help biascon(Quantitative Bais Aanlysis in Epidemiology)

Title

biascon -- performs bias analysis for unmeasured and/or unknown confounder

Syntax

biascon
depvar indepvar
[if] [in]
[, options]

Options
p0(#) the prevalence of the confounder among the unexposed and the default is 0.43

p1(#) the prevalence of the confounder among the exposed and the default is 0.42

effect0(#) the association between the confounder and the outcome among those who were not exposed and the default is 1.5

effect1(#) the association between the confounder and the outcome among those who were exposed and the default equals to the effect0

typeeffect(#) the type of confounder-outcome association. 1: risk ratio which is the default; 2: odds ratio, and 3: risk difference

generate generate newvar containing the predicted binary confounding variable for each individual;

seed specifies the initial value of the random-number seed;

biasconi
a b c d
[if] [in]
[, options]

Options
p0(#) the prevalence of the confounder among the unexposed and the default is 0.43

p1(#) the prevalence of the confounder among the exposed and the default is 0.42

effect0(#) the association between the confounder and the outcome among those who were not exposed and the default is 1.5

effect1(#) the association between the confounder and the outcome among those who were exposed and the default equals to the effect0

typeeffect(#) the type of confounder-outcome association. 1: risk ratio which is the default; 2: odds ratio, and 3: risk difference

Description

Command biascon, which is one of the command among the package biasepi, performs bias analysis for unmeasured and unknown confounders.

Combining the three commands (biasselect, biascon, biasmis) is able to perform multiple bias modelinging.
Combining the existing Stata commands for probalistic distributions, biascon is able to perform probalistic bias analysis

Options

p0 the prevalence of the confounder among the unexposed and the default is 0.43

p1 the prevalence of the confounder among the exposed and the default is 0.42

effect0 the association between the confounder and the outcome among those who were not exposed and the default is 1.5.

effect1 the association between the confounder and the outcome among those who were exposed. The default is effect1=effect0, which indicates there is no effect modification.

typeeffect the type of association between the confounder and outcome. 1: risk ratio which is the default; 2: odds ratio, and 3: risk difference

Examples

1. Simple bias analysis for unknown confounder, given the assocation between the confounder-outcome is risk ratio

.biasconi 232 133 4677 6031, p0(0.4325) p1(0.4247) effect0(1.51) typeeffect(1)

2. Simple bias analysis for unknown confounder, given the assocation between the confounder-outcome is odds ratio:

.biasconi 232 133 4677 6031, p0(0.4325) p1(0.4247) effect0(1.53) typeeffect(2)

3. Simple bias analysis for unknown confounder, given the assocation between the confounder-outcome is risk difference:

.biasconi 232 133 4677 6031, p0(0.4325) p1(0.4247) effect0(0.0137) typeeffect(3)

More examples

click on her

References

Lash, Timothy L., Fox, Matthew P., Fink, Aliza K. 2009.

Applying Quantitative Bias Analysis to Epidemiologic Data

The online resource for the reference textbook.

Author

Chunsen Wu, the University of Southern Denmark; Odense University Hospital, Denmark

cwu@health.sdu.dk

chunsen.wu@rsyd.dk

Also see

Help: biasepi, biasselect, biascon, biasmis, biassurv, biastab2

Stored results

biascon and biasconi store the following in r():

Scalars

r(cRR) Observed risk ratio

r(cOR) Observed odds ratio

r(cRD) Observed risk difference

r(RR_c1) Corrected risk ratio among the strata confounder=1

r(OR_c1) Corrected odds ratio among the strata confounder=1

r(RD_c1) Corrected risk difference among the strata confounder=1

r(RR_c0) Corrected risk ratio among the strata confounder=0

r(OR_c0) Corrected odds ratio among the strata confounder=0

r(RD_c0) Corrected risk difference among the strata confounder=0

r(mhRR) The Mantel Haenszel Method: risk ratio

r(mhOR) The Mantel Haenszel Method: odds ratio

r(mhRD) The Mantel Haenszel Method of Greenland and Robins: risk difference

Matrices

r(O) Observed 2*2 table

r(C1) 2*2 table among the strata confounder=1

r(C0) 2*2 table among the strata confounder=0

r(R) RR, OR, and RD

r(P) Probabilities of confounder variable for the 2*2 table