Craig K Enders

Dados Biográficos

ID3482573
NOMECraig K Enders
PRENOMESCraig K
SOBRENOMEEnders
ASSINATURAENDERS C K
AFILIAÇÕESArizona State University
ORCID0000-0002-7048-8369
VERIFICADOSim
TOTAL DE OBRAS39
TOTAL DE CITAÇÕES49
TOTAL COMO AUTOR39
TOTAL COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO2001
ANO MAIS RECENTE DE PUBLICAÇÃO2026
ÍNDICE H4

  • Demystifying Posterior Distributions

    Han Du, Fang Liu et al.ARTICLEMultivariate Behavioral Research2026

    Bayesian statistics have gained significant traction across various fields over the past few decades. Bayesian statistics textbooks often provide both code and the analytical forms of parameters for simple models. However, they often omit the process of deriving posterior distributions or limit it to basic univariate examples focused on the mean and variance. Additionally, these resources frequently assume a strong background in linear algebra an…

  • To Disaggregate or Not to Disaggregate

    Open AccessRemus Mitchell, Craig K Enders et al.ARTICLEMultivariate Behavioral Research2026

    It is routinely recommended that level-1 variables in multilevel models be disaggregated when they are of substantive importance. Yet, the consensus on the disaggregation of level-1 covariates is more mixed. Disaggregation clarifies interpretation and reduces bias in the covariate, though some methodologists argue that it is unnecessary when the covariate itself is not of substantive interest. Our study builds off recent work to explore the trade…

  • The Role of Prior Knowledge in Effects of Embodied Pedagogies on Learning

    Icy Zhang, Alice Xu et al.ARTICLEJournal of Educational Psychology2025

    Background: Embodied learning pedagogies are increasingly popular, but our understanding of how embodied pedagogies enhance learning of complex concepts in higher education over longer periods of time remains nascent, particularly how learners’ prior knowledge might interact with different types of embodied pedagogies. We propose the Performing First Hypothesis as an organizing framework, which posits that learners with lower prior knowledge, bec…

  • An Investigation of Factored Regression Missing Data Methods for Multilevel Models with Cross-Level Interactions

    S Natasha Beretvas, Brian T Keller et al.ARTICLEMultivariate Behavioral Research2023

    A growing body of literature has focused on missing data methods that factorize the joint distribution into a part representing the analysis model of interest and a part representing the distributions of the incomplete predictors. Relatively little is known about the utility of this method for multilevel models with interactive effects. This study presents a series of Monte Carlo computer simulations that investigates Bayesian and multiple imputa…

  • A Bayesian Latent Variable Selection Model for Nonignorable Missingness

    Han Du, Craig K Enders et al.ARTICLEMultivariate Behavioral Research2022

    Missing data are exceedingly common across a variety of disciplines, such as educational, social, and behavioral science areas. Missing not at random (MNAR) mechanism where missingness is related to unobserved data is widespread in real data and has detrimental consequence. However, the existing MNAR-based methods have potential problems such as leaving the data incomplete and failing to accommodate incomplete covariates with interactions, non-li…

  • Is Item Imputation Always Better? An Investigation of Wave-Missing Data in Growth Models

    Juan Diego Vera, Craig K EndersARTICLEStructural Equation Modeling: A…2021

    Questionnaire data present challenges, as a missing item of a multi-item scale would lead to a total missing scale. A researcher applying multiple imputation to an incomplete multi-item questionnaire can impute the incomplete items prior to computing scale scores or impute the scale score entirely. Methodologist have favored item-level imputation because it greatly enhances precision in comparison to scale-level imputation; however, this benefit …

  • A Comparison of Multilevel Imputation Schemes for Random Coefficient Models

    Craig K Enders, Timothy Hayes et al.ARTICLEMultivariate Behavioral Research2018

    Literature addressing missing data handling for random coefficient models is particularly scant, and the few studies to date have focused on the fully conditional specification framework and "reverse random coefficient" imputation. Although it has not received much attention in the literature, a joint modeling strategy that uses random within-cluster covariance matrices to preserve cluster-specific associations is a promising alternative for rand…

  • The Effects of Middle School Weight Climate on Youth With Higher Body Weight

    Open AccessJaana Juvonen, Leah M Lessard et al.ARTICLEJournal of Research on Adolescence2018Referências: 8

    This study examines whether social-emotional difficulties associated with higher body weight vary across schools as a function of the school's weight climate. Weight climate, characterized by weight-policing, was assessed indirectly by examining how strongly self-reported weight predicts victim reputation within 26 ethnically diverse middle schools. Social-emotional indicators included self-reported loneliness, school belonging, and self-esteem. …

  • Gender Norm Salience Across Middle Schools

    Open AccessDanielle Sayre Smith, Hannah L Schacter et al.ARTICLEJournal of Youth and Adolescence2018Citada por: 4Referências: 41

  • Multiple imputation as a flexible tool for missing data handling in clinical research

    Open AccessCraig K EndersARTICLEBehaviour Research and Therapy2017

  • Centering Predictor Variables in Three-Level Contextual Models

    Ahnalee Brincks, Ahnalee M Brincks et al.ARTICLEMultivariate Behavioral Research2017

    Hierarchical data are becoming increasingly complex, often involving more than two levels. Centering decisions in multilevel models are closely tied to substantive hypotheses and require researchers to be clear and cautious about their choices. This study investigated the implications of group mean centering (i.e., centering within context; CWC) and grand mean centering (CGM) of predictor variables in three-level contextual models. The goals were…

  • Evaluation of Multi-parameter Test Statistics for Multiple Imputation

    Yu Liu, Craig K EndersARTICLEMultivariate Behavioral Research2017

    In Ordinary Least Square regression, researchers often are interested in knowing whether a set of parameters is different from zero. With complete data, this could be achieved using the gain in prediction test, hierarchical multiple regression, or an omnibus F test. However, in substantive research scenarios, missing data often exist. In the context of multiple imputation, one of the current state-of-art missing data strategies, there are several…

  • Addressing Item-Level Missing Data

    Gina L Mazza, Craig K Enders et al.ARTICLEMultivariate Behavioral Research2015

    Often when participants have missing scores on one or more of the items comprising a scale, researchers compute prorated scale scores by averaging the available items. Methodologists have cautioned that proration may make strict assumptions about the mean and covariance structures of the items comprising the scale (Schafer & Graham, 2002 Schafer, J.L., & Graham, J.W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7…

  • A Comparison of Imputation Strategies for Ordinal Missing Data on Likert Scale Variables

    Wei Wu, Fan Jia et al.ARTICLEMultivariate Behavioral Research2015

    This article compares a variety of imputation strategies for ordinal missing data on Likert scale variables (number of categories = 2, 3, 5, or 7) in recovering reliability coefficients, mean scale scores, and regression coefficients of predicting one scale score from another. The examined strategies include imputing using normal data models with naïve rounding/without rounding, using latent variable models, and using categorical data models such…

  • Implementation and Evaluation of a Multidimensional Nutrition and Physical Activity Initiative Funded by a Community Health Foundation

    Open AccessJames Pann, Angela Yehl et al.ARTICLEThe Foundation Review2014

    Poor diet and physical inactivity have been estimated to account for nearly 400,000 deaths a year in the U.S. and are contributing factors to obesity. Nearly one-third of children and two-thirds of adults are overweight or obese. Therefore, in early 2007 Health Foundation of South Florida (HFSF) embarked on a five-year responsive grantmaking initiative, Healthy Eating Active Communities. · The initiative's aim was to improve healthy eating habits…

  • Value-Expressive Volunteer Motivation and Volunteering by Older Adults

    Morris A Okun, Holly P O’Rourke et al.ARTICLEThe Journals of Gerontology…2014Citada por: 6Referências: 5

    Religiosity may provide the way, and value-expressive volunteer motivation the will, to volunteer. The implications of our findings for the forecasted shortage of older volunteers are discussed

  • Dealing With Missing Data in Developmental Research

    Open AccessCraig K EndersARTICLEChild Development Perspectives2013

    Approaches to handling missing data have improved dramatically in recent years and researchers can now choose from a variety of sophisticated analysis options. The methodological literature favors maximum likelihood and multiple imputation because these approaches offer substantial improvements over older approaches, including a strong theoretical foundation, less restrictive assumptions, and the potential for bias reduction and greater power. Th…

  • A Bayesian Approach for Estimating Mediation Effects With Missing Data

    Craig K Enders, Amanda J Fairchild et al.ARTICLEMultivariate Behavioral Research2013

    Methodologists have developed mediation analysis techniques for a broad range of substantive applications, yet methods for estimating mediating mechanisms with missing data have been understudied. This study outlined a general Bayesian missing data handling approach that can accommodate mediation analyses with any number of manifest variables. Computer simulation studies showed that the Bayesian approach produced frequentist coverage rates and po…

  • A Comparison of Item-Level and Scale-Level Multiple Imputation for Questionnaire Batteries

    Amanda C Gottschall, Stephen G West et al.ARTICLEMultivariate Behavioral Research2012

    Behavioral science researchers routinely use scale scores that sum or average a set of questionnaire items to address their substantive questions. A researcher applying multiple imputation to incomplete questionnaire data can either impute the incomplete items prior to computing scale scores or impute the scale scores directly from other scale scores. This study used a Monte Carlo simulation to assess the impact of imputation method on the bias a…

  • Analyzing longitudinal data with missing values.

    Craig K EndersARTICLERehabilitation Psychology2011

    Missing data methodology has improved dramatically in recent years, and popular computer programs now offer a variety of sophisticated options. Despite the widespread availability of theoretically justified methods, researchers in many disciplines still rely on subpar strategies that either eliminate incomplete cases or impute the missing scores with a single set of replacement values. This article provides readers with a nontechnical overview of…

  • An introduction to modern missing data analyses

    Open AccessAmanda N Baraldi, Craig K EndersARTICLEJournal of School Psychology2010

  • Interpersonal Relationships and the Development of Behavior Problems in Adolescents in Urban Schools

    Open AccessMarjorie Montague, Wendy Cavendish et al.ARTICLEJournal of Youth and Adolescence2010Citada por: 4Referências: 36

  • Emotional and cardiovascular sensitization to daily stress following childhood parental loss

    Linda J Luecken, Amy Kraft et al.ARTICLEDevelopmental Psychology2009Citada por: 2Referências: 3

    Adverse childhood events can influence the development of emotional and physiological self-regulatory abilities, with significant consequences for vulnerability to psychological and physical illness. This study evaluated stress sensitization and inoculation models of the impact of early parental death on stress exposure and reactivity in late adolescence/young adulthood. Ambulatory blood pressure (BP) and diary reports of minor stress were collec…

  • Does devoutness delay death? Psychological investment in religion and its association with longevity in the Terman sample

    Michael E Mccullough, Howard S Friedman et al.ARTICLEJournal of Personality and Social…2009Citada por: 8Referências: 4

    Religious people tend to live slightly longer lives (M. E. McCullough, W. T. Hoyt, D. B. Larson, H. G. Koenig, & C. E. Thoresen, 2000). On the basis of the principle of social investment (J. Lodi-Smith & B. W. Roberts, 2007), the authors sought to clarify this phenomenon with a study of religion and longevity that (a) incorporated measures of psychological religious commitment; (b) considered religious change over the life course; and (c) examine…

  • Centering predictor variables in cross-sectional multilevel models

    Craig K Enders, Davood TofighiARTICLEPsychological Methods2007

    Appropriately centering Level 1 predictors is vital to the interpretation of intercept and slope parameters in multilevel models (MLMs). The issue of centering has been discussed in the literature, but it is still widely misunderstood. The purpose of this article is to provide a detailed overview of grand mean centering and group mean centering in the context of 2-level MLMs. The authors begin with a basic overview of centering and explore the di…