Table 1.

Difference between univariable- and multivariable exposure effects as combination of confounding bias and the noncollapsibility effect

Difference between multivariable- and univariable effect estimate $({\mathit{\beta }}_1^{{}^{\mathbf{\prime }}}-{\mathit{\beta }}_1$)	Confounding bias (${\mathit{\beta }}_1-{\mathit{\beta }}_1^{\mathbf{\ast }}$)	Noncollapsibility effect (${\mathit{\beta }}_1^{\mathbf{\ast }}-{\mathit{\beta }}_1^{{}^{\mathbf{\prime }}}$)
Negative	Negative value	Negative value
	Zero	Negative value
	Negative value	Zero
	Positive value	Greater negative value than the positive confounding bias value
	Greater negative value than the positive noncollapsibility effect value	Positive value
Zero	Zero	Zero
	Equal positive value as the negative noncollapsibility effect value	Equal negative value as the positive confounding bias value
	Equal negative value as the positive noncollapsibility effect value	Equal positive value as the negative confounding bias value
Positive	Positive value	Positive value
	Zero	Positive value
	Positive value	Zero
	Negative value	Greater positive value than the negative confounding bias value
	Greater positive value than the negative noncollapsibility effect value	Negative value