Calculates the pooled difference between proportions and standard error according to Agresti-Caffo across multiply imputed datasets.

pool_propdiff_ac Calculates the pooled difference between proportions and standard error according to Agresti-Caffo across multiply imputed datasets.

pool_propdiff_ac(object, conf.level = 0.95, dfcom = NULL)

Arguments

object

An object of class 'mistats' ('Multiply Imputed Statistical Analysis').

conf.level

Confidence level of the confidence intervals.

dfcom

Complete data degrees of freedom. Default number is taken from function propdiff_ac

Value

The proportion, the Confidence intervals, the standard error and statistic.

Details

For the pooled difference between proportions the difference between proportions according to Wald are used. The Agresti-Caffo difference is used to derive the Agresti-Caffo confidence intervals.

References

Agresti, A. and Caffo, B. Simple and Effective Confidence Intervals for Proportions and Differences of Proportions Result from Adding Two Successes and Two Failures. The American Statistician. 2000;54:280-288.

Fagerland MW, Lydersen S, Laake P. Recommended confidence intervals for two independent binomial proportions. Stat Methods Med Res. 2015 Apr;24(2):224-54.

See also

with.milist, propdiff_ac

Author

Martijn Heymans, 2021

Examples

imp_dat <- df2milist(lbpmilr, impvar="Impnr")
ra <- with(imp_dat, expr=propdiff_ac(Chronic ~ Radiation))
res <- pool_propdiff_ac(ra)
res
#>      Prop diff 95 CI low 95 CI high
#> [1,] 0.2785441 0.1185021  0.4252316
#> attr(,"class")
#> [1] "mipool"