Rank likelihood-based estimation of low birth weight in Ethiopia

Low birth weight is a significant risk factor associated with high rates of neonatal and infant mortality, particularly in developing countries. However, most studies conducted on this topic in Ethiopia have small sample sizes, often focusing on specific areas and using standard models employing maximum likelihood estimation, leading to potential bias and inaccurate coverage probability. This study used a novel approach, the Bayesian rank likelihood method, within a latent traits model, to estimate parameters and provide a nationwide estimate of low birth weight and its risk factors in Ethiopia. Data from the Ethiopian Demographic and Health Survey (EDHS) of 2016 were used as a data source for the study. Data stratified all regions into urban and rural areas. Among 15, 680 representative selected households, the analysis included complete cases from 10, 641 children. The evaluation of model performance considered metrics such as the root mean square error, the mean absolute error, and t..., , , # Rank likelihood-based estimation of low birth weight in Ethiopia

Low birth weight data was obtained from the Ethiopian Demographic and Health Survey (EDHS).

Raw data: **Lowbirthweight.sav**

## Description of the data and file structure

#### Lowbirthweightdata\_data

*childweight*: categorical weight of the child at birth
*motherage*: age of the mothers
*ancvisti*: number of antenatal care visits that the mothers attended
*birthorder*: order of birth for the child
*birthinterval*: time between successive births (months)
*bmi*: body mass index of the mothers
*Regions*: the region where the child born
*CLID*: cluster-level ID that indicates from which cluster the information is obtained

## Sharing or accessing information

Our data is taken from the DHS website ([http://dhsprogram.com](http://dhsprogram.com). Low birth weight data was extracted from the 2016 EDHS. EDHS 2016 was conducted using standardized survey design and data collection procedures.