An application of mixed-effect models to analyse contraceptive use in Malawian women

Table 4 Parameter estimates of EA- and district-random effect models and classical single-level regression model

Parameter	Mixed effect model	Classical linear model
Parameter	EAREM	DREM	SLM
Fixed effects
Intercept	−3.962	− 3.817	−3.300
Parity	0.451	0.417	0.344
Age	− 0.059	−0.056	− 0.045
Place-of-residence(urban)
Rural	−0.211	-0.208	−0.167
Region (northern)
Central	0.214	0.157	0.189
Southern	0.164	0.099	0.140
Education (no education)
Primary	0.381	0.360	0.369
Secondary	0.635	0.611	0.587
Secondary	0.704	0.666	0.620
Occupation (not working)
Manual	0.473	0.453	0.421
Agriculture	0.368	0.316	0.295
Business	0.661	0.667	0.564
Office	0.467	0.433	0.397
Marital-Status (never married)
Widowed/divorced	1.434	1.479	1.251
Separation	1.562	1.579	1.342
Married	2.594	2.597	2.175
Religion (Christian)
Muslim	−0.521	−0.349	−0.544
Other	−0.442	− 0.445	− 0.362
Religions no religion	− 0.264	− 0.215	− 0.171
Random effects
\( {\sigma}_{u(intercept)}^2 \)	0.120	0.086
\( {\sigma}_{u(age)}^2 \)	0.001	0.0005
\( {\sigma}_{u(parity)}^2 \)	0.011

EAREM Enumeration-Area random effect model, DREM District random effect model, SLM Single-level model

ISSN: 2055-7426