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Full-Text Articles in Applied Mathematics
Multiple Baseline Interrupted Time Series: Describing Changes In New Mexico Medicaid Behavioral Health Home Patients’ Care, Jessica Reno
Multiple Baseline Interrupted Time Series: Describing Changes In New Mexico Medicaid Behavioral Health Home Patients’ Care, Jessica Reno
Mathematics & Statistics ETDs
In 2016, the CareLink New Mexico behavioral health homes program began enrolling Medicaid recipients with the goal of increasing care coordination, improving access to services, and decreasing long-term costs of care for adults with serious mental illness (SMI) and children with severe emotional disturbance (SED). To evaluate these aims, a retrospective interrupted time series study using Medicaid claims data was designed. First, a comparable subset of non-enrolled individuals was selected from the pool of Medicaid recipients with SMI or SED using propensity score matching. Then, segmented regression was applied to three outcomes: total Medicaid charges, number of outpatient behavioral health …
"A Comparison Of Variable Selection Methods Using Bootstrap Samples From Environmental Metal Mixture Data", Paul-Yvann Djamen
"A Comparison Of Variable Selection Methods Using Bootstrap Samples From Environmental Metal Mixture Data", Paul-Yvann Djamen
Mathematics & Statistics ETDs
In this thesis, I studied a newly developed variable selection method SODA, and three customarily used variable selection methods: LASSO, Elastic net, and Random forest for environmental mixture data. The motivating datasets have neuro-developmental status as responses and metal measurements and demographic variables as covariates. The challenges for variable selections include (1) many measured metal concentrations are highly correlated, (2) there are many possible ways of modeling interactions among the metals, (3) the relationships between the outcomes and explanatory variables are possibly nonlinear, (4) the signal to noise ratio in the real data may be low. To compare these methods …
An Improved Method For Spectroscopic Quality Classification, Elizabeth G. Mayer
An Improved Method For Spectroscopic Quality Classification, Elizabeth G. Mayer
Mathematics & Statistics ETDs
Spectral quality classification is a vital step in data cleaning before the
analysis of magnetic resonance spectroscopy (MRS) data can be done. This
analysis compares five methods of quality classification; three of these are
legacy methods, Maudsley et al. (2006), Zhang et al. (2018), and
Bustillo et al. (2020), and two newly created methods that used a random forests
classifier (RFC) to inform their classifications. We found that the random forest
classifier was the most accurate at predicting spectra quality (balanced
accuracy for RF of 88% vs legacy of 70%, 72%, or 72%). A
Random-Forests-Informed Filtering method (RFIFM) for quality …
Estimation Of Growth Curves By Least Square Splines, Dorothy Rybaczyk Pathak
Estimation Of Growth Curves By Least Square Splines, Dorothy Rybaczyk Pathak
Mathematics & Statistics ETDs
The primary object of this dissertation is to present some contributions to the theory of estimation of growth curves by least square splines in the presence of unknown unequal variances. The theoretical developments rest heavily on the standard least square theory and the theory of polynomial spline functions. A modification of the Aitken procedure of weighted least squares is used to estimate regression parameters. It is shown that this modification of the Aitken procedure does not unduly influence the nice least square properties of estimators so obtained; the estimators re main unbiased, consistent and asymptotically efficient.
The techniques developed in …