Repeated-measure ANOVA was conducted to test the differences among week 0, week 10, week 20, and week 25 for the scores of BEHAVE-AD, NPI, and the actigraph parameters in the SZL and placebo groups. When a significant difference was detected, a post hoc test (Bonferroni test) was conducted between the SZL and placebo groups. A significant difference was defined as P < 0.05. SPSS windows version 17.0 was used for statistical analyses. All data are expressed as the mean ± standard deviation.
Spss windows version 17
Manufactured by IBM
Sourced in United States
SPSS Windows version 17.0 is a statistical software package that provides advanced analytical capabilities for data analysis. It offers a wide range of tools for data management, statistical modeling, and reporting. The software is designed to work on the Windows operating system.
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Lab products found in correlation
11 protocols using spss windows version 17
1
Repeated-Measure ANOVA on Behavioral Outcomes
2
Atherosclerotic Vessel Dysfunction Assessment
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Participant characteristics and plaque thickness are presented as mean ± SD. Fluorescence-activated cell sorting (FACS) and ELISA values are presented as medians. The clinical characteristics of each group were compared using the Mann–Whitney nonparametric test. Statistical significance among groups was determined via one-way analysis of variance (ANOVA). Probability values were two-tailed, and values of p < 0.05 were considered statistically significant (SPSS, Windows version 17.0, Chicago, IL, USA). Pearson correlation coefficients were used to assess the association between ultrasound findings (IMT and plaque number) and changes in blood factors associated with atherosclerotic vessel dysfunction. Values of the coefficient constant r and r2 are provided. A value of p ≤ 0.05 was regarded as significant (SPSS, Windows version 17.0, Chicago, IL, USA).
3
Methylation Status and Clinico-Pathological Features
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Correlations between methylation status and clinico-pathological features of the patients were assessed by using the Chi-square test. Disease-free interval (DFI), progression-free survival (PFS) and overall survival (OS) curves were calculated by using the Kaplan–Meier method and comparisons were performed using the log-rank test. P-values <0.05 were considered as statistically significant. Statistical analysis was performed by using the SPSS Windows version 17.0 (SPSS Inc., Chicago, IL, USA).
4
Statistical Analysis of Clinical Data
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All clinical and laboratory data were evaluated in relation with each other and compared in different patient profiles and control groups. Statistical analyses were performed by using SPSS Windows Version 17.0, SPSS Inc., Chicago, IL, USA. Data were expressed as mean plus or minus SD except when indicated otherwise. Correlation comparisons between paired samples were made by Pearson’s product moment correlation coefficient. Statistical comparisons of numeric data were made using Student’s t-test and classified data were evaluated by chi-square test. A two-sided p-value <0.05 was considered to indicate statistical significance.
5
Methylation Status and Clinico-Pathological Factors
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Correlations between methylation status and clinico-pathological features of the patients were assessed by using the Chi-square test. Disease-free interval (DFI) and overall survival (OS) curves were calculated by using the Kaplan–Meier method and comparisons were performed using the log-rank test. P-values < 0.05 were considered as statistically significant. Statistical analysis was performed by using the SPSS Windows version 17.0 (SPSS Inc., Chicago, IL, USA).
6
Evaluating Sleep Disorders Treatment
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Repeated-measure ANOVA was conducted to test the differences among changes in outcomes at baseline and every 2 weeks for 6 weeks. When a significant difference was detected, a post hoc test (Bonferroni test) was conducted between the standard and randomized groups in order to compare the levels of NA and ESA, and the IRLSRS and ESS scores. Differences at baseline between the standard group and randomized group were analyzed using the t-test. A significant difference was defined as P < 0.05. SPSS Windows version 17.0 was used for statistical analyses. All data are expressed as the mean ± standard deviation.
7
Statistical Analysis of Hormone Levels
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Statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS) Windows version 17.0 (SPSS Inc., Chicago, IL). Distribution of the continuous variables was checked using the Kolmogorov-Smirnov test. Student’s t-test was used for variables with normal distribution. After testing the skewed distribution, comparisons between the groups were tested using the Mann-Whitney U-test. The chi-square test was used to analyze nominal variables. Continuous variables were expressed as mean ± standard error (SE). The level of change in late follicular phase progesterone was tested using paired samples t-test or two-related samples test according to the variables distribution. A value of p < 0.05 was accepted as statistically significant.
8
Statistical Analysis of Heavy Metals in Sediments
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A statistical tool, SPSS® (Windows Version 17.0), was used to examine the data. Descriptive statistics include mean, range and standard deviation. Depending on the data type, various datasets have been subjected to correlation analysis. Principal component analysis (PCA) was applied for source analysis of heavy metals in sediments. The details of PCA used for data analysis are mentioned elsewhere [8 (link)]. Before multivariate analysis, Shapiro-Wilk’s normality test (p> 0.01) was used to determine the normality of the data. Logarithmic transformation was used to normalize the original data.
9
Circulating Factors and Carotid Atherosclerosis
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Laboratory and clinical data were expressed as mean ± SD. Fluorescence-activated cell sorting (FACS) values were presented as medians. Clinical characteristics of the two groups were compared using t-test. Statistical significance among groups was determined via one-way analysis of variance (ANOVA). Probability values were two-tailed, and p-values ≤ 0.05 were considered statistically significant (GraphPad Prism 6.0, La Jolla, CA, USA). Pearson correlation coefficients were used to assess the association between the parameters of carotid atherosclerosis based on ultrasonographic findings (mean IMT and plaque numbers) and changes in circulating factors in the group without or with previous CVD. Values of the coefficient constant r and R2 were provided. A p-value
≤ 0.05 was considered statistically significant (SPSS, Windows version 17.0, Chicago, Illinois, USA).
10
Analyzing Anthropological and Biochemical Data
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The Statistical Package for Social Science (SPSS), Windows version 17 (SPSS Inc., Chicago, Illinois, USA) was used to analyse the data. An unpaired Student's t test was performed to assess the comparison between the two groups. ANOVA-Bonferroni analysis was performed to explore the relationship with the anthropological and biochemical characteristics. In appropriate situations, we performed a Chi-square (χ2) test. Statistically significant values were regarded as having a P value of <0.05.
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