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Spss software for windows 19

Manufactured by IBM
Sourced in United States

SPSS Statistics is a software package used for statistical analysis. It is designed to work on Windows 19.0 operating system. The core function of SPSS Statistics is to provide statistical analysis capabilities, including data management, data analysis, and data presentation.

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Lab products found in correlation

2 protocols using spss software for windows 19

1

Elderly Survival Analysis in Cancer

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All statistical analyses were performed using the Statistical Product and Service Solutions (SPSS) software for Windows 19.0 (SPSS Inc., Chicago, Illinois). The study subjects were stratified by age into two groups - adults (<65) and the elderly (≥65). Using the Chi squared (χ2) test, selected clinical-pathological and treatment characteristics were compared between the two groups. CSS was determined by using the Kaplan-Meier method. The 5-year and 10-year CSS rates in elderly group were estimated from the survival curves, and the differences in CSS rates was determined by the 2-sided log-rank test. Cox proportional hazards analysis was performed to evaluate the risk factors of CSS in elderly group. All P values were two-sided, and P < 0.05 was considered to be statistically significant. Since the SEER database is publicly available and de-identified, our study was exempt from any approval from the institutional review board.
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2

Effects of Dietary Intervention on Glycemic Control and Inflammation

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Data were expressed as mean ± SD or median (interquartile range) for continuous variables and as number (percentage) for categorical variables. Variables of HOMA-IR, TNF-α, and IL-6 were transformed by the natural logarithm because their distributions were heavily skewed. The statistical analyses were performed according to our previous methods.21 (link) Baseline characteristics of the 2 groups were compared using the Student’s t-test, Wilcoxon’s signed-rank test, or a Pearson’s χ2 test as appropriate. Differences in variables between the groups at baseline or after the 5-week intervention were analyzed using the Student’s t-test, and differences between the baseline and final variable measurements after the 5-week intervention were compared using the paired Student’s t-test. The changes in the glycemic control, inflammatory profiles, and dietary intake from baseline were analyzed using an analysis of covariance (ANCOVA, generalized linear model). All data were analyzed with an intention-to-treat basis without imputation using SPSS software for WINDOWS 19.0 (SPSS Inc, Chicago, IL, USA) and a 2-sided P<0.05 was considered significant.
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