Methodological development for questionnaire studies

Topics covered by already published papers:

• Bias in sibling and co-twin control studies due to measurement error:

  • _{Gustavson, K., Ask Torvik, F., Davey Smith, G., Røysamb, E, Eilertsen, E.M.   (2024). Familial confounding or measurement error? How to interpret findings from sibling and co-twin control studies. European Journal of Epidemiology. https://doi.org/10.1007/s10654-024-01132-6.}

    • _{To increase the usefulness of the analyses, we have developed a shinyapp- SibSim - where users can estimated expected bias due to measurement error in their sibling control study. Please feel free to try it out.}

• Using negative control variables to handle unmeasured confounding: 

  • _{Gustavson, K, Davey Smith, G, Eilertsen, E (2022). Handling unobserved confounding in the relation between prenatal risk factors and child outcomes: a latent variable strategy. European Journal of Epidemiology, 37(5).}

• Preventing bias due to selective non-response: 

  • _{Gustavson, K., Røysamb, E, Borren, I. (2019). Preventing bias from selective non-response in population-based survey studies: findings from a Monte Carlo simulation study. BMC Medical Research Methodology, 19,120.}

• Implications of regression towards the mean in longitudinal studies: 

  • _{Gustavson, K. Borren, I (2014). Bias in the study of prediction of change: a Monte Carlo simulation study of the effects of selective attrition and inappropriate modeling of regression toward the mean. BMC Medical Research Methodology, 14,133.}

We are currently working on the following topics:

• Bias in factor analysis of psychological data: How to interpret divergent results from different studies.
• Bias in the prediction of change with two-wave data