Using R to conduct univariate meta-analyses is becoming common for publication. However, R can also conduct multivariate meta-analysis (MMA). However, newcomers to both R and MMA may find using R to conduct MMA daunting. Given that, R may not be easy for those unfamiliar with coding. Likewise, MMA is a topic of advanced statistics. Thus, it may be…

In this paper, we provide an introduction to the factored regression framework. This modeling framework applies the rules of probability to break up or "factor" a complex joint distribution into a product of conditional regression models. Using this framework, we can easily specify the complex multivariate models that missing data…

Background: Counts are familiar outcomes in education research settings, including those involving tests of interventions. Clustered data commonly occur in education research studies, given that data are often collected from students within classrooms or schools. There is a wide array of distributions and models that can be used for clustered…

Multilevel modeling (MLM) is a statistical technique for analyzing clustered data. Despite its long history, the technique and accompanying computer programs are rapidly evolving. Given the complexity of multilevel models, it is crucial for researchers to provide complete and transparent descriptions of the data, statistical analyses, and results.…

Recent work on measuring growth with categorical outcome variables has combined the item response theory (IRT) measurement model with the latent growth curve model and extended the assessment of growth to multidimensional IRT models and higher order IRT models. However, there is a lack of synthetic studies that clearly evaluate the strength and…

Recent work on measuring growth with categorical outcome variables has combined the item response theory (IRT) measurement model with the latent growth curve (LGC) model (e.g., McArdle, 1988) and extended the assessment of growth to multidimensional IRT models (e.g., Hsieh, von Eye, & Maier, 2010; Huang, 2013) and higher-order IRT models…

In today's age of information, the use of data is very powerful in making informed decisions. Data analytics is a field that is interested in identifying and interpreting trends and patterns within big data to make data-driven decisions. We focus on informal statistical inference and data modeling as a means of developing students' data analytics…

Cluster analysis is a set of statistical methods for discovering new group/class structure when exploring data sets. This article reviews the following popular libraries/commands in the R software language for applying different types of cluster analysis: from the stats library, the kmeans, and hclust functions; the mclust library; the poLCA…

This study aims to use group technology to classify students at the classroom level into clusters according to their learning style preferences. Group technology is used, due to the realization that many problems are similar, and that by grouping similar problems, single solutions can be found for a set of problems. The Felder and Silverman style,…

Nonnormality of univariate data has been extensively examined previously (Blanca et al., 2013; Micceri, 1989). However, less is known of the potential nonnormality of multivariate data although multivariate analysis is commonly used in psychological and educational research. Using univariate and multivariate skewness and kurtosis as measures of…

This study explores the types of learning profiles that evolve from student use of video annotation software for reflective learning. The data traces from student use of the software were analysed across four undergraduate courses with differing instructional conditions. That is, the use of graded or non-graded self-reflective annotations. Using…

Meta-analysis is a statistical technique that allows an analyst to synthesize effect sizes from multiple primary studies. To estimate meta-analysis models, the open-source statistical environment R is quickly becoming a popular choice. The meta-analytic community has contributed to this growth by developing numerous packages specific to…

The aim of the study is to compare TIMSS 2011 proficiency levels with the proficiency levels defined by the researchers using cluster analysis for Turkey, Korean, Norway, and Morocco in 4th and 8 th grades in the fields of science and mathematics. Therefore, it is tried to be reached that these cut-off scores for each country can serve the…

User interface (UI) design patterns for mobile applications provide a solution to design problems and can improve the usage experience for users. However, there is a lack of research categorizing the uses of design patterns according to users' hand dominance in a learning-based mobile UI. We classified the main design patterns for mobile…

The efforts to improve the quantitative reasoning (quantitative literacy) skills of college students in the United States have been gaining momentum in recent years. At the same time, the blended learning approach to course delivery has gained in popularity, promising better learning with flexible modalities and pace. This paper presents the…