Although widely recognized as a comprehensive framework for representing score reliability, generalizability theory (G-theory), despite its potential benefits, has been used sparingly in reporting of results for measures of individual differences. In this article, we highlight many valuable ways that G-theory can be used to quantify, evaluate, and improve psychometric properties of scores. Our illustrations encompass assessment of overall reliability, percentages of score variation accounted for by individual sources of measurement error, dependability of cut-scores for decision making, estimation of reliability and dependability for changes made to measurement procedures, disattenuation of validity coefficients for measurement error, and linkages of G-theory with classical test theory and structural equation modeling. We also identify computer packages for performing G-theory analyses, most of which can be obtained free of charge, and describe how they compare with regard to data input requirements, ease of use, complexity of designs supported, and output produced. (PsycINFO Database Record

SYNGAP1 loss-of-function variants are causally associated with intellectual disability, severe epilepsy, autism spectrum disorder and schizophrenia. While there are hundreds of genetic risk factors for neurodevelopmental disorders (NDDs), this gene is somewhat unique because of the frequency and penetrance of loss-of-function variants found in patients combined with the range of brain disorders associated with SYNGAP1 pathogenicity. These clinical findings indicate that SYNGAP1 regulates fundamental neurodevelopmental processes that are necessary for brain development. Here, we describe four phenotypic domains that are controlled by Syngap1 expression across vertebrate species. Two domains, the maturation of cognitive functions and maintenance of excitatory-inhibitory balance, are defined exclusively through a review of the current literature. Two additional domains are defined by integrating the current literature with new data indicating that SYNGAP1/Syngap1 regulates innate survival behaviors and brain structure. These four phenotypic domains are commonly disrupted in NDDs, suggesting that a deeper understanding of developmental Syngap1 functions will be generalizable to other NDDs of known or unknown etiology. Therefore, we discuss the known molecular and cellular functions of Syngap1 and consider how these functions may contribute to the emergence of disease-relevant phenotypes. Finally, we identify major unexplored areas of Syngap1 neurobiology and discuss how a deeper understanding of this gene may uncover general principles of NDD pathobiology.

In this article, we illustrate ways in which generalizability theory (G-theory) can be used with continuous latent response variables (CLRVs) to address problems of scale coarseness resulting from categorization errors caused by representing ranges of continuous variables by discrete data points and transformation errors caused by unequal interval widths between those data points. The mechanism to address these problems is applying structural equation modeling (SEM) as a tool in deriving variance components needed to estimate indices of score consistency and validity. Illustrations include quantification of multiple sources of measurement error, use of non-nested and nested designs, derivation of indices of consistency for norm- and criterion-referenced interpretation of scores, estimation of effects when changing measurement procedures and designs, and disattenuation of correlation coefficients for measurement error. These illustrations underscore the effectiveness of G-theory with continuous latent response variables in providing stable indices of reliability and validity that are reasonably independent of the number of original scale points used, unevenness of scale intervals, and average degree of item skewness. We discuss general distinctions in reliability estimation within G-theory, SEM, and classical test theory; make specific recommendations for using G-theory on raw score and CLRV metrics; and provide computer code in an online supplement for doing all key analyses demonstrated in the article using R and M (PsycINFO Database Record

It remains unclear to what extent neurodevelopmental disorder (NDD) risk genes retain functions into adulthood and how they may influence disease phenotypes. SYNGAP1 haploinsufficiency causes a severe NDD defined by autistic traits, cognitive impairment, and epilepsy. To determine if this gene retains therapeutically-relevant biological functions into adulthood, we performed a gene restoration technique in a mouse model for SYNGAP1 haploinsufficiency. Adult restoration of SynGAP protein improved behavioral and electrophysiological measures of memory and seizure. This included the elimination of interictal events that worsened during sleep. These events may be a biomarker for generalized cortical dysfunction in SYNGAP1 disorders because they also worsened during sleep in the human patient population. We conclude that SynGAP protein retains biological functions throughout adulthood and that non-developmental functions may contribute to disease phenotypes. Thus, treatments that target debilitating aspects of severe NDDs, such as medically-refractory seizures and cognitive impairment, may be effective in adult patients.

In this article, we illustrate how generalizability theory (G-theory) can extend traditional assessment methods for designing, improving, and evaluating results from both objectively and subjectively scored measures of individual differences. Our illustrations include quantification of multiple sources of measurement error, derivation of unique indexes of consistency for norm- and criterion-referenced interpretations of scores, estimation of score consistency when changing a measurement procedure, and disattenuation of correlation coefficients for measurement error. We also expand G-theory analyses beyond the item level to include parcels and split measures and highlight linkages among G-theory, classical test theory, and structural equation modeling. Computer code and sample data are provided in online supplements to help readers apply the demonstrated techniques to their own assessments.