Table_4.xls (9.5 kB)

Hierarchical regression with Nano Risk Index as dependent variable.

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posted on 15.09.2014 by Christian E. H. Beaudrie, Terre Satterfield, Milind Kandlikar, Barbara H. Harthorn

*p<.05.

**p<.01.

***p<.001.

Notes: N = 404. Independent variables were entered in six steps, where I through VI indicate model steps, and cell entries are standardized (β) regression coefficients.

a

Paired dummy variables, where ‘NSE’ is coded as DNEHS = 0, DNREG = 0, ‘NEHS’ is coded as DNEHS = 1, DNREG = 0, and ‘NREG’ is coded as DNEHS = 0, DNREG = 1.

b

1 = female, 0 = male.

c

1 = PhD, 0 = Bachelors/Masters.

d

Standardized continuous variable.

e

1 = physical sciences, 0 = other, where ‘physical sciences’ includes chemistry, physics, materials science, chemical engineering, electrical engineering, and mechanical engineering.

f

Paired dummy variables, where ‘academic vs government’ is coded as academic  =  0, government = 1, and ‘academic vs other’ is coded as academic = 0, other = 1.

g–k

Continuous index variables, described above.

Hierarchical regression with Nano Risk Index as dependent variable.

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