Expanding the Markov chain tool box: distributions of occupation times and waiting times

Dudel, Christian

doi:10.4054/mpidr-wp-2017-017

Cited by 2 publications

(2 citation statements)

References 43 publications

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“…The baseline age for all measures (i)-(iii) is 50. Descriptions of how to calculate metrics (i) and (ii) can be found in Dudel (2018) and Roth and Caswell (2018).…”

Section: Analytic Strategymentioning

confidence: 99%

Understanding cognitive impairment in the U.S. through the lenses of intersectionality and (un)conditional cumulative (dis)advantage

Hale¹,

Schneider²,

Mehta³

et al. 2022

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“…The baseline age for all measures (i)-(iii) is 50. Descriptions of how to calculate metrics (i) and (ii) can be found in Dudel (2018) and Roth and Caswell (2018).…”

Section: Analytic Strategymentioning

confidence: 99%

Understanding cognitive impairment in the U.S. through the lenses of intersectionality and (un)conditional cumulative (dis)advantage

Hale¹,

Schneider²,

Mehta³

et al. 2022

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“…That is, we assume that transition probabilities PrðS tþk ¼ s 0 0 jS t ¼ s 0 Þ, where s 0 and s 0 0 are arbitrary states, are not affected by unobserved transitions. For the description of our method, it is not important which of the several approaches to estimating transition probabilities or rates is used (e.g., Dudel 2021;Lynch and Brown 2005) or which assumptions are used to derive DLE and related quantities from the probabilities or rates such as the assumption of mid-interval transitions mentioned above or alternative assumptions.…”

Section: Bounds On Bias Due To Unobserved Final Transitions Notation mentioning

confidence: 99%

How bad could it be? Worst-case bounds on bias in multistate models due to unobserved transitions

Dudel

Schneider

2021

Sociological Methods & Research

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Multistate models are often used in social research to analyze how individuals move between states. A typical application is the estimation of the lifetime spent in a certain state, like the lifetime spent in employment, or the lifetime spent in good health. Unfortunately, the estimation of such quantities is prone to several biases. In this paper, we study the bias due to the often implicitly used assumption that there are no unobserved transitions between states. This assumption does often not hold for the panel data typically used to estimate multistate models, as the states occupied by individuals are only known at specific points in time, and further transitions between panel waves are not recorded. We present partially identified estimates of the lifetime spent in a state, or worse-case bounds, which show the maximum possible level of bias due to unobserved transitions. We provide two examples studying the lifetime spent in disability (disabled life expectancy; DLE). The first example applies our methods to results on cohort trends in DLE in the U.S. taken from Crimmins et al. (2009). In the second example, we replicate findings from Mehta and Myrskylä (2017), and apply our methods to data from the U.S. Health and Retirement Study (HRS) in order to estimate the effects of health behaviors on DLE.

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Expanding the Markov chain tool box: distributions of occupation times and waiting times

Abstract: Working papers of the Max Planck Institute for Demographic Research receive only limited review. Views or opinions expressed in working papers are attributable to the authors and do not necessarily refl ect those of the Institute.

Cited by 2 publications

References 43 publications

Understanding cognitive impairment in the U.S. through the lenses of intersectionality and (un)conditional cumulative (dis)advantage

Understanding cognitive impairment in the U.S. through the lenses of intersectionality and (un)conditional cumulative (dis)advantage

How bad could it be? Worst-case bounds on bias in multistate models due to unobserved transitions

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