Description Usage Arguments Value Examples
Fixed effect model for standard meta-analysis of excess relative risk (ERR) or excess odds ratio (EOR) estimates.
1 | pexfix(err, u, l, conf.level = 0.95)
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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. |
conf.level |
Coverage for confidence interval |
Object of class "metaan.era". A list that print the output from the pexfix 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 (SE Effect): The standard error 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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | 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)
donne <- data.frame(cbind(study, Risk, lower_ci, upper_ci))
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))
pexfix(err=donne$Risk, u=donne$upper_ci, l=donne$lower_ci,
conf.level=0.95)
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