funnelplot: Risk-adjusted funnel plot

In cgrcusum: Continuous Time Generalized Rapid Response CUSUM

Description

This function can be used to construct a risk-adjusted funnel plot.

Usage

funnelplot(data, ctime, p0, glmmod, followup, conflev = c(0.95, 0.99))

Arguments

data	data.frame containing the following named columns: entrytime numeric - time of entry into study, survtime numeric - time from entry until event, censorid integer - (optional) censoring indicator (0 = right censored, 1 = observed), instance integer or character - indicating which instance (f.e. hospital) the observation belongs to and optionally additional covariates used for risk-adjustment.
ctime	construction time at which the funnel plot should be determined. Constructed over whole data when not specified
p0	The baseline failure probability at entrytime + followup for individuals. If not specified, average failure proportion over whole data is used instead.
glmmod	a generalized linear regression model as produced by the function glm(). Standard practice: glm(as.formula(paste("(survtime <= followup) & (censorid == 1)~" ,paste(covariates, collapse='+'))), data = data). Alternatively, a list with: $formula (~ covariates) $coefficients (named vector specifying risk adjustment coefficients for covariates - names must be the same as in $formula and colnames of data).
followup	The followup time for every individual. At what time after subject entry do we consider the outcome?
conflev	A vector of confidence levels of interest. Default is c(0.95, 0.99).

Value

An object of class "funnelplot" containing:

• data: A data.frame containing:

  • $instance instance number

  • $observed observed number of failures at instance

  • $expected expected (risk-adjusted) number of failures at instance

  • $numtotal total number of individuals considered at this instance

  • $p (risk-adjusted) proportion of failure at instance

  • $conflevels worse/normal/better performance than expected at this confidence level

• call: the call used to obtain output

• plotdata: data used for plotting confidence intervals

• conflev: specified confidence level(s)

There are plot and summary methods for "funnelplot" objects.

Author(s)

Daniel Gomon

See Also

plot.funnelplot, summary.funnelplot

Other qcchart: bercusum(), bkcusum(), cgrcusum()

Examples

varsanalysis <- c("age", "sex", "BMI")
exprfitfunnel <- as.formula(paste("(entrytime <= 365) & (censorid == 1)~",
 paste(varsanalysis, collapse='+')))
surgerydat$instance <- surgerydat$Hosp_num
glmmodfun <- glm(exprfitfunnel, data = surgerydat, family = binomial(link = "logit"))
funnel <- funnelplot(data = surgerydat, ctime = 3*365, glmmod = glmmodfun, followup = 100)
plot(funnel)

cgrcusum documentation built on Nov. 22, 2021, 9:09 a.m.