Initially, descriptive statistics were performed regarding the detection rate of E. coli for all animals separated by sex, age class, and management type (liberation directly from ponds or after temporary captivity in the enclosure). Following the classification scheme published by Sandoval-Hernández et al. (27 (link)), sampled animals were categorized as juveniles or adults based on their body size (< 2.0 m and ≥ 2.0 m, respectively). Fisher’s exact test was calculated to determine differences in detection frequencies of tetracycline-resistant E. coli in cloacal swabs between animals of different sexes, age classes, and animals sampled of different management types before release. The results of the statistical tests were considered significant for p < 0.05. Statistical calculations were performed using SAS software version 9.3 for Windows (SAS Institute Inc., Cary, NC, United States).
Sas software version 9.3 for windows
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SAS software version 9.3 for Windows is a comprehensive data analysis and statistical software package. It provides tools for data management, statistical analysis, and report generation. The software is designed to work on the Windows operating system.
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Lab products found in correlation
3 protocols using sas software version 9.3 for windows
1
Prevalence of Antibiotic-Resistant E. coli in Wildlife
2
Evaluating Participant Knowledge and Decision Conflict in Clinical Trials
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Descriptive statistics were calculated for the baseline background data, FCCHL score, and the time required by the physician/CRC to explain the trial. To compare between groups and to confirm the balance of each group, the t-test was conducted for continuous variables, and Fisher's exact test used for categorical variables.
To analyze participant knowledge and DCS score, the paired t-test was used to compare scores before and after the intervention for each group. In addition, a t-test was performed on the between-group score difference after the intervention and the score difference before and after the intervention in each group. For both scores, the intervention group tended to have lower or higher pre-intervention values than the control group; therefore, a covariance analysis was performed using the pre-/post-intervention differences as dependent variables and pre-intervention values as a covariate. For the knowledge score, the interaction term was not included in the model because no interaction was detected between the pre-intervention value and the effect of the intervention. A usability test summarized the results of each item.
All tests were two-sided with a significance level of 5%. SAS software version 9.3 for Windows (SAS Institute Inc., Cary, NC, USA) was used for analysis.
To analyze participant knowledge and DCS score, the paired t-test was used to compare scores before and after the intervention for each group. In addition, a t-test was performed on the between-group score difference after the intervention and the score difference before and after the intervention in each group. For both scores, the intervention group tended to have lower or higher pre-intervention values than the control group; therefore, a covariance analysis was performed using the pre-/post-intervention differences as dependent variables and pre-intervention values as a covariate. For the knowledge score, the interaction term was not included in the model because no interaction was detected between the pre-intervention value and the effect of the intervention. A usability test summarized the results of each item.
All tests were two-sided with a significance level of 5%. SAS software version 9.3 for Windows (SAS Institute Inc., Cary, NC, USA) was used for analysis.
3
Survival Analysis of Colon Cancer
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Associations between categorical variables (cluster of differentiation, MGMT status, gender, microsatellite instability status, tumor location) were calculated using χ 2 -test, Fisher's exact test, or Kruskal-Wallis test as appropriate. Mann-Whitney test was used to compare the continuous variables between groups.
Intraoperative and clinical follow-up data were obtained from hospital charts. Disease-specific survival was measured from the date of surgery to the date of death related to colonic carcinoma (ie, death unrelated to colonic carcinoma was censored at the time of death). Univariate survival analysis was performed using the log-rank test and illustrated using Kaplan-Meier Curves. P-values o 0.05 were considered statistically significant. Statistical analysis was performed using SAS software version 9.3 for Windows (SAS Institute, Cary, NC, USA).
Intraoperative and clinical follow-up data were obtained from hospital charts. Disease-specific survival was measured from the date of surgery to the date of death related to colonic carcinoma (ie, death unrelated to colonic carcinoma was censored at the time of death). Univariate survival analysis was performed using the log-rank test and illustrated using Kaplan-Meier Curves. P-values o 0.05 were considered statistically significant. Statistical analysis was performed using SAS software version 9.3 for Windows (SAS Institute, Cary, NC, USA).
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