Multiple imputation using auxiliary imputation variables that only predict missingness can increase bias due to data missing not at random.

Background: Epidemiological and clinical studies often have missing data, frequently analysed using multiple imputation (MI). In general, MI estimates will be biased if data are missing not at random (MNAR). Bias due to data MNAR can be reduced by including other variables ("auxiliary variables") in imputation models, in addition to those required for the substantive analysis.

Multiple imputation of missing data under missing at random: including a collider as an auxiliary variable in the imputation model can induce bias.

Epidemiological studies often have missing data, which are commonly handled by multiple imputation (MI). In MI, in addition to those required for the substantive analysis, imputation models often include other variables ("auxiliary variables"). Auxiliary variables that predict the partially observed variables can reduce the standard error (SE) of the MI estimator and, if they also predict the probability that data are missing, reduce bias due to data being missing not at random.

Multiple imputation of missing data under missing at random: compatible imputation models are not sufficient to avoid bias if they are mis-specified.

Objectives: Epidemiological studies often have missing data, which are commonly handled by multiple imputation (MI). Standard (default) MI procedures use simple linear covariate functions in the imputation model. We examine the bias that may be caused by acceptance of this default option and evaluate methods to identify problematic imputation models, providing practical guidance for researchers.

Age-specific effects of weight-based body size on fracture risk in later life: a lifecourse Mendelian randomisation study.

Musculoskeletal conditions, including fractures, can have severe and long-lasting consequences. Higher body mass index in adulthood is widely acknowledged to be protective for most fracture sites. However, sources of bias induced by confounding factors may have distorted previous findings.

Parental depressive symptoms across the first three years of a child's life and emotional and behavioural problem trajectories in children and adolescents.

Background: The risk associated with parental perinatal depressive symptoms and the continuum of emotional and behavioural problems in offspring is unclear. This study aimed to investigate the association between maternal and paternal perinatal depressive symptoms and behavioural problem trajectories in offspring aged 3-16 years.

Methods: We used data from the Avon Longitudinal Study of Parents and Children (ALSPAC) in Bristol, Avon, United Kingdom (UK).

Association of Maternal Depressive Symptoms During the Perinatal Period With Oppositional Defiant Disorder in Children and Adolescents.

Importance: An association between perinatal maternal depression and risk of oppositional defiant disorder (ODD) in offspring has not been established. Identifying early determinants of ODD can help inform preventative intervention efforts.

Objective: To investigate the association between maternal perinatal depressive symptoms and the risk of ODD in offspring aged 7 to 15 years.

State anxiety and alcohol choice: Evidence from experimental and online observational studies.

Background: Experimental studies have investigated the effects of physical, psychological and pharmacological stressors (that induce state anxiety) on alcohol outcomes. However, no study has investigated the effects of state anxiety on alcohol outcomes, and the moderating role of drinking to cope (DTC) motives, using the 7.5% carbon dioxide (CO) challenge.

Maternal smoking during pregnancy and offspring smoking initiation: assessing the role of intrauterine exposure.

Aims: To assess whether associations between maternal smoking during pregnancy and offspring smoking initiation are due to intrauterine mechanisms.

Design: Comparison of associations of maternal and partner smoking behaviour during pregnancy with offspring smoking initiation using partner smoking as a negative control (n = 6484) and a Mendelian randomization analysis (n = 1020), using a genetic variant in the mothers as a proxy for smoking cessation during pregnancy.

Setting: A longitudinal birth cohort in South West England.

The effect of foraging parameters on the probability that a dive is successful.

In this paper, we investigate the foraging decisions of an animal that dives to obtain its food. It might seem reasonable to use the probability that the diver is successful in any dive as an indicator of habitat quality. We use a dynamic model of optimal prey choice to show that this interpretation of diving success is not generally valid.