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Spss statistical software for windows ver 18.0

Manufactured by IBM
Sourced in United States

SPSS statistical software for Windows (ver. 18.0) is an analytical tool used for data management, statistical analysis, and predictive modeling. It provides a comprehensive set of features for data exploration, hypothesis testing, and reporting. The software is designed to assist researchers, analysts, and decision-makers in organizing, analyzing, and interpreting complex data sets.

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Lab products found in correlation

3 protocols using spss statistical software for windows ver 18.0

1

Statistical Analysis of Prognostic Factors

Check if the same lab product or an alternative is used in the 5 most similar protocols
Comparisons between categorical variables were performed using Pearson’s χ2 test or Fisher’s exact test where appropriate. Continuous variables were compared using Student's t-test (when values were normally distributed) or the Mann-Whitney test (when values had a distribution that departed significantly from normal). The survival analysis was calculated using the Kaplan-Meier method and compared using the log-rank test. A multivariate analysis using Cox’s proportional hazard model was performed to evaluate the prognostic factors. A value of p<0.05 was considered statistically significant. All data were analyzed using SPSS statistical software for Windows (ver. 18.0; SPSS Inc., Chicago, IL).
All continuous variable data are expressed as the mean ±standard error (when values were normally distributed) or the median (range) (when values had a distribution that departed significantly from normal). All data regarding categorical variables are shown as n (proportion).
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2

Statistical Analysis for Comparative Studies

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Comparisons between categorical variables were performed using Pearson’s χ2 test or Fisher’s exact test where appropriate. Continuous variables were compared using Student’s t test (when values were normally distributed) or the Mann-Whitney test (when the values had a distribution that departed significantly from normal). Survival analysis was performed using the Kaplan-Meier method and comparison were made using the log-rank test. Univariate and multivariate analyses using Cox’s proportional hazard models were performed to evaluate the prognostic factors. The correlation between two variables was examined by Pearson’s correlation analysis (when the variables were normally distributed) or Spearman’s correlation analysis (when the variables had a distribution that departed significantly from normal). A value of P < 0.05 was considered statistically significant. All data were analyzed using SPSS statistical software for Windows (ver. 18.0; SPSS Inc., Chicago, IL, United States).
All continuous variable data were expressed as mean ± standard error (when the values were normally distributed) or medians (range) (when the values had a distribution that departed significantly from normal). All data regarding categorical variables are shown as n (proportion).
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3

Statistical Analysis of Prognostic Factors

Check if the same lab product or an alternative is used in the 5 most similar protocols
Comparisons between categorical variables were performed using Pearson's χ2 test or Fisher's exact test where appropriate. Continuous variables were compared using Student's t-test (when values were normally distributed) or the Mann-Whitney test (when values had a distribution that departed significantly from normal). The survival analysis was calculated using the Kaplan-Meier method and compared using the log-rank test. Univariate and multivariate analyses using Cox' proportional hazard model were performed to evaluate the prognostic factors. The correlation between two variables was examined by Pearson's correlation analysis (when values were normally distributed) or Spearman's correlation analysis (when values had a distribution that departed significantly from normal). A value of p<0.05 was considered statistically significant. All data were analyzed using SPSS statistical software for Windows (ver. 18.0; SPSS Inc., Chicago, IL, USA).
All continuous variable data are expressed as the mean ± standard error (when values were normally distributed) or the median (range) (when values had a distribution that departed significantly from normal). All data regarding categorical variables are shown as n (proportion).
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