ABSTRACT
The poor performance of grade 10 learners has been a big concern over the last few years and in the effort to understand this phenomenon there has been efforts to present models that explain it. Modelling semi-continuous data with the presence of excess zeros has become a common phenomenon in real life situations. Common models such as linear models cannot handle zero-inflated data. This study aimed at exploring the factors which influence Khomas Region grade 10 learners’ pass rate using Generalized Linear Models (GLM). The data used for this study was obtained from the Directorate of National Examination and Assessment for the year 2016, with permission from the Permanent Secretary of the Ministry of Education. Descriptive statistics were used to describe the socio-demographic variables, namely: age, location and type of school. Six GLMs were fitted (Poisson, Negative Binomial, Hurdle Poisson, Hurdle Negative Binomial, Zero Inflated Poisson and Zero- Inflated Negative Binomial) to assess their goodness of fit on modelling the zero-inflated DNEA count data. The goodness of fit of each model was determined using the Akaike Information Criterion (AIC) value. All analyses were done using the R software version 3.3.1, with its MASS, pscl, and AER packages, as well as the Statistical Package (SPSS). The Zero- Inflated Negative Binomial performed better based on its lowest AIC values among the six fitted GLMs. The results revealed that the age of the learner, school location and the type of school (private/state) had significant differential in pass rate with p-values less than 0.05 in the Zero- Inflated Negative Binomial model.
MUMBUU, R (2021). Zero-Augmented Models For Exploring The Factors Affecting The Pass Rate Of Grade 10 Learners In Khomas Region In 2016. Afribary. Retrieved from https://afribary.com/works/zero-augmented-models-for-exploring-the-factors-affecting-the-pass-rate-of-grade-10-learners-in-khomas-region-in-2016
MUMBUU, RAPIKAMA "Zero-Augmented Models For Exploring The Factors Affecting The Pass Rate Of Grade 10 Learners In Khomas Region In 2016" Afribary. Afribary, 21 Apr. 2021, https://afribary.com/works/zero-augmented-models-for-exploring-the-factors-affecting-the-pass-rate-of-grade-10-learners-in-khomas-region-in-2016. Accessed 22 Nov. 2024.
MUMBUU, RAPIKAMA . "Zero-Augmented Models For Exploring The Factors Affecting The Pass Rate Of Grade 10 Learners In Khomas Region In 2016". Afribary, Afribary, 21 Apr. 2021. Web. 22 Nov. 2024. < https://afribary.com/works/zero-augmented-models-for-exploring-the-factors-affecting-the-pass-rate-of-grade-10-learners-in-khomas-region-in-2016 >.
MUMBUU, RAPIKAMA . "Zero-Augmented Models For Exploring The Factors Affecting The Pass Rate Of Grade 10 Learners In Khomas Region In 2016" Afribary (2021). Accessed November 22, 2024. https://afribary.com/works/zero-augmented-models-for-exploring-the-factors-affecting-the-pass-rate-of-grade-10-learners-in-khomas-region-in-2016