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Stata software version 14 for windows

Manufactured by StataCorp
Sourced in United States

STATA software version 14 for Windows is a statistical software package designed for data analysis, management, and visualization. It provides a comprehensive set of tools for researchers, analysts, and statisticians to conduct various types of quantitative analysis. The software is capable of handling a wide range of data types and offers a wide range of statistical techniques, including regression analysis, time series analysis, and multivariate methods.

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4 protocols using stata software version 14 for windows

1

Glycemic Indices and Outcome Analysis

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Statistical analysis was performed using the STATA software version 14 for Windows (Stata Corp., College Station, TX, US). Based on the results of normality tests, continuous variables (i.e., duration of disease, glycemic indices) are presented either as mean±SD, and categorical outcomes (i.e., meeting the preset glycemic targets) are demonstrated as proportions (95% confidence interval [95% CI]) or mean±SEM.
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2

Comprehensive Metabolic Analysis in Patients

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Statistical analysis was performed using the STATA software version 14 for Windows (Stata Corp., College Station, TX, US).
Based on the results of normality tests, continuous variables (i.e. blood pressure, duration of disease, glycemic, and lipid indices) are presented either as mean ± standard deviation (SD)/standard error. Categorical outcomes (i.e. meeting the preset glycemic, blood pressure and lipid control targets) are demonstrated as proportions (95% confidence interval [95% CI]) or mean ± S.E.M. For comparing multivariate sample means, we used Multivariate Analysis of Variance (MANOVA) analysis.
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3

Survival Analysis of Cancer Progression

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In our study, categorical variables were compared using Pearson's chi-squared tests for. OS was calculated using the Kaplan—Meier method and compared using the log-rank test. We also used cumulative incidence risk to analyze the first events of CNS progression. Other first events of non-CNS progression, death or loss to follow-up beyond progression were analyzed as competing risks. HRs were used in Cox proportional hazard models, and the corresponding 95% CIs were used to compare the OS between the treatment subgroups. The Statistical Package for the Social Sciences for Windows software version 18.0 (SPSS Inc., Chicago, IL, USA) were used for all statistical analyses. OS and cumulative incidence curves were plotted using STATA for Windows software version 14.0 (StataCorp, College station, TX, USA). A two-sided P < 0.05 was considered statistically significant.
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4

Statistical Analysis of Clinical Outcomes

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In our study, categorical variables were analyzed using Pearson's chi-squared tests, except in instances where a small sample size of < 5 required the use of a Fisher's exact test. OS and PFS curves were calculated using the Kaplan-Meier method and compared by the log-rank test. Multivariate analysis of PFS was performed using the Cox proportional hazards model in which HRs and 95.0% CIs were derived for comparisons between the treatment subgroups of interest. All statistical analyses were conducted using Statistical Package for the Social Sciences for Windows software version 18.0 (SPSS Inc., Chicago, IL, USA). PFS curves were plotted using Stata for Windows software version 14.0 (StataCorp, College station, TX, USA). A two-sided P < 0.05 was considered statistically significant.
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