Dataset for Child schooling/ Out of school children in Kwara state, Nigeria
Description
This data is a primary data collected with the use of a questionnaire to analyse the situation of child schooling in Kwara State, Nigeria. This data has been coded, and the data was collected from Ilorin, Offa, Lafiagi and Patigi, representing the three senatorial districts in the state, Kwara Central, Kwara South and Kwara North. This work has been approved by the Ethics committee of the Universiti Sains Malaysia (JEPEM), and all the conditions were strictly adhered to in the data collection process. This data was collected from about 1120 households across six local governments within the three senatorial districts and is representative of the state. Attached with the data set is a table describing the dataset and the questionnaire with the informed consent form.
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Steps to reproduce
This data was acquired with the use of questionnaires. This study adopted a random and systematic probability sampling technique. For the questionnaire, the households were randomly selected to give all households equal opportunity, as proposed by (Agresti & Finlay, 2009). However, the communities were divided into areas for enumerations, with specified number of questionnaires administered to each area. This ensures that there is no spatial dependence to provide adequate representation. Using these two sampling techniques is due to the fact that random sampling ensures representation, but it is not the best when considering spatial dependence, and on the other hand, systematic sampling is not representative, but it helps in reducing spatial dependence. Hence, using these two together ensures the study has a good sample (see; Cheng & Masser, 2003). Questionnaire Design The objective of this study and theory serves as a guide for designing the research questionnaire and model specification. This aims to ensure that there is no omission of relevant information while analysing data. The questions cover the head of households, individuals in the households, household demographic characteristics, community characteristics, education, employment status, the standard of living, and the nature of dependents, among other things. The questionnaire includes both open-ended and close-ended questions. Measurement of Variables for Analysis A number of the variables were recoded after the collection of data. The variables were recoded to suit the specified models for each study objective. Some of the categorical variables were changed to a binary form that is 0 and 1 as may be applicable, for example, gender, vocational training, among others, and ordered will be coded as applicable. Dependent Variable Child Schooling Child schooling was divided into enrolment and attainment. The determinants of enrolment show the variables that influence why some children have never enrolled, why some were enrolled and dropped out, and why others are currently enrolled. Also, attainment will be used to show the factors determining the highest level of education.