Latent Markov modeling is used as an alternative to the Current Population Survey (Census, 2002) reinterviewing methodology for estimating the measure-ment error in the recorded employment status. This alternative methodology, which is implemented in the syntax version the Latent GOLD program, turns out to be a promising new approach for estimating measurement error in longitudinal surveys. However, it is important to take into account unobserved heterogeneity in the initial-state and transition probabilities because the size of the measurement error is overestimated when unobserved heterogeneity is not taken into account
In psychological research, statistical models of latent state-trait (LST) theory are popular for the...
esearchers use finite mixture models (FMMs) to analyze linked survey and administrative data on labo...
Cross-sectional latent class regression models, also known as switching regressions or hidden Markov...
Measurement errors can induce bias in the estimation of transitions, leading to erroneous conclusion...
Measurement errors can induce bias in the estimation of transitions, leading to erroneous conclusion...
When time-intensive longitudinal data are used to study daily-life dynamics of psychological constru...
A logistic model relating the rates of transition between two states to a vector of covariates is co...
Longitudinal data is essential for understanding how the world around us changes. Most theories in t...
Previous work by the author used Markov Latent Class Analysis (MLCA) to make aggregate estimates of ...
In the field of both education and psychology, if future situations are thought to be related to the...
Invariance of the measurement model (MM) between subjects and within subjects over time is a prerequ...
Invariance of the measurement model (MM) between subjects and within subjects over time is a prerequ...
Longitudinal surveys provide a key source of information for analysing dynamic phenomena. Typical e...
Drawing inferences about dynamics of psychological constructs from intensive longitudinal data requi...
Longitudinal and repeated measurement data commonly arise in many scientific researchareas. Traditio...
In psychological research, statistical models of latent state-trait (LST) theory are popular for the...
esearchers use finite mixture models (FMMs) to analyze linked survey and administrative data on labo...
Cross-sectional latent class regression models, also known as switching regressions or hidden Markov...
Measurement errors can induce bias in the estimation of transitions, leading to erroneous conclusion...
Measurement errors can induce bias in the estimation of transitions, leading to erroneous conclusion...
When time-intensive longitudinal data are used to study daily-life dynamics of psychological constru...
A logistic model relating the rates of transition between two states to a vector of covariates is co...
Longitudinal data is essential for understanding how the world around us changes. Most theories in t...
Previous work by the author used Markov Latent Class Analysis (MLCA) to make aggregate estimates of ...
In the field of both education and psychology, if future situations are thought to be related to the...
Invariance of the measurement model (MM) between subjects and within subjects over time is a prerequ...
Invariance of the measurement model (MM) between subjects and within subjects over time is a prerequ...
Longitudinal surveys provide a key source of information for analysing dynamic phenomena. Typical e...
Drawing inferences about dynamics of psychological constructs from intensive longitudinal data requi...
Longitudinal and repeated measurement data commonly arise in many scientific researchareas. Traditio...
In psychological research, statistical models of latent state-trait (LST) theory are popular for the...
esearchers use finite mixture models (FMMs) to analyze linked survey and administrative data on labo...
Cross-sectional latent class regression models, also known as switching regressions or hidden Markov...