Data are presented as means±SD or proportions. Skewed variables (ie, diabetes duration, triglycerides, and 25(OH)D level) were logarithmically transformed to improve normality prior to analysis. The unpaired Student t test, one-way analysis of variance, and the χ2 test with Yates correction for continuity were used to analyze the differences among the clinical and biochemical characteristics of participants. Multivariate logistic regression analysis was also performed to test the independent association of the serum 25(OH)D level with the presence of microvascular complications (ie, the dependent variable). Two forced-entry multivariate regression models were performed. The dependent variable was included as a composite end point: patients with neither retinopathy nor nephropathy (coded as 0) and patients with both complications or with one or the other (coded as 1). Covariates were chosen as potential confounding factors on the basis of their significance in univariate analysis or on the basis of their biological plausibility. Results are presented as ORs with 95% CIs. ORs for all continuous variables were computed for each SD increase. Statistical analysis was performed with SPSS V.19.0 statistical package software. p Values <0.05 were considered statistically significant.
Spss v 19.0 statistical
Manufactured by IBM
Sourced in United States
SPSS V.19.0 is a statistical software package that provides data analysis, data management, and data documentation capabilities. It is designed to perform a wide range of statistical analyses, including descriptive statistics, regression, correlation, and more. The software is intended to help users analyze and interpret data effectively.
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Lab products found in correlation
6 protocols using spss v 19.0 statistical
1
Vitamin D and Microvascular Complications in Diabetes
2
Impact of Microsurgery Training on Surgeons
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SPSS v. 19.0 statistical software was used to conduct the statistical analysis of this study. Descriptive statistics are presented as the mean and standard deviation. The impact of microsurgery training between DIS and JR groups was compared using the independent sample t-test. The significance level was set at 0.05.
3
Statistical Analysis of Cohort Study
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The results of continuous variables in the cohort study were presented as the mean ± SD. The baseline characteristics of each group were compared using the χ2 test or a one-way analysis of variance test. Statistical analyses were performed using the SPSS V.19.0 statistical software (SPSS). p < 0.05 was considered significant. To describe the biologically functional significance of selected gene sets, we used the hypergeometric test to determine the enrichment of GO terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The significance of differences was evaluated with either the Student's t-test when only two groups were compared, or the hypergeometric test for a Venn diagram. Hierarchical clustering was performed using the Cluster 3.0 software.
4
Statistical Analysis of Experimental Data
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Data were expressed as mean ± SD. Experimental data were analyzed using SPSS v19.0 statistical software (IBM Corp., Armonk, NY, USA, 2012) with the least significant differences between samples being p < 0.05.
5
Statistical Analysis of Clinical Data
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SPSS v19.0 statistical software was used for analysis (IBM Corp., Armonk, NY). Continuous variables were expressed as mean ± SD, while categorical variables were expressed as percentages. Measurement data (such as patient age and lesion size) were analyzed using the t test, and count data (such as underlying diseases, NAPD morphology and location, postoperative complications, and pathological results) were analyzed using the Pearson Chi-squared test. Statistical significance was set at P < .05.
6
Comparative Analysis of Physiological Parameters
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The experimental data were presented as mean ± standard deviation (M ±SD) and analyzed with IBM SPSS v. 19.0 statistical software (IBM Corp., Armonk, USA). The normality of the data was analyzed using the Shapiro-Wilk test, and the value of p > 0.05 indicated that the data were normally distributed. The Levene's test was used to analyze the homogeneity of variance, and the value of p > 0.05 indicated that the data conformed to homogeneity of variance. The one-way analysis of variance (ANOVA) test for repeated measures, followed by the post hoc least significant difference (LSD) test were used for overall comparisons between groups across multiple time points. The value of p < 0.05 was considered statistically significant.
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