimum angle of resolution (logMAR) vision to facilitate statistical analysis. The standard logMAR visual acuity with hand motion and finger count is 2.4 and 2.1, respectively.[10 (link)]
8
Survival Analysis of SIRT2 Levels
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All statistical analyses were carried out using the SPSS 18.0 statistical software package. All data were statistically analyzed using one-way ANOVA with a Bonferroni correction, followed by Fisher's exact test. Bivariate correlations were calculated by Spearman's rank correlation coefficients. Kaplan-Meier curves were sued to analyze the patient survival by SIRT2 levels. All values are depicted as mean ± standard deviation and are considered significant if p < 0.05.
9
Nonparametric Statistical Analysis of Data
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All data were statistically analyzed using SPSS 18.0 statistical software. The data were expressed as median, and the overall variance analysis was carried out using nonparametric Kruskal-Wallis H and Mann-Whitney U tests, as the data obtained were not consistent with normal distribution and variance was not homogeneous. P-values of < 0.05 were considered statistically significant.
10
Bone Cement Leakage Risk Analysis
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Statistical analysis was carried out using SPSS 18.0 statistical software. The normally distributed measurement data are represented by ‾x ± s. The comparisons of the indicators between the two groups were performed by the t-test and χ2 test. Binary logistic multiple regression analysis was used to assess the correlations. P < 0.05 was considered statistically significant. A ROC curve was generated, and the area under the curve and cut-off value of PSBCV/VCV% were calculated to assess the correlation between the PSBCV/VCV% and the presence of bone cement leakage in the paravertebral vein.
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