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Spss for windows software package version 20

Manufactured by IBM
Sourced in United States

SPSS for Windows software package, version 20.0, is a data analysis tool that enables users to perform statistical analyses on various types of data. The software provides a wide range of statistical techniques, including descriptive statistics, regression analysis, and hypothesis testing, among others. SPSS for Windows version 20.0 is designed to run on the Microsoft Windows operating system.

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Lab products found in correlation

4 protocols using spss for windows software package version 20

1

Genetic Associations and Survival Analysis

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SPSS for Windows software package version 20.0 (SPSS Inc., Chicago, IL, USA) was used to analysis the data. Genotypic association were provided by the SNPstats online analysis software including the codominant, dominant, recessive, and overdominant genetic models [27 (link)], and the Hardy-Weinberg equilibrium was evaluated by chi-squared test. The level of significance was set at P < 0.05. The effects of different genotypes and alleles were evaluated by odds ratio (OR) and respective 95% confidence intervals (95% CI). Kaplan-Meier plots and the log-rank test were used to estimate the relationships of AXIN1 genotypes with patients' outcomes (recurrence and death). Considering age at first diagnosis, sex, smoking status, tumor grade, and clinical stage, Cox regression analysis model was used for multivariate survival analysis.
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2

Predictors of Abnormal CT Findings

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Continuous and categorical variables were presented as median (IQR) and n (%), respectively. SPSS for Windows software package, version 20.0 (SPSS Inc, Chicago, IL) was used. Mann-Whitney U test or χ2 test was used to compare differences between the normal CT group and the abnormal CT group. To explore the risk factors associated with abnormal CT findings, univariate and multivariate logistic regression models were used. By referring to the relevant literature, we selected age, gender, body temperature, underlying diseases, symptoms, white blood cell count, neutrophil count, lymphocyte count, and C-reactive protein as variables for stepwise logistic regression analysis (20 (link)). At the same time, parameters of odds ratios that were difficult to estimate were excluded due to the small number of cases as well as the parameters that had collinearity with the underlying disease. A P-value < 0.05 was considered statistically significant.
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3

Comparing CT Findings in Viral Infections

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Statistical analyses were performed to compare the CT findings in infections by the 3 different viruses. The SPSS for Windows software package, version 20.0 (SPSS Inc, Chicago, IL) was used. Categorical variables were compared using the χ2 or Fisher exact test, and continuous variables were compared using the Mann–Whitney U test. A P-value < 0.05 were considered statistically significant.
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4

Longitudinal Analyses of Lipids and Antiepileptic Drugs

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The data were analyzed using SPSS for Windows software package, version 20.0 (SPSS, Chicago, IL). Longitudinal analyses were performed to evaluate changes in lipid concentrations, BMI scores, and number of antiepileptic drugs used during 24 months period. Pairwise comparisons were also performed between baseline and each date point data. Finally we compared variables between patient groups with and without dyslipidemia at baseline and at month-12. Due to non-parametric distribution of data, Mann Whitney, Wicoxon, and Friedmann-tests with a Bonferroni post hoc correction were used for continuous variables, X-square, Mc Nemar, and Cochrane Q tests for categorical variables. A p-value less than 0.05 was regarded as statistically significant.
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