Etiologic fraction analysis for continuously distributed outcome variables and empirical analogy with dichotomized outcome variables.
BACKGROUND
It is not clear from the published literature whether R2 estimated from linear regression models for continuously distributed outcome variables is analogous to the etiologic fraction for dichotomized outcome variables. This article attempts to address this issue.


METHODS
Continuous and dichotomous outcomes of the same underlying attributes (gestational age and fetal growth) were compared using data from a recent study of birthweight distributions in ethnic Caucasian infants.


RESULTS
The relative magnitudes of the etiologic fraction and R2 were quite similar for the same underlying attributes. For example, R2 and etiologic fraction for weight gain rate ranked 2 and 3, respectively, for fetal growth and ranked 4.5 and 5, respectively, for gestational duration.


CONCLUSIONS
R2 estimated from linear regression models for continuously distributed outcome variables appears analogous to the etiologic fraction for dichotomized outcome variables. If due consideration is given to the underlying biological mechanisms of the studied attributes, R2 can be used as a measure of public health impact.
Wen
S W
SW
Department of Epidemiology and Biostatistics, Faculty of Medicine, McGill University, Montreal, Quebec, Canada.
Kramer
M S
MS
D001724:Birth Weight; D015984:Causality; D003627:Data Interpretation, Statistical; D005314:Embryonic and Fetal Development; D005317:Fetal Growth Retardation / Q000453:epidemiology / Q000209:etiology; D006801:Humans; D007230:Infant, Low Birth Weight; D007231:Infant, Newborn; D007234:Infant, Premature; D016014:Linear Models; D016015:Logistic Models; D011792:Quebec / Q000453:epidemiology; D012307:Risk Factors; D044465:White People