Motivational interviewing and feedback for college drinkers: Handling missing values with complete case analysis and multiple imputation

Objective: In this secondary data analysis, three statistical methodologies were implemented to handle cases with missing data in a motivational interviewing and feedback study. The aim was to evaluate the impact that these methodologies have on the data analysis. ^ Methods: We first evaluated whether the assumption of missing completely at random held for this study. We then proceeded to conduct a secondary data analysis using a mixed linear model to handle missing data with three methodologies (a) complete case analysis, (b) multiple imputation with explicit model containing outcome variables, time, and the interaction of time and treatment, and (c) multiple imputation with explicit model containing outcome variables, time, the interaction of time and treatment, and additional covariates (e.g., age, gender, smoke, years in school, marital status, housing, race/ethnicity, and if participants play on athletic team). Several comparisons were conducted including the following ones: 1) the motivation interviewing with feedback group (MIF) vs. the assessment only group (AO), the motivation interviewing group (MIO) vs. AO, and the intervention of the feedback only group (FBO) vs. AO, 2) MIF vs. FBO, and 3) MIF vs. MIO.^ Results: We first evaluated the patterns of missingness in this study, which indicated that about 13% of participants showed monotone missing patterns, and about 3.5% showed non-monotone missing patterns. Then we evaluated the assumption of missing completely at random by Little's missing completely at random (MCAR) test, in which the Chi-Square test statistic was 167.8 with 125 degrees of freedom, and its associated p-value was p=0.006, which indicated that the data could not be assumed to be missing completely at random. After that, we compared if the three different strategies reached the same results. For the comparison between MIF and AO as well as the comparison between MIF and FBO, only the multiple imputation with additional covariates by uncongenial and congenial models reached different results. For the comparison between MIF and MIO, all the methodologies for handling missing values obtained different results. ^ Discussions: The study indicated that, first, missingness was crucial in this study. Second, to understand the assumptions of the model was important since we could not identify if the data were missing at random or missing not at random. Therefore, future researches should focus on exploring more sensitivity analyses under missing not at random assumption.^

Infant breastfeeding patterns by sex: Do males feed more?

Background: Most studies have looked at breastfeeding practices from the point of view of the maternal behavior only, however in counseling women who choose to breastfeed it is important to be aware of general infant feeding patterns in order to adequately provide information about what to expect. Available literature on the differences in infant breastfeeding behavior by sex is minimal and therefore requires further investigation. Objectives: This study determined if at the age of 2 months there were differences in the amount of breast milk consumed, duration of breastfeeding, and infant satiety by infant sex. It also assessed whether infant sex is an independent predictor of initiation of breastfeeding. Methods: This is a secondary analysis of data obtained from the Infant Feeding Practices Survey II (IFPS II) which was a longitudinal study carried out from May 2005 through June 2007 by the Food and Drug Administration and the Centers for Disease Control and Prevention. The questionnaires asked about demography, prenatal care, mode of delivery, birth weight, infant sex, and breastfeeding patterns. A total of 3,033 and 2,552 mothers completed the neonatal and post-neonatal questionnaires respectively. ^ Results: There was no significant difference in the initiation of breastfeeding by infant sex. About 85% of the male infants initiated breastfeeding compared with 84% of female infants. The odds ratio of ever initiating breastfeeding by male infants was 0.93 but the difference was not significant with a p-value of 0.49. None of the other infant feeding patterns differed by infant gender. ^ Conclusion: This study found no evidence that male infants feed more or that their mothers are more likely to initiate breastfeeding. Each baby is an individual and therefore will have a unique feeding pattern. Based on these findings, the major determining factors for breastfeeding continue to be maternal factors therefore more effort should be invested in promoting breastfeeding among mothers of all ethnic groups and social classes.^