| oddsratio {vcd} | R Documentation |
Computes (log) odds ratios and their asymptotic standard errors for (possibly) stratified data.
oddsratio(x, stratum = NULL, log = TRUE) ## S3 method for class 'oddsratio': plot(x, conf_level = 0.95, type = "o", xlab = NULL, ylab = NULL, xlim = NULL, ylim = NULL, whiskers = 0.1, baseline = TRUE, transpose = FALSE, ...)
x |
a 2 by 2 by ... table. |
stratum |
vector of strata dimensions. |
log |
if FALSE, ordinary odds ratios are computed. |
conf_level |
if not NULL or FALSE,
conf_level-% confidence intervals are plotted for each data
point. |
type |
plot type. |
xlab |
label for the x-axis. Defaults to "Strata" if
transpose is FALSE. |
ylab |
label for the y-axis. Defaults to "Strata" if
transpose is TRUE. |
xlim |
x-axis limits. Ignored if transpose is FALSE. |
ylim |
y-axis limits. Ignored if transpose is TRUE. |
baseline |
if TRUE, a red dashed line is plotted at a
value of 1 (in case of odds) or 0 (in case of log-odds). |
transpose |
if TRUE, the plot is transposed. |
whiskers |
width of the confidence interval whiskers. |
... |
other graphics parameters (see par). |
An object of class "logoddsratio", which is simply a vector of
(log) odds ratios with dimensionality depending on stratum,
along with the following attributes:
ASE |
a numeric vector with the asymptotic standard errors. |
log |
logical indicating whether log odds ratios or common odds ratios are computed. |
The summary method prints the standard errors and—for log
odds ratios—also computes and prints asymptotic z tests
(standardized log odds ratios) and the corresponding p values.
There is a confint method for computing confidence intervals
for the (log) odds ratios.
The plot method plots (log) odds ratios, computed by oddsratio
for 2 x 2 x k tables, along with confidence
intervals.
David Meyer David.Meyer@R-project.org
M. Friendly (2000), Visualizing Categorical Data. SAS Institute, Cary, NC.
## load Coal Miners data
data("CoalMiners")
## compute log odds ratios
lor <- oddsratio(CoalMiners)
lor
## summary with z tests
summary(lor)
## confidence intervals
confint(lor)
## visualization
plot(lor,
xlab = "Age Group",
main = "Breathelessness and Wheeze in Coal Miners")
## add quadratic model
g <- seq(25, 60, by = 5)
m <- lm(lor ~ g + I(g^2))
lines(fitted(m), col = "red")