NAME: 	Low Birth Weight Data [Paired] (LOWBWTM11.DAT)
KEYWORDS:  Logistic Regression (for a matched 1-1 case-control study)
SIZE:  112 observations (56 cases, 56 controls), 9 variables

SOURCE: Hosmer and Lemeshow (2000) Applied Logistic Regression: Second 
	Edition.  These data are copyrighted by John Wiley & Sons Inc. and must 
	be acknowledged and used accordingly.  Data were collected at Baystate 
	Medical Center, Springfield, Massachusetts.



DESCRIPTIVE ABSTRACT:

The goal of this study was to identify risk factors associated with
giving birth to a low birth weight baby (weighing less than 2500 grams).
Data were originally collected on 189 women, 59 of which had low birth weight
babies and 130 of which had normal birth weight babies.  Pairs were then 
selected from this low birth weight data.  For each case a control was 
selected after matching on age.  Four variables which were
thought to be of importance were age, weight of the subject at her last
menstrual period, race, and the number of physician visits during the first
trimester of pregnancy.



NOTE: 

This data set consists of the paired data.  The complete original
data set for this low birth weight data may be found in lowbwt.dat and
a 3 to 1 matched data set created from the low birth weight data may be
found in mlowbwt.dat.



LIST OF VARIABLES:

Columns   Variable                                              Abbreviation
-----------------------------------------------------------------------------
11-12   Pair Number                                             PAIR
   
19      Low Birth Weight (0 = Birth Weight ge 2500g,            LOW
                          l = Birth Weight < 2500g)
  
25-26   Age of the Mother in Years                              AGE
     
31-33   Weight in Pounds at the Last Menstrual Period           LWT
     
41      Race (1 = White, 2 = Black, 3 = Other)                  RACE
     
50      Smoking Status During Pregnancy (1 = Yes, 0 = No)       SMOKE
     
57      History of Premature Labor (0 = None, 1 = Yes)          PTD
     
63      History of Hypertension (1 = Yes, 0 = No)               HT
     
69      Presence of Uterine Irritability (1 = Yes, 0 = No)      UI
     
-----------------------------------------------------------------------------

PEDAGOGICAL NOTES:
        
These data have been used as an example of fitting a logistic
regression model for matched case-control studies.


STORY BEHIND THE DATA:
        
Low birth weight is an outcome that has been of concern to physicians
for years. This is due to the fact that infant mortality rates and birth
defect rates are very high for low birth weight babies. A woman's behavior
during pregnancy (including diet, smoking habits, and receiving prenatal care)
can greatly alter the chances of carrying the baby to term and, consequently,
of delivering a baby of normal birth weight.
        
The variables identified in the code sheet given in the table have been
shown to be associated with low birth weight in the obstetrical literature. The
goal of the current study was to ascertain if these variables were important
in the population being served by the medical center where the data were
collected.


References:

1. Hosmer and Lemeshow, Applied Logistic Regression, Wiley, (1989).