| effx {Epi} | R Documentation |
The function calculates the effects of an exposure on a response, possibly stratified by a stratifying variable, and/or controlled for one of more confounding variables.
effx( response, type = "metric",
fup = NULL,
exposure,
strata = NULL,
control = NULL,
weights = NULL,
alpha = 0.05,
base = 1,
digits = 3,
data = NULL )
response |
The response variable - must be numeric |
type |
The type of responsetype - must be one of "metric",
"binary", "failure", or "count" |
fup |
The fup variable contains the follow-up time for a
failure response |
exposure |
The exposure variable can be numeric or a factor |
strata |
The strata stratifying variable - must be a factor |
control |
The control variable(s) - these are passed as a
list of there are more than one. |
weights |
Weights |
base |
Baseline for the effects of a categorical exposure, default 1 |
digits |
Number of significant digits for the effects, default 3 |
alpha |
1 - confidence level |
data |
data refers to the data used to evaluate the function |
The function is a wrapper for glm. Effects are calculated as differences in means for a metric response, odds ratios for a binary response, and rate ratios for a failure or count response.
The k-1 effects for a categorical exposure with k levels are relative to a baseline which, by default, is the first level. The effect of a metric (quantitative) exposure is calculated per unit of exposure.
The exposure variable can be numeric or a factor, but if it is an ordered factor the order will be ignored.
comp1 |
Effects of exposure |
comp2 |
Tests of significance |
The function attaches the frame specified in the
data= argument, so there is a possibility that a variable in the
Global environment is masked by the attached frame. Watch out for this
warning in the output!
Michael Hills
www.mhills.pwp.blueyonder.co.uk
data(births)
births$hyp <- factor(births$hyp,labels=c("normal","hyper"))
births$sex <- factor(births$sex,labels=c("M","F"))
# bweight is the birth weight of the baby in gms, and is a metric
# response (the default)
# effect of hypertension on birth weight
effx(bweight,exposure=hyp,data=births)
# effect of hypertension on birth weight stratified by sex
effx(bweight,exposure=hyp,strata=sex,data=births)
# effect of hypertension on birth weight controlled for sex
effx(bweight,exposure=hyp,control=sex,data=births)
# effect of gestation time on birth weight
effx(bweight,exposure=gestwks,data=births)
# effect of gestation time on birth weight stratified by sex
effx(bweight,exposure=gestwks,strata=sex,data=births)
# effect of gestation time on birth weight controlled for sex
effx(bweight,exposure=gestwks,control=sex,data=births)
# lowbw is a binary response coded 1 for low birth weight and 0 otherwise
# effect of hypertension on low birth weight
effx(lowbw,type="binary",exposure=hyp,data=births)
# etc.