Data were analyzed using the SPSS software version 15.0 for Windows (SPSS Inc., Chicago, IL, USA). Categorical variables were presented as frequency and percentage. The c2 test was used to compare the categorical variables. The Kolmogorov–Smirnov test was used to assess the distribution of continuous variables. Student’s t-test was used for variables with normal distribution, and the values were presented as mean±SD. Continuous variables without normal distribution were analyzed using Mann–Whitney U test, and the values obtained were presented as median (50th) values and interquartile ranges (25th and 75th). Receiver operating characteristic (ROC) curve analysis was performed to identify the optimal cut-off values for stroke/TIA history. The effects of different variables on stroke/TIA history were calculated by univariate analysis for each variable. The variables for which the unadjusted p value was 0.10 in logistic regression analysis were identified as potential risk markers and were included in the full model. Model A was developed to evaluate the effect of intra-left atrial EMD in multiple logistic regression analysis, while Model B was developed to evaluate the effect of inter-atrial EMD. The odds ratios (OR) and 95% confidence intervals (CI) were calculated. A two-tailed p value of <0.05 was considered statistically significant.
Spss software version 15.0 for windows
Manufactured by IBM
Sourced in United States
SPSS software version 15.0 for Windows is a statistical analysis software package. It provides tools for data manipulation, analysis, and visualization. The software is designed to help users manage and analyze data efficiently.
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Lab products found in correlation
32 protocols using spss software version 15.0 for windows
1
Atrial Electromechanical Delay and Stroke Risk
2
Statistical Analysis of Continuous Variables
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Statistical analyses were conducted using SPSS software, version 15.0 for Windows (SPSS Inc, Chicago, Illinois, United States). Descriptive data were recorded as mean ± SD unless otherwise specified. The Shapiro–Wilk test was used to assess normality of the continuous variables. Two-tailed t tests were used to assess the differences in variables between groups. An analysis of variance (ANOVA) test was used for the comparison of three or more data. Bonferroni test was used for post-hoc analysis. The Pearson correlation coefficient was determined to assess the association between continuous variables, according to the normality of distribution. Independent variables significantly associated with scores in the univariate analysis (P < 0.05) and potentially confounding parameters were included as independent covariables in the multivariate analysis by multiple regression analysis. A two-sided P value less than 0.05 was considered statistically significant.
3
Statistical analysis
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Student’s t-test was used to compare the means of two groups. Two-sided P-values less than 0.05 were considered significant. All analyses were performed using SPSS software version 15.0 for Windows (SPSS Inc., Chicago, IL).
4
Identifying Risk Factors in Systemic Sclerosis
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Data were analyzed with the SPSS software version 15.0 for Windows (SPSS Inc., Chicago, IL, USA). Categorical variables were presented as frequency and percentage. The χ2 test and Fisher’s exact test were used to compare categorical variables. The Kolmogorov-Smirnov test was used to assess the distribution of continuous variables. Student’s t-test was used for variables with normal distribution and the values were presented as mean±SD. Continuous variables without normal distribution were analyzed using Mann-Whitney U test and obtained values were presented as median (50th) values and interquantile ranges (25th and 75th). Multivariate logistic regression analysis was used to evaluate the independent associates of the risk of systemic sclerosis. Parameters with a p value of less than 0.1 in univariate analysis were included in the model. Receiver operating characteristics (ROC) analysis was used to determine the cut-off value and the sensitivity/specificity of PAP. The odds ratios (OR) and 95% confidence intervals (CI) were calculated. A two-tailed p value of <0.05 was considered statistically significant.
5
Statistical Analysis of Severe RMS Risk Factors
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Data were analyzed with the SPSS software version 15.0 for Windows (SPSS Inc., Chicago, IL, USA). Categorical variables were presented as frequency and percentage. The χ2 test and Fisher’s exact test were used to compare categorical variables. The Kolmogorov–Smirnov test was used to assess the distribution of continuous variables. Student’s t-test was used for variables with normal distribution, and the values were presented as mean ± standard deviation. Continuous variables without normal distribution were analyzed using Mann–Whitney U-test, and the values obtained were presented as median (50th) values and interquartile ranges (25th and 75th). One-way analysis of variance and Kruskal–Wallis test were used for parametric and nonparametric variables to compare tertiles, respectively. Multivariate logistic regression analysis was used to evaluate the independent association of the risk of severe RMS. Parameters with a P-value of less than 0.1 in univariate analysis were included in the model. The odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. A two-tailed P-value of <0.05 was considered statistically significant.
6
Identifying Risk Factors for Pulmonary Embolism
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Statistical analysis was performed with SPSS software, version 15.0 for Windows (SPSS Inc., Chicago, IL). Results were given as percentages, mean and standard deviations, or median and ranges. Differences in clinicopathological parameters between patients with and without PE were determined by means of the χ2 test. Variables with P < .05 in univariable analysis were included in the multivariable analysis. Multivariable stepwise logistic regression analysis was used to identify independent risk factors for PE. The hazard ratio and 95% confidence interval were calculated. Overall, survival curves were calculated using the Kaplan–Meier method. Comparisons between curves were carried out by the log-rank test. P < .05 was considered statistically significant.
7
Statistical Analysis of Experimental Data
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Statistical analysis was performed using SPSS-software version 15.0 for Windows (SPSS Inc., Chicago, IL, USA): Kolmogorov-Smirnov test and unpaired samples t-test. Data were presented as a mean ± standard deviation (SD).
8
Corneal Neovascularization Histomorphometric Analysis
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To evaluate the neovascularization intensity histomorphometrically, digitally saved micrographic images from the light microscope were used. A point grid was put on the screen where the density of neovascularization was maximum in the corneal tissue. The numbers of neovascularization refer to the total density for that sagittal section in an area where neovascularization were found. The grid size on the image was scaled to real size for estimation of maximum density of neovascularization (No/mm2) [17 , 18 (link)]. The calculations were made by two independent histologists in a double-blinded design.
Data were given as the median and 95% confidence interval. Statistical analyses were performed using SPSS software version 15.0 for Windows (SPSS, Chicago). The Mann-Whitney-U test was used for comparisons between the administration methods and control groups. The Kruskal-Wallis analysis of variance test was performed for multiple comparisons of groups. If the Kruskal-Wallis analysis of variance test was significant, then pair-wise comparison of groups was carried out to determine the difference. To account for multiple comparisons, adjusted P values were taken into consideration. Differences were considered statistically significant when P values were less than 0.05.
Data were given as the median and 95% confidence interval. Statistical analyses were performed using SPSS software version 15.0 for Windows (SPSS, Chicago). The Mann-Whitney-U test was used for comparisons between the administration methods and control groups. The Kruskal-Wallis analysis of variance test was performed for multiple comparisons of groups. If the Kruskal-Wallis analysis of variance test was significant, then pair-wise comparison of groups was carried out to determine the difference. To account for multiple comparisons, adjusted P values were taken into consideration. Differences were considered statistically significant when P values were less than 0.05.
9
Weight Loss Evaluation Protocol
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Categorical variables are presented as counts and proportions. The Kolmogorov-Smirnov test was used to evaluate the distribution of continuous variables relative to a normal distribution. Continuous variables are presented as means (with standard deviations). A paired Student t test was used to evaluate differences between the preoperative and postoperative periods. The associations between study parameters and weight loss were determined by the Pearson correlation test. SPSS software version 15.0 for Windows (Chicago, Ill., USA) was used for all statistical analyses. A two-sided p value <0.05 was considered statistically significant.
10
Statistical Analysis of Research Data
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SPSS software version 15.0 for windows (Statistical Package for the Social Sciences, Chicago, IL, USA) was used for data analysis using the Student's t test and Chi-square test. P-value 0.05 was considered as statistically significant.
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