Stata se 11.2 for windows

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Stata/SE 11.2 for Windows is a statistical software package designed for data analysis, management, and visualization. It provides a comprehensive suite of tools for researchers, analysts, and professionals working with complex data. The software offers a wide range of statistical techniques, data manipulation capabilities, and graphical options to facilitate efficient data analysis and reporting.

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Stata (4799 citations) Stata 11 (1613 citations) Stata/SE (293 citations) STATA/SE 11.0 (137 citations) STATA 11 for Windows (11 citations) STATA/SE version 11.2 for Windows (6 citations) Stata 11.2 SE (2 citations)

4 protocols using stata se 11.2 for windows

Meta-analysis of Biomarker Hazard Ratios

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Comprehensive meta-analysis (Version 2, Biostat, Englewood NJ) and Stata (Stata/SE 11.2 for Windows; StataCorp LP, College Station, Texas, USA) were used to pool and to meta-analyse results from the individual studies. Pooled results were extracted and analysed as Hazard Ratios (HR) with 95% confidence intervals. Hazard ratios for biomarkers were analysed by subgroup, where possible. Overall Hazard ratios are also presented. A random-effects model was used and 2-sided P values from an inverse variance statistical method are reported.
Statistical heterogeneity was evaluated using the I² statistic [26 , 27 (link)], which assesses the appropriateness of pooling individual study results and the 95% CI for I² were calculated using Higgins et al’s method [28 (link), 29 (link)]. Where I² was >50%, the degree of heterogeneity was considered substantial. Potential publication bias was appraised by visual inspection of the funnel plot of effect size against the SE for each study, with asymmetry formally assessed with Egger’s regression test.

Barron E., Lara J., White M, & Mathers J.C. (2015). Blood-Borne Biomarkers of Mortality Risk: Systematic Review of Cohort Studies. PLoS ONE, 10(6), e0127550.

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Statistical Analysis of Continuous and Categorical Data

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Analyses were performed using STATA/SE 11.2 for Windows; continuous variables were expressed as the mean ± standard deviation or median and range; categorical data were expressed as numbers (percentages). Statistical analyses were performed using the χ² test and Mann-Whitney test for independent samples, when appropriate. A P value < 0.05 was used as a threshold for statistical significance.

Berardi A., Buffagni A.M., Rossi C., Vaccina E., Cattelani C., Gambini L., Baccilieri F., Varioli F, & Ferrari F. (2016). Serial physical examinations, a simple and reliable tool for managing neonates at risk for early-onset sepsis. World Journal of Clinical Pediatrics, 5(4), 358-364.

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Statistical Analysis of Experimental Data

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Statistical analyses were performed using Stata/SE 11.2 for Windows (StataCorp, College Station, TX, USA). Where appropriate, data are presented as the mean ± standard deviation of at least three independent samples. Two sample's mean comparison was performed using Student's t-test. One-way analysis of variance was used to determine differences among at least three groups, and a Bonferroni multiple comparison was performed to test variances within groups. Two-tailed P<0.05 was considered to indicate a statistically significant difference.

Mu Y., Zhou H., Wu W.J., Hu L.C, & Chen H.B. (2015). Dynamic expression of miR-206-3p during mouse skin development is independent of keratinocyte differentiation. Molecular medicine reports, 12(6).

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Immunohistochemical Analysis of AIM1 in Prostate Cancer

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All graphs and statistical analyses for in vitro and in vivo experiments were generated using Prism 6.0 (GraphPad Softward, Inc., La Jolla, CA) using t-test statistics. For analysis of immunohistochemical expression data, since scores were non-normally distributed, non-parametric tests were used to compare their differences depending on the examined tissue. Comparisons were made for membranous and cytoplasmic AIM1 expression. Scores between benign prostate, prostate cancer, and lymph-node metastasis were compared using the Kruskal–Wallis test, adjusting for tied values. Pairwise comparisons were done using the Wilcoxon rank-sum (Mann–Whitney U) test. A two-tailed P < 0.05 was considered statistically significant, except for post hoc comparisons. For the latter, the significance threshold was adjusted using Šidák’s correction, and set to P < 0.017. Data were analyzed using Stata/SE 11.2 for Windows (StataCorp LP, College Station, TX). Gene set enrichment analysis was carried out using the DAVID functional annotation tool^{69 (link)}.

Haffner M.C., Esopi D.M., Chaux A., Gürel M., Ghosh S., Vaghasia A.M., Tsai H., Kim K., Castagna N., Lam H., Hicks J., Wyhs N., Biswal Shinohara D., Hurley P.J., Simons B.W., Schaeffer E.M., Lotan T.L., Isaacs W.B., Netto G.J., De Marzo A.M., Nelson W.G., An S.S, & Yegnasubramanian S. (2017). AIM1 is an actin-binding protein that suppresses cell migration and micrometastatic dissemination. Nature Communications, 8, 142.

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