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Psychological researchers often use standard linear regression to identify relevant predictors of an outcome of interest, but challenges emerge with incomplete data and growing numbers of candidate predictors. Regularization methods like the LASSO can reduce the risk of overfitting, increase model interpretability, and improve prediction in future samples; however, handling missing data when using regularization-based variable selection methods is complicated. Using listwise deletion or an ad hoc imputation strategy to deal with missing data when using regularization methods can lead to loss of precision, substantial bias, and a reduction in predictive ability. In this tutorial, we describe three approaches for fitting a LASSO when using multiple imputation to handle missing data and illustrate how to implement these approaches in practice with an applied example. We discuss implications of each approach and describe additional research that would help solidify recommendations for best practices. [ABSTRACT FROM AUTHOR]

Objective: The consequences of maternal depressed mood on children's growth, health, and cognitive and language development are examined over the first 3 years of life. Method: Pregnant women in 24 periurban township neighborhoods in Cape Town, South Africa (N = 1,238 mothers) were randomized by neighborhood to a home visiting intervention or a standard care condition. Reassessments were conducted for 93%-85% of mothers at 2-weeks, 6-, 18-, and 36-months postbirth. Regressions were conducted on measures of children's growth, behavior, language, and cognition to examine the impact of four patterns of depressed mood: antenatal only (n = 154, 13.8%), postnatal only (n = 272, 24.3%), antenatal and postnatal (n = 220, 19.7%), and no depressed mood on any assessment (n = 473, 42.3%). Results: Patterns of depressed mood were similar across intervention conditions. Depressed mothers were significantly less educated, had lower incomes, were less likely to be employed or to have electricity; were more likely to report problematic drinking of alcohol, experience food insecurity, interpersonal partner violence, and to be HIV seropositive. At 36 months, the pattern of maternal depressed mood over time was significantly associated with children's compromised physical growth, both in weight and height, and more internalizing and externalizing symptoms of behavior problems. Measures of language and cognition were similar across maternal patterns of depressed mood. Conclusions: Mothers who report depressed mood face significantly more life challenges, both environmental stressors related to poverty and other problematic behaviors. More proximal, postnatal depressed mood appears to have a larger influence on their children, compared with antenatal depressed mood. [ABSTRACT FROM AUTHOR]