Data were cleaned, missing data was addressed, and the assumptions of the general linear model were assessed prior to testing the significance of the proposed structural model. Participants who did not complete at least 80% of a given measure were eliminated. In order to determine if missing data were missing at completely at random, Little’s Missing Completely at Random (MCAR) test was conducted. The results of Little’s MCAR suggested that the missing data were not MCAR (ꭓ2[3624] = 4126.296, p < .001). As discussed in Tabachnick and Fidell (2013), missing data can be classified as MCAR, missing at random (MAR), or missing not at random (MNAR). Missing data for all items in this data set fell below the recommended 5% missingness value
