The SPSS program version 22 (IBM SPSS Statistics V22.0 for Windows, SPSS Inc., USA) was used for all statistical analyses. The descriptive statistics was used to analyze the demographic data as well as the median and interquartile range (IQR) of outcomes. The Shapiro-Wilk test was used to test for the normality of the data. If the data were found to not have a normal distribution, the Wilcoxon signed-rank test and the Friedman’s test were used to investigate differences between tablet tilt angles and among time intervals, respectively. The significant level was set at α = 0.05 for the primary analyses. If a significant difference among time intervals was found, pairwise comparisons by the Wilcoxon signed-rank test would be conducted. The adjusted significance level for the 10 pairwise comparisons was set at α = 0.005.
Spss statistics v22.0 for windows
Manufactured by IBM
Sourced in United States
SPSS Statistics V22.0 for Windows is a software program developed by IBM that provides advanced statistical analysis capabilities. The core function of the software is to analyze data, create reports, and generate statistical models. SPSS Statistics V22.0 for Windows supports a wide range of data types and offers a variety of statistical techniques, including regression analysis, hypothesis testing, and data mining.
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Lab products found in correlation
13 protocols using spss statistics v22.0 for windows
1
Tablet Tilt Angle Evaluation Using SPSS
2
Probiotic Effects on Bone Density
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Statistical analysis was performed using IBM © SPSS © Statistics v 22.0 for Windows. The data are expressed as mean ± standard deviation. One-way analysis of variance (ANOVA) was applied to analyze the association between existing probiotic combinations and bone mineral density measurement parameters. Tukey post hoc analysis was performed when the ANOVA outcomes exhibited significance (p ≤ 0.05).
3
Comparative Analysis of Antioxidant Profiles
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In order to identify statistically significant differences between TPC, antioxidant activity and phenolic compounds of different extracts, analysis of variance (ANOVA) and Student–Newman–Keuls test were applied to the analytical data. In the case of anthocyanins, an independent sample test was applied. Spearman's correlation coefficient was used to study the contribution of each phenolic compound in the antioxidant activity. The statistical package used was the IBM SPSS statistics v.22.0 for Windows.
4
Statistical Analysis of Anti-Platelet Aggregation
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The IBM SPSS statistics v.22.0 for Windows statistical package was employed to carry out statistical analysis. Anti-platelet aggregation data set was submitted to the ANOVA analysis and the Tukey’s post-hoc test, while the Student-Newman-Keuls test was applied to the chemical data in order to determine the significant differences between samples.
5
Genetic Variation and Bone Health
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IBM© SPSS© Statistics V. 22.0 for Windows was applied for obtaining all statistical outcomes. Continuous variables were expressed as mean ± standard deviation (SD).
Children and adolescents’ height, weight, age, BMI, and biochemical parameters (TC, LDL, Non-HDL, HDL, and TG) were tested for normal distribution by the Kolmogorov-Smirnov test. Chi-square test was used to evaluate the differences between grouped variables. The chi-square goodness of fit test was applied to assess the Hardy-Weinberg equilibrium. In addition, genotype and allele frequencies were calculated using chi-square.
Analysis of covariance (ANCOVA) test was employed for evaluating the differences between the VDR polymorphisms, and biochemical and demographic parameters adjusted for age and sex. Logistic regression analysis was used to observe the association between VDR polymorphisms and lumbar spine and, neck Z-scores, under additive, dominant and recessive genetic models adjusted for age, sex, BMI, and puberty, in 3 statistical models. Model 1 was adjusted for age and sex, Model 2 for age, sex and BMI; and Model 3 for age, sex, BMI and the Tanner stage of puberty. Linear regression was performed to evaluate the possible impact of VDR genetic variations on BMD. The minor allele for each SNP was considered as the reference allele. P values less than 0.05 reflect statistically significant results.
Children and adolescents’ height, weight, age, BMI, and biochemical parameters (TC, LDL, Non-HDL, HDL, and TG) were tested for normal distribution by the Kolmogorov-Smirnov test. Chi-square test was used to evaluate the differences between grouped variables. The chi-square goodness of fit test was applied to assess the Hardy-Weinberg equilibrium. In addition, genotype and allele frequencies were calculated using chi-square.
Analysis of covariance (ANCOVA) test was employed for evaluating the differences between the VDR polymorphisms, and biochemical and demographic parameters adjusted for age and sex. Logistic regression analysis was used to observe the association between VDR polymorphisms and lumbar spine and, neck Z-scores, under additive, dominant and recessive genetic models adjusted for age, sex, BMI, and puberty, in 3 statistical models. Model 1 was adjusted for age and sex, Model 2 for age, sex and BMI; and Model 3 for age, sex, BMI and the Tanner stage of puberty. Linear regression was performed to evaluate the possible impact of VDR genetic variations on BMD. The minor allele for each SNP was considered as the reference allele. P values less than 0.05 reflect statistically significant results.
6
Repeated Measures ANOVA Analysis
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Analyses were done with ANOVA-RM for the difference in means in repeated measurements, and with the Tukey Test between pairs. A P < 0.05 was considered significant. The study power was 85.7%. Data are presented as number (percent), mean (standard deviation, SD), and 95% confidence interval, CI). IBM-SPSS-22 was used for statistical analyses (IBM SPSS Statistics v. 22.0 for Windows; Armonk, NY, USA).
7
Cephalometric Analysis of Maxillary Expansion
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The statistical analysis was performed by using the software IBM-SPSS-22 (IBM Corp. Released 2013. IBM SPSS Statistics v 22.0 for Windows; Armonk, NY, USA). A descriptive and analytical analysis of the variables obtained was carried out. Pearson’s chi-square test (χ2) was used to analyse the differences between the MES and the study subgroups (gender, age and cephalometric parameters). The analysis of variance test (ANOVA) with Duncan’s test as a post-hoc test was carried out to study the differences between inter- and intra-group quantitative measures. A 95% confidence interval was used, and a statistical significance level of 5% was used for all tests (p < 0.05). A randomly selected 20% of each group was measured in order to analyse intra-examiner reliability.
8
Statistical Analysis of Stroke and Arrhythmia Outcomes
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Continuous variables were expressed as mean ± standard deviation (SD), and categorical variables were expressed as numbers (percentages). The normal distribution of samples was checked using the Kolmogorov–Smirnov test. In the case of normal distribution, between-group comparisons were made using the Student’s t test. In the absence of normal distribution, the Mann–Whitney U test was applied. Kaplan–Meier methodology was employed to determine the probability of stroke recurrence, AF, and other arrhythmias. Data for patients without an event were censored at the end of the observation period. Censored data constituted data pertaining to patients without any event during the observation period, whose ICM was explanted without any detected event, or those that were lost to follow-up or could not be observed during the study period. The level of significance was set at p < 0.05. All analyses were performed using IBM SPSS Statistics V22.0 for Windows.
9
Comparative Statistical Analysis of Anonymized Data
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Data were anonymized and access was restricted only for authorized personnel with the only purposed of this study, according to local regulations. Due to the nature of our study, sample size calculation was not necessary.
To meet secondary objectives, the Kolmogorov—Smirnov test was performed to estimate the goodness of fit and, according to this result, comparison were evaluated with ANOVA test for quantitative variables and Kruskall-Wallis test for nominal variables. Single 2x2 comparisons for categorical variables were performed through chi-squared or Fisher exact test. IBM SPSS Statistics v.22.0 for Windows was used for statistical analysis. We considered statistically significant a 2-tails value of p < 0.05.
To meet secondary objectives, the Kolmogorov—Smirnov test was performed to estimate the goodness of fit and, according to this result, comparison were evaluated with ANOVA test for quantitative variables and Kruskall-Wallis test for nominal variables. Single 2x2 comparisons for categorical variables were performed through chi-squared or Fisher exact test. IBM SPSS Statistics v.22.0 for Windows was used for statistical analysis. We considered statistically significant a 2-tails value of p < 0.05.
10
Menstrual History and Aortic Atherosclerosis
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Except for those who refuse to disclose their menstrual or reproductive history, all data were retained to the greatest extent after data cleaning and logical inspection. Missing values were filled manually with reference to the mode and the median. Kolmogorov–Smirnov test was used to assess the normality of data. Continuous variables with skewed distribution were represented by the median with Q1–Q3. Categorical variables were represented by frequency and percentage. Variables were compared using the Mann–Whitney U test or chi-squared test as applicable. The logistic regression model was used to estimate the adjusted association between MRH and aICAS with an odds ratio (OR) and 95% CI. The change-in-estimate method was used to get confounding factors included in the multivariate adjustment (18 (link)). We also performed a sensitivity analysis deleting all missing values. Two-tail test with a significant P < 0.05 was used for analysis. All statistical analyses were performed by IBM SPSS Statistics V22.0 for Windows (IBM Corporation, Released 2013, Armonk, New York, USA).
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