Validating effectiveness of subgroup identification for longitudinal data.
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DOI: 10.1002/sim.7500
Abstract: In clinical trials and biomedical studies, treatments are compared to determine which one is effective against illness; however, individuals can react to the same treatment very differently. We propose a complete process for longitudinal data… read more here.
Keywords: longitudinal data; validating effectiveness; individual treatment; treatment ... See more keywords
Multivariate longitudinal data analysis with censored and intermittent missing responses.
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DOI: 10.1002/sim.7692
Abstract: The multivariate linear mixed model (MLMM) has emerged as an important analytical tool for longitudinal data with multiple outcomes. However, the analysis of multivariate longitudinal data could be complicated by the presence of censored measurements… read more here.
Keywords: longitudinal data; censored intermittent; analysis; intermittent missing ... See more keywords
Proportional likelihood ratio mixed model for discrete longitudinal data.
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DOI: 10.1002/sim.8902
Abstract: Rathouz and Gao [2] and Luo and Tsai [3] proposed valuable extensions to the generalized linear model for modeling a nonlinear monotonic relationship between the mean response and a set of covariates. In their extensions… read more here.
Keywords: longitudinal data; likelihood; likelihood ratio; model ... See more keywords
Multiply robust subgroup analysis based on a single-index threshold linear marginal model for longitudinal data with dropouts.
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DOI: 10.1002/sim.9386
Abstract: Identifying subpopulations that may be sensitive to the specific treatment is an important step toward precision medicine. On the other hand, longitudinal data with dropouts is common in medical research, and subgroup analysis for this… read more here.
Keywords: data dropouts; medicine; treatment; model ... See more keywords
Variable selection in semiparametric regression models for longitudinal data with informative observation times.
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DOI: 10.1002/sim.9417
Abstract: A common issue in longitudinal studies is that subjects' visits are irregular and may depend on observed outcome values which is known as longitudinal data with informative observation times (follow-up). Semiparametric regression modeling for this… read more here.
Keywords: regression; informative observation; longitudinal data; semiparametric regression ... See more keywords
Multivariate single index modeling of longitudinal data with multiple responses.
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DOI: 10.1002/sim.9763
Abstract: In medical studies, composite indices and/or scores are routinely used for predicting medical conditions of patients. These indices are usually developed from observed data of certain disease risk factors, and it has been demonstrated in… read more here.
Keywords: longitudinal data; index; multiple responses; data multiple ... See more keywords
Robust and efficient estimating equations for longitudinal data partial linear models and its applications
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DOI: 10.1007/s00362-020-01181-5
Abstract: Composite quantile regression (CQR) is a good alternative of the mean regression, because of its robustness and efficiency. In longitudinal data analysis, correlation structure plays an important role in improving efficiency. However, how to specify… read more here.
Keywords: longitudinal data; partial linear; robust efficient; estimating equations ... See more keywords
Mixture of multivariate t nonlinear mixed models for multiple longitudinal data with heterogeneity and missing values
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DOI: 10.1007/s11749-018-0612-4
Abstract: The multivariate t nonlinear mixed-effects model (MtNLMM) has been shown to be effective for analyzing multi-outcome longitudinal data following nonlinear growth patterns with fat-tailed noises or potential outliers. This paper considers the problem of clustering… read more here.
Keywords: longitudinal data; missing values; mixture multivariate; multivariate nonlinear ... See more keywords
Variable selection for generalized partially linear models with longitudinal data
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DOI: 10.1007/s12065-020-00521-6
Abstract: Variables selection and parameter estimation are of great significance in all regression analysis. A variety of approaches have been proposed to tackle this problem. Among those, the penalty-based shrinkage approach has been most popular for… read more here.
Keywords: longitudinal data; selection; selection generalized; variable selection ... See more keywords
Empirical likelihood method for longitudinal data generated from unequally-spaced Lèvy processes
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DOI: 10.1007/s42952-019-00047-3
Abstract: By introducing the notion of “empirical likelihood function of observing sums”, unequally-spaced time series data and longitudinal data generated from Levy processes can be analyzed. Characteristic function is further incorporated to handle the situations where… read more here.
Keywords: longitudinal data; method; unequally spaced; function ... See more keywords
Within- and between-person and group variance in behavior and beliefs in cross-cultural longitudinal data.
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DOI: 10.1016/j.adolescence.2017.06.002
Abstract: This study grapples with what it means to be part of a cultural group, from a statistical modeling perspective. The method we present compares within- and between-cultural group variability, in behaviors in families. We demonstrate… read more here.
Keywords: longitudinal data; cross cultural; group; person ... See more keywords