Fixed effect model for standard meta-analysis of excess relative risk (ERR) or excess odds ratio (EOR) estimates.

pexfix(err, u, l, 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.

conf.level

Coverage for confidence interval

Value

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

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) 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)
#> #> Standard meta-analysis with fixed effect model #> ------------------------------------------------- #> #> Effect SE Effect Lower CI Upper CI #> 0.41 0.02 0.37 0.46 #> #> ------------------------------------------------- #> #> Test of heterogeneity #> #> Cochran Q statistic Degree of Freedom P-Value #> 153.24 10.00 0 #> #> ------------------------------------------------- #> #> Higgins and Thompson I^2 (%) #> 93.47 #> _________________________________________________ #>