Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…

Building on the work of Bollen (2007) and Bollen & Bauldry (2011), Bainter and Bollen (this issue) clarifies several points of confusion in the literature regarding causal indicator models. This author would certainly agree that the effect indicator (reflective) measurement model is inappropriate for some indicators (such as the social…

This observational, cross-sectional study examined students' retrospective recall of emotional distress when studying sensitive topics in psychology, and whether hardiness had a mediated pathway to emotional distress through a mental health condition (MHC). Psychology undergraduates (155 women, 34 men) from South Australian universities completed…

There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…

This study investigated how affective factors like attitude and motivation contribute to science achievement in PISA 2006 using linear structural modeling. The data set of PISA 2006 collected from 4942 fifteen-year-old Turkish students (2290 females, 2652 males) was used for the statistical analyses. A total of 42 selected items on a four point…

Researchers have become increasingly interested in programs' main and interaction effects of two variables (A and B, e.g., two treatment variables or one treatment variable and one moderator) on outcomes. A challenge for estimating main and interaction effects is to eliminate selection bias across A-by-B groups. I introduce Rubin's causal model to…

The aim of this study is to examine teachers' motivation as a great mediator for teachers' readiness in applying ICT in their teaching and learning. Apart from that, this study was carried out to differentiate the influence of exsogenous variables from the endogenous variables based on the academic fields (pure science and social science). This is…

Constructing a computational model of conceptual change for a computer-based scientific inquiry learning environment is difficult due to two challenges: (i) externalizing the variables of conceptual change and its related variables is difficult. In addition, defining the causal dependencies among the variables is also not trivial. Such difficulty…

In a time of growth in secondary education online programs, there have been few studies directed at understanding secondary online programs and the students they serve. That is particularly true for large, inner-city public school districts with a diverse student body. This is a mixed methods case study which identified that students' primary…

Using student achievement data from British Columbia, Canada, this study is an exploration of the differences that lie within the private school sector using hierarchical linear modeling to analyze the data. The analysis showed that when controlling for language, parents' level of educational attainment, and prior achievement, the private school…

Most reading time studies using naturalistic texts yield data sets characterized by a multilevel structure: Sentences (sentence level) are nested within persons (person level). In contrast to analysis of variance and multiple regression techniques, hierarchical linear models take the multilevel structure of reading time data into account. They…

Purpose: This study simultaneously examined predictors of phonological awareness within the framework of 2 theories: the phonological distinctness hypothesis and the lexical restructuring model. Additionally, age as a moderator of the relations between predictor variables and phonological awareness was examined. Method: This cross-sectional…

Nonlinear relationships and latent variable assumptions can lead to serious specification errors in structural models. A quadratic relationship, described by a linear structural model with a latent variable, is shown to have less predictive validity than a simple manifest variable regression model. Advocates the use of simpler preliminary…

The data discussed in this paper are from the television game show "Friend or Foe", and can be used to examine whether age, gender, race, and the amount of prize money affect contestants' strategies. The data are suitable for a variety of statistical analyses, such as descriptive statistics, testing for differences in means or proportions, and…

Structural equation models merge multiple regression, path analysis, and factor analysis techniques into a single data analytic framework. Measurement models are developed to define latent variables, and structural equations are then established among the latent variables. Explains the development of these models. (KS)