Table 5.

Country-level factors associated with infant and under-five mortality rates in Ghana using penalised regression

	$L_1$penalisation: L
	Rigorous theory-driven penalisation for LASSO using covariate dependent penalty level	Rigorous theory-driven penalisation for square root LASSO using covariate dependent penalty level	ten folds cross-validation LASSO	LASSO based on extended Bayesian information criteria
Country-level factors influencing infant-five mortality rate in Ghana
Internet use	−0.15		−0.10	−0.10
Female labour force participation	−9.31	−7.88	−3.73	−4.42
Birth rate		2.30
Government effectiveness			0.71	0.79
Tuberculosis			0.06	0.05
Access to electricity			−0.01
Access to drinking water-rural			−0.80	−0.77
Government effectiveness			0.71
Prevalence of HIV			0.92
Urban Population			−0.45	−0.49
Government expenditure on education			−0.03	−0.01
Country-level factors influencing the under-five mortality rate in Ghana
Internet use	−0.23		−0.07	−0.18
Female labour force participation	−17.54	−14.56	−16.29	−6.53
Birth rate		4.38	2.47
Government effectiveness			0.86	1.14
Tuberculosis				0.10
Access to electricity				−0.01
Access to drinking water-rural				−1.41
Government effectiveness				1.14
Prevalence of HIV				1.62
Urban population				−0.79
Government expenditure on education				−0.04

Parameter estimates were based on 25 selected country-level covariates. Details of the covariates studied can be found in online supplementary S8.

LASSO, Least Absolute Shrinkage and Selection Operator.