Variance Decomposition Using an IRT Measurement Model

Large scale research projects in behaviour genetics and genetic epidemiology are often based on questionnaire or interview data. Typically, a number of items is presented to a number of subjects, the subjects’ sum scores on the items are computed, and the variance of sum scores is decomposed into a number of variance components. This paper discusses several disadvantages of the approach of analysing sum scores, such as the attenuation of correlations amongst sum scores due to their unreliability. It is shown that the framework of Item Response Theory (IRT) offers a solution to most of these problems. We argue that an IRT approach in combination with Markov chain Monte Carlo (MCMC) estimation provides a flexible and efficient framework for modelling behavioural phenotypes. Next, we use data simulation to illustrate the potentially huge bias in estimating variance components on the basis of sum scores. We then apply the IRT approach with an analysis of attention problems in young adult twins where the variance decomposition model is extended with an IRT measurement model. We show that when estimating an IRT measurement model and a variance decomposition model simultaneously, the estimate for the heritability of attention problems increases from 40% (based on sum scores) to 73%

Automated Feedback Can Improve Hypothesis Quality

Stating a hypothesis is one of the central processes in inquiry learning, and often forms the starting point of the inquiry process. We designed, implemented, and evaluated an automated parsing and feedback system that informed students about the quality of hypotheses they had created in an online tool, the hypothesis scratchpad. In two pilot studies in different domains (“supply and demand” from economics and “electrical circuits” from physics) we determined the parser's accuracy by comparing its judgments with those of human experts. A satisfactory to high accuracy was reached. In the main study (in the “electrical circuits” domain), students were assigned to one of two conditions: no feedback (control) and automated feedback. We found that the subset of students in the experimental condition who asked for automated feedback on their hypotheses were much more likely to create a syntactically correct hypothesis than students in either condition who did not ask for feedback

The Familial Clustering of Age at Menarche in Extended Twin Families

The timing of puberty is complex, possibly involving many genetic factors that may interact with environmental influences. Familial resemblance for age at menarche was studied in a sample of 4,995 female twins, 1,296 sisters, 2,946 mothers and 635 female spouses of male twins. They had indicated their age at menarche as part of a larger longitudinal survey. We assessed assortative mating for age at menarche, gene–environment interaction effects and estimated the heritability of individual differences in pubertal timing. There was significant evidence of gene–environment interaction, accounting for 1.5% of the variance. There was no indication of consistent mate assortment on age at menarche. Individual differences in age at menarche are highly heritable, with additive genetic factors explaining at least 70% of the true variation. An additional 1.5% of the variation can be explained by a genotype–environment interaction effect where environmental factors are more important in individuals genetically predisposed for late menarche

Genetic Covariance Structure of Reading, Intelligence and Memory in Children

This study investigates the genetic relationship among reading performance, IQ, verbal and visuospatial working memory (WM) and short-term memory (STM) in a sample of 112, 9-year-old twin pairs and their older siblings. The relationship between reading performance and the other traits was explained by a common genetic factor for reading performance, IQ, WM and STM and a genetic factor that only influenced reading performance and verbal memory. Genetic variation explained 83% of the variation in reading performance; most of this genetic variance was explained by variation in IQ and memory performance. We hypothesize, based on these results, that children with reading problems possibly can be divided into three groups: (1) children low in IQ and with reading problems; (2) children with average IQ but a STM deficit and with reading problems; (3) children with low IQ and STM deficits; this group may experience more reading problems than the other two

Individual differences in puberty onset in girls: Bayesian estimation of heritabilities and genetic correlations

We report heritabilities for individual differences in female pubertal development at the age of 12. Tanner data on breast and pubic hair development in girls and data on menarche were obtained from a total of 184 pairs of monozygotic and dizygotic twins. Genetic correlations were estimated to determine to what extent the same genes are involved in different aspects of physical development in puberty. A Bayesian estimation approach was taken, using Markovchain Monte Carlo simulation to estimate model parameters. All three phenotypes were to a significant extent heritable and showed high genetic correlations, suggesting that a common set of genes is involved in the timing of puberty in general. However, gonadarche (menarche and breast development) and adrenarche (pubic hair) are affected by different environmental factors, which does not support the three phenotypes to be regarded as indicators of a unitary physiological factor. © 2006 Springer Science+Business Media, Inc