# Table 5 Determinants of life time number of partners for men.

REGRESSION MODEL
(1) Y = N (2) Y = √N (3) Y = ln(N+1)
Covariable β se(β) β se(β) β se(β)
Age (years) .906 .292 n.s.   -.184 .089
Square root of age n.s.   .845 .161 2.482 1.028
African American 26.72 6.611 1.197 .316 .482 .125
Mexican American n.s.   -.799 .253 -.459 .100
Regular Partner n.s.   -.504 .253 -.271 .102
Overweight n.s.   n.s.   n.s.
Obese -13.22 5.61 -.748 .253 -.292 .100
Height n.s.   n.s.   n.s.
Income >20,000\$ n.s.   -.759 .283 -.329 .113
N of weekly drinks n.s.   n.s.   n.s.
Smoking (ever) n.s.   n.s.   .189 .089
Education n.s.   n.s.   n.s.
Constant -12.65 10.44 -.446 .936 -5.478 2.913
1. n.s. = not selected by stepwise regression
2. Stepwise regression (p entry .05, p removal .10) of number of number of life time partners, and the root number of life time partners on selected covariables. The β coefficients represent the increase in the outcome variable (e.g. number of partners) for every unit increase (e.g. one year, for age) of the covariable to which it belongs.