An application of statistical models in mental health research

Whitmore, G. À.; Neufeldt, Aldred H.

doi:10.1007/bf02476771

Cited by 8 publications

(2 citation statements)

References 11 publications

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“…The strike ends when the process first encounters the zero level where the parties agree and settle. In addition to Lancaster (1972), refer to applications described in Whitmore and Neufeldt (1970), Whitmore (1975Whitmore ( , 1979Whitmore ( , 1983Whitmore ( , 1986Whitmore ( , 1995, Doksum and Hóyland (1992), Doksum and Normand (1995), Lu (1995), Whitmore and Schenkelberg (1997) and Horrocks and Thompson (2004), to name a few. Onar and Padgett (2000) and Padgett and Tomlinson (2004) extend the Wiener diffusion model to an accelerated testing context.…”

Section: Examples Of First-hitting-time Modelsmentioning

confidence: 99%

Threshold Regression for Survival Analysis: Modeling Event Times by a Stochastic Process Reaching a Boundary

Lee¹,

Whitmore²

2006

Statist. Sci.

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232

132

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Many researchers have investigated first hitting times as models for survival data. First hitting times arise naturally in many types of stochastic processes, ranging from Wiener processes to Markov chains. In a survival context, the state of the underlying process represents the strength of an item or the health of an individual. The item fails or the individual experiences a clinical endpoint when the process reaches an adverse threshold state for the first time. The time scale can be calendar time or some other operational measure of degradation or disease progression. In many applications, the process is latent (i.e., unobservable). Threshold regression refers to first-hitting-time models with regression structures that accommodate covariate data. The parameters of the process, threshold state and time scale may depend on the covariates. This paper reviews aspects of this topic and discusses fruitful avenues for future research.

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Section: Examples Of First-hitting-time Modelsmentioning

confidence: 99%

Threshold Regression for Survival Analysis: Modeling Event Times by a Stochastic Process Reaching a Boundary

Lee¹,

Whitmore²

2006

Statist. Sci.

Self Cite

232

132

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“…Our estimation methodology builds on Lancaster's (1990, p. 118) formulation of a Wiener process duration model, but goes a step further by controlling for unobserved heterogeneity. Wiener process duration models are most common in the health literature, where time to death/admission/discharge is modeled as the first crossing of a barrier by a health process (e.g., Whitmore and Neufeldt, 1970, and Whitmore and Eaton, 1977, as cited by Seshadri, 1999, and Ting Lee, et al, 2000). Jovanovic (1984, 1979) models job turnover and employment transitions with a Wiener process model.…”

Section: Introductionmentioning

confidence: 99%

Benchmarking for Productivity Improvement: A Health‐care Application*

Ackerberg

Machado

Riordan

2006

Int Economic Review

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A methodology is developed and applied to compare the performance of publicly funded agencies providing treatment for alcohol abuse in Maine. The methodology estimates a Wiener process that determines the duration of completed treatments, while allowing for agency differences in the effectiveness of treatment, costs of treatment, standards for completion of treatment, patient attrition, and the characteristics of patient populations. Notably, the Wiener process model separately identifies agency fixed effects that describe differences in the effectiveness of treatment ("treatment effects"), and effects that describe differences in the unobservable characteristics of patients ("population effects"). The estimated model enables hypothetical comparisons of how different agencies would treat the same populations. The policy experiment of transferring the treatment practices of more cost-effective agencies suggests that Maine could have significantly reduced treatment costs without compromising health outcomes by identifying and transferring best practices.

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Applications of Random Walk and Diffusion Models in the Life and Behavioral Sciences

Schwarz

2022

Random Walk and Diffusion Models

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An application of statistical models in mental health research

Cited by 8 publications

References 11 publications

Threshold Regression for Survival Analysis: Modeling Event Times by a Stochastic Process Reaching a Boundary

Threshold Regression for Survival Analysis: Modeling Event Times by a Stochastic Process Reaching a Boundary

Benchmarking for Productivity Improvement: A Health‐care Application*

Applications of Random Walk and Diffusion Models in the Life and Behavioral Sciences

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