Factor mixture modeling (FMM) incorporates both continuous latent variables and
categorical latent variables in a single analytic model clustering items and observations …

This paper provides theoretical and methodological underpinnings for optimal investment
decisions in the oil & gas industry. In doing so, this paper investigates how to transition from …

Multilevel factor mixture modeling (FMM) is a hybrid of multilevel confirmatory factor analysis
(CFA) and multilevel latent class analysis (LCA). It allows researchers to examine population …

Farmer's credit is significant to growing the farmer's revenue and the progression of the rural
economy. Several scholars have focused on the impact of social capital on the farmers' …

Purpose Carefully selecting the sample size for a research study is one of the most
fundamental ways to utilize resources in an ethical manner, maximize impact and …

Factor mixture modeling (FMM) is generally complex with both unobserved categorical and
unobserved continuous variables. We explore the potential of item parceling to reduce the …

Factor mixture modeling (FMM) has been increasingly used in behavioral and social
sciences to examine unobserved population heterogeneity. Covariates (eg, gender, race) …

This paper reviews the family of techniques found in structural equation modeling (SEM).
Specifically, the review covers historical, mathematical, and graphical representations of …

Opioid use disorder (OUD) is a critical public health concern. Medication for opioid use
disorder (MOUD), including buprenorphine, is essential for treating OUD. Patients with OUD …

On the heels of the COVID-19 pandemic, discussions within healthcare institutions and the
public at large concerning the inefficiencies pertaining to health management in the United …