Sensitivity Analyses. The sensitivity analyses, which investigated the implications of including patients with missing information in at least one data source for routes to diagnosis or milestone date, displayed similar findings as the main analysis (Tables A.3-A.4 in Appendix A). And the basic characteristics of excluded and included patients were similar (Table A.5 in Appendix A).
Sensitivity Analyses. Calculate one-way and/or multi-way sensitivity analyses for direct prescription costs and incremental prescription costs (savings). § An explanation of the methods used to calculate the sensitivity analyses must be included as well as the assumptions used in calculating the values. § Cite all relevant references.
Sensitivity Analyses. We conducted sensitivity analyses, removing the 15 participants from Alabama with ZIP code STI prevalence assigned to the participant census tract from the analytic data set, to explore potential bias introduced by this substitution. The rounded odds ratio estimates for Final Model with and without these 15 participants were the same for all outcomes. Discussion Our analyses reveal that neighborhood characteristics are associated with sexual risk behaviors among women HIV-infected and HIV-uninfected women living in the South and that these relationships vary by type of sexual intercourse. Specifically, greater social disorder was associated with a lower odds of AI and UAI. Neighborhood characteristics were not associated with UVI in our sample. Unprotected receptive anal intercourse confers high risk of transmission of STIs, including HIV.42,50 Studies exploring individual-level predictors of UAI among women suggest that UAI may be influenced by complex social and economic factors, yet no multilevel studies in which individuals are nested in neighborhoods have explored relationships of neighborhoods characteristics to UAI specifically.42,43,51 In this analysis, greater social disorder was associated with a lower odds of UAI. The direction of this relationship was unexpected. Elements of the neighborhood disorder component, including STI prevalence and violent crime, are associated with partner concurrency, STI acquisition, and greater perceived sexual partner risk.21,22,27 It is possible that women living in neighborhoods with greater social disorder perceived their partners to be riskier, and that these perceptions discouraged engaging in AI or promoted condom use during AI.52-54 Notably, the reduced models which tested associations between tract-level social disorder, AI, and UAI, excluding participant-level characteristics that may lie on the causal pathway (i.e., income, QOL, alcohol and illicit substance use, sex exchange, and homelessness), found that excluding these participant-level characteristics attenuated relationships towards the null. Latkin and colleagues found that individual perceptions of neighborhood social disorder are influenced by individual- and network-level characteristics and that relationships of social disorder to sexual risk are complex.49,55 It is possible that women who are homeless or engaged in high risk activities (e.g., sex exchange) may be more acutely aware of their neighborhood environments and consequently may perceiv...
Sensitivity Analyses. All analyses were re-estimated to control for the effect of possible confounders sex and cognitive ability (MSEL). The effect of missing data was addressed by re- estimating the models with listwise deletion. The results of the models after adjustment for sex and with listwise deletion did not change. However, when controlling for cognitive ability at 36 months, the relationship between BI at 9 months and anxiety at 36 months become significant; all other patterns of findings remain the same. Further results for Models 2.1 to 2.3 are summarised in Appendix 1. Table 2.3 Summary of Exploratory Mediation Analyses Predictors (24 months) Mediator (36 months) Outcome (36 months) Total Effect Direct Effect Indirect Effect (95% CI Bootstrap) Percentage of Total Effect Mediated Behavioural Inhibition ASD Anxiety .42 (.10) *** .28 (.08) ** .14 (.06, .22) ** 33 % Effortful Control ASD Anxiety -.39 (.08) *** -.09 (.09) -.31 (-.41, -.21) *** 79 % Behavioural Inhibition Anxiety ASD .28 (.10) ** .06 (.09) .22 (.12, .32) *** 79 % Effortful Control Anxiety ASD -.59 (.07) *** -.43 (.09) *** -.16 (-.25, -.08) ** 27 % 85 *** p < .001, ** p < .01, * p < .05
Sensitivity Analyses. Even though all dyads were unique, due to the design of the study, 20 parents in this sample belonged to two dyads because they participated with two children. To exclude the possibility that the results were driven by these parents, we excluded one dyad of each. We chose to remove the dyad with the lower maltreatment score to maintain as much variability as possible. The same was true for children, as 19 children participated with two parents. Again, we excluded the dyad with the lower maltreatment score. This left us with 42 dyads to repeat the main analysis. The association of RScs with maltreatment remained similar in strength in this smaller sample (β = -.29, p =.04, see Table S4).
Sensitivity Analyses. In Aphekom, we perform a separate assessment of uncertainties when computing a) the number of health outcomes attributable to air pollution, and b) unit costs.2 Indeed, we apply Low, Central (also referred to as Best) and High estimates to the range of health outcomes provided by the epidemiological computations. The complete economic results will thus represent a range of monetary valuations (Low, Central and High) for each health outcome. We apply the same rule as Cafe (2005): a +/- 33% range around the best / central estimate of the unit economic values except for the valuation of mortality, for which a specific uncertainty assessment is done. Categorization of costs According to accepted practice (see for instance Xxxxxx et al., 1996; or Akobundu et al., 2006), three components related to the cost of a health outcome can be distinguished.
Sensitivity Analyses. In collaboration with City staff, develop up to three (3) sensitivity analyses to evaluate the financial and rate impacts of changes to key variables or other factors of interest.
Sensitivity Analyses. In the development of the HIV-ERSD cohort, those who were preemptively referred or waitlisted were excluded. Those who were preemptively referred and waitlisted were compared to those to evaluate the differences between the two groups. Additionally, one of the classifications for being HIV positive was having a prescription for an antiretroviral regimen. Though, only patients who used Medicare to fill their prescriptions were captured. Differences between those who had a Medicare prescription claim and those who did not was assessed.
Sensitivity Analyses. Offer up to three (3) sensitivity analyses to evaluate the financial and rate impacts of changes to load growth, power costs, project timing and priority, project funding, conservation initiatives or other changes specified by the City. » The resulting revenue requirement and multi-year rate strategy developed will meet the City’s specified financial metrics, goals and objectives and deliver a self-sustaining, electric utility financial planning toolset TASK 4: COST-OF-SERVICE ANALYSIS The cost-of-service analytical task will establish a defensible basis for assigning “cost shares” and establishing “equity” for the City’s customers. This is accomplished with the development of a series of allocations, based on customer data and engineering / planning criteria to assign utility cost recovery to customers in proportion to their estimated demands. Specific consideration will be given to total utility costs in relationship to the functions identified in Exhibit 1. We have included traditional and unbundled cost-of-service functions. The unbundling analysis has proven beneficial in aligning rates by service function in preparation of meeting alternative service requests for example - distributed generation.
