Stata se v13

Manufactured by StataCorp

Sourced in United States

STATA SE v13.1 is a statistical software package developed by StataCorp. It is designed to provide users with comprehensive data analysis and management tools. The software is capable of performing a wide range of statistical analyses, including regression, time series, and multilevel modeling. STATA SE v13.1 is intended for use by researchers, analysts, and professionals who require advanced statistical capabilities.

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Lab products found in correlation

Stata v14, by StataCorp (1 mentions) Statistica v 12, by StatSoft (1 mentions) Spss statistics v25, by IBM (1 mentions) Stata statistical software release 13, by StataCorp (1 mentions)

41 protocols using stata se v13

Effect of Niacin on Incident Diabetes: A Meta-Analysis

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To identify the potential effect of niacin on incident diabetes, we calculated an overall risk ratio (RR), with associated 95% CIs, as the ratio of cumulative incidence from the available data for all non-diabetic participants at baseline and for those who developed diabetes during trial follow-up. Study-specific RRs were pooled in a random-effect model meta-analysis. We assessed statistical heterogeneity across all studies using the I² statistic, which is derived from Cochrane's Q ((Q−df/Q)×100) and provides a measure of the proportion of overall variation attributable to the heterogeneity between studies.
Despite using both published and unpublished data, we nonetheless formally investigated publication bias by producing a funnel plot and undertaking an Egger test. We additionally undertook sensitivity analyses, using the fixed-effect inverse-variance method, to compare trials that had and had not used laropiprant in combination with niacin, and to compare trials that had and had not used background statin treatment. We repeated the main analysis after excluding the largest trial and also performed an analysis using a fixed-effects model. All p values were two-sided, and p<0.05 was considered statistically significant. We analysed data with StataSE V.13 (StataCorp).

Goldie C., Taylor A.J., Nguyen P., McCoy C., Zhao X.Q, & Preiss D. (2015). Niacin therapy and the risk of new-onset diabetes: a meta-analysis of randomised controlled trials. Heart, 102(3), 198-203.

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Social Position and Mental Health

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All analyses were conducted in STATA/SE V.13 (Stata, Texas, USA), using ‘svy’ commands to allow for the sampling design and attrition up to age 11 years. Kendall's tau-b test was used to examine the extent to which family income and perceived social position were associated. Two types of regression analyses were conducted. Proportional ORs (PORs) and 95% CIs were estimated using ordinal regression analysis to examine positive mental health (ordinal scores), according to family income and perceived social position. ORs and 95% CIs were estimated using logistic regression to examine poor self-esteem and life satisfaction (binary outcomes), according to family income and perceived social position. Models were estimated before and after adjustment for confounders.

Bannink R., Pearce A, & Hope S. (2016). Family income and young adolescents’ perceived social position: associations with self-esteem and life satisfaction in the UK Millennium Cohort Study. Archives of Disease in Childhood, 101(10), 917-921.

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Prevalence and Predictors of PIP

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The overall prevalence of PIP in the study population and the prevalence per individual STOPP criterion in 2013 (the study period) were calculated as a proportion of all eligible persons in the dataset, and reported as percentage estimate and 95% confidence intervals (CI). Adjusted logistic regression analyses were used to calculate odds ratios (OR) and 95% CI to investigate the association between any (versus no) PIP and polypharmacy (categorised as 0-3 versus ≥4 repeat drug classes), age group (≤44, 45-64, 65-84, ≥85 years) and gender (male, female). There were no missing data for the variables of interest. Analyses were performed using STATA SE v13 (StataCorp, College Station, TX, USA).

Barry H.E., Cooper J.A., Ryan C., Passmore A.P., Robinson A.L., Molloy G.J., Darcy C.M., Buchanan H, & Hughes C.M. (2016). Potentially Inappropriate Prescribing Among People with Dementia in Primary Care: A Retrospective Cross-Sectional Study Using the Enhanced Prescribing Database. Journal of Alzheimer's disease : JAD, 52(4).

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Multilevel Survival Analysis of Dementia Risk

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This prospective study employed multilevel survival analysis. The data of 11 032 people living in 44 local districts were used in this study. The multilevel analysis framework relied on the assumption that the health outcome of individuals is partially affected by the district in which they live. The multilevel model evaluated the change in outcome across districts (random effects) and the influences of community-level factors on the outcome, accounting for specific constituent features (fixed effects). Multilevel survival analysis was employed to compute the HR and 95% CI for the onset of dementia at follow-up. The HR of the social support variable was determined as the 1% variation in the proportion of aggregated social support. For the analyses, all four social support indicators at the community level and sociodemographic factors were concurrently adjusted. Furthermore, three sensitivity analyses were conducted, excluding (1) 1 year, (2) 2 years and (3) 3 years after baseline. The STATA SE V.13 (Stata Corp, College Station, Texas, USA) was used for the analysis, and the ‘stmixed’ command was used (the ‘mestreg’ command has become a standard feature in STATA V.14).

Miyaguni Y., Tabuchi T., Aida J., Saito M., Tsuji T., Sasaki Y, & Kondo K. (2021). Community social support and onset of dementia in older Japanese individuals: a multilevel analysis using the JAGES cohort data. BMJ Open, 11(6), e044631.

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Age-Stratified Sampling and Statistical Analysis of Older Adults

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To account for the age-stratified design, we generated sampling weights and applied them using 2011 Census population data for Ottawa, representing 116,593 older adults. We followed this up by univariate analysis of the data by gender, age, mother tongue language, immigration, income, and education and calculated coefficients of variation (CV). Estimates were considered reliable for use if the CV was less than 16.6 per cent; estimates where the CV was between 16.6 per cent and 33.3 per cent were interpreted with caution due to the high sampling variability; and estimates with CVs greater than 33.3 per cent were deemed unreliable. All statistical analyses were conducted using Stata SE V.13 using Pearson’s chi-squared tests with α = 0.05 to assess for statistical significance – these p values are presented in Tables 3, 4, and 5. We made multiple comparisons between pairs if the overall chi-squared test indicated significance and adjusted them with a Bonferroni correction.

Russell K., Taing D, & Roy J. (2017). Measurement of Fall Prevention Awareness and Behaviours among Older Adults at Home. Canadian Journal on Aging, 36(4), 522-535.

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Influenza Infection and Social Activity

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To determine whether certain types of social activity were more likely to result in influenza infection, we set participation in each activity as an explanatory variable, instead of participation in any social activity, and this yielded 14 models. Data from all the respondents were analysed. Number of participating activities was included as a covariate, to measure the effect of participating in each activity. ORs for influenza infection were calculated in relation to participation in each activity, stratified by vaccination status and sex. All analyses were performed with STATA SE V.13 (StataCorp).

Shobugawa Y., Fujiwara T., Tashiro A., Saito R, & Kondo K. (2018). Social participation and risk of influenza infection in older adults: a cross-sectional study. BMJ Open, 8(1), e016876.

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Exploring HIV Risk Factors among Transgender Women

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Means and standard deviations were provided for continuous variables, while counts and their corresponding percentages were supplied for nominal variables; bivariate contrasts were tested for significance using student's t-tests for continuous variables, and chi-square tests of association for nominal variables. Multivariate logistic regression analysis was carried out to explore the associations between self-reported HIV serostatus and participants' demographics, recent substance use, and sexual risk behaviors. Given the particularly long data collection phase (i.e., seven years), time is included as a statistical control in all multivariate models (coded in 6-month intervals), to account for potential shifts in HIV risk/prevalence in the local community of transwomen that may have occurred during the data collection phase. Coefficient estimates for the logistic regression are presented as adjusted odds ratios (AOR), which in this instance describe the factor change in the estimated odds of self-reporting an HIV-positive status for each unit increase in the predictor variable, when controlling for all covariates. All significance tests were two-tailed, and all analyses were carried out using Stata SE v13 (StataCorp, College Station, TX; 2013).

Reback C.J, & Fletcher J.B. (2014). HIV Prevalence, Substance Use, and Sexual Risk Behaviors among Transgender Women Recruited Through Outreach. AIDS and behavior, 18(7), 1359-1367.

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Thyroid Function and Cardiac Geometry

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The Statistica v12.0 (StatSoft Scandinavia AB, Sweden) software system was used for univariate statistical analyses. The Wilcoxon signed-rank test and Fisher’s (two-tailed) exact test were applied to evaluate the differences in the studied parameters. The level of statistical significance was set to p<0.01 due to multiplicity. A regression analysis was performed using STATA/SE v13 (StataCorp, TX, USA). In the linear regression, correlation of LV geometry changes was tested in the uni- and multivariate analyses with the following factors as age, BMI, systolic blood pressure, TSH, free T3, free T4, TRAb, TPOAb (all-continuous). Results with p<0.05 were considered as statistically significant.

Tsymbaliuk I., Unukovych D., Shvets N, & Dinets A. (2015). Cardiovascular Complications Secondary to Graves’ Disease: A Prospective Study from Ukraine. PLoS ONE, 10(3), e0122388.

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Amphetamine-Related Psychosis Epidemiology

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Analyses were conducted using Stata SE v13 (StataCorp, 2015) . People with and without amphetamine-related psychoses were compared using binary logistic regressions conducted separately for candidate demographic and diagnostic variables. The setting, problem and timing of service contact in the two years prior to index admission were described and differences compared using binary logistic regression. Regressions were adjusted by inclusion of multiple covariates for significant potential confounders including age (grouped by decade), sex, country of birth (Australia or other), indigenous status (indigenous compared to non-indigenous), rurality (major metropolitan compared to outer metropolitan and rural or remote) and disadvantage based on statistical local area of usual residence (most disadvantaged 40% of state compared to least disadvantaged 60%).
Differences in type of prior diagnosis were examined separately for each service setting. The two years prior to index admission was divided into eight three-month periods, and service contacts for each period were quantified. Since ED and Community Mental Health contacts in the 1-2 weeks prior to index admission are likely to have reflected acute management of the episode resulting in admission, the 3 months prior to admission were examined after exclusion of the final two weeks.

Sara G., Lappin J., Dobbins T., Dunlop A.J, & Degenhardt L. (2017). Escalating patterns of emergency health care prior to first admission with amphetamine psychosis: A window of opportunity?. Drug and alcohol dependence, 180.

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Analyzing Salt Delivery Variations

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Differences in the amount of salt delivered between the two shakers were compared using repeated measures ANOVA tests. One-way tests were used with data from experiments 1–3, and a two-way test with data from experiment 4. All analyses were conducted in Stata SE v13.0 (see S1 Appendix).

Goffe L., Wrieden W., Penn L., Hillier-Brown F., Lake A.A., Araujo-Soares V., Summerbell C., White M., Adamson A.J, & Adams J. (2016). Reducing the Salt Added to Takeaway Food: Within-Subjects Comparison of Salt Delivered by Five and 17 Holed Salt Shakers in Controlled Conditions. PLoS ONE, 11(9), e0163093.

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