Modeling multiple risks during infancy to predict quality of the caregiving environment: Contributions of a person-centered approach

Abstract

The primary goal of this study was to compare several variable-centered and person-centered methods for modeling multiple risk factors during infancy to predict the quality of caregiving environments at six months of age. Nine risk factors related to family demographics and maternal psychosocial risk, assessed when children were two months old, were explored in the understudied population of children born in low-income, non-urban communities in Pennsylvania and North Carolina (N = 1047). These risk factors were 1) single (unpartnered) parent status, 2) marital status, 3) mother’s age at first child birth, 4) maternal education, 5) maternal reading ability, 6) poverty status, 7) residential crowding, 8) prenatal smoking exposure, and 9) maternal depression. We compared conclusions drawn using a bivariate approach, multiple regression analysis, the cumulative risk index, and latent class analysis (LCA). The risk classes derived using LCA provided a more intuitive summary of how multiple risks were organized within individuals as compared to the other methods. The five risk classes were: married low-risk; married low-income; cohabiting multiproblem; single low-income; and single low-income/education. The LCA findings illustrated how the association between particular family configurations and the infants’ caregiving environment quality varied across race and site. Discussion focuses on the value of person-centered models of analysis to understand complexities of prediction of multiple risk factors.

Productive procrastination: academic procrastination style predicts academic and alcohol outcomes

“…Given the significant correlations found between all four procrastination strategies above, we proceeded with person-centered analyses, which are capable of modeling co-occurring procrastination strategies and are a more statistically appropriate choice when predictor variables are correlated (Lanza, Rhoades, Greenberg, Cox, & Family Life Project Key Investigators, 2011; Park, Lee, Sun, Klemmack, Roff, & Koenig, 2013). Using a person-centered approach, we attempted to identify 1) which procrastination strategies co-occur and 2) whether certain combinations of co-occurring strategies (which we call procrastination “styles”) are associated with academic and alcohol outcomes.…”

Patterns of Early Reading and Social Skills Associated With Academic Success in Elementary School

“…Based on increasing interest in more holistic, subgroup-based approaches to understanding child development (Bellanti & Bierman, 2000;Lanza et al, 2011;, the first aim of the present study was to identify subgroups of children displaying patterns of two theoretically and practically significant domains-reading and social skills-during kindergarten. By categorizing children based on 1 SD cutpoints, we identified known subgroups in a nationally representative sample that represented combinations of below-average, average, and aboveaverage performance on reading and social skills.…”

Effect Size, Statistical Power, and Sample Size Requirements for the Bootstrap Likelihood Ratio Test in Latent Class Analysis

“…This technique, a form of finite mixture modeling (see McLachlan & Peel, 2000), can be used to identify underlying subgroups in a population. LCA can identify subgroups characterized by the intersection of particular behaviors, risk factors, or symptoms (e.g., Bucholz, Hesselbrock, Heath, Kramer, & Schuckit, 2000; Keel et al, 2004; Lanza et al, 2011; Rindskopf & Rindskopf, 1986; Uebersax & Grove, 1990), such as symptoms of psychosis (e.g., Shevlin, Murphy, Dorahy, & Adamson, 2007), nicotine withdrawal symptoms (e.g., Xian et al, 2005), or adolescent risk behaviors (e.g., Collins & Lanza, 2010). Despite the benefits of the measurement model provided by LCA, several difficulties in applications of this method remain.…”