Trajectories of school absences across compulsory schooling and their impact on children's academic achievement: An analysis based on linked longitudinal survey and school administrative data

Abstract

Prior research has identified that school absences harm children's academic achievement. However, this literature is focused on brief periods or single school years and does not consistently account for the dynamic nature of absences across multiple school years. This study examined dynamic trajectories of children's authorised and unauthorised absences throughout their compulsory school career in England. It investigated the consequences of these absence trajectories for children's achievement at the end of compulsory schooling. We analyse linked administrative data on children's absences and achievement from the National Pupil Database and survey data from the Millennium Cohort Study for a representative sample of children born in 2000/2001 in England (N = 7218). We used k-means clustering for longitudinal data to identify joint authorised-unauthorised absence trajectories throughout compulsory schooling and a regression-with-residuals approach to examine the link between absence trajectories and achievement. We identified five distinct absence trajectories: (1) 'Consistently Low Absences', (2) 'Consistently Moderate Authorised Absences', (3) 'Moderately Increasing Unauthorised Absences', (4) 'Strongly Increasing Unauthorised Absences', and (5) 'Strongly Increasing Authorised Absences'. We found substantial differences between trajectory groups in GCSE achievement, even when accounting for significant risk factors of school absences. Compared to 'Consistently Low Absences', 'Strongly Increasing Unauthorised Absences' reduced achievement by -1.23 to -1.48 standard deviations, while 'Strongly Increasing Authorised Absences' reduced achievement by -0.72 to -1.00 SD for our continuous outcomes. 'Moderately Increasing Unauthorised Absences' (-0.61 to -0.70 SD) and 'Consistently Moderate Authorised Absences' (-0.13 to -0.21 SD) also negatively affected achievement compared to 'Consistently Low Absences'. Our research underscores the critical importance of examining entire trajectories of absenteeism and differentiating between types of absences to fully grasp their associations with academic outcomes and design targeted interventions accordingly.

Fig 1. Mean authorised and unauthorised absences over time by absence trajectory cluster.

Note. Linked MCS-NPD data, N = 7,218, weighted. CLA = Consistently Low Absence, CMAA = Consistently Moderate Authorised Absences, MIUA = Moderately Increasing Unauthorised Absences, SIAA = Strongly Increasing Authorised Absences, SIUA = Strongly Increasing Unauthorised Absences. Mean absences above 40% are truncated.

Fig 2. Differences in achievement by absence trajectory–adjusted for baseline and time-varying risk factors.

Note. Linked MCS-NPD data, N = 7,218, weighted. Reference category: Consistently Low Absence (CLA). CMAA = Consistently Moderate Authorised Absences, MIUA = Moderately Increasing Unauthorised Absences, SIAA = Strongly Increasing Authorised Absences, SIUA = Strongly Increasing Unauthorised Absences. Thick vertical lines indicate the 84%-Confidence Interval, and thin vertical lines the 95%-Confidence Interval.