Teaching Multivariate Linear mixed model in Multiple Longitudinal Data to the Medical Students: A Case Study of Child Development Data

The aim of this study was to teach medical students the multivariate linear mixed statistical model in multiple longitudinal data: A case study of child development data. The research method was descriptive-analytical and based on longitudinal data. The statistical population of the study consisted of 100 students who were randomly selected and participated in two training workshops based on statistical modeling of t and normal mixed multivariate linear distributions based on children's growth data (height, weight and head circumference). After the training course, they participated in practical test. Mean and standard deviation and statistical modeling of multivariate mixed linear t-distribution were used to analyze the data. The results showed that the amount of height variable parameters according to MtLMM and MnLMM models for breastfed infants was significantly higher than formula (P <0.05). Also, the estimation of weight variable parameters for infants who used formula was significantly higher (P <0.05) compared to infants who consumed only formula. The trainings provided to the two groups led to a significant increase in students' learning (P <0.05). The students stated that teaching a multivariate statistical model in longitudinal data revealed the important of using this model in medical research and life sciences.