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Mental Illness Estimations

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Estimation Errors and Criticisms Most of the data used to estimate prevalence of a mental illness is collected through cross-sectional studies that are obtained retrospectively. As a whole, Almansa et al. (2014) go even further to state that “epidemiological studies about lifetime disorders typically do not use adequate methods of analysis” (Almansa et al., 2014). Due to this cross-sectional study design and retrospective data collection, the estimations of lifetime prevalence obtained by direct computation tend to underestimate the actual lifetime prevalence for the given mental illness or disorder (Almansa et al., 2014). In order to understand how some of these basic prevalence calculations are made, consider the following provided example. …show more content…

It can be said to model the time-to-event data. The event of a survival analysis is the occurrence of interest. In the context of this study, the occurrence would be the first symptom of a disorder. The time for a survival analysis is the time until the event is observed, or the study is concluded. This time observation “can be measured in days, weeks, years, etc.” (Despa, n.d.). The survival time would indicate the time until the observed individual exhibits the first symptom for a disorder. A survival function concentrates on the time until the desired event transpires. The “cumulative probability of events over time” is calculated “while adjusting other influential covariates” (Singh & Mukhopadhyay, 2011). If an individual in the study does not experience the event of interest during the study, then their information becomes censored. Survival analysis is particularly useful when confronted by censored data (Singh & Mukhopadhyay, 2011). Censorship is a main component in developing functions for survival analysis. For this study, censoring occurs when the information regarding the survival time (time until the first symptom of a disorder occurs) is lacking; thus, there is information present for a variable but it is not

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