Data are presented as mean ± standard deviations. Statistical analysis was performed using SPSS 21.0 J for Windows. The χ2 and t tests were performed for the comparison of DCSM and control groups (univariate analysis). A P value of less than 0.05 was considered statistically significant. We performed logistic regression analysis of selected significant variables (P<0.05) from the univariate analysis. The area under the receiver operating characteristic curve (ROC) is the concordant index (c-index), which was used to identify which radiographic measurements were most effective in predicting DCSM. Pearson correlation test was used to evaluate the correlation strength between the T1 slope and C2–C7 angle in the DCSM and control groups.
Spss 21.0 j for windows
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SPSS 21.0 J for Windows is a comprehensive software suite for statistical analysis. It provides a wide range of statistical procedures, data management, and visualization tools to help users analyze and interpret data. The software is designed to be user-friendly and offers a graphical user interface for easy navigation and analysis.
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Lab products found in correlation
7 protocols using spss 21.0 j for windows
1
Radiographic Predictors of Degenerative Cervical Spinal Myelopathy
2
Vascular Reactivity in Diabetes
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All the data were averaged for each patients. Thus, the numbers of subject indicated in figures are the number of patients. Statistical comparisons of mean value of 5-HT- or AngII-induced vasoconstriction were made using two-way analysis of variance (ANOVA). If significant differences in vasoconstriction between the DM and non-DM groups were found, the rank-sum test of the increasing effect of DM on the vasoconstriction induced by AngII or 5-HT was carried out using the Mann-Whitney U test. Statistical comparisons of 5-HT2A receptor and AT1R in the membrane fraction of the SV smooth muscle were made using Welch's t-test. The data are presented as mean±standard error of the mean (SEM). Significance was assumed at P<0.05. Statistical analyses were performed using SPSS 21.0 J for Windows.
3
Quantifying Dental Tissue Formation
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The percentage of nestin-positive perimeters in the total perimeter of the pulp-dentin border was calculated on Weeks 1, 2, and 3 using Image J software (Image J 1.45s, National Institutes of Health). Similarly, the percentage of newly formed hard tissue and the percentage of occurrence of tertiary dentin or bone-like tissue areas in the total area of the pulp chamber were quantified on Weeks 1, 2, and 3 using WinRoof image processing software (WinRoof Version 7.4; Mitani Corporation, Tokyo, Japan). All data were presented as the mean and standard deviation of each group and analyzed by the Student t test using statistical software (SPSS 21.0 J for Windows).
4
Dental Pulp Cell Dynamics
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The numbers of Ki-67- positive cells in the coronal and root pulp of each sample (3.4 × 104 grid was selected) and the percentage of TUNEL-positive areas was calculated separately. All data were presented as the mean and standard deviation of each group. Furthermore, the number of cells in the coronal and root pulp at Week 1 and 2 after pulp capping treatments and between groups were compared using one-way analysis of variance (ANOVA) multiple comparisons adjusted by the Bonferroni test using statistical software (SPSS 21.0 J for Windows; SPSS Japan, Tokyo, Japan).
5
Sleep Duration and Disability Risk
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All analyses were performed using SPSS 21.0 J for Windows (SPSS Japan Inc., Tokyo, Japan). Participants were divided into three groups according to sleep duration (short: ≤6.0 h, mid: 6.1 to 8.9 h, long: ≥9.0 h) [20] [21] [22] and categorized with respect to presence or absence of EDS. Continuous data are presented as means ± standard deviations (SDs). Characteristics were summarized as means ± SDs for continuous variables and as counts and percentages for categorical variables. Comparisons were performed using analysis of variance and Pearson's chi-square test for categorical data. Kaplan-Meier survival analysis for the incidence of disability was performed to compare sleep duration or presence of EDS. Furthermore, univariate and multivariate Cox's proportional hazard regression models were conducted to assess hazard ratios (HR) with 95% confidence intervals (CI) for the risk of incident disability. In multivariate analysis, potential confounders included age, sex, BMI, education level, number of medications, MMSE score, chronic disease, depressive symptoms, smoking habits, alcohol consumption, and physical activity. The significance level was set at p < 0.05 for all tests.
6
Statistical Analysis with IBM SPSS
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We used IBM SPSS 21.0J for Windows (Tokyo, Japan) for all statistical analyses, with a significance level of p < 0.05.
7
Cognitive Impairment Analysis Protocols
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Data are presented as means ± standard deviation. Descriptive statistics, the χ2 test, one-way analysis of variance (ANOVA), and Student’s t-test were used to compare the differences between the normal group and the CI group. The χ2 test was used to explore the difference in the success rate of the imitation test between sexes. ANOVA was used to compare MMSE scores among error-pattern types. The t-test was performed to examine differences in MMSE scores between sexes and between the normal and CI groups. A P-value of less than 0.05 denoted statistical significance. All analyses were performed using SPSS 21.0J for Windows (IBM Japan, Tokyo, Japan).
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