Descriptive statistics and frequency distributions of anomalies were calculated for the impaction and control groups and by jaw within each impaction group. Differences in baseline characteristics between patient groups were assessed with an independent t-test, Χ2 or Fisher’s exact test depending on the outcome and the event frequency. A univariable exact logistic regression was implemented to assess potential associations between type of anomalies, group and jaw. Odds ratios, associated 95% confidence intervals and p-values were calculated. Statistical significance was set at 0.05, and all analyses were conducted using Stata 14.1 statistical software (Stata Corp, College Station, TX, USA).
Stata 14.1 statistical software
Manufactured by StataCorp
Sourced in United States
Stata 14.1 is a comprehensive, integrated statistical software package that provides a wide range of data analysis, management, and graphics capabilities. It is designed to handle large and complex datasets, perform advanced statistical modeling, and produce high-quality visualizations. Stata 14.1 supports a variety of data formats and offers a user-friendly interface for efficient data manipulation and analysis.
Automatically generated - may contain errors
Lab products found in correlation
3 protocols using stata 14.1 statistical software
1
Analyzing Dental Anomaly Patterns
2
Predictors of Toe Tourniquet in Adults
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Descriptive statistics were reported as median and interquartile range (IQR) for continuous variables and frequency and percentage for categorical variables. Logistic regression was used to perform univariate and multivariate analyses to identify predictors of TT in this particular population. Multivariate models included covariates with P < 0.2 in univariate analysis. Finally, we performed an analysis to investigate the performance of DUS for the diagnosis of TT in adults. Statistical analyses were performed using Stata 14.1 statistical software (Stata, College Station, TX, USA). All tests were two-sided with a significance level at P < 0.05.
3
Survival Analysis of Treatment Outcomes
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Descriptive analyses of the study groups were performed using χ 2 and ANOVA. Kaplan-Meier (KM) estimates were computed, and log-rank tests were applied to compare the survival function between the treatment groups. Univariable and multivariable logistic and Cox regression methods were used to analyze the 30-day and 1-year outcomes and identify their predictors. Variables included in the multivariate model were based on the univariable analysis, prior literature, guidance of likelihood ratio tests, and Akaike information indices with a goal to achieve model parsimony. All analyses were performed using Stata 14.1 statistical software (StataCorp, College Station, TX), and statistical significance was accepted at P<0.05.
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