Description Usage Arguments Value Author(s) References Examples
This function calculates (transformed versions of) the ratio of total number of observed versus expected events with the corresponding sampling variance.
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| OE | vector with the estimated ratio of total observed versus total expected events | 
| OE.se | Optional vector with the standard errors of the estimated O:E ratios. | 
| OE.cilb | Optional vector to specify the lower limits of the confidence interval for  | 
| OE.ciub | Optional vector to specify the upper limits of the confidence interval for  | 
| OE.cilv | Optional vector to specify the levels of aformentioned confidence interval limits. (default: 0.95, which corresponds to the 95% confidence interval). | 
| EO | Optional vector with the estimated ratio of total expected versus total observed events | 
| EO.se | Optional vector with the standard errors of the estimated E:O ratios | 
| citl | Optional vector with the estimated calibration-in-the-large statistics | 
| citl.se | Optional vector with the standard error of the calibration-in-the-large statistics | 
| N | Optional vector to specify the sample/group sizes. | 
| O | Optional vector to specify the total number of observed events. | 
| E | Optional vector to specify the total number of expected events | 
| Po | Optional vector to specify the (cumulative) observed event probabilities. | 
| Po.se | Optional vector with the standard errors of  | 
| Pe | Optional vector to specify the (cumulative) expected event probabilites
(if specified, during time  | 
| data | Optional data frame containing the variables given to the arguments above. | 
| slab | Optional vector with labels for the studies. | 
| add | a non-negative number indicating the amount to add to zero counts. See ‘Details’ | 
| g | a quoted string that is the function to transform estimates of the total O:E ratio; see the details below. | 
| level | level for confidence interval, default  | 
| ... | Additional arguments. | 
An object of class c("mm_perf","data.frame") with the following columns:
The (transformed) O:E ratio.
Standard errors of the (transformed) O:E ratio.
Lower confidence interval of the (transformed) O:E ratios. The level is specified in
level. Intervals are calculated on the same scale as theta by assuming a Normal distribution.
Upper confidence interval of the (transformed) c-statistics. The level is specified in
level. Intervals are calculated on the same scale as theta by assuming a Normal distribution.
Method used for calculating the (transformed) O:E ratio.
Method used for calculating the standard error of the (transformed) O:E ratio.
Thomas Debray <thomas.debray@gmail.com>
Debray TPA, Damen JAAG, Snell KIE, Ensor J, Hooft L, Reitsma JB, et al. A guide to systematic review and meta-analysis of prediction model performance. BMJ. 2017;356:i6460.
Debray TPA, Damen JAAG, Riley R, Snell KIE, Reitsma JB, Hooft L, et al. A framework for meta-analysis of prediction model studies with binary and time-to-event outcomes. Stat Methods Med Res. 2019 Sep;28(9):2768–86.
Snell KI, Ensor J, Debray TP, Moons KG, Riley RD. Meta-analysis of prediction model performance across multiple studies: Which scale helps ensure between-study normality for the C -statistic and calibration measures? Stat Methods Med Res. 2017.
| 1 2 3 4 5 6 7 8 9 10 11 12 13 | ######### Validation of prediction models with a binary outcome #########
data(EuroSCORE)
# Calculate the total O:E ratio and its standard error
est1 <- oecalc(O = n.events, E = e.events, N = n, data = EuroSCORE, slab = Study)
est1
# Calculate the log of the total O:E ratio and its standard error
est2 <- oecalc(O = n.events, E = e.events, N = n, data = EuroSCORE, slab = Study, g = "log(OE)")
est2
# Display the results of all studies in a forest plot
plot(est1)
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