Stata statistical software release v 16

Manufactured by StataCorp

Stata Statistical Software: Release V.16 is a comprehensive software package for data analysis, data management, and graphics. It provides a wide range of statistical tools for researchers, analysts, and professionals across various fields. The software is designed to handle large datasets and offers a user-friendly interface for data manipulation, statistical modeling, and reporting.

Automatically generated - may contain errors

Lab products found in correlation

Stata v 16, by StataCorp (1 mentions) Stata, by StataCorp (1 mentions) R statistical software v 4, by R Project for Statistical Computing (1 mentions)

Spelling variants of this product

Stata Statistical Software (1123 citations) Stata V.16 (752 citations) Stata Statistical Software: Release 16 (148 citations) Stata (Release 16, (55 citations) Stata Statistical Software: Release (37 citations) STATA software 16.0 (27 citations) Stata statistical software V.16 (20 citations) Stata 16 statistical software (18 citations) Stata software V.16.0 (18 citations) STATA software release 16 (4 citations)

3 protocols using stata statistical software release v 16

Descriptive Analysis of Missing Data Handling

Check if the same lab product or an alternative is used in the 5 most similar protocols

Initially, we conducted a descriptive analysis of baseline characteristics as well as a number of times subjects were measured in total and stratified by disease severity. Variables of continuous nature were be presented as medians and IQR and categorical variables as frequencies and percentages.
For all analyses, we excluded measurements where all items in the instrument under investigation were missing. Any remaining missingness in the data was managed by single value imputation using chained equations.22 (link) Results are presented with 95% CIs where appropriate. All analyses were conducted in Stata V.16 (StataCorp. 2019. Stata Statistical Software: Release V.16, StataCorp).

Valentin J.B., Mainz J., Johnsen S.P., Kristensen K, & Kristensen S. (2024). Rasch analysis of a patient-reported outcome measure for self-perceived health among psychiatric patients in Denmark. BMJ Open Quality, 13(1), e002519.

+ Open protocol

+ Expand

Factors Associated with Low-Acuity Visits

Check if the same lab product or an alternative is used in the 5 most similar protocols

We present results as point prevalence or median in the bivariate analysis exploring the differences between low-acuity and high-acuity consultations. We used Pearson’s χ² for categorical and Mann-Whitney U test for continuous variables. To identify factors associated with low-acuity visits, all statistically significant variables p<0.05 at the bivariate level were included in a binary multiple logistic regression model including baseline characteristics (gender, site). We performed sensitivity analysis with a different definition of low-acuity, and with the exclusion of neonates whose visits are classified as high-acuity per our definition, as they get an ATS of 3 or below. We performed all analyses using STATA (STATACorp. 2019. STATA Statistical Software: Release V.16., STATACorp).

Jaboyedoff M., Starvaggi C., Suris J.C., Kuehni C.E., Gehri M., Keitel K, & Pellaton R. (2021). Characteristics of low-acuity paediatric emergency department consultations in two tertiary hospitals in Switzerland: a retrospective observational study. BMJ Paediatrics Open, 5(1), e001267.

+ Open protocol

+ Expand

Statistical Analysis of Author Data

Check if the same lab product or an alternative is used in the 5 most similar protocols

Continuous data were visualised using histograms to ascertain normality, and median values were calculated. Categorical data were analysed to answer specific study questions, and the χ² test was used to compare the distributions of author characteristics across various groups of authors. Statistical analysis and graphing were conducted using STATA Statistical Software Release V.16 (StataCorp). A p<0.05 was considered significant. R Statistical Software V.4.0.3 (R Foundation for Statistical Computing, Vienna, Austria) was used to generate choropleth maps with packages tidyverse, sp, geojsonio, ggplot2 and mapproj.

Ravi K., Bentounsi Z., Tariq A., Brazeal A., Daudu D., Back F., Elhadi M., Badwi N., Shah S.S., Bandyopadhyay S., Khalil H., Kimura H., Sekyi-Djan M.N., Abdelrahman A., Shaheen A., Mbonda Noula A.G., Wong A.T., Ndajiwo A., Souadka A., Maina A.N., Nyalundja A.D., Sabry A., Hind B., Nteranya D.S., Ngugi D.W., de Wet E., Tolis E.A., Wafqui F.Z., Essangri H., Moujtahid H., Moola H., Narain K., Ravi K., Wassim K., Odiero L.A., Nyaboke L.S., Metwalli M., Naisiae M., Pueschel M.G., Turabi N., El Aroussi N., Makram O.M., Shawky O.A., Outani O., Carides P., Patil P., Halley-Stott R.P., Kurbegovic S., Marchant S., Moujtahid S., El Hadrati S., Agarwal T., Kidavasi V.A., Agarwal V., Steyn W., Matumo W., Fahmy Y.A., Omar Z., Amod Z., Eloff M., Hussein N.A, & Sharma D. (2021). Systematic analysis of authorship demographics in global surgery. BMJ Global Health, 6(10), e006672.

+ Open protocol

+ Expand

About PubCompare

Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.

We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.

However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.

Ready to get started?

Revolutionizing how scientists
search and build protocols!