Description Usage Arguments Details Value Examples
View source: R/summary.FluMoDL.R
This function creates a summarized version of a 'FluMoDL' object. It contains the sets of coefficients and variance-covariance matrices for the incidence proxy terms (for influenza, and for RSV if provided), and the predictions for these terms.
1 2 |
object |
An object of class 'FluMoDL' |
... |
Further arguments passed to or from other methods. |
These summaries can be used to run a multivariate meta-analysis
and calculate
pooled effect estimates and BLUP (Best Unbiased Linear Predictor) estimates
for influenza (and RSV if provided).
An object of class 'summary.FluMoDL'. This is a list containing the following elements:
A string describing the meaning of the coefficients. Defaults to
"summary", meaning a first-stage model summary. Alternatively, "blup" means
Best Unbiased Linear Predictor (BLUP) coefficients, and "pooled" refers to coefficients
pooled in the course of a multivariate meta-analysis. See metaFluMoDL
.
A string with an additional description. For objects created
with summary.FluMoDL()
it is an empty string, but see metaFluMoDL
.
A list of numeric vectors, with names 'proxyH1', 'proxyH3' and 'proxyB' (and 'proxyRSV' if provided in the function arguments), containing the model coefficients for these terms.
A list of variance-covariance matrices, with names 'proxyH1', 'proxyH3' and 'proxyB' (and 'proxyRSV' if provided in the function arguments), for the respective model coefficients.
A list with names 'proxyH1', 'proxyH3' and 'proxyB' (and 'proxyRSV'
if provided in the function arguments), containing
predictions (in the form of crosspred
objects) for each exposure.
These can be plotted in both the exposure-response and lag-response dimensions, see
crosspred
, plot.crosspred
and the example below.
1 2 3 4 5 6 7 8 9 10 11 12 | data(greece) # Use example surveillance data from Greece
m <- with(greece, fitFluMoDL(deaths = daily$deaths,
temp = daily$temp, dates = daily$date,
proxyH1 = weekly$ILI * weekly$ppH1,
proxyH3 = weekly$ILI * weekly$ppH3,
proxyB = weekly$ILI * weekly$ppB,
yearweek = weekly$yearweek))
summ <- summary(m)
summ
# Plot the association between A(H1N1)pdm09 activity and mortality:
plot(summ$pred$proxyH1, "overall")
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.