Baseline socio-demographic, psychosocial, behavioral, and clinical characteristics were summarized by participants’ enrollment HIV status: HIV-uninfected, newly diagnosed, or previously diagnosed. Participants who were newly diagnosed were compared with those who were previously diagnosed and those who were HIV-uninfected using Chi-Square tests or Fisher’s Exact test for categorical variables, and Wilcoxon Rank-Sum test for continuous variables. Separate multivariate logistic regression models were used to assess associations between baseline characteristics and being newly diagnosed with HIV, versus being previously diagnosed with HIV and HIV-uninfected participants, respectively. Only covariates that were found to have a p-value of <0.10 in bivariate analysis were included in the multivariate models. SAS® version 9.2 statistical software was used to perform all analyses.
Sas version 9.2 statistical
Manufactured by SAS Institute
SAS® version 9.2 is a statistical software package that provides a comprehensive set of tools for data analysis, modeling, and reporting. It offers a wide range of statistical procedures, data management capabilities, and advanced analytics functionalities.
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Lab products found in correlation
3 protocols using sas version 9.2 statistical
1
Socio-demographic Factors and HIV Status
2
Assessing Treatment Means Differences
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For all responses, the normal distribution and constant variance assumptions on the error terms were verified by examining the residual (Montgomery, 2009), analysis of variance (ANOVA) was done using SAS version 9.2 statistical software (SAS institute, 2008) . To asses, the different among treatment mean separation will carry out using least significant difference (LSD) at 5%.
3
Tinnitus Prevalence in Older Adults
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Given the rarity of (severe) tinnitus among the young (18-44 years), we limited the multivariate analyses to middle-age and elderly adults ( ≥ 45 years). Odds ratios (ORs) for any, chronic and severe tinnitus, and corresponding 95% confidence intervals (CIs), were estimated using unconditional multiple logistic regression after adjustment for sex, age, level of education, geographic area, smoking status, alcohol consumption and BMI. All the analyses were performed with the SAS, version 9.2, statistical package (SAS Institute).
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