In this article we outline an application of the causal TRT procedure and missing data methods to a dataset of progressed pupils (pupils who moved to the subsequent grade although they did not meet the promotional criteria in their current grade) in poor school communities. The technique approximates the contributing effect of binary treatment on a continuous or discrete outcome. With the application of the procedure in this study, we aimed to approximate the contributing effect of the intervention treatment, specifically extra classes for progressed learners on their learning outcomes as suggested by the policy on progression. Inverse probability weighting (IPW) and multiple imputation (MI) were employed to address the missing data. A sample of 828 learners from 4 schools in the Pietermaritzburg district was selected for this study. Our findings indicate that the causal treatment had a positive effect on these learners’ results. Moreover, multiple imputation proved to be a better method for imputing missing data over the inverse probability weighting. We recommend the use of monitored extra classes to improve progressed learners’ results. Additionally, we recommend the use of multiple imputation over inverse probability weighting when the missing data is less than 5%.

https://doi.org/10.15700/saje.v46n2a2610

ORCiD iDs of authors:
S. Mabungane – https://orcid.org/0000-0002-0922-7733
S. Ramroop – https://orcid.org/0000-0001-9305-6967
H. Mwambi - https://orcid.org/0000-0001-9654-400X