Stata software se 14

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Sourced in United States

STATA software SE/14.0 is a comprehensive statistical software package designed for data analysis, visualization, and reporting. It provides a wide range of statistical tools and techniques to help researchers, analysts, and professionals perform advanced data analysis. The software is capable of handling large datasets and offers a user-friendly interface for efficient data management and processing.

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4 protocols using stata software se 14

Statistical Analysis of Research Data

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The Shapiro–Wilk test was used to evaluate the normality of distribution. The student’s t test was used to assess differences between two groups. Cuzick’s test was used for trend analysis. Spearman’s rank correlation was calculated between AAI and IPE. Tests were performed using STATA software SE/14.0 (StataCorp LLC, College Station, TX, USA) and were considered statistically significant at 95% (p < 0.05).
The Shapiro–Wilk test was used to evaluate the normality of distribution. The student’s t test was used to assess differences between two groups. Cuzick’s test was used for trend analysis. Spearman’s rank correlation was calculated between AAI and IPE. Tests were performed using STATA software SE/14.0 (StataCorp LLC, College Station, TX, USA) and were considered statistically significant at 95% (p < 0.05).

Guarducci G., Messina G., Carbone S., Urbani A, & Nante N. (2022). Inter-Regional Patients’ Migration for Hospital Orthopedic Intensive Rehabilitation: The Italian Experience. International Journal of Environmental Research and Public Health, 19(21), 13726.

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Analyzing Spatial-Temporal Trends in Biomarkers

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For every region, both for Gandy’s Nomogram and for the two graphical representations mentioned above, the points born from the coordinates of the X and Y axis were linked to obtain a vector. If there was a monophasic trend over the years (same direction of the points), 2011 was linked to 2019. If there was a biphasic trend over the years (change of law), 2011 was linked to the point of changing direction, which was linked to 2019 [13 (link),31 (link),35 ]. The STATA software SE/14.0 (StataCorp LLC, College Station, TX, USA) was used for data management and for statistical analysis. Trends were studied with Cuzick’s test, and the difference in the ORD/DH ratio between residents and mobility admissions was studied with the Mann–Whitney U-test. Finally, the correlations between AI, EI and NB × 1000 inhabitants were studied through Sperman’s rank correlation test. The level of significance was set up at the level of 95% (p < 0.05).

Guarducci G., Messina G., Carbone S, & Nante N. (2023). Identifying the Drivers of Inter-Regional Patients’ Mobility: An Analysis on Hospital Beds Endowment. Healthcare, 11(14), 2045.

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Demographic Factors and COC Contraindications

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The continuous variables are presented as the mean ± standard deviation (SD), and the categorical variables as number and percentage. The association between the demographic variables such as age, BMI, educational level, marital status, and parity and the dependent variable (contraindications to COCs) was assessed using univariate logistic regression. The statistical analysis was conducted using STATA Software SE/14.0 (StataCorp LLC, Station, TX, USA).

Assiri G.A., Bannan D.F., Alshehri G.H., Alshyhani M., Almatri W, & Mahmoud M.A. (2022). The Contraindications to Combined Oral Contraceptives among Reproductive-Aged Women in an Obstetrics and Gynaecology Clinic: A Single-Centre Cross-Sectional Study. International Journal of Environmental Research and Public Health, 19(3), 1567.

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Comparing Health Profiles Using CIRS Cards

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For the comparisons of the health profiles delineated by the physician of the clinic and by the epidemiological team, we used Cohen’s kappa (κ), which measures the inter-rater agreement between categorical scales when there are two raters. To interpret the results of Cohen’s kappa, we referred to the following intervals: from 0.01 to 0.20 slight agreement, from 0.21 to 0.40 fair agreement, from 0.41 to 0.60 moderate agreement, from 0.61 to 0.80 substantial agreement and from 0.81 to 1.00 almost perfect or perfect agreement [27 (link),28 (link)]. Finally, the ANOVA test was used to test for differences between the means of three or more groups, and the Student’s t-test was used to assess differences between two controls. We used STATA software SE/14.0 (StataCorp LLC, College Station, TX, USA) to calculate them. This identified the main differences and systematic errors made when using the scale. Moreover, our results are reported graphically on a model that we have elaborated ad hoc in order to make the reading of the health profiles obtainable from the CIRS cards immediate.

Napolitani M., Guarducci G., Abinova G., Messina G, & Nante N. (2022). How to Improve the Drafting of Health Profiles. International Journal of Environmental Research and Public Health, 19(6), 3452.

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