When estimating causal effects, unmeasured confounding and model misspecification are both potential sources of bias. We propose a method to simultaneously address both issues in the form of a semi-parametric sensitivity analysis. In particular, our approach incorporates Bayesian Additive Regression Trees into a two-parameter sensitivity analysis…

This study examined global competence of Chinese international students sojourning in a non-Anglophone European country as a mediator between foreign language proficiency (i.e., English and local language) and social and academic adaptation, and social connectedness in international community. A sample of 206 Chinese students in Belgium responded…

Making causal inferences from a quasi-experiment is difficult. Sensitivity analysis approaches to address hidden selection bias thus have gained popularity. This study serves as an introduction to a simple but practical form of sensitivity analysis using Monte Carlo simulation procedures. We examine estimated treatment effects for a school-based…

Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of…

This article presents a simple approach to making quick sample size estimates for basic hypothesis tests. Although there are many sources available for estimating sample sizes, methods are not often integrated across statistical tests, levels of measurement of variables, or effect sizes. A few parameters are required to estimate sample sizes and…

When fitting hierarchical regression models, maximum likelihood (ML) estimation has computational (and, for some users, philosophical) advantages compared to full Bayesian inference, but when the number of groups is small, estimates of the covariance matrix (S) of group-level varying coefficients are often degenerate. One can do better, even from…

When fitting hierarchical regression models, maximum likelihood (ML) estimation has computational (and, for some users, philosophical) advantages compared to full Bayesian inference, but when the number of groups is small, estimates of the covariance matrix [sigma] of group-level varying coefficients are often degenerate. One can do better, even…

This study evaluated three types of bias--total, measurement, and selection bias (SB)--in three sequential mixed-mode designs of the Dutch Crime Victimization Survey: telephone, mail, and web, where nonrespondents were followed up face-to-face (F2F). In the absence of true scores, all biases were estimated as mode effects against two different…

This ex-post-facto quasi-experimental research design was conducted by selecting a convenient sample of approximately 2,000 3rd grade ELLs who took the regular reading and math English STAAR test during the 2014-15 school year in an urban southern Texas school district. This study was conducted using a quantitative research method of data…

The purpose of this study was to investigate levels of engagement as measured by the CCSSE among Latino students attending Washington National Community College (WNCC), a community college on the east coast of the United States. For this longitudinal study, the researcher compared CCSSE data collected in 2008, 2010, 2012 and 2014 from Latino…

Purpose: Sentence processing can be affected following a traumatic brain injury (TBI) due to linguistic or cognitive deficits. Language-related event-related potentials (ERPs), particularly the P600, have not been described in individuals with TBI history. Method: Four young adults with a history of closed head injury participated. Two had severe…

Multiple imputation (MI), a two-stage process whereby missing data are imputed multiple times and the resulting estimates of the parameter(s) of interest are combined across the completed datasets, is becoming increasingly popular for handling missing data. However, MI can result in biased inference if not carried out appropriately or if the…

Online purposive samples have unknown biases and may not strictly be used to make inferences about wider populations, yet such inferences continue to occur. We compared the demographic and drug use characteristics of Australian ecstasy users from a probability (National Drug Strategy Household Survey, n = 726) and purposive sample (online survey…

We extend a unified and easy-to-use approach to measurement error and missing data. In our companion article, Blackwell, Honaker, and King give an intuitive overview of the new technique, along with practical suggestions and empirical applications. Here, we offer more precise technical details, more sophisticated measurement error model…

Because of the limited research on the perceptions of nursing faculty on horizontal violence, this convergent mixed method study investigated the phenomenon of bullying behaviors among nursing faculty and the faculty's intent to stay in academe following exposure to bullying. 300 nursing faculty members of the Nursing Educator Discussion list…