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Stata se version 15.0 for windows

Manufactured by StataCorp
Sourced in United Kingdom

Stata/SE version 15.0 for Windows is a software application designed for data analysis, statistical modeling, and graphics. It provides a comprehensive set of tools for managing, analyzing, and visualizing data. The software is optimized for large datasets and offers advanced statistical techniques for researchers, analysts, and professionals working with data-driven decision-making.

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Lab products found in correlation

2 protocols using stata se version 15.0 for windows

1

Prognostic Value of Pretreatment Smoking Status in SCLC

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The primary outcome was overall survival (OS), and the secondary endpoint was progression‐free survival (PFS). The effect sizes namely HR and 95% CI or P‐value of the dichotomous variable (“smokers” or “never‐smokers” of pretreatment smoking status) were extracted from each study and pooled to assess the prognostic value of pretreatment smoking status for SCLC. Cochran's Q test and Higgins' I2 statistic were performed to evaluate the heterogeneity of the included studies based on I2 and P‐values. If I2 was ≤50% and P‐value was >0.10, the heterogeneity in different included studies was acceptable and we chose a fixed‐effects model to combine all studies, otherwise a random‐effects model was used. We also conducted sensitivity analysis to assess the influence of each study on the overall analysis and final result. Publication bias was assessed by Begg's funnel plot and Egger's linear regression. When the combined HR was >1, the range of 95% CI did not cross 1, and for two‐tailed P‐values <0.05, the result was considered statistically significant and served as an adverse prognostic factor. All statistical analyses were performed using the Review Manager software (RevMan V.5.3, Cochrane Collaboration, London, UK) and Stata/SE version 15.0 for Windows (Stata Corporation, College Station, TX, USA).
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2

Depressive Symptoms Prevalence and Predictors

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Frequencies and percentages of incident and persistent depressive symptoms were calculated. The first longitudinal logistic regression model estimated incident depressive symptoms in 2017, excluding those with depressive symptoms in 2015, and the second model estimated persistent depressive symptoms (in both 2015 and 2017). Models were adjusted by chronic diseases, sociodemographic factors, lifestyle factors, social participation and BMI; confounders were included based on literature review.9 ,17 (link)P ≤ 0.05 was considered statistically significant. Missing data were discarded. Statistical analyses were conducted with Stata SE version 15.0 for Windows.
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