Genomic inflation factors under polygenic inheritance

Population structure, including population stratification and cryptic relatedness, can cause spurious associations in genome-wide association studies (GWAS). Usually, the scaled median or mean test statistic for association calculated from multiple single-nucleotide-polymorphisms across the genome is used to assess such effects, and 'genomic control' can be applied subsequently to adjust test statistics at individual loci by a genomic inflation factor. Published GWAS have clearly shown that there are many loci underlying genetic variation for a wide range of complex diseases and traits, implying that a substantial proportion of the genome should show inflation of the test statistic. Here, we show by theory, simulation and analysis of data that in the absence of population structure and other technical artefacts, but in the presence of polygenic inheritance, substantial genomic inflation is expected. Its magnitude depends on sample size, heritability, linkage disequilibrium structure and the number of causal variants. Our predictions are consistent with empirical observations on height in independent samples of ~4000 and ~133,000 individuals.

Do instructional attributes pose multicollinearity problems? An empirical exploration

It is commonly perceived that variables ‘measuring’ different dimensions of teaching (construed as instructional attributes) used in student evaluation of teaching (SET) questionnaires are so highly correlated that they pose a serious multicollinearity problem for quantitative analysis including regression analysis. Using nearly 12000 individual student responses to SET questionnaires and ten key dimensions of teaching and 25 courses at various undergraduate and postgraduate levels for multiple years at a large Australian university, this paper investigates whether this is indeed the case and if so under what circumstances. This paper tests this proposition first by examining variance inflation factors (VIFs), across courses, levels and over time using individual responses; and secondly by using class averages. In the first instance, the paper finds no sustainable evidence of multicollinearity. While, there were one or two isolated cases of VIFs marginally exceeding the conservative threshold of 5, in no cases did the VIFs for any of the instructional attributes come anywhere close to the high threshold value of 10. In the second instance, however, the paper finds that the attributes are highly correlated as all the VIFs exceed 10. These findings have two implications: (a) given the ordinal nature of the data ordered probit analysis using individual student responses can be employed to quantify the impact of instructional attributes on TEVAL score; (b) Data based on class averages cannot be used for probit analysis. An illustrative exercise using level 2 undergraduate courses data suggests higher TEVAL scores depend first and foremost on improving explanation, presentation, and organization of lecture materials.

Exploratory factor analysis and psychometric evaluation of the Teachers Reporting Attitude Scale for Child Sexual Abuse

This paper presents an evaluation of an instrument to measure teachers’ attitudes towards reporting child sexual abuse and discusses the instrument’s merit for research into reporting practice. Based on responses from 444 Australian teachers, the Teachers’ Reporting Attitude Scale for Child Sexual Abuse (TRAS - CSA) was evaluated using exploratory factor analysis. The scale isolated three dimensions: commitment to the reporting role; confidence in the system’s response to reports; and concerns about reporting. These three factors accounted for 37.5% of the variance in the 14-item measure. Alpha coefficients for the subscales were 0.769 (commitment), 0.617 (confidence), and 0.661 (concerns). The findings provide insights into the complexity of studying teachers’ attitudes towards reporting of child sexual abuse, and have implications for future research.

The factor structure of the COPE Questionnaire in a sample of clinically depressed and anxious adults

The Coping Orientation to Problems Experienced is a multidimensional scale designed to assess how people respond to stress. The COPE has been validated in a variety of populations displaying variations in factor structure. However, in terms of mental health populations, it has only been validated in alcohol-dependent samples. This paper investigated the factor structure of the COPE in a sample of adults diagnosed with depression and anxiety. Two hundred and seventy-one patients attending cognitive behaviour therapy for anxiety and depression completed the COPE. Confirmatory factor analysis found a poor fit for both lower order and higher order factors based upon the Lyne and Roger (2000) study. Exploratory factor analyses identified six primary subscales (Active Planning, Social Support, Denial, Acceptance, Disengagement, Restraint) which explained approximately 60% of the variance in coping. These 6 subscales may assist researchers and clinicians to validly measure coping in anxious and depressed adults.