Kimberly Fine

• Doctor of Philosophy
• PostDoc Position at Indiana University Bloomington

BACKGROUND AND OBJECTIVES Opioids are involved in an increasing proportion of suicide deaths. This study examined the association between opioid analgesic prescription initiation and suicidal behavior among young people. METHODS We analyzed Swedish population-register data on 1 895 984 individuals ages 9 to 29 years without prior recorded opioid p...

The literature on latent change score models does not discuss the importance of using a precise time metric when structuring the data. This study examined the influence of time metric precision on model estimation, model interpretation, and parameter estimate accuracy in bivariate LCS (BLCS) models through simulation. Longitudinal data were generat...

Importance Concerns about adverse outcomes associated with opioid analgesic prescription have led to major guideline and policy changes. Substantial uncertainty remains, however, regarding the association between opioid prescription initiation and increased risk of subsequent substance-related morbidity. Objective To examine the association of opi...

Modeling within-person change over time and between-person differences in change over time is a primary goal in prevention science. When modeling change in an observed score over time with multilevel or structural equation modeling approaches, each observed score counts toward the estimation of model parameters equally. However, observed scores can...

Previous research has shown functional mixed-effects models and traditional mixed-effects models perform similarly when recovering individual trajectories when data were generated following a parametric structure. We extend this previous work and compare nonlinear mixed-effects (NMEM) and functional mixed-effects models’(FMEM) ability to recover un...

College students and their friends become more similar in weight status over time. However, it is unclear which mediators explain this relationship. Using validated survey measures of diet, physical activity, alcohol intake, sleep behaviors, mental health, and food security status, we take a comprehensive look at possible factors associated with ex...

Objectives: To examine the relationship between acculturation and diet quality of preschoolers in the Phoenix area. There is little research on how the dietary intake of preschoolers outside of the home is impacted by parental acculturation in food secure and insecure households. Methods: This study was a cross-sectional secondary data analysis...

Multilevel modeling is a data analytic framework that is appropriate when analyzing data that are dependent due to the clustering of observations in higher-level units. Clustered data appear in a variety of disciplines, which makes multilevel modeling a necessary data analytic tool for many researchers. Longitudinal data are a special kind of clust...

Growth curve modeling is one of the main analytical approaches to study change over time. Growth curve models are commonly estimated in the linear and nonlinear mixed-effects modeling framework in which both the mean and person-specific curves are modeled parametrically with functions of time such as the linear, quadratic, and exponential. However,...

This didactic article aims to provide a gentle introduction to penalized splines as a way of estimating nonlinear growth curves in which many observations are collected over time on a single or multiple individuals. We begin by presenting piecewise linear models in which the time domain of the data is divided into consecutive phases and a separate...