alpexfix: Pooled excess risk estimate using the alternative fixed...

In Package-Metaan-Rep/Metaan: Meta-Analysis of Published Epidemiological Studies

Description

Fixed effect meta-analysis of excess relative risk (ERR) or excess odds ratio (EOR) estimates with Richardson et al 2020 alternative model.

Usage

alpexfix(err, u, l, d, conf.level = 0.95)

Arguments

err	A numeric vector of the risk estimated from the individual studies
u	A numeric vector of the upper bound of the confidence interval of the risk reported from the individual studies.
l	A numeric vector of the lower bound of the confidence interval of the risk reported from the individual studies.
d	A numeric vector of the maximum dose reported from the individual studies.
conf.level	Coverage for the confidence interval

Value

Object of class "metaan.arf". A list that print the output from the alpexfix function. The following could be found from the list :

• err_tot (Effect): The pooled effect from excess relative risk (ERR) or excess odd ratio (EOR) estimates

• sd_tot_lnERR (SE-Log(Effect)): The standard error of the logarithm of the pooled effect (see reference Richardson et al 2020 for more details)

• l_tot (Lower CI): The lower confidence interval bound of the pooled effect (err_tot)

• u_tot (Upper CI): The upper confidence interval bound of the pooled effect (err_tot)

• Cochrane_stat (Cochran’s Q statistic): The value of the Cochrane's statistic of inter-study heterogeneity

• Degree_freedom (Degree of Freedom): The degree of freedom

• p_value (P-Value): The p-value of the statistic of Cochrane

• I_square (Higgins’ and Thompson’s I^2 (%)): I square value in percent (%) indicating the amount of the inter-study heterogeneity

References

Richardson, D. B., Abalo, K., Bernier, M. O., Rage, E., Leuraud, K., Laurier, D., ... & Little, M. P. (2020). Meta-analysis of published excess relative risk estimates. Radiation and Environmental Biophysics, 1-11.

Examples

study <- c("Canada", "Northern USA", "Chicago", "Georgia","Puerto", "Comm", "Madanapalle",
"UK", "South Africa", "Haiti", "Madras")
Risk <- c(0.205, 0.411, 0.254, 1.562, 0.712, 0.983, 0.804, 0.237, 0.625, 0.198, 1.012)
lower_ci <- c(0.086, 0.134, 0.149, 0.374, 0.573, 0.582, 0.516, 0.179, 0.393, 0.078, 0.895)
upper_ci <- c(0.486, 1.257, 0.431, 6.528, 0.886, 1.659, 1.254, 0.312, 0.996, 0.499, 1.145)
dose <- c(32.586, 15.257, 72.431, 6.528, 10.886, 11.659, 17.254, 20.312, 10.996, 30.499,
41.145)

donne <- data.frame(cbind(study, Risk, lower_ci, upper_ci, dose))

donne$Risk <- as.numeric(as.character(donne$Risk))
donne$upper_ci <- as.numeric(as.character(donne$upper_ci))
donne$lower_ci <- as.numeric(as.character(donne$lower_ci))
donne$dose <- as.numeric(as.character(donne$dose))

alpexfix(err=donne$Risk, u=donne$upper_ci, l=donne$lower_ci, d=donne$dose,
 conf.level=0.95)

Package-Metaan-Rep/Metaan documentation built on Dec. 28, 2021, 6:40 a.m.