Contraception: Contraceptive use in Bangladesh

In mlmRev: Examples from Multilevel Modelling Software Review

Description

These data on the use of contraception by women in urban and rural areas come from the 1988 Bangladesh Fertility Survey.

Usage

data(Contraception)

Format

A data frame with 1934 observations on the following 6 variables.

woman

Identifying code for each woman - a factor

district

Identifying code for each district - a factor

use

Contraceptive use at time of survey

livch

Number of living children at time of survey - an ordered factor. Levels are 0, 1, 2, 3+

age

Age of woman at time of survey (in years), centred around mean.

urban

Type of region of residence - a factor. Levels are urban and rural

Source

http://www.bristol.ac.uk/cmm/learning/mmsoftware/data-rev.html

References

Steele, F., Diamond, I. And Amin, S. (1996). Immunization uptake in rural Bangladesh: a multilevel analysis. Journal of the Royal Statistical Society, Series A (159): 289-299.

Examples

str(Contraception)
summary(Contraception)
(fm1 <- glmer(use ~ urban+age+livch+(1|district), Contraception, binomial))
(fm2 <- glmer(use ~ urban+age+livch+(urban|district), Contraception, binomial))

Example output

Loading required package: lme4
Loading required package: Matrix
'data.frame':	1934 obs. of  6 variables:
 $ woman   : Factor w/ 1934 levels "1","2","3","4",..: 1 2 3 4 5 6 7 8 9 10 ...
 $ district: Factor w/ 60 levels "1","2","3","4",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ use     : Factor w/ 2 levels "N","Y": 1 1 1 1 1 1 1 1 1 1 ...
 $ livch   : Factor w/ 4 levels "0","1","2","3+": 4 1 3 4 1 1 4 4 2 4 ...
 $ age     : num  18.44 -5.56 1.44 8.44 -13.56 ...
 $ urban   : Factor w/ 2 levels "N","Y": 2 2 2 2 2 2 2 2 2 2 ...
     woman         district    use      livch         age             urban   
 1      :   1   14     : 118   N:1175   0 :530   Min.   :-13.560000   N:1372  
 2      :   1   1      : 117   Y: 759   1 :356   1st Qu.: -7.559900   Y: 562  
 3      :   1   46     :  86            2 :305   Median : -1.559900           
 4      :   1   25     :  67            3+:743   Mean   :  0.002198           
 5      :   1   6      :  65                     3rd Qu.:  6.440000           
 6      :   1   30     :  61                     Max.   : 19.440000           
 (Other):1928   (Other):1420                                                  
Generalized linear mixed model fit by maximum likelihood (Laplace
  Approximation) [glmerMod]
 Family: binomial  ( logit )
Formula: use ~ urban + age + livch + (1 | district)
   Data: Contraception
      AIC       BIC    logLik  deviance  df.resid 
 2427.616  2466.587 -1206.808  2413.616      1927 
Random effects:
 Groups   Name        Std.Dev.
 district (Intercept) 0.4608  
Number of obs: 1934, groups:  district, 60
Fixed Effects:
(Intercept)       urbanY          age       livch1       livch2      livch3+  
   -1.68965      0.73298     -0.02659      1.10913      1.37634      1.34518  
Generalized linear mixed model fit by maximum likelihood (Laplace
  Approximation) [glmerMod]
 Family: binomial  ( logit )
Formula: use ~ urban + age + livch + (urban | district)
   Data: Contraception
      AIC       BIC    logLik  deviance  df.resid 
 2417.017  2467.123 -1199.508  2399.017      1925 
Random effects:
 Groups   Name        Std.Dev. Corr 
 district (Intercept) 0.6174        
          urbanY      0.8011   -0.80
Number of obs: 1934, groups:  district, 60
Fixed Effects:
(Intercept)       urbanY          age       livch1       livch2      livch3+  
   -1.71164      0.81517     -0.02652      1.12555      1.36814      1.35461  

mlmRev documentation built on April 5, 2020, 9:07 a.m.