All analyses were performed with the software IBM SPSS Statistics, version 15.0 (SPSS, Inc, Chicago, IL, USA) or Stata 11.0 (StataCorp, College Station, TX, USA). The collected data were analyzed using descriptive statistics. Shapiro-Wilk's W test and graphical analysis were used to check for normal distribution. The intraclass correlation coefficient statistic was used to test intergrader reliability. One-way analysis of variance was used to determine difference in means between TAS and FRT (FIRT, FMRT, and FCRT) with DR stages. Post hoc Tukey honestly significant difference (HSD) was used to confirm statistically significant comparisons. Pearson correlation coefficient was used to determine any correlation between FRT and systemic quantitative variables with P values adjusted with Bonferroni correction. Linear regression was performed between TAS of FRT with highly correlative variables. Student's t-test was used to compare FRT between patients with and without systemic variables (e.g., presence absence of CAD or DR). P < 0.05 was considered statistically significant unless otherwise stated.
Spss statistics version 15
Manufactured by IBM
Sourced in United States
SPSS Statistics Version 15.0 is a comprehensive set of data analysis tools that provides advanced statistical analysis capabilities. It is designed to handle a wide range of data types and offers a variety of statistical techniques for analyzing and interpreting data. The software is used for tasks such as data management, data exploration, and hypothesis testing.
Automatically generated - may contain errors
22 protocols using spss statistics version 15
1
Multimodal Ophthalmic Imaging Analysis
2
Statistical Analyses of Continuous and Categorical Data
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All statistical analyses were performed using SPSS™ Statistics version 15.0 (SPSS™, Chicago, IL, USA) and MedCalc version 15.2. All continuous variables were evaluated for normal distribution using the Kolmogorov–Smirnov test. Categorical variables are presented as a percentage of the total. For between-group comparisons, the Student's t-test and the Wilcoxon test were used for continuous variables, and the chi-squared or Fischer's exact test was used for categorical data. The correlation of variables was obtained using Spearman's or Pearson's rank correlation coefficient. Parametric data are presented as the mean ± standard deviation, and nonparametric data are presented as the median and interquartile range (IQR). Significance was defined as P < 0.05. Based on the logistics model, combining predictors, or probabilities, were applied to establish the empirical and binormal model of the receiver operating characteristic (ROC) curve.
3
Statistical Analysis of Continuous and Categorical Data
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SPSS statistics version 15.0 (SPSS Inc., Chicago, IL, USA) was employed for data analyses. Continuous variables are expressed as mean±standard deviation in normally distributed variables. If the variables are not normally distributed, they are presented as median and interquartile range: median (25th and 75th percentiles). Student’s t-test or Wilcoxon’s signed-rank test was employed for group comparison of continuous variables with normal or non-normal population distributions, respectively. Categorized values were compared using the chi-squared test. P-value <0.05 was considered significant.
4
Anti-Jo-1 Autoantibody Analysis Protocol
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The Kolmogorov-Smirnov test was used to assess the distribution of continuous variables. Results are presented as means ± standard deviations (SD) for continuous variables and as frequencies (%) for categorical variables. Medians and interquartile ranges (75th -25th) were calculated for continuous variables with nonnormal distribution. Student's t-test or Mann-Whitney U test were used for continuous variables, and the chisquare test or Fisher's exact test were used for categorical variables in order to compare patients with and without of anti-Jo-1 autoantibodies. Odds ratios (OR) 95% confidence intervals (CI) were estimated by a logistic regression model that was used to evaluate the association between anti-Jo-1 positivity and relevant covariates with statistical significance in the univariate analysis. We adopted P values < 0.05 to indicate statistical significance. SPSS Statistics, version 15.0 (Chicago, USA), was used for all analyses performed.
5
Comparing Physiological Changes in Patients with MI
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The statistical analyses were conducted using SPSS Statistics, Version 15.0.
Mann-Whitney testing was employed to compare anthropometric, spirometric, and
performance values between both groups. A Wilcoxon test was carried out to
compare these values before and after MI within each group. A Fisher’s exact
test was employed to compare gender and pancreatic insufficiency between the 2
groups.
Mann-Whitney testing was employed to compare anthropometric, spirometric, and
performance values between both groups. A Wilcoxon test was carried out to
compare these values before and after MI within each group. A Fisher’s exact
test was employed to compare gender and pancreatic insufficiency between the 2
groups.
6
Prognostic Factors in WBRT Outcomes
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Summary statistics were calculated, including medians and ranges for continuous variables and frequencies and proportions for categorical variables. MS was analyzed from the first day of each course of WBRT to the date of death using the Kaplan Meier method with 95% confidence intervals. Log rank tests compared survival curves by RPA class and primary histology. Cox proportional hazard analysis described factors associated with survival. Factors that were significant at the P < .10 level on univariate analysis (UVA) were incorporated into multivariate analysis, with hazard ratios and 95% confidence intervals reported. The final multivariate model included factors that were significant at the P < .05 level, which were then used to construct a prognostic index (the ReRT score). A score of 1 was assigned to each variable for ease of clinical use. MS was determined for each ReRT score group (scores of 0-2, 3, or 4-5) using the Kaplan-Meier method and compared using the log rank test. UVA was also performed using a logistic binary regression analysis to explore factors associated with very short survival (≤30 days). A two-sided P-value of <.05 was considered significant. All statistical analyses were conducted using IBM SPSS Statistics Version 15 (IBM Corp., Armonk, NY).
7
Comparative Analysis of Experimental Treatments
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All values in the text and tables were expressed as mean ± SD. The data were analyzed using the software Statistical Package for the Social Sciences (IBM SPSS Statistics, version 15, SPSS Inc.) system. Unpaired t-test, χ2 test, and Fisher exact test were used for group differences. A p value less than 0.05 was considered statistically significant.
8
Comparative Statistical Analysis Protocol
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Among the descriptive statistics, continuous variables were shown as mean and standard deviation (SD). For data not normally distributed, median with data range (minimum to maximum or interquartile range) was used. Categorical variables are shown as number and percentages. The Mann-Whitney U test was used for the comparison of continuous inter-group values. All analyses were performed with IBM SPSS Statistics, version 15.
9
Postural Balance and Mobility Analysis
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All statistical analyses were performed using SPSS Statistics, version 15, software (IBM Corporation, USA). p < 0.05 was considered statistically significant. The demographic characteristics (age, height, and body mass index), postural balance, mobility levels, and fear of falling of the cases were expressed as means ± standard deviations (minimum–maximum).
A Kolmogorov-Smirnov test was used to determine the distribution of the data. Since the groups were not evenly distributed, the data obtained from patients before and after treatment were assessed by the Wilcoxon signed-rank test. Additionally, the analysis of differences between the 2 groups was assessed by the Mann-Whitney U test.
A Kolmogorov-Smirnov test was used to determine the distribution of the data. Since the groups were not evenly distributed, the data obtained from patients before and after treatment were assessed by the Wilcoxon signed-rank test. Additionally, the analysis of differences between the 2 groups was assessed by the Mann-Whitney U test.
10
Exploring Neurological Symptoms in TBI Patients
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The statistical analyses were performed using IBM SPSS Statistics Version 15 (IBM, Armonk, NY). The means and standard deviations were computed to describe the continuous variables, and frequencies were used to describe the categorical variables. Chi-Square test was used to examine the difference of prevalence of neurological symptoms in subgroups. Shapiro-Wilk test was used to examine the distribution of data. Two-independent sample t-test (normally distributed data) or non-parametric tests (Mann-Whitney U-test for non-normally distributed data) were used to explore the differences in scores of scales and inflammatory biomarkers between the TBI patients with and without neurological symptoms, such as depression, headaches, sleep disturbance, and irritability. Bivariate correlation analysis (Pearson correlation test for continuous data and Spearman correlation test for categorical data) were conducted to explore the correlations between the inflammatory biomarkers and the neurological symptoms, and binary logistic regression analysis was used to identify the risk factors for the neurological symptoms.
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