Many applications of biomedical science involve unobservable constructs, from measurement of health states to severity of complex diseases. In this dissertation I utilize joint latent variable methods to combine item selection and validation to identify significant items in a symptom scale and determine how these symptoms relate to gold standard diagnostic measures. Joint latent variable models eliminate bias inherent in traditional two-stage methods and provide a global test of the association between the underlying construct and a clinical measure. In Chapter 1, a review of latent variable methods for multivariate outcomes is provided. Chapter 2 proposes a Multiple Indicator Multiple Cause (MIMIC) model to perform item reduction and ...
Objective: Patient-reported outcomes (PROs) are measures collected from a patient to determine how h...
Drawing inferences about dynamics of psychological constructs from intensive longitudinal data requi...
Histologic tumor grade is a strong predictor of risk of recurrence in breast cancer. Nevertheless, t...
Many applications of biomedical science involve unobservable constructs, from measurement of health ...
Many applications of biomedical science involve unobservable constructs, from measurement of health ...
In chronic diseases, research often centers on discovering a latent trait trajectory that manifests ...
Background Modeling latent variables such as physical disability is challenging since its measuremen...
In health cohort studies, repeated measures of markers are often used to describe the natural histor...
Latent Variable Models (LVM) are widely used in social, behavioural, and educational sciences to unc...
textSocial science researchers are increasingly using multi-group confirmatory factor analysis (MG-C...
Observational health data are a rich resource that present modelling challenges due to data complexi...
In the thesis, we assess the use of latent vari able models applied to diagnostic accuracy and dis e...
In clinical research, interest sometimes lies in analysing variables which are not measured directly...
This paper investigates how the major outcome of a confirmatory factor investigation is preserved wh...
Latent variable models are widely used in social sciences in which interest is centred on entities s...
Objective: Patient-reported outcomes (PROs) are measures collected from a patient to determine how h...
Drawing inferences about dynamics of psychological constructs from intensive longitudinal data requi...
Histologic tumor grade is a strong predictor of risk of recurrence in breast cancer. Nevertheless, t...
Many applications of biomedical science involve unobservable constructs, from measurement of health ...
Many applications of biomedical science involve unobservable constructs, from measurement of health ...
In chronic diseases, research often centers on discovering a latent trait trajectory that manifests ...
Background Modeling latent variables such as physical disability is challenging since its measuremen...
In health cohort studies, repeated measures of markers are often used to describe the natural histor...
Latent Variable Models (LVM) are widely used in social, behavioural, and educational sciences to unc...
textSocial science researchers are increasingly using multi-group confirmatory factor analysis (MG-C...
Observational health data are a rich resource that present modelling challenges due to data complexi...
In the thesis, we assess the use of latent vari able models applied to diagnostic accuracy and dis e...
In clinical research, interest sometimes lies in analysing variables which are not measured directly...
This paper investigates how the major outcome of a confirmatory factor investigation is preserved wh...
Latent variable models are widely used in social sciences in which interest is centred on entities s...
Objective: Patient-reported outcomes (PROs) are measures collected from a patient to determine how h...
Drawing inferences about dynamics of psychological constructs from intensive longitudinal data requi...
Histologic tumor grade is a strong predictor of risk of recurrence in breast cancer. Nevertheless, t...