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Smith, Kendal N.; Lamb, Kristen N.; Henson, Robin K. – Gifted Child Quarterly, 2020
Multivariate analysis of variance (MANOVA) is a statistical method used to examine group differences on multiple outcomes. This article reports results of a review of MANOVA in gifted education journals between 2011 and 2017 (N = 56). Findings suggest a number of conceptual and procedural misunderstandings about the nature of MANOVA and its…
Descriptors: Multivariate Analysis, Academically Gifted, Gifted Education, Educational Research
Nimon, Kim; Henson, Robin K. – Journal of Experimental Education, 2015
The authors empirically examined whether the validity of a residualized dependent variable after covariance adjustment is comparable to that of the original variable of interest. When variance of a dependent variable is removed as a result of one or more covariates, the residual variance may not reflect the same meaning. Using the pretest-posttest…
Descriptors: Statistical Analysis, Construct Validity, Pretesting, Pretests Posttests
Lane, Forrest C.; Henson, Robin K. – Online Submission, 2010
Education research rarely lends itself to large scale experimental research and true randomization, leaving the researcher to quasi-experimental designs. The problem with quasi-experimental research is that underlying factors may impact group selection and lead to potentially biased results. One way to minimize the impact of non-randomization is…
Descriptors: Quasiexperimental Design, Research Methodology, Educational Research, Scores
Henson, Robin K. – 2002
In General Linear Model (GLM) analyses, it is important to interpret structure coefficients, along with standardized weights, when evaluating variable contribution to observed effects. Although often used in canonical correlation analysis, structure coefficients are less frequently used in multiple regression and several other multivariate…
Descriptors: Heuristics, Multivariate Analysis
Odom, Leslie R.; Henson, Robin K. – 2002
Prior to conducting a statistical analysis, sufficient data screening methods should be used for all research variables to identify miscoded, missing, or otherwise messy data. The primary purpose of these exercises was to demonstrate the role of data screening techniques and their potential to improve the performance of statistical methods. A…
Descriptors: Data Analysis, Data Collection, Heuristics, Regression (Statistics)
Henson, Robin K. – 1999
This paper illustrates how canonical correlation analysis can be employed to implement all the parametric tests that canonical methods subsume as special cases. The point is heuristic: all analyses are correlational, all apply weights to measured variables to create synthetic variables, and all yield effect sizes analogous to "r"…
Descriptors: Correlation, Effect Size, Heuristics, Multivariate Analysis
Henson, Robin K. – 1998
This paper explains how analysis of covariance (ANCOVA) and related statistical corrections work and discusses difficulties with the use of these corrections under certain circumstances. ANCOVA is essentially a regression of a covariate variable on the dependent variable from the entire sample ignoring group membership, at least, if ANCOVA…
Descriptors: Analysis of Covariance, Educational Research, Groups, Heuristics